The Development Of Timing Control And Temporal Organization In Coordinated Action: INVARIANT RELATIVE TIMING, RHYTHMS AND COORDINATION (TECHNIQUES IN BEHAVIORAL & NEURAL SCIENCES)

THE DEVELOPMENT OF TIMING CONTROL AND TEMPORAL ORGANIZATION IN COORDINATED ACTION Invariant Relative Timing, Rhythms and Coordination

ADVANCES IN PSYCHOLOGY

81 Editors:

G. E. STELMACH

P. A. VROON

NORTH-HOLLAND AMSTERDAM LONDON NEW YORK TOKYO

THE DEVELOPMENT OF TIMING CONTROL AND TEMPORAL ORGANIZATION IN COORDINATED ACTION Invariant Relative Timing, Rhythms and Coordination

Edited by

Jacqueline FAGARD Laboratoire de Psycho-Biologie de I’ Enfant EPHE-CNRS (URA 315) Paris, France

Peter H. WOLFF The Children’s Hospital Boston, Massachusetts, U.S.A.

1991

NORTH-HOLLAND AMSTERDAM LONDON NEW YORK TOKYO

NORTH-HOLLAND ELSEVIER SCIENCE PUBLISHERS B.V. Sara Burgerhartstraat 25 P.O. Box 211, 1000 AE Amsterdam, The Netherlands

Distributors for the United States and Canada: ELSEVIER SCIENCE PUBLISHING COMPANY, INC. 655 Avenue of the Americas New York, N.Y. 10010,U.S.A.

Library o f Congress Cataloging-in-Publication

Data

T h e D e v e l o p m e n t o f t i m i n g c o n t r o l a n d t e m p o r a l o r g a n i z a t i o n in coordinated action i n v a r i a n t r e l a t i v e t i m i n g . r h y t h m s , and c o o r d i n a t i o n / e d i t e d by J a c q u e l i n e F a g a r d , P e t e r H. W o l f f . p. cm. -- ( A d v a n c e s in p s y c h o l o g y ; 81) I n c l u d e s b i b l i o g r a p h i c a l r e f e r e n c e s and indexes. I S B N 0-444-88795-4 1 . M o t o r a b i l i t y in c h i l d r e n . 2. M o t o r a b i l i t y . I. F a g a r d . J a c q u e l i n e . 11. Wolff. P e t e r H. 111. S e r i e s A d v a n c e s in p s y c h o l o g y ( A m s t e r d a m . N e t h e r l a n d s ) ; 81. W 1 A D 7 9 8 L v. 81 I WE 103 [ D N L M 1. M o t o r S k i l l s . 2. M o v e m e n t . D4896 1 R J 1 3 3 . D 4 8 1991 165.$'!23--dC20 DNLMIDLC for Library o f Congress 91-27173 CIP

1SBN:O 444 887954 @

ELSEVIER SCIENCE PUBLISHERS B.V., 1991

All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, without the prior written permission of the publisher, Elsevier Science Publishers B.V./ Permissions Department, P.O. Box 521, 1000 AM Amsterdam, The Netherlands. Special regulations for readers in the U.S.A. - This publication has been registered with the Copyright Clearance Center Inc. (CCC), Salem, Massachusetts. Information can be obtained from the CCC about conditions under which photocopies of parts of this publication may be made in the U.S.A. All other copyright questions, including photocopying outside of the U.S.A., should be referred to the copyright owner, Elsevier Science Publishers B.V., unless otherwise specified. No responsibility is assumed by the Publisher for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions or ideas contained in the material herein. Printed in The Netherlands

CONTENTS

VII

List of contributors Preface P.H.Wolff and J. Fagard

XI

Section I: Theoretical considerations on the concept of timing in motor coordination. 1

Chapter 1

TIMING CONTROL IN MOTOR SEQUENCES P. Viviani and G. Laissard

Chapter 2

INVARIANT RELATIVE TIMING IN MOTORPROGRAM THEORY H. Heuer

37

RELATIVE TIMING FROM THE PERSPECTIVE OF DYNAMIC PATTERN THEORY: STABILITY AND INSTABILITY P.G. Zanone and J.A.S. Kelso

69

Chapter 3

Chapter 4

CENTRAL GENERATORS AND THE SPATIOTEMPORAL PATTERN OF MOVEMENTS Yu.1. Arshavsky, S. Grillner, G.N. Orlovsky, and Yu.V. Panchin

93

Section II: Current research on temporal patterns of movements in early motor development. Chapter 5

Chapter 6

Chapter 7

ENDOGENOUS MOTOR RHYTHMS IN YOUNG INFANTS P.H. Wolff

119

EVIDENCE AND ROLE OF RHYTHMIC ORGANIZATION IN EARLY VOCAL DEVELOPMENT IN HUMAN INFANTS R.D. Kent, P.R. Mitchell, and M. Sancier

135

THE ROLE OF REFLEXES IN THE PATTERNING OF LIMB MOVEMENTS IN THE FIRST SIX MONTHS OF LIFE P.M. Mc Donne11 and V.L. Corkum

15 1

vi

Contents

Chapter 8

Chapter 9

Chapter 10

DEVELOPMENT OF INFANT MANUAL SKILLS: MOTOR PROGRAMS, SCHEMATA, OR DYNAMIC SYSTEMS? G.F. Michel TIMING IN MOTOR DEVELOPMENT AS EMERGENT PROCESS AND PRODUCT E. Thelen

175

201

SOFT ASSEMBLY OF AN INFANT LOCOMOTOR ACTION SYSTEM E.C. Goldfield

213

Chapter 11

TIMING INVARIANCES IN TODDLERS'GAIT B. Bril and Y. Brenikre

23 1

Chapter 12

THE DEVELOPMENT OF INTRALIMB COORDINATION IN THE FIRST SIX MONTHS OF WALKING J.E. Clark and S.J. Phillips

245

Section 111: Current research on development of timing during childhood. Chapter 13

HOW TO STUDY MOVEMENT IN CHILDREN M.G. Wade and W. Berg

Chapter 14

COORDINATIVE STRUCTURES AND THE DEVELOPMENT OF RELATIVE TIMING IN A POINTING TASK D.L. Southard

Chapter 15

Chapter 16

SYNCHRONIZATION AND DESYNCHRONIZATION IN BIMANUAL COORDINATION A DEVELOPMENTAL PERSPECTIVE J. Fagard THE DEVELOPMENT OF TIMING ACROSS FOUR LIMBS: CAN SIMPLICITY PRODUCE COMPLEXITY? M.A. Roberton

261

281

305

323

Section IV: Discussion paper Chapter 17

THE ROLE OF TIMING IN MOTOR DEVELOPMENT J.C. Fentress

34 1

Author Index

367

Subject Index

385

CONTRIBUTORS

Arshavsky, Yu.1.

Inst. of Problems of Information Transmission Academy of Sciences Ermolova St. 19 Moscow, 101447 USSR

Berg, W.

Division of Kinesiolo , University of Minnesota 110 Cooke Hall 1900 niversity Ave. S.E. Minneapolis, MN 55455 USA

Breni*re, Y.

Laboratoire d e Physiologie du Mouvernent UA CNRS 631, UniversitC Paris XI 9 1405 Orsay France

Bril, B.

Laboratoire d e Physiologie du Mouvement UA CNRS 631, UniversitC Paris XI 91405 Orsay France

Clark, J.

Biomechanics Laboratory Dept of Kinesiology University of Maryland College Park, MD 20742 USA

Corkum, V.L.

Department of Psychology University of New Brunswick Fredericton, NB, E3B 6E4 Canada

Fagard, J.

Laboratoire d e Psycho-Biologie de l’Enfant, EPHE-CNRS 41 rue Gay-Lussac 75005 Paris France

Fentress, J.C.

De ts of Psychology and Biology Da housie University Halifax, Nova Scotia B3H 451 Canada

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Contributors

Goldfield, E.C.

Child Develo ment Department Connecticut Eollege BOX 5352,270 Mohe an Ave. New London ,CT 063fO-4196 USA

Grillner, S.

Nobel Institute of Neurophysiology Karolinska lnstitute Stockholm, Box 60400, S-104 01, Sweden

Heuer, H.

Institut fur Arbeitsphysiologie an der Universitat Dortmund Ardeystrasse 67 D-4600, Dortmund 1 Germany

Kent, R.D.

Waisman Center University of Wisconsin-Madison 1500 Highland Ave. Madison, WI, 53705-2280 USA

Kelso, J.A.S.

Florida Atlantic University P.O. Box 3091 Boca Raton, FL 33431-0991 USA

Laissard, G.

Facultt de Psychologie et des Sciences de 1’Education 24 rue GCntral-Dufour 1211 G e n k e 4 Switzerland

McDonnell, P.M.

Department of Psychology University of New Brunswick Fredericton, NB, E3B 6E4 Canada

Michel, G.F.

Department 22%Eiversity 2219 N. Kenmore Chicago, IL 60614-3298, USA

Mitchell, P.R.

Department of Communication Disorders Marshall Universit Smith Hall, 400 Hal Greer Blvd: Huntington, WV, 25755-2675 USA

Orlovsky, G.N.

Nobel Institute of Neurophysiology Karolinska Institute, Stockholm, Box 60400, S-104 01 Sweden

Contributors

Panchin, YU,V.

Inst. of Problems of Information Transmission Academy of Sciences Ermolova St. 19 Moscow, 101447 USSR

Phillips, S.J.

Biomechanics Laboratory Department of Kinesiology University of Maryland College Park, MD 20742 USA

Roberton, M.A.

Motor Development & Child Study Laboratory Dpt of Physical Education and Dance University of Wisconsin-Madison 318 Lathro Hall Madison, $1 53706 USA

Sancier, M.

Waisman Center University of Wisconsin-Madison 1500 Highland Avenue Madison ,WI 53705-2280 USA

Southard, D.L.

Department of Physical Education Texas Christian University Box 32901 Fort Worth, TX 76129 USA

Thelen, E.

Department of Psychology Indiana University Bloomington, In 47405 USA

Viviani, P.

FacultC de Psychologie et des Sciences de I’Education 24 rue GCnCral-Dufour 1211 Gentve 4 Switzerland

Wade, M.G.

Division of kinesiolo University of Minnesota 110 Cooke Hall 1900 niversity Avenue S.E. Minneapolis, MN 55455 USA

Wolff, P.H.

The Children’s Hospital 300 Lon ood Ave. Boston, c a 02115 USA

Zanone, P.G.

Florida Atlantic University P.O. Box 3091 Boca Raton, FL,33431-0991 USA

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PREFACE

"Everything is useful, nothing is indispensable". Norman Douglas The indissoluble link between coordinated actions and the timing of individual units of movement can be investigated in terms of absolute timin (velocity and acceleration) of discrete movements, the frequency and temporay stability of re etitive movements (rhythms, cycles), and the invariance (absolute or r e k t i v e ) of relative timing of component units as the temporals atial requirements of the goal directed task change. On a larger time scale, tEe timing of developmental events may alter, to a greater o r lesser extent, any one o r more of these timin parameters in coordinated action. This volume examines t i e development of timing in coordinated action from several different ontogenetic perspectives. Some chapters emphasize the qualitative changes in manifest motor behavior during the early growth years, and examine the relation between temporal characteristics of pre- and perinatal movements and goal directed actions with qualitatively different rules of temporal organization. Other contributors stress the developmentally invariant timing characteristics of species-typical and perhaps genetically programmed motor patterns of nonhuman organisms. Their work examines t h e molecular machinery that generates circumscribed motor patterns with stable tem oral characteristics, as well as the reversible influences of peripheral feec rback on, and the interactions among discrete pattern generators. Despite their basic theoretical differences, both formulations imply the same generic hypothesis: that the tem oral characteristics of manifest movement or action are controlled by centray agencies acting on the peripheral skeleto-muscular system in a hierarchic top-down mode. A number of chapters advance the radically different hypothesis that the temporal characteristics of coordinated behavior are a p o s t e r i o r i or emergent roperties of d namic interactions among many component movements at a focal level, rat e r than the prescribed consequences of a p r i o r i nervous system mechanisms that function independent of the motor patterns they control. The primary phenomenon of coordinated action to be explained by empirical studies is not the timing characteristics of movement p e r se, but the processes by which the nearly infinite number of otentially independent degrees of freedom coo erate to induce a relative y small number of low dimensional ensembles o?motor activity or synergies. The formulation further assumes that quantitative changes of any one or more organismic, cognitive, and environmental variables produce qualitative changes in the intrinsic dynamics of patterned motor behavior, and that the rules of temporal organization governing the novel motor patterns cannot be inferred from, o r A linearly reduced to, quantitative changes in individual variables. developmental analysis of coordinated action from this perspective must therefore examine man hysical, allometric, physiological, and biomechanical variables, some of whicg gave no obvious relation to motor behavior as such.

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Prdace

All chapters make it clear that the timing of coordinated action cannot be investigated systematically without a definition of the basic units of behavior and their o erating characteristics. Empirical studies of human motor and behavioral evelopment have traditionally chosen segmental, inter- segmental or supra-segmental reflexes as the preferred basic units of motor behavior, but the boundaries separating reflexes from voluntary actions have rarely been defined precisely by the behavioral sciences; and the term has taken on a range of supernumerary connotations, some of which clearly defeat the original heuristic advantages of the behaviorist approach. In its most pristine version, the behavioral reflex refers to simple, stereotypic stimulus-response sequences that operate as autonomous units and are assumed to have a particular, although often unspecified, anatomical locus. Sometimes the primitive reflex is viewed as the hylo enetic ancestor and basic building block from which more elaborate re lex c ains a r e constructed, a t other times as a naturally occurring, neurologically driven entity that differs categorically from volunta motor actions, or as a major ontogenetic impediment that must be i x i b i t e d by higher cortical influences before the development of voluntary actions can proceed in a n orderly fashion. Contemporary theories of motor development rarely adopt such rigid definitions of the reflex, but several chapters suggest that "reflex-like'' behaviors still serve as a convenient point of departure for describing the origins of motor timing and the development of motor coordination. The dynamical systems perspective, on the other hand, does away with the notion of reflex alto ether, and instead adopts the concept of "soft molded" low dimensional ensem les or "coordinative structures" without fixed central nervous system representations as the basic units of action for empirical investigations. Coordinative structures are defined as loose coalitions amon many potentially independent degrees of freedom that can b e assemble$ disassembled, and reassembled in different combinations, depending on the organism's initial conditions, the component units of action recruited for a given task, and the environmental conditions. The developmental implications of the three major formulations about the relation of timin and coordinated action appear t o diver e so greatly as to be irreconcilable. %et, the experimental findings reviewed ere suggest that the theoretical boundaries may not be as sharply drawn as they a r e sometimes resented. For example, central pattern generators allow considerable Lexibility for adaptation to changing environmental requirements; motor programs and motor schemas are not as hierarchically prescriptive as they are sometimes portrayed; and a dynamical systems perspective on spontaneous pattern formation does not, and could not, dispense entirely with structural constraints and a modular or anization of behavior. To be comprehensive, a developmental description of timing in coordinated action must therefore incorporate both modular constraints and interactive processes of "the system as a whole". A sim le tally of theoretical preferences expressed in the various chapters mi t! ive the impression that the dynamical systems perspective now dominates t i e i e l d . In part, the imbalance may be due to editorial selection biases, but the sheer number and remarkable success of semi-po ular books on the theoretical foundations of the "new physics", the origins of the universe, chaos theory, and the dynamics of com lex biolo ical systems, suggests that the influence implied by the paradigm shift, of whica the dynamical perspective is one expression, extends considerably beyond any traditional field of investigation. On the other hand, the almost promiscuous ap lication of the perspective to almost all domains of the natural and psycho ogical sciences

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might imply that the approach aspires to become a "theory of everything". While that was clearly not the intent of those who apply the new rigorously and responsibly, the epistemological status of the ynamical gerspective remains ambiguous, particularly when applied t o complex human ehavior. As a minimum, the paradigm offers investigators from many disciplines a new metaphor for the interpretation of research findings, even when they cannot translate their findin s into formal differential or difference equations. On the other hand, many of t i e chapters indicate that it is possible to go beyond such metaphorical applications, and to apply formal mathematical research strategies to make theoretically informed and ex erimentally testable predictions. However, the limits of relevance of t l! e dynamical systems perspective t o developmental issues have not been adequately explored, and there is no a priorr reason to assume that all of the relevant empirical questions about timing in coordinated action will be elucidated by rigorous mathematical anal sis. As a number of the contributions indicate, the more traditional researc strategies therefore remain viable alternatives.

zaradigm

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SECTION I: Theoretical considerations on the concept of timing in motor coordination. Chapter 1

TIMING CONTROL IN MOTOR SEQUENCES P. Viviani and G. Laissard

Chapter 2

INVARIANT RELATIVE TIMING IN MOTORPROGRAM THEORY H. Heuer

Chapter 3

RELATIVE TIMING FROM THE PERSPECTIVE OF DYNAMIC PATTERN THEORY: STABILITY AND INSTABILITY P.G. Zanone and J.A.S. Kelso

Chapter 4

CENTRAL GENERATORS AND THE SPATIOTEMPORAL PATTERN OF MOVEMENTS Yu. I. Arshavsky, S. Grillner, G.N. Orlovsky, and Yu. V. Panchin

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The Development of Tmin Control and Temporal 0yn.ization in 8.mdhated Action J. Fagard an PH. Wolf€ (Editors) 8 Elsevia Science Publishers B.V., 1991

1

Timing control in motor sequences Paolo Viviani and Gerard Laissard Department of Psychobiology, Faculty of Psychology and Educational Sciences, University of Geneva, 24 rue du G6n6ral Dufour CH-1211 Geneva, Switzerland 1. Introduction

Timing control in motor sequences is a more elusive problem than we thought it was. Not surprisingly, the issue gets a high priority in the agenda of such diverse disciplines as experimental psychology, functional neurophysiologyand mathematical modelling. New insights and concepts from all these disciplines are being contributed that, eventually, will have to be reconciled. Even if we had the necessary competence (which we don’t), we couldn’t possibly compress in a chapter an exhaustive survey of the many competingviews that are currently being debated in the literature. Our choice, therefore, has been to focus on just one facet of the problem. In so many words, the question to be discussed here is whether temporal structure in motor sequences is dictated by a dedicated functional module somewhere in the nervous system (the Motor Program view), or is instead an emerging property of the implementation stage (the System-Dynamic view). We begin by distinguishing several types of movements, each of which requires special consideration. The internal clock hypothesis will then be introduced in relation with a class of discrete motor sequences (simple and rhythmic tapping) that has been extensively investigated in the laboratory. Next, we discuss some aspects of the timing of continuous movements which can be reconciled with both the Motor Program and System-Dynamic views. Finally, we will consider in some detail two phenomena, proportional (ratiomorphic) scaling and contextual effects, both of which are generally supposed to bear directly on the main theme of the chapter. On the basis of recent data on the motor sequences used for typing, we discuss the extent to which this general belief is in fact well founded. 2. Types of movements

By necessity, all human movements are continuous: provided that the spatial and temporal resolution of the measuring devices is sufficient, one can always describe the

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P. Eviani and G.Lairsurd

trajectory and the kinematics of these movements by time-differentiable functions. Nevertheless, in motor control theory it is both customary and useful to identify certain movements as discrete, and to reserve the term continuous for all the others. A movement is considered discrete whenever it can be decomposed into a sequence of identifiable units of motor actions. The criteria for identifying these units are neither homogeneous nor very sharp (cf Young & Schmidt, 1990; Viviani, 1986). The least controversial among them are those stated as kinematic conditions involving velocity and/or acceleration (d Hulstijn & van Galen, 1983; Morasso, Mussa Ivaldi & Ruggiero, 1983). Many would agree, for instance, that if there are points where the tangential velocity drops to zero, then the section of the movement comprised between any two such points qualifies as a unit (some use the term stroke), and the movement as a whole is discrete. In other contexts, the segmentation of the movement into units can be justified by the presence of abrupt changes in the value of some control parameter (Soechting & Terzuolo, 1987a, see also later). Finally, functional criteria can also be invoked to claim that a discrete articulation underlies the physical continuity of the gesture (Soechting & Terzuolo, 198%). Which one among these options one considers as being more appropriate depends on the questions that are addressed. The alternatives are not mutually exclusive, however: one and the same segmentation may result from applying different criteria. Thus, for example, by most accounts typing and piano playing are considered discrete movements, and individual keypresses are seen as the basic units of this motor skill. It should be obvious, however, that the discrete vs continuous opposition makes sense only within a preassigned level of analysis. A movement may be considered discrete at a coarse-grained level but, if we zoom into a small portion of the trajectory and adopt a fine-grained resolution, it might be more appropriate to consider that portion as being continuous. This is the case, for instance, when in typing we concentrate on the finger transport phase between keypresses (Gentner, Grudin & Conway, 1980). The distinction between discrete and continuous movements overlaps somehow with another important distinction in motor control theory, namely that between periodic and aperiodic movements. It is often the case in fact that at least one point within the cycle of a periodic movement is salient from either the kinematic or functional point of view. Then, the cycles (or fractions thereof) qualify as units, and the movement as a whole is discrete. Simple, rhythmic and polyrhythmic tapping are all prototypical examples of the discrete, periodic motor tasks studied in the laboratory. On the other side, many continuous movements (e.g. the flexion of the forearm or the throwing of a ball) are also aperiodic. The overlap is not a one-to-one correspondence, however. For example, the typing movements mentioned above are discrete but not periodic. Also, the continuous tracing of a circle with the fingertip is periodic and continuous.

Timing Control in Motor Sequences

3

3. Schemes for timing control

The reason for distinguishing different types of movement is that certain issues in motor control theory need to be dealt with differently for each type. This is true in particular for the control of timing and rhythm in motor sequences. A popular (but not universally shared) view on the organization of learned and skilled movements is based on the "motor program" concept which was first coached as a "memory drum" metaphor (Henry & Rogers, 1960) and, ultimately, evolved into the so-called "Generalized Motor Program" (GMP) hypothesis (cf Gallistel, 1980; Keele, 1981; Schmidt, 1988). According to this hypothesis, structural stability in motor performances is ensured by an abstract plan implemented by an appropriate parametric algorithm. Flexibility in the execution is provided instead by the possibility to set the parameters of the algorithm according to contingent contextual requirements. Historically, the main motivation for the emergence the motor program concept was to account for the preservation of serial order in complex motor behavior (Lashley, 1951). Over the years Lashley's argument that order should be coded in fairly abstract terms before the beginning of the movement, was extended implicitly to the relative timing among the ordered components of the behavior. The obvious fact that a set of temporal relationships implies an order,has blurred somehow the necessary distinction between timing and order. One should keep in mind instead the possibility that these two aspects of the performance be controlled by coordinated but otherwise distinct mechanisms. In fact, such a possibility has been evoked to resolve certain contradictions that emerge from the analysis of rhythmic tapping (Vorberg & Hambuch, 1978).Be as it may, our well-documentedcapability to execute a given gesture at different speeds squares nicely with the GMP hypothesis. One simply has to imagine that the spatial and sequential aspects of the gesture are captured by the abstract plan, and that a "speed knob is available to speed up or slow down execution, as the case may be (incidentally, also the size of a gesture can often be changed at will while preserving its shape; thus, we may also need a "size knob; more later on the relation between these two knobs).

In a subsequent section we will argue that the notion of "program" (generalized or otherwise) is actually neither necessary nor sufficient for countenancing speed and size knobs. Here we elaborate instead on the above contention that possible accounts of how the "speed knob is implemented depend on the type of movement. A few examples are sufficient to illustrate the variety of possible strategies that are available to control relative and absolute timing, and the fact that different movements may require different strategies. Consider first a typical aperiodic continuous movement: the flexion of the forearm. For a given amplitude, duration depends mainly on the intensity of the agonist motor commands, and, to a lesser extent, on the timing of the braking action by

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P. Kviani and G.Laissard

antagonist synergies (relative to the onset of the movement)(Gielen, van den Oosten, & Pull ter Gunne, 1985). Thus, duration per se may neither be represented centrally, nor controlled as an independent parameter. Force parameters are also likely to be involved in the control ofperiodic continuous movements. In fact, whenever moving masses are not negligible, the cycle period can be set in principle by balancing active and inertial forces (Lestienne, 1979). In this case, however, some control of timing is arguably necessary whenever the period of the movement must be tuned to an external rhythm. Further, such a control can be either a direct one, or as we shall see later - mediated by an intervening kinematic variable. The case for an independent control of timing is even more cogent when one considers composite rhythms generated with low-inertia articular segments (as,for instance, in tapping). Simultaneousand independent control of time and force seems to be involved when producing stressed rhythms (Semjen, Garcia-Colera & Requin, 1984). Finally, neither force nor absolute time appear to be directly represented and programmed in some discrete aperiodic movements. In typing, for instance, intervals seem to be controlled by sets of time ratios (see later).

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Much behavioral evidence can be cited for each of the above possibilities. Also, physiological evidence exists that timing control for different types of movements involves distinct structures in the nervous system. It is known, for example, that the basic control modules for quadrupedal locomotion are located in the spinal chord and remain functional after a high spinal section (cf Grillner, 1975). The rhythm of other innate movements, such as breathing, is controlled instead by modules located in the reticular formation. Both walking and breathing rhythms, of course, are also accessible to voluntary modulations. Conversely, the execution of learned and highly skilled motor sequences (e.g. writing or playing an instrument) certainly involve cortical structures, but peripheral feedbacks have demonstrable influence nonetheless. Given this wealth of possibilities, the only sensible option for the behavioral psychologist is to try and isolate a minimal set of functional control modes that, either alone or in combination, account satisfactorily for the major experimental facts. That such an option is actually viable remains to be proved, however. In several cases models have been developed within the motor program framework which fare reasonably well for specific conditions, but no comprehensive scheme has emerged so far that can encompass all movement types. Moreover, the motor program view itself is not the only possible framework. Indeed, a number of competing views has emerged recently which share the common belief that, in many (if not all) cases, temporal structure in motor sequences reflects less a central blue-print than the intrinsic properties of the movement execution stages. In what follows we will consider some of the arguments raised in this debate, with an emphasis on those few cases where competing proposals have been spelled out in sufficient detail.

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4. The internal clock

Strictly speaking a movement is periodic if all its components repeat after a fixed time interval (cycle). Weaker definitions are also possible, however. In simple tapping, for instance, attention is concentrated on keypress times, disregarding the intercalated finger displacements. Thus, as long as these points of discontinuity are equally spaced in time, the movement is considered periodic. A rhythmic structure arises whenever, in addition to the start and end points, other discontinuitieswithin the cycle divide a measure into subintervals. Humans have the innate ability of memorizing, producing and reproducing rhythmic discrete structures of great complexity. Thus we must possess a sophisticated system for coding the subdivision of the cycle into component intervals. It is still debateable whether one and the same coding is used for memorizing and for producing rhythms (Keele, Pokorny, Corcos & Ivry, 1985). In the meantime, investigations of possible coding schemes tend to adopt distinctively different styles depending on whether the emphasis is on memory or action. As for the former, the main thrust has been toward defining the most compact form that structural information can take. Most recent work along this line (e.g. Collard & Povel, 1982; Deutsch & Feroe, 1981; Greeno & Simon, 1974; Longuet-Higgins, 1978) is based on the notions of structural trees and hierarchical codes introduced by Restle(1970) and Leeuwenberg (1971). Little effort is generally made to relate these fairly abstract schemes to the concepts that are more familiar to the motor theorist. This is instead a more serious concern for those interested in schemes for coding action. By far the most important concept in this context is that of internal clock. Whenever a periodic temporal sequence is maintained over an extended period, it is intuitively appealing to postulate a module that provides centrally the desired pace. In its simplest formulation, the module - the functional equivalent of a tunable clock or metronome which times out the cycle onset - can accommodate the basic experimental facts concerning isochronous tapping. On the fast side, our capability to tune the tapping frequency is limited sharply by biomechanical constraints. On the slow side there is no well defined limit. The variability of the intervals increases with the period, but the degradation is smooth and monotonic (Michon, 1967). In the intermediate range, most individuals find it quite easy to either synchronize their movement to an external signal or to maintain an extemporaneous tempo (Bartlett & Bartlett, 1959; Treisman, 1963). In this range the Weber fraction of the clock is about 5% and the variability with which one can synchronize taps to an external reference can be very low indeed (Hopkins ,1984 reports standard deviation for the asynchrony as low as 6 msec). The isochronous clock metaphor can be used to factor out this variability into central and efferent components (Wing & Kristofferson, 1973a,1973b).

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P. Kviani and C.Luissard

A single clock is of course insufficient to control the production of rhythmic sequences. In order to deal with these more complex cases, the basic module has been generalized in two directions. Serial (association)models postulate as many independent timekeepers as there are component intervals within a measure (Vorberg & Hambuch, 1978). Each timekeeper triggers the next one. The last timekeeper feeds back on the first one. There are two major shortcomings with these schemes. Firstly, they run into serious memory problems. Secondly, they cannot account for certain idiosyncrasies observed in rhythmic tapping, and, in particular, for the fact that rhythms with integral ratios among intervals are strongly preferred over all the others (cf Fraisse, 1956; Essens & Povel, 1985; Essens, 1986). These rhythms are much easier to learn and, once learned, they tend to remain stable in time. Those with non-integral ratios drift instead progressively toward the closest integral approximation. Even people with intensive training (e.g. professional musicians) have difficulties to overcome this bias (Sternberg, Knoll & Zukofsky, 1982). In addition, certain patterns of serial covariance suggest the existence of higher-order timing mechanisms that elude the serial model (Vorberg & Hambuch, 1984). A number of hierarchical schemes have been developed to cope with these difficulties. The simplest type of model posits an isochronous metronome that controls the duration of the measure and, at the same time, triggers a set of serial mechanisms that generate the subunits. Essens and Povel (Essens, 1986; Essens & Povel, 1985; Povel, 1981) attempted to explain the bias for integer ratios by assuming that the superordinate clock segments the temporal pattern into equal intervals (measures) and expresses the intervals smaller than the measure as fractions of its length. Failure to find a clock period that subdivides the measure into rational segments would translate into a difficulty to execute the pattern (Povel, 1984). A hierarchical model was tested satisfactorily with data from a polyrhythmic bimanual tapping task (Jagacinski, Marshburn, Klapp & Jones, 1988). Despite their greater complexity, also hierarchical models have problems, however. For instance, two such models considered by Vorberg and Hambuch (1978) did not fare much better than the serial model in explaining variances and covariances of the tapping times. Both serial and hierarchical models presuppose the possibility of measuring time durations, but not much attention has been given of late to the question of how this is achieved. The so-called "counting models" represent one notable exception. They all derive from one basic idea put forward long time ago by Hoagland (1933), namely that durations are determined by counting the number of pulses issued by one basic master clock (the interval between pulses is supposed to be at least one order of magnitude smaller than the smallest interval to be measured). Counting mechanisms have been advocated to explain temporal discrimination (Creelman, 1962; Kristofferson, 1984; Treisman, 1963) and speed-accuracy trade off (Green & Luce, 1973) data. Applications to tapping synchronization have also been proposed (Hopkins, 1984) under the general hypothesis that perception and motor control share a common timing mechanism (see

Timing Control in Motor Sequences

7

above). Overt motor responses in this case are supposed to be triggered whenever accumulated counts reach a preset threshold value (cf Heath & Willcox, 1990). Two features of the counting models are particularly interesting in the context of motor control theory. The first is that, by stipulating the stochastic properties of the pulse train, one can provide a principled basis for factoring out action variability into central and efferent components. The second is that the temporal structure of rhythmic movements is coded as a sequence of numbers (the count thresholds), quite independently from the absolute tempo at which the rhythm is performed. Thus the model provides a simple explanation for our capability to produce the same rhythm at different tempi: it is sufficient to modulate the frequency of the master clock to obtain a change in tempo without affecting the rhythm. From the functional point of view, the clocks that we have considered so far are digital devices. To conclude this section and, at the same time, introduce a main character of the next one, we would like to mention the possibility of using analog devices instead. To exemplify, let us consider a simple parallel scheme for the generation of rhythmic tapping. Suppose that a collection of oscillators is available which are all tuned to the tempo of the main measure of the rhythm. The common period could actually derive from one master oscillator. Suppose further that a notable point of the oscillations (e.g. the zero crossing with maximum positive derivative) can be detected and used to trigger a "go" signal to the motor centers. The subdivision of the measure into intervals can then be obtained by setting appropriately the relative phases between the oscillators. Consider, for instance, a rhythm with a main measure of 1400 msec divided in four intervals according to the scheme 3-1-2-2 (i.e. a measure containing four successive intervals of 525,175,350 and 350 msec). Then, one clock would mark the beginning of the measure. Three other clocks with phase differences of 314 x , x , and -112 x with respect to the first one would mark instead the beginning of the second, third and fourth interval, respectively (Figure 1). In this scheme, learning to produce a rhythm amounts to learn how to lock relative phases into a preassigned pattern. The stability of rhythmic sequences with integer ratios could then be explained by the fact that symmetric points within the cycle provide an easier reference for phase locking. 5. Continuous periodic movements

In most versions of the tapping task the time structure of the sequence is induced by the experimenter. By contrast, most periodic or quasi-periodic movements performed outside the laboratory are either self-paced, or executed under some global, unspecific temporal constraint. Nevertheless, even in these real-life movements the involvement of an internal timing mechanism is still suggested by the common observation that whatever

8

P. Kviani and G.Lairsad I

I

3

I

1

I

2

I

I

I

I

I

2

Figure 1. Hypothetical scheme for generating a rhythm by phase-locked oscillatom.

pace one chooses for a periodic movement - say, pedalling on a bicycle - is generally maintained over a period of time. Unlike tapping or similar laboratory conditions, however, these unsupervised movements are sometimes continuous with no clearly identifiable points within their cycle. Therefore, if indeed the internal timing mechanism is functionally similar to a controllable metronome, it remains to be seen how the movement cycle can be anchored to the beats of this reference. One possibility is to imagine that the pace-keeping function is assumed by the motor commands themselves (Shaffer, 1982). In order to see how this might work one must recall that many periodic movements with closed trajectories result from composing vectorially .harmonic displacements along non-overlapping axes (Hollerbach, 1981). These oscillatory components - which necessarily have the same frequency - may then play the same role of the common reference introduced at the end of the preceding section to explain the production of rhythmic tapping. In other words, as in the escapement of mechanical clocks, one and the same oscillatory mechanism would provide simultaneously the commands for the movement and the reference for maintaining a constant pace (Kelso & Tuller, 1984). The idea that we have just outlined might appear as a mere qualification of the internal-clock hypothesis. In fact, it represents a profound departure from that notion. A

Timing Control in Motor Sequences

9

whole line of theorizing, sometimes referred to as System-Dynamic approach, has emerged from the intuition that the unfolding of dynamic processes - such as those involved in movement execution - do have morphogenetic potentialities and, in particular, the power to impose a time structure upon the various phases of the movement. Here we cannot do justice to this theoretical approach which involves subtle arguments on the nature of non-linear systems. Excellent expositions are available, however (e.g. Kugler & Turvey, 1987; Saltzman & Kelso, 1983), along with a number of reports on the experimental support for the theory (e.g. Kelso, 1984; Rosenblum & Turvey, 1988; Turvey, Rosenblum, Schmidt & Kugler, 1986). For the purpose of the presentation it will be sufficient to highlight the cleavage between the System-Dynamic approach and the conceptual framework within which most internal-clock models are developed. Central to the latter is the notion of internal representation i.e. the belief that, before becoming an overt, observable property of a sequence, temporal structure is coded in some sort of internal blue-print that the motor control system reads out at the moment of the execution. These blue-prints are a pivotal concept in the motor program view wherein all aspects of the movement, not only the temporal ones, are supposed to have a corresponding internal representation. By contrast, there is no explicit internal representation of time in the System-Dynamicview which considers this variable as intrinsic to the motor plan. Perhaps, it would be incorrect to construe the System-Dynamic approach as being totally incompatible with the motor program approach if only because both admit that the spatial determinants of learned gestures need to be coded internally prior to execution. It is true, however, that as far as timing control goes, opinions diverge considerably. Further research is obviously needed before a final judgment can be passed on these matters. It is not too soon, however, to remark that any evidence of a coupling between temporal and spatial aspects of movement sequences may turn out to be relevant to the debate. It is clear in fact that, if temporal structure were an emerging property of the implementation of a predetermined spatial plan, the coupling between temporal and spatial aspects should be strongly constrained by the dynamic equations. Failure by the experimental data on space-time coupling to comply with these constraints would be seriously damaging to System-Dynamic theory. Conversely, the theory would receive strong support if the actual form of the coupling could be deduced from dynamic principles. Data on spatio-temporal coupling have been available for quite some time now (Binet & Courtier, 1893; Freeman, 1914). In the following section we present only a limited selection of recent results from experiments in which size and shape of the trajectory are controlled while the tempo is left unconstrained. The data are relative to drawing movements, but the main conclusions can be generalized also to other motor tasks.

P. fivhni and G. Laksard

10

6. Spatio-temporal coupling

Suppose you ask someone to draw continuously an elliptic trajectory of a certain size and eccentricity,without specifying, however, the speed of the movement. Each individual will select idiosyncratically a tempo which he is comfortable with and, as noted before, will spontaneously maintain a stable pace. Suppose now that you ask the same person to repeat the exercise doubling the size of the ellipse. What happens to the tempo ? Within the conceptual framework common to all motor program models, the question bears directly on the nature of the parameter ("knob)that is being controlled. If the average velocity used for the smaller trajectory were available in memory, and if the person were to maintain this internal reference, the tempo should then be halved. Conversely, if the relevant timing parameter were the period of a cycle, and again a spontaneous tendency existed to keep this parameter unchanged, the tempo should not be affected. Average (sea

4

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I

I

2

4

6

8

10

20

40

60

80

(cm)

perimeter P Figure 2. Relation between the perimeter P and the period T of ellbtic movements executed continuously. Each data point is the average of 12 measures (6 subjects and 2 trials). Different symbols are used to indicate the age of the subjects (A :adults). porn Viviani and Schneider, 1991).

Timing Control in Motor Sequences

11

velocity should instead be doubled. Experiments show that the new tempo is indeed slower than the previous one. The drop, however, is far smaller than 50%. Figure 2 summarizes the results of a study in which the spontaneous variations of the tempo were measured across a wide range of movement sizes both in adult and children (Viviani & Schneider, 1991). On average, a 20-fold increase in movement size results into mere three-fold increase in the period. Apparently, movement period is more rigidly constrained than average speed. Thus, although neither of the two extreme hypotheses envisaged above holds true exactly, tenants of the motor programming view would take these results as supporting evidence for the internal clock concept. Surely, the same results would have a different interpretation if we did not commit ourselves to the belief that kinematic quantities, such as average speed or period, are directly represented and controlled in the motor system. Indeed, relative invariance of these quantities across conditions can also be construed as the indirect result of a principled covariation among other quantities. It has long been known, for instance, that in many aperiodic movements (e.g. eye saccades, head rotations, handwriting) peak velocity scales with the linear extent of the trajectory so that movement duration is weakly dependent on movement size (cf. Viviani & Terzuolo, 1983). By analogy, the relative invariance of the cycle period in the data of Figure 2 may also be taken to suggest some compensatory mechanism whereby average speed over a movement cycle increases as a function of the perimeter of the ellipse. Although equivalent from mathematical point of view, this interpretation and the one based on the internal clock idea have somewhat divergent implications vis 6 vis motor control theory. Specifically, the former does away with the assumption that frequency or period are represented explicitly in the motor planning stage. The simple experiment that we have described cannot, alone, discriminate between competing interpretations. The following argument speaks, however, in favor of a velocity control. The clock hypothesis implies that timing in periodic movements is controlled by means that are different from those utilized in aperiodic ones where, by definition, there is no such a thing as a period, and where velocity scaling is well documented (see above). By contrast, there are data to suggest that velocity control might have similar compensatory roles in both cases. Without going into any detail, these data show that the instantaneous velocity of many (periodic and aperiodic) hand movements can be factored into two multiplicative components. One component depends on the curvature of the trajectory and accounts for the instantaneous modulations of the velocity (Viviani & Terzuolo, 1980,1982;Lacquaniti, Terzuolo & Viviani, 1983). The other component, called velocity gain factor, is constant over stretches of trajectory that correspond to identifiable units of motor action (Viviani & McCollum, 1983; Viviani & Cenzato, 1985; Viviani &

P. Wvhni and G. Laissard

12

Schneider, 1991). Analysis shows that the gain factor for a unit correlates positively with the linear extent of the corresponding stretch of trajectory. This correlation thus provides the basis for the so-called Zsochrony Principle (Lacquaniti, Terzuolo & Viviani, 1984) i.e. for the compensatory control of average velocity that is postulated in the covariance hypothesis. In conclusion, while the analysis of simple, continuous, periodic movements is compatible both with the internal clock model and with the notion that timing is instead an emerging property of the planning stage, the analysis of more complex, nonperiodic trajectories clearly favors the second possibility. 7. Rhythmic continuous movements

Just like tapping, also continuous movements may have a rhythmic structure and, in this case too, the structure can either arise from within or be imposed externally. Here we concentrate on the first case, the only one for which there are experimental results that we are aware of. Let us illustrate how these internally-generated rhythms can be investigated within the framework of the covariance hypothesis described in the previous section. Figure 3 shows typical recordings of two continuous drawing movements in which I-

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Figure 3. A,B: examples of continuous drawing movements. Experiments show that the average velocity over each figural unit is modulated by the corresponding perimeter. C: Rhythmicity emerges spontaneously during the execution of the pattern (A:from Viviani and McCollum, 1983; B, C :from Viviani and Cenzato, 1985).

Timing Control in Motor Sequences

13

there is evidence of rhythmic structure (Viviani & McCollum, 1983; Viviani & Cenzato, 1985). As we shall see in a moment, each of them exemplifies what we said in the first section about segmentation, namely that certain movements in which the tangential velocity never goes to zero can nevertheless be decomposed into units of motor action using the velocity control parameters as a criterion. Let us assume that a compensatory adjustment of average velocity as a function of linear extent is at work in the execution of the trajectories depicted in Figure 3. Moreover, let us qualify the covariance hypothesis by assuming that the units of motor action in these movements represent the portion of trajectory that is planned prior to execution. The question then arises: how large is this portion ? In order to address the problem, it is convenient to envisage two cases. On the one hand, one could surmise that trajectories such as those in Figure 3 are construed by the motor system as a whole (i.e. there is only one unit of motor action). In this case velocity should scale with the total perimeter of the figure. On the other hand, since the trajectories comprise distinct figural elements (for example, the small and the large ellipse in panel B), it could also be supposed that these elements are planned independently, and that the velocity within each element is scaled according to the corresponding linear extent. The two possibilities entail distinct predictions on the way the rhythm of the movement changes when one varies both absolute and relative sizes of the figural elements. We have demonstrated elsewhere (Viviani & Cenzato, 1985) that, if the double ellipse shown in Figure 3B is planned as a unit, the average velocity within the large (1) and small (s) loop are given by:

v, =

-1

v,

V~P, (p1+ps)a ~

-1 = V0Pd (P1+Ps)',

respectively, where V, is a constant, P, and P, are the linear extent of the loops and the exponent a is a parameter determined experimentally (.4 i a i .6). By contrast, if each loop is planned separately the isochrony principle predicts:

v,

1+(I = VoP1S

v,

1* a = V0Pp89

,

Then, it is immediate to verify that in the first hypothesis the ratio of the durations of the loops is equal to:

P. Kviani and G. Laissurd

14

In the second hypothesis one has instead:

Experiments with double ellipses in which the lengths P, and P, are varied (Schneider, 1987) have shown that the two possibilities are not mutually exclusive (Figure 4). When

do. 4

0.2

0.3

0.4

0.5

0.6

Log( P2/P 1 1

Figure 4. Coupling between the planning of two units of motor action. Double elliptic patterns such as those shown in Figure 3B where traced continuously and spontaneously. Both the overall size of the pattern (indicated by different symbols) and the ratio between the outer (2) and inner (1) ellipses where varied. Average velocity increases as a function of the overall size (see text). At the same time the slope of the relation (in log units) between the ratio of the perimeters and the ratio of theperiods decreasesfrom 0.65 to 0.45. Thefirst value agrees perfectly with the first hypothesis mentioned in the tat. The second approaches the value predicted by the second hypothesis (from Schneider, 1987).

Timing Control in Motor Sequences

15

the overall rhythm of the movement is relatively slow (less that 1 complete cycle per second) the total period is divided into two intervals whose ratio is well predicted by the first hypothesis. However, as one progressively increases the rhythm, the ratio T,/T, changes pan' pmsu and approaches the value implied by the second hypothesis. Similar results can be obtained for other trajectories similar to those in Figure 3. On the basis of these results we speculated that both possible representations of the trajectory (i.e. the global and the segmented one) are entertained simultaneously by the motor system, and that the relative weight of these representations in the control of velocity changes with the overall rhythm. However, it is only fair to stress that, although the covariation hypothesis accounts satisfactorily for the rhythmic features of certain spontaneous motor performances, overt time structure in these performances may still be a n indirect consequence of velocity control without entailing necessarily the existence of a corresponding internal representation. From what we have seen so far, one cannot yet rule out conclusively the more parsimonious view that such a representation is needed only in those motor tasks - like musical performance - where the time structure is imposed from without.

In a subsequent section some data on typing will be presented suggesting that such a parsimonious view is not really tenable. Before turning to these matters though, we would like to hark back once more on the opposition between the motor program concept and the competing view that time structure (at least in spontaneous movements) is an emerging property of the movement execution stage. The classical motor program scheme may well be insufficient to explain some of the data on continuous periodic movements, if only because it provides no clue as to how the "speed knobs" are actually controlled. Nonetheless, to the extent that the scheme is consistent with the very same concept of internal representation that is countenanced by the covariance hypothesis, one can conceive of suitable qualifications of the general idea for accommodating also these data. Current versions of the "emerging properties" view are equally inadequate to account for the time structure of certain complex movements. The inadequacy, however, seems to be of a more fundamental nature. By renouncing to all forms of representation, it becomes in fact difficult to imagine how non-linearities and limit cycle properties alone can come to grips with the phenomenon of isochrony. An example of the limitations inherent to whatever approach does away with internal representations is provided by the so-called "cost-minimizing'' models for trajectory formation (Hogan, 1984; Uno, Kawato & Suzuki, 1989). It can be demonstrated mathematically that a motion is specified uniquely by the stipulation that the motion minimizes some quadratic measures of cost. Under the sensible assumption that biological systems are optimal in this sense, a set of boundary conditions is sufficient to predict both form and kinematics of any movement between two points. Furthermore, it can be shown by simulation that if one specifies a mandatory

16

P. Kviani and G.Lairsard

via point for the movement which divides the trajectory into two segments of unequal length, the average velocities across segments scale with the corresponding lengths as predicted by the isochrony principle (Flash & Hogan, 1985). All this seems very promising were it not for the fact that, in all cases, the total duration of the movement is one of the boundary conditions. The formalism does not (and cannot, in principle) predict the experimental fact that average velocity increases pan' pmm with the total linear extent of the trajectory. As we argued before, such a covariation requires the availability, before the inception of the. movement, of an internal representation of the trajectory length. A more specific critique of the "emergingproperties"view is postponed until some recent results on contextual effects in motor sequences are introduced. 8. Language-related motor sequences

Language production in all its forms - speaking, typing, handwriting - represents an ideal form of serial motor behavior for addressing some of the issues left open at the end of the previous section. The main features of language-related motor sequences are the following: 1 - Language is fundamentally discrete. To some extent all forms of language production partake the discrete nature of the message (cf Butterworth, 1980,1983; Levelt, 1989). Although handwriting and speaking movements are physically continuous, there is evidence that the segmentation of the message into a hierarchy of units (letters, words, phonemes, syllables) is reflected into the motor output. Segmentation is also present in discontinuous forms of production such as typing (Shaffer, 1978) and Morse code tapping (Bryan & Harter, 1897,1899) where linguistic units correspond to systematic groupings of the strokes ,

2 - Unlike music playing, the timing of the motor sequences used to express language is normally not prescribed. Basically, these sequences are self-paced.

3 - Whatever the mode of expression, a continuously updated portion of the linguistic message must be represented centrally prior to the actual transcoding into a motor output.

- Physical and biological constraints do play a role in the temporal structuring of the motor output. These factors, however, are not nearly as important as in most other forms of movement involving large masses. Finally, and in a similar vein,

4

5 - Language production is mediated by physiological mechanisms that, philogenetically,

Timing Control in Motor Sequences

17

did not evolve for that purpose. It is probably no accident that these mechanisms are much more flexible and less stereotyped than those which subserve more primitive functions, such as locomotion or breathing.

In sum, at the molar level of analysis that is relevant here, language motor sequences are aperiodic, discrete and self-paced. Let us consider first the implications of point 3 above for the debate on the nature of motor planning. The key issue in this debate is whether: a) the linguistic representation of the intended message per se is sufficient to drive directly the execution of the chain of units of motor actions that correspond to linguistic units, or: b) it is necessary, before execution, to translate the linguistic representation into a corresponding motor representation. Since hypothesis a) is more parsimonious than hypothesis b), the burden of the proof lies entirely on the latter, and our question can be reformulated as follows: what kind of findings about language production can count as evidence for a programming stage? 9. Motor programs, again

Before attempting to answer the above question on the basis our own current research on typing it is necessary to sharpen the definition of the term "program". In the literature this term is used (and occasionally misused) in many different ways. A core meaning does emerge, however, at the intersection of a few, basic qualifications: 1 - A motor program is a preordained set of instructions for specifymg the various aspects of the movement. The set is represented somewhere in the motor cortex. 2 - The set itself, and the nature of its constituents are independent of sensory afferences.

3 - Instructions are mandatory. However, they may be parametrized. This affords the program with flexibility. 4 - The parameters are specified by nervous processes that are independent of the program. Parameter setting may be dependent on sensory inputs. It may also depend adaptively on reafferences. Hence, parametric control provides the basis for motor learning.

Even from this synthetic definition, it should be obvious that motor programs, if they exist at all, bear little relationship with the familiar computer programs. In particular, motor programs are not supposed to implement algorithms nor, indeed, to perform any kind of symbolic calculation. Their instructions refer directly or indirectly to overt

18

P. Viviani and G.Laksard

dynamic and/or kinematic variables. Thus, quite unlike what happens in computers, the parameters of the motor program specify the modalities of the execution rather then the result. This is most clear with timing parameters which, supposedly, regulate the pace at which the instructions are executed. Such a regulation, of course, is neither possible nor in fact relevant in a computer program. The way which absolute and relative timing are controlled in a sequence of movements is considered important in the debate on the nature of motor programs. In particular, proportional scaling - i.e. the possibility of modulating the total duration of a motor sequence while preserving the ratio among the durations of the components - is often cited as convincing evidence in favor of parametric programming (cf Keele, 1981; Schmidt, 1988). According to Summers (1975) relative timing is an integral part of the motor program and cannot be entered independently of the sequencing. Some authors (e.g. Carter & Shapiro, 1984) assume, implicitly or explicitly, that parametric control of speed implies proportional scaling and viceversa. Others (Heuer & Schmidt, 1988) suggest instead that proportional scaling is but one of the options the motor program has, an option that is taken whenever ratio invariance has strategic value in the general economy of the movement. Conversely, violations of the proportional scaling rule have been cited in arguments against the necessity to postulate a central representation of the motor plan (Gentner, 1987). Gentner considers that proportional scaling is, at the very best, a convenient approximation for describing some very special instances of movement (see later). If so, he reasons, there is no longer a valid motivation for postulating an (explicit) parametric control of timing. Before taking up the empirical question of whether proportional scaling is a real phenomenon, let us remark that the importance of the phenomenon in the debate on the reality of parametric programming has been perhaps overstated. To begin with, the assumption is often made that parametric scaling of time - provided that it exists - must be ratiomorphic (i.e. linear). The premise is appealingly simple, but it obscures the fact linearity is neither a sufficient, nor a necessary condition for parametric control. The importance of scalability for motor programming is not contingent upon linearity and should be assessed independently of this further qualification. Unfortunately, no attempt has been made so far to test specific nonlinear models. Further, the hypothesis that serial order results from the interplay among activation, competition for limited resources, and constraints (Rumelhart & Norman, 1982) - an hypothesis which amounts to dismiss the very notion of a central representation of the motor plan - is not really incompatible with proportional scaling. Indeed, many physical processes that have nothing to do with motor programming result into linear covariations among observable quantities. Notice that nothing in the definition of motor program adopted here refers to how timing is specified

Timing Control in Motor Sequences

19

other than by stipulating that processes "outside" the program itself take care of this aspect of the movement. Accordingly, the definition is neutral in this debate in the sense that it can accommodate the different positions summarized above and many others as well. At the moment, we believe, the status of proportional scaling ought to be debated exclusively in empirical terms by investigating if, when and how the phenomenon occurs. 10. Is proportional scaling real ?

In his review Gentner (1987) searches for evidence of this particular scaling rule through a wide range of movement types. According to this author the results in the literature are inconclusive (due to methodological problems) for arm and wrist movements, convincingly negative for most locomotion movements, mixed for speech and handwriting, and negative for typing. Departures from proportionality may indeed be expected in walking where stance and swing components of the Philippson step cycle have an entirely different nature. Even so, however, the proportion of the cycle occupied by the two phases is weakly dependent on walking speed (Shapiro, Zernicke, Gregor & Diestel, 1981). That timing changes are not ratiomorphic can also be expected when one looks at fine-grained details of speech movements such as the relative duration of the syllabic components. It is known in fact that, at the phonetic level, assimilatory and Kent & Minifie, 1977; Fowler, 1980) and coarticulatory phenomena are conspicuous (6. that decelerations of the rhythm occur at segmental boundaries (Klatt, 1976). By contrast, systematic departures from proportional scaling in tasks such as handwriting and typing, if confirmed, would indeed mean trouble for the whole concept. Let us then consider in some detail the typing task and the form that the proportional model takes in this case. Professional typists can modulate intentionally the average typing rate, either in response to an explicit request to do so, or to comply with some external constraints (such as, for instance, the necessity to minimize error rate). Moreover, even under steady operating conditions, the time that it takes to type a given word fluctuates spontaneously by as much as 70%. Irrespective of the reasons why the duration of the typing sequence for a word may change from one instance to another (see Shaffer, 1978; Terzuolo & Viviani, 1980), the proportional model states that changes result from the combined effects of a single rate parameter and of motor variability. Suppose you ask a typist to transcribe n times a word with m+ 1 letters (m interstroke intervals). Let d, denote the interval between letter j and j+ 1 in the i-th repetition, and Ti the total word duration for that repetition. Then, changing slightly Gentner's (1987) notation, we express the proportional scaling model by the following relation:

20

P. Eviani and G.Laissard

In this equation K,is the rate parameter that may change from one repetition to the next but stays constant within any given typing sequence, (Dj,j = 1,m) is the (abstract) central representation of the word template, and e is a term that summarizes all sources of variability that affect the transcoding between the central representation and the keypresses. By definition, the latter component is never under voluntary control, and is modelled conveniently by a random variate with a mean of 0 and constant variance. The modelling of the rate parameter K depends instead on the context in which the typing task is executed. If duration changes are only due to spontaneous rate fluctuations, K too can be modelled by a gaussian random variate with constant mean and variance. If equation 1 is to account also for intentional and systematic modulations of typing rate, the parameter K is best conceptualized as a component, as one usually does within a fixed-factor scheme for the analysis of variance. Here we consider only the case of spontaneous fluctuations.

To test the validity of the proportional model in the presence of spontaneous rate fluctuations Gentner (1987) proposed the following strategy. Consider, for any pair of letters in a given word, the slope sj of the linear regression across repetitions between the total word duration Ti and the normalized interstroke interval dij/T,. The proportional model implies that this slope should be close to zero. Statistical procedures can be used to decide, with a preassigned rejection criterion, whether sj differs from this theoretical value. Consider next the set of regression slopes for all letter pairs within many words, each of which is typed several times. Gentner suggests that the model must be rejected if more than the expected number of slopes turns out to be significantly different from zero. Thus, for instance, if one adopts a 0.05 rejection criterion for each regression, no more than 5% of the slopes can exceed the critical value associated to that criterion. The application of this test both on his own data and on two recordings published by Terzuolo and Viviani (1979,1980) led Gentner to reject the proportional model for typing. The test is not completely rigorous because the errors in the two variates being correlated are not independent. However, as noted by the same Gentner, the problem can be fiied by raising the critical value in the statistical test by an amount that can be estimated through numerical simulation. Other objections to the strategy outlined above are instead more serious and undermine the validity of the conclusion that has been reached. To begin with, one can question the very idea of considering each regression on an equal footing and pooling together the results for pairs of letters that belong to different words. Indeed, too many lines of evidence point to the fact that word sequences constitute a coherent motor unit for such a strategy to be justified. Secondly and more

Timing Control in Motor Sequences

21

importantly, it is questionable whether proportional scaling should be dealt with as ayesor-no issue and settled in statistical terms as one does to ascertain the presence of an experimental effect. Accurate ratiomorphic scaling across many letter pairs cannot be the result of chance, much less so if it occurs in about 65% of the tested pairs (see Table 5 in Gentner, 1987). If in fact the phenomenon is present in a substantial number of cases (and by this we mean words, not letter pairs), the interesting scientific question is why it does exist in those cases and not in others. Plainly, certain regularities in motor behavior are important even if they do not manifest themselves in 95% of the cases. 11. New data confirm the proportional model A sensible strategy to assess the relevance of the proportional model should be based

on two principles: 1) The accuracy with which equation 1 describes interval modulations must be tested globally for all pairs within a word, and 2) Deviations from linearity for a set of words must be used to evaluate a global index of adequacy of the model. Such a strategy was implemented to analyze typing sequences produced by two professionals. One-line pseudo-sentences were created by choosing at random among a basic set of 30 english words (we describe later the criterion with which the words were selected). Pseudo-sentences were displayed sequentially on the computer screen and transcribed immediately by the typist. 120 repetitions of each of the 30 words in the set were recorded, but we eliminated the first 10 occurrences of the word in the session and the 10 longest instances. Among the 100 word sequences retained for analysis spontaneous fluctuations in duration were of the order of 60%. Data analysis involved four steps. First, the sequence of keypress times for each repetition was symmetrized with respect to its center of gravity. The second step was to estimate simultaneously the quantities K, and Dj by fitting equation 1 to the measured intervals d, with a least-square technique. Figure 5 A shows a typical example of the resulting linear regression through all the data points for one word. Although this is not visible in the figure, the bundle of regression lines converges into a single point. The accuracy with which equation 1represents the actual results is quite good as one can see from the correlation coefficients associated to each line. Panel B in the same figure illustrates the result of the third step of the procedure which consisted, so to speak, to pull to infinity the point of convergence of the bundle so that all regressions lines become parallel. Finally, the fourth step was to perform a two-way analysis of variance of the intervals d, both before and after step 3. The first (nominal) factor in this ANOVA is the letter (index j) within the word. The second factor is the total duration Ti of the sequences (the 100 repetitions were divided into 10 batches of 10 instances each). Since sequences are symmetrized (step 1above) the amount of rate modulation can be gauged

P. Viviani and G.Laksard

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Timing Control in Motor Sequences

23

by the size of the F-ratio for the interaction between factors. The huge value of this ratio before step 3 (Panel A) confirms what we said before, namely that spontaneous rate modulations were indeed quite large. The same interaction F-ratio after step 3 (Panel B) measures instead the extent to which the proportional model captures the nature of these modulations. If the interaction turns out to be non-significant, one can be satisfied that the proportional model is an excellent approximation to the data. Moreover, even if the value of the F-ratio is greater that the selected critical threshold, as in the example shown, one can still use this value as a descriptive statistics of the deviations from linearity. Steps 1to 3 above involve certain mathematical arguments that need not to be detailed here (Viviani and Laissard, in preparation). Suffice here to say that the algorithm implemented in these three steps is more efficient than the one described earlier by Terzuolo and Viviani (1980), and its interpretation is more intuitive. Moreover, the distribution of the variances across repetitions of the keypress times after step 4 is somewhat different. Aside from that, there is no qualitative difference between the results obtained with this improved technique and those obtained with the earlier one. The Fratio for the example shown in panel B of Figure 5 is larger than most of those that measured in the two professional typists whose data have been fully analyzed so far. Even so, the alignment of the data points can be considered quite good, as far as the results of behavioral experiments go. Thus, contrary to the conclusions reached by Gentner (1982,1987), we feel confident that proportional scaling is a significant feature of the control of timing in professional dactylography, at least within the range of duration variations that are observed spontaneously. Departures from ratio invariance in the scaling of interstroke intervals do occur for some words. They do not detract, however, from the reality of the ratio-preserving property for which we coined the term Homothetic Principle. 12. Contextual effects confirm the template model

The demonstration that the homothetic principle applies to such a highly complex serial behavior as typing represents a valuable contribution to the understanding of timing control. We have already warned, however, that such a demonstration, by itself, does not afford a decisive argument for justifying the concepts of motor program and motor representation. What else could then be the hallmark of a motor program, the piece of evidence that would truly be at odds with the competing activation theory ? One obvious candidate is the presence of hierarchical dependencies in either the spatial or temporal characteristics of the motor sequence. Attempts to identify such dependencies have been made in the case of rhythmic tapping but, as we mentioned before, the case for a

24

P. Eviani and G.Lahard

hierarchy there is not unequivocal. More conclusive evidence comes instead from the analysis of certain aperiodic sequences such as those that compose a fetching movement of the hand. As shown by Jeannerod and his group (cf Jeannerod, 1988) the transport phase of the hand toward the object, the shaping of the fingers, and the closing of the fingergrip unfold in time in a fashion that strongly suggest hierarchical coordination. Evidence for motor programming also comes from the analysis of the relative variance of kinematic and dynamic variables. It is an old qualitative observation that, in many skilled movements, the variability, both in time and space, of the terminal phase of the movement is smaller than that of the preceding phases. Thus, for instance, if you are hammering down a nail, the position in space of the elbow varies more across the series of blows than the position of the hammer’s head. This is difficult to explain within the framework of the activation theory because the more distal biomechanical segment should inherit the variability of all the preceding proximal segments. Instead, as pointed out by Bernstein (1967) half a century ago, and by many others thereafter, there are schemes within the motor program viewpoint for allaying this difficulty. The relation between the complexity of a motor response and the latency for initiating the response in a RT paradigm provides further support to the Motor Program view. Studies in speech (Klapp, Anderson & Berrian, 1973; Sternberg, Monsell, Knoll & Wright, 1978) and Morse code tapping (Klapp & Wyatt, 1976) have shown that latencies increase with the number of units of motor action in the response (for additional evidence, see Kornblum and Requin, 1984). This strongly suggests that some advance planning for the ensuing movement must take place before its inception. More specifically, there must be at least one level of the planning where the movement is represented as a sequence of units. Finally, a forth - and, in our view, more cogent - kind of evidence in favor of the motor program concept comes from the analysis of contextual effects. What these effects are, and why they are relevant to our question, is again illustrated by some experimental analyses of the typing skill. We saw that typing is a prime example of discrete, sequential movement; moreover, it is aperiodic since - contrary to popular belief - skilled typists do not press keys at a even pace. There are several reasons for the presence of rhythmic structure in the sequence of keypress intervals. First come the constraints related to the execution itself. Biomechanical and physiological reasons induce a ranking into the average interval between successive keypressings. From the longest to the shortest one has: letter pairs typed with the same finger, those that require two fingers of the same hand, pairs of identical letters, and pairs that require the use of the two hands. Since a rigid association between fingers and keys is an integral part of the typing skill, part of the rhythm reflects simply the standard outlay of the letters on keyboards (the so-called QWERTY outlay). A second component of the rhythm is the relative frequency of the digrams in the

Timing Control in Motor Sequences

25

language. It has been shown that, over and above keyboard constraints, frequent pairs are, on average, typed faster than rare ones (Fox & Stansfield, 1964; Terzuolo & Viviani, 1980) (notice, however, that a major concern in the design of the keyboard was to prevent letterbars from getting tangled; thus, some frequent digrams were assigned to distant keys). Thirdly, typing rhythm is influenced by the nature of the text being transcribed. When the text is a piece of normal prose, rhythmic modulations are normally quite consistent across repetitions. Instead, when real words are replaced by random sequences of letters, the pace at which keys are pressed slows down (Genest, 1956). At the same time the intervals become much more variable. Both effects are reduced but are still present when the distribution of the spaces between sequences is the same as in real prose (Thomas & Jones, 1970). These three sources of rhythmic modulation can be accommodated within the general framework of activation theory. Also modest variations in the temporal structure for small letter groups embedded in different words can perhaps be accommodated because the theory predicts the presence of coarticulatory effects. Not much more can, however. In particular, the theory bars the possibility of extensive contextual effects. In fact, Shaffer (1978) found significant differences between the interstroke intervals for words like Whig and whim which share the initial 3-letter sequence and interpreted these differences as evidence for preplanning or preprogramming of the typing movement. Shaffer's conclusion might still be questioned because he did not control the left context of the triples. However, the basic idea of his experiment is correct, and the paradigm that he used can be improved easily to eliminate all possible doubts. Consider the words daughter and laughter which share the 7-letters sequence a-u-g-h-t-e-r. The difference in meaning (and in pronunciation) between the two words is due only to the first letter. Therefore, according to activation theory, "coarticulation" effects are expected only in the immediate surrounding of this sole difference. Thus, for instance, the g-h-t group should be typed in the same way irrespective of the context in which it embedded. More generally, any letter triple deeply embedded into identical contexts should give rise to identical motor sequences. A recent experiment has shown conclusively that this is not the case. We selected in the Oxford dictionary 15 special pairs of words. Each word in a pair shares a seven letters string (e.g. twitted and outwitted, pliantly and valiantly). "Sentences" formed by random permutations of these 30 words were transcribed repeatedly by professional typists (the same material was also used for the analysis of temporal scaling). Attention was concentrated on the letter triples at the center of the identical strings common to the word pairs (i.e. itt and ant in the examples above). Let T, and T, be the intervals between the first and the second letter, and the second and the

P. Uviani and G. Laissard

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Figure 6. Contextual effects in the structure of motor sequences used for typing. Data in two professional typists (upper and lower panels). Each panel compares two cumulative probability distributions of parameter b defined in the t a t for the indicated letter triples. Distributions are calculated on the basis of I00 repetitionsfor eachpair of words. Lejlpanels compare the results obtained in different days when the triples are embedded in the same word The distributions are almost indistinguidmble,indicating the high level of consistency in the motor performances of the subjects. Right panels compare the distributions of 6 for letter triples embedded in different words. The fact that the distributions are sie@cantly different demonstrates that the temporal structure of the typing sequences is, in general, dictated by the entire word and not by local letter clusters.

Timing Control in Motor Sequences

21

third letter of the target triple, respectively. The time structure the triple can be summarized by a single variable 6 = (T2-Tl)/(T2+Tl).Figure 6 compares the cumulative distributions of 6 for 2 of the 15 pairs (each curve is based on 100 repetitions). For all pairs the two distributions are significantly different (P < < 0.0001 at the Kolmogorov test). Since target triples are flanked by the same letters pairs, these results demonstrate the existence of a component of the local structure that depends globally on the word being typed (possibly, on the pronunciation of the word), and not on the immediate context within the sequence. On the basis of this evidence we feel justified in rejecting activation theory as well as any other account of the time structure in typing sequences that considers this structure only as an emerging property of the implementation stage. By the same token, also feel justified in proposing that some form of motor programming must take place between the linguistic coding of the input and the delivery of the motor commands. To be sure, the data are too limited to speculate on the nature of such an intermediate stage. Nonetheless, they are sufficientto establish that, within this stage, a continuously updated chunk of the output is represented in fairly abstract terms (the motor template). Notice in fact that the discriminating variable b depends only on the ratio between the two successive intervals TI and T,,and not on their actual duration. 13. Conclusions

The quest for one general scheme for the control of timing in motor sequences is probably hopeless. To be sure, there are few cases in which a solution is so strongly supported by experimental evidence to rule out alternate explanations. Yet, for each type of movement there is at least one scheme that seems to be more plausible than the others. So we end up with a number of conceptual models that are only loosely connected to each other. Force pulses are the most likely candidates for the role of controlled variable in continuous aperiodic movements. Whether pulse intensity or width or both are preset before movement inception is still open to debate. Plausible arguments have been presented for assigning to velocity an important role in setting up the rhythmic properties of continuous periodic movements. The arguments make reference to an internal representation of the metrical properties of the movements and, therefore, share some of the premises of the motor program view. For the same reason, these arguments lead to a conflict with the System-Dynamic view which, in its turn, provides one of the most convincing accounts of certain phenomena of bimanual coordination (Kelso, 1984). Time intervals are supposed to be represented and controlled directly in discrete periodic movements such as rhythmic tapping, but we have seen that clock models fail to capture certain peculiar features of the actual performances. Finally, the analysis of an important class of discrete aperiodic movements (typing) has led us to postulate the existence of motor templates. These abstract internal representations (the D values in equation 1)

P. Kviani and G.Lahard

28

differ from those hypothesized by clock models insofar as they do not specify directly the timing of the sequences. Nevertheless, both constructs fall within the general category of central blue-print that is common to all motor programming theories.

As a conclusion, let us reiterate once more that the phenomenon of proportional scaling for typing does not suffice per se to settle the debate on whether or not it is necessary to countenance a motor programming stage, let alone to specify how this putative stage might be organized. However, to the extent that contextual effects - such as those demonstrated in the last section - are incompatible with a radical rejection of any form of internal representation, at least one component of the motor program concept (point 1 above) seems to have some relevance. Acknowledgments: The preparation of this chapter has been partly supported by FNRS Research Grant 31.25265.88 (MUCOM ESPRIT Project). We are grateful to Natale Stucchi for discussing with us many of the issues considered here.

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Turvey, M.T., Rosenblum, L.D., Schmidt, R.C., & Kugler, P.N. (1986) Fluctuations and phase symmetry in coordinated rhythmic movements. Journal of Experimental Psychology: Human Perception and Performance, 12, 564-583. Uno, Y., Kawato, M., & Suzuki, R. (1989) Formation and control of optimal trajectory in human multijoint arm movement. Biological Cybernetics, 61, 89-101. Viviani, P. (1986) Do units of motor action really exist ? In: H. Heuer and C. F r o m (Eds.) Generation and Modulation of Action Patterns. Berlin: Spinger Verlag, pp. 201-216. Viviani, P., & Terzuolo, C.A. (1980) Space-Time invariance in learned motor patterns. In: G.A. Stelmach and J. Requin (Eds.) Tutorials in Motor Behavior. Amsterdam: NorthHolland, pp. 525-533. Viviani, P., & Terzuolo, C.A. (1982) Trajectory determines movement dynamics. Neuroscience, 7, 431-437. Viviani, P., & Terzuolo, C.A. (1983) The organization of movement in handwriting and typing. In B. Butterworth (Ed.) Language Production :vol II. Development, Writing and Other Language Processes. New York, NY: Academic Press, pp. 103-146. Viviani, P., & McCollum, G. (1983) The relation between linear extent and velocity in drawing movements. Neuroscience, 10, 211-218. Viviani, P., & Cenzato, M. (1985) Segmentation and coupling in complex movements. Journal of Experimental Psychology: Human Perception and Performance, 11, 828-845. Viviani, P., & Schneider, R. (1991) A developmental study of the relation between geometry and kinematics in drawing movements. Journal of Experimental Psychology: Human Perception and Performance, 17, 198-218. Vorberg, D., & Hambuch, R. (1978) On the temporal control of rhythmic performance. In: J. Requin (Ed.) Attention & Performance UI.Hillsdale, NJ: Lawrence Erlbaum Associates, pp.535-555. Vorberg, D., & Hambuch, R. (1984) Timing of two-handed rhythmic performance. In: J. Gibbon and L. Allan (Eds.) Timing and Time Perception. Annals of the New York Academy of Science Vol 423. New York: New York Academy of Science, pp. 391-406.

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Wing, A.M., & Kristofferson A.B. (1973a) The timing of interresponse intervals. Perception & Pychophysics, 13, 455-460. Wing, A.M., & Kristofferson A.B. (1973b) Response delays and the timing of discrete motor responses. Perception & Pychophysics, 14.5-12. Young, D.E., & Schmidt, R.A. (1990) Units of motor behavior: Modifications with practice and feedback. In: M. Jeannerod (Ed.) Attention & Performance XUI. Hillsdale, NJ: Lawrence Erlbaum Associates, pp. 763-795.

The Development of Timing Control and Temporal Ckganization in Chrdinated Action J. Fagard and P.H. Wolf€ (Editors) d Elsevier Science Publishers B.V., 1991

37

Invariant relative timing in motor-program theory Herbert Heuer Fachbereich Psychologie der Philipps-Universitat, Gutenbergstr. 18, D-3550 Marburg, FRG One of the aggravations in motor research is the large number of different human movements. Although our everyday language provides us with well-established categories to manage this manifold, there is no well-defined and generally accepted classification system which satisfies scientific criteria. In the face of an almost unlimited variability it is comforting to have some invariant characteristics. Invariant features can be used as defining characteristics for sets .of movements. More importantly, they suggest inferences about the nature of internal representations or structures that underly movement production. This chapter is about an invariance that has received a great deal of attention, the invariance of relative timing. I shall start with a brief description of the phenomenon and its incorporation into a particular kind of theory, the notion of a generalized motor program. In the second section several points of criticism will be discussed that can be raised against the phenomenon and its theoretical underpinnings. Finally, a relaxed concept of a generalized motor program will be outlined. Before all this, however, I want to remind the reader that this chapter is written from a particular theoretical stance and that it neglects other perspectives on the phenomenon of invariant relative timing (e.g. Kelso, 1981). In spite of this constraint it contains some material which is relevant for the phenomenon itself and quite independent of its theoretical interpretation. 1. A PHENOlzENON TO CLOSE A THEORETICAL GAP

The apparently seminal observation of invariant relative timing can be found in a technical report by Armstrong (1970). His subjects had to learn a pattern of elbow flexions and extensions. Occasionally they got the target duration of 4 s wrong in their reproductions. In these instances it seemed that they compressed or expanded the whole pattern fairly uniformly. Following Armstrong's rather accidental observations relative timing has been studied more systematically, and several reports of its invariance when total duration was varied have been published. Reviews are available (e.g.

H. Heuer

38

Schmidt, 1985; Gentner, 1987) so that there is no need to present the data in detail again. Invariant relative timing has been found in different skills and with different methodologies. With regard to skills, briefly practiced experimental tasks have been used like the one of Armstrong (1970) or sequences of key presses (e.g. Summers, 1975) and discrete aimed movements (e.g. Carter & Shapiro, 1984). On the other hand, highly practiced skills were studied in which the relative timing was self-selected rather than experimenter-imposed, e.g. typing (Terzuolo & Viviani, 1979, 1980) or walking/running (Shapiro, Zernicke, Gregor & Diestel, 1981). With respect to methodology relative timing has been compared across conditions in which total duration was varied explicitly by way of different instructions, or the variance of relative timing has been examined taking advantage of the spontaneous variability of total duration. Many other methodological differences between studies are apparent, and some of them will be touched upon below. For the moment I shall take the phenomenon of invariant relative timing for granted and consider its formal description. Depending on how movement characteristics are measured, there are at least two different ways. The first description refers to a continuously recorded signal like position, velocity or acceleration of a limb. The invariance of relative timing in this case is equivalent to scaling the argument of a prototypical curve f(t) by a rate parameter r+ which varies across different productions i of the movement but is constant during each single execution: fi(t)

=

f(t/ri)

(1)

In this equation fl(t) is the signal as recorded for a single execution i of the movement: it is derived from the prototypical curve f(t) by way of a uniform temporal expansion (rol) or compression (ri=ring

(2)

with x1.3 as the duration of segment j in execution i, r+ as the rate parameter, and nj as the prototypical duration of the segment.

Invariant Relative Timing in Motor-Propm Theory

39

In most studies relative-timing invariance has been tested for segment durations rather than for continuously recorded signals. Among the reasons for this preference are probably the nature of the recordings which for many tasks are not continuous and the suitability of discrete segment durations for a conventional statistical treatment like analysis of variance or regression analysis. However, it should be noted that Equations (1) and (2) are not really equivalent. While Equation (2) is implied by Equation (l), the reverse is not true. Equation ( 2 ) can hold for some but not all of the possible segmentations of a motor pattern, and only when it holds for all segmentations it implies Equation (1). The phenomenon of invariant relative timing hit upon a theoretical gap that had appeared in the early seventies. At that time the notion of a generalized motor program has been developed independently in several places (e.g. Kalveram, Merz & Riegels, 1973; Pew, 1974; Schmidt, 1975). The most explicit and detailed treatment which probably made the concept popular was the one by Schmidt (1975); the historical and experimental background of the notion is described in several review chapters (e.g. Summers, 1989; Heuer, 1990a). Basically a generalized motor program is thought to control a set of movements with certain common characteristics. The specifics of each member of the set are determined by the program's parameters which serve to adjust the basic pattern quickly to the particular demands. For the parameters to serve this purpose, there must be rules available which specify the parameter values that result in the desired characteristics of the movement. Such rules have been called lgschematall by Schmidt (1975). As long as no explicit statements are made about the common characteristics of a set of movements and the variable characteristics that are determined by parameters, the notion of a generalized motor program is somewhat like an empty shell. This then is the theoretical gap that waited to be closed by some results on invariant characteristics of sets of motor patterns. Schmidt (1980, 1985) took the step to hypothesize that the relative timing is a common characteristic of a set of movements that are under control of the same generalized motor program, while total duration (or average speed) is determined by parameters. This step apparently is straightforward. The resulting concept will be called a generalized motor program with invariant relative timing. The notion of a generalized motor program with invariant relative timing has found its most explicit formulation in impulse-variability models for rapid aimed movements (Schmidt, Zelaznik, Hawkins, Frank & Quinn, 1979; Meyer, Smith & Wright, 1982). These models posit the validity of Equation (1) for force-time curves, that is, they assume "shape constancyll (Schmidt, Sherwood, Zelaznik & Leikind, 1985). However, the notion is not limited to rapid aimed movements. After all,

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invariant relative timing had been observed in various other motor patterns which often had a duration of some seconds rather than only a few hundred milliseconds. Before I turn to arguments that complicate the phenomenon of invariant relative timing and its embrace by motor-program theory, I want to emphasize two points. First, the notion of a generalized motor program with invariant relative timing is conceptually simple and thus attractive. It generates welldefined sets of movements with a common characteristic, namely relative timing (or temporal pattern), several testable predictions can be derived from it, and it provides conceptual underpinnings for the study of discrete units in temporally extended motor patterns. Second, there is a simple and wellknown principle for its implementation (cf. Lashley, 1951; Rosenbaum, 1985): when a spatial representation of events is read, like in retrieval from a computer memory or in the serial activation of a chain of neurons, a temporally ordered sequence of events will result. The duration of the sequence depends on the %lock rate", that is, the speed of reading, but its relative timing remains invariant across different clock rates and thus different total durations. 2.

QUESTIONING THE NOTION OF A GENERALIZED HOTOR P R O G M WITH INVARIANT RELATIVE TIMING

In this section the simple story about a phenomenon to close a theoretical gap will be called in question. First I shall ask whether relative timing is really invariant, and the conclusion will be negative. This, however, does little or no harm to the notion of a generalized motor program with invariant relative timing because of the slightly ironic argument that the concept, which has been derived from observations of invariant relative timing, does not predict the phenomenon except for special conditions. However, and this will be a second point, other predictions can be derived which failed to pass experimental tests. The third point, finally, is the argument that the notion of relative timing as an essential characteristic of a generalized motor program reintroduces a conceptual difficulty that originally the concept had been designed to avoid. IS relative timing invariant? Invariance of relative timing has been observed in several experiments, but there are also several studies which failed to find support. Inconsistencies are of two different types that will be considered in turn. First, different conclusions can come from studies of different motor patterns or different variations of a particular pattern. Such inconsistencies primarily indicate that the concept of a generalized motor program with invariant relative timing may have a limited domain of validity. Second, different conclusions do also come 2.1.

Invariant Relative Timing in Motor-Program Theory

41

from studies of almost identical tasks, even from analyses of identical data sets, and these inconsistencies appear to pose more serious problems.

2.1.1. The generality of relative-timing invariance There are at least two dimensions on which the generality of relative-timing invariance can be assessed. The first one is the task dimension. In principle it is possible, or even likely, that relative timing is invariant for only some tasks but not for others. At least there is no convincing a priori reason for relative timing to be an essential characteristic of all generalized motor programs. As far as I am aware, however, there is no clear-cut evidence on task differences. But, there are some motor patterns which require an additional assumption to maintain the claim that their relative timing is invariant. Consider a very simple up-and-down movement of the index finger. Heuer (1984a) varied the duration of this movement. When his subjects increased the movement time from 200 to 4 0 0 ms (under the instruction to start the movement as rapidly as possible upon presentation of an imperative signal), they did so by increasing the duration of the reversal segment while the durations of the up and down strokes were hardly changed. Thus total duration was raised primarily by modification of the duration of a particular segment. Similar observations have been made in more complex motor patterns like swimming or throwing (cf. Roth, 1987). Motor patterns which contain Itdistinguished segments" for the modification of total duration do not exhibit invariant relative timing as a whole. However, there is no particular reason to claim that relative timing should be invariant for whole patterns. Motor-program theory is not explicit about the duration of a program. According to some data a program might control a motor pattern for a few seconds (e.9. Shapiro, 1977; Monsell, 1986), but its temporal domain could also be much smaller. Thus it can be assumed that some patterns are controlled by two or more programs in sequence. Relative timing should be invariant within the temporal domain of each single program only, and the timing at the transition between programs remains somewhat in the air. In fact, the invariance of relative timing can be used to identify the boundaries between segments that are controlled by different motor programs. An example has been provided by Young, Schmidt and Lange (1990) for a throwing-like rapid reversal movement. The second dimension on which the generality of invariant relative timing can be assessed is made up from different kinds of variations. Of course, in order to observe an invariance some characteristics of the motor pattern have to

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be varied. In principle it is possible that a particular invariance might be limited to certain such variations. Originally invariant relative timing has been observed when total duration was varied. Thereafter, the set of variations for which relative-timing invariance was postulated has been enlarged. Impulse-variability models, for example, posit invariant relative timing also for different amplitudes and accuracy requirements of rapid aimed movements (cf. Schmidt et al., 1979, 1985; Meyer et al., 1982). With respect to duration and amplitude the evidence appears somewhat mixed. Howarth, Beggs and Bowden (1971) observed constant distances in constant proportions of movement time when duration was varied by way of a pacing signal; however, Zelaznik, Schmidt and Gielen (1986) found that the relative timing of acceleration profiles was not invariant across different total durations. With respect to amplitude, Schmidtke (1961) observed constant relative distances in constant proportions of movement time, but again the invariance might be less than perfect (cf. MacKenzie, Marteniuk, Dugas, Liske & Eickmeier, 1987). Finally, with respect to different accuracy requirements the evidence is clear. No matter whether target size is reduced or subjects are instructed for accuracy rather than speed, the relative duration of the deceleration phase increases when movements become more accurate (MacKenzie et al., 1987; Fisk & Goodale, 1989). For the sake of the following argument I shall simplify the mixed evidence and assume that in rapid aimed movements relative timing approximates invariance when duration or amplitude is varied, but not upon variation of accuracy requirements. Such a result appears interesting and has a certain intuitive appeal. However, it poses a serious problem for the notion of a generalized motor program with invariant relative timing. The parameters of such a program determine the total duration of the movement and certainly other features like its amplitude, but they cannot specify the relative timing of the pattern because this is an essential characteristic of the program itself. Therefore the data enforce the assumption that movements with different accuracy requirements are controlled by different generalized motor programs. This is a fairly unplausible assumption, partly because it requires qualitatively different control processes (different programs) for different values of a continuous task variable like target width.

The evasiveness of relative-timing invariance Sometimes conflicting conclusions on the invariance of relative timing do not come from different tasks or different movement characteristics that have been varied, but from highly similar experiments or even one and the same set of data. For example, invariant relative timing has been observed in typing by one group of researchers (Terzuolo & Viviani, 1979, 1980; Viviani & Terzuolo, 1980, 1982a), but not by 2.1.2.

Invarianr Relative Timing in Motor-Program Theory

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another one (Gentner, 1982a, b; 1987). A second example is locomotion. Using the relative durations of the four segments of the Philippson step cycle, Shapiro, Zernicke, Gregor and Diestel (1981) observed invariant relative timing within each mode of coordination (walking, running) when the treadmill speed was varied. This finding contrasts with other published reports according to which the cycle time of a single leg is modified more by changing the duration of stance than by changing the duration of swing (e.9. Herman, Wirta, Bampton & Finley, 1976). In addition, when Gentner (1987) re-analyzed Shapiro et al's data, he could not confirm the previously reported invariance. The reason for conflicting conclusions which refer to the same task or even the same set of data is simple. There are different methods to test whether relative timing is invariant or not. At the one extreme, relative-timing invariance can be demonstrated in a highly convincing manner with the proper visual presentation of the data (e.g. Terzuolo & Viviani, 1980); at the other extreme, with sufficiently stringent statistical procedures the hypothesis of relative-timing invariance can be rejected (e.g. Gentner, 1982a; Heuer, 1984b). In his review paper Gentner (1987) applied fairly stringent tests, mainly the so-called mmconstant-proportion testmm, and there were only few data sets which passed them. This finding suggests the conclusion that invariant relative timing in a s t r i c t sense does not exist at all. Whether or not relative timing will be found invariant does therefore only depend on the power of the statistical procedures; invariance of relative timing tends to evade statistical power. Supposing that the conclusion is valid, is it also sufficient to reject the notion of a generalized motor program with invariant relative timing? The answer is no for at least two different reasons. The first one is very general. How good a fit can one expect between a simple model of a complex system and real data? There is no reason to expect a perfect fit; therefore, whether or not the model will be rejected is necessarily a matter of statistical power only. However, statistical tests for goodness-of-fit, although they are common in the mathematical branch of Psychology, are not the only means to evaluate a model. In biocybernetic modelling, for example, the evaluation is often intuitive. A model can be judged useful when it captures important qualitative aspects of the data, and a certain discrepancy between nature and human conceptualizations of it can be accepted. With such a relaxed criterion the notion of a generalized motor program with invariant relative timing is useful: it captures a strong and conspicuous tendency towards invariant relative timing that has been observed in many skills. It should be stressed that this is not a final evaluation but only a preliminary one that is based on the data discussed so far. There are good reasons to revise the judgement, but

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these are not related to the failure to find a perfect invariance. As a matter of fact, in addition to the general argument about goodness of fit there is a more specific argument according to which the notion of a generalized motor program with perfectly invariant relative timing in principle does not predict that a perfect invariance will be observed. To this argument I shall turn next. Defense of a central invariance At a first glance the notion of a generalized motor program with invariant relative timing looks very much like a restatement of the empirical observation. However, the relation between theory and observation is not quite as simple. The theoretical concept refers to a central level of control, but the observations are made on peripheral kinematics. The timing of peripheral events can be determined to variable degrees by a central program and by peripheral factors (e.g. Heuer, 1981). Most obviously, even a perfect invariance at a central level of control can be distorted as the central commands enter the motoneuron pools, are transformed into linear forces in the muscles, into joint torques, joint movements, and finally movement of an end effector (cf. Schmidt, 1985). In short, there is no reason to suppose that the various transformations on the way from the central command to kinematic variables leave the relative timing unaffected. Therefore, the notion of a generalized motor program with invariant relative timing does not really predict that relative-timing invariance in a strict sense should be observed; at the most it leads one to expect a tendency towards invariance. The recognition of possible distortions of the relative timing of central commands poses the problem of how the invariance of relative timing at a central level can be tested more directly. Two approaches have been suggested which have received only little or no experimental attention so far. The general idea of the first approach is to vlwork upwardvv from the periphery towards the central commands. As one vvworksupwardv1from kinematics one quickly encounters the electric activity of the muscles. The EMG signal seems to be as far up as this approach has been pursued. However, the results were not very promising. While Carter and Shapiro (1984) observed relative-timing invariance on the kinematic level as well as with the EMG signal, the results of Shapiro and Walter (1986) suggest that invariances might be harder rather than easier to find in the EMG signal than in the kinematics. Studying rapid aimed movements, they found constant relative durations of the acceleration and deceleration phases when total duration was varied or duration together with amplitude to maintain a constant average speed. In contrast, the relative duration of the first agonist burst failed to remain invariant under both sets of conditions. There is no doubt that the EMG signal is vlcloserlvto the 2.1.3.

Invariant Relative Timing in Motor-Program Theory

45

output of the motor program than the kinematics and that, in analyzing it, the potential distortions of relative timing through the complex electro-mechanical transformations are eliminated. This, however, does not necessarily imply that the EMG signal is also more similar to the central commands of interest. Such would be the case only when the central commands, as far as their relative timing is concerned, would be subjected to a series of fundamentally unrelated distortions. If the distortions were related to each other it could happen that some central signal were very similar to a peripheral signal, while at intermediate levels signals were quite different. This would be the case, in particular, if the central commands would be transformed to cancel later distortions e.g. by the electro-mechanical transformation. Therefore, there is no conclusive reason for relative timing to become more invariant as one llmovesupward1#from the kinematics. The second approach relies on observations on the kinematic level: the data, however, are analyzed in terms of a model that distinguishes between a central and a peripheral level and posits certain relations between them (Heuer, 1988a). Basically the model is a slight modification of the timing model proposed by Wing and Kristofferson (1973 a,b). As a start, the validity of Equation (2) is assumed, but it is taken as a description of invariant relative timing on a central level of control rather than on the peripheral level of observation. A relation between the central events and their peripheral manifestations is established by way of assuming "motor delays". Thus, for the observed duration of segment j (as defined by two peripheral events j and j-1) in execution i of a particular movement one obtains: x~.j=r~nj + mi,j

-

mL,j-l

(3)

In this Equation rL again is the rate parameter and S l j the prototypical segment duration: in contrast to Equation (2), however, n j refers to segments as defined by central rather than peripheral events. The motor delays between the central events and their respective peripheral manifestations are designated as mL.j-l and m1.j for the start and the end of the segment, respectively. For the analyses of mean intervals, variances and covariances that are based on Equation (3) additional assumptions are made: motor delays of different events are assumed to be uncorrelated among each other and with the rate parameter. These additional assumptions are nontrivial and can be violated. For example, motor delays are likely to be correlated for segments of very short duration. The two-level model of invariant relative timing suggests a re-evaluation of the existing procedures to test invariance and the results that were obtained with them. Under the assumptions of the model none of the procedures is really adequate. In particular, the hypothesis of relative-timing

H. Heuer

46

invariance will be rejected, although relative timing at a central level is invariant, whenever the mean motor delays are different across the different events. when the regression of segment duration on total duration is computed for single executions of a particular movement, the distortions through different mean motor delays can even cause a non-linearity (cf. Heuer, 1988a). With respect to results, the model suggests a particularly interesting re-evaluation of the data reported by Zelaznik et al. (1986) for rapid aimed movements. These data had been taken by Zelaznik et al. themselves as well as by Schmidt (1985) and Gentner (1987) as clearcut evidence against relative-timing invariance. However, they are fully in line with the two-level model and in addition point to an important insight that has been mentioned before: Timing, as recorded on the kinematic surface of a movement, results from central as well as peripheral factors. Zelaznik et al. (1986) varied the target movement time in different experimental conditions by way of instruction: the range was from 125 to 225 ms in the first experiment and from 150 to 250 ms in the second one. According to the two-level model the mean duration of segment j in condition c, Ec (Xj), is related to the mean movement time in that condition, E,(X), by: m

E = ( x ~ )=

[ n 3 / p L n s ) i E=(x)

-

m

{ [ n j / (*-I Z n-)

1 [E(Mm)-E(Mo) 1 + [E(MJ)-E(MJ-~)I )

(4)

E(Mo) and E(Mm) are the mean motor delays at the start and end of the movement, E(M3-L) and E(M3) the mean motor delays at

the start and end of segment j. Equation ( 4 ) is linear with the relative prototypical segment duration Slj/ZR, as the slope. The intercept will differ from zero except when all mean motor delays are equal: thus, in general, segment durations will not be proportional to total duration. The regressions of mean segment durations on mean total duration were linear in both experiments of Zelaznik et al. (1986). Segments were defined in terms of landmarks of the acceleration profiles: they lasted from the start of the movement to peak acceleration, zero crossing, and peak deceleration. The intercepts of the respective regression lines in the two experiments were 27/20, 27/12, and 27/29 ms, the slopes were .00/.01, .34/.38, and .70/1.00 ms/ms. The non-zero intercepts are damaging to available tests of invariant relative timing; however, in terms of the two-level model they only indicate different mean motor delays. Also the zero slope for the first segment until peak acceleration is inconsistent with relative-timing invariance on a peripheral level: in contrast, in terms of the two-level model it indicates that the duration of the corresponding central segment is zero. Thus the central events that give rise to the start of the

Invariant Relative Timing in Motor-Program Theory

47

movement and peak acceleration are not separated in time, or both peripheral events result from a single central one; in terms of the model peak acceleration is not a centrally timed event, but its timing (relative to the start of the movement) is determined only by the motor delay, that is, by more peripheral factors. In addition to a re-evaluation of the available procedures and results, the two-level model does also suggest new procedures to test the invariance of relative timing. These procedures are no longer concerned with relative-timing invariance at the peripheral level of observation, but rather with whether the observed timing is consistent with a central invariance or not. They are based on variances and covariances as are the tests of the timing model of Wing and Kristofferson (1973 a, b) and its variants (e.g. Vorberg & Hambuch, 1978; Jagacinski, Marshburn, Klapp & Jones, 1988). Among the several criteria that can be derived to test the assumption of a central invariance there is one of particular interest. Consider four segments j, k, s and t with durations Xj, X-, X-, and Xt; the capital letters denote random variables. For any set of four such intervals it can be shown that the twolevel model requires the following equation to hold: cov(xj,x~)COV(Xk,Xt)

-

cov(X~,Xt)cov(xk,x.I) = 0

(5)

All these covariances are between non-adjacent intervals, that is, the analysis can only be applied to a motor pattern with at least five segments (j=l, k=2, s=4, t=5). In many readers Equation (5) will probably elicit a d4jA vu. The source for this experience will become more obvious when the covariances are replaced by correlations, which does not affect the validity of the equation under the two-level model. In fact, the equation is known as the tetrad equation and it was used as a test of Spearman's model of general intelligence (Spearman, 1927). The similarity between the two-level model and Spearman's model of general intelligence is not limited to test procedures, but includes their formal structures as well. It probably invites speculation about why human minds come up with almost identical theories on such disparate subject matters as the timing of motor patterns and the performance on tests of intelligence. Is relative timing mandatory? The notion of a generalized motor program with invariant relative timing is not a simple re-statement of experimental observations. One of the differences that was discussed in the previous section is related to the level to which the theoretical statement refers and on which the observations are made. A second difference is related to the potential role of strategies for the tendency towards relative-timing invariance. To this I shall turn next. Invariance of relative timing can result from the inability 2.2.

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of subjects to modify the temporal structure of a learned motor pattern or from their unwillingness. In the first case the tendency towards relative-timing invariance would be a mandatory phenomenon, but in the latter case it would be strategic. The experiments that have been discussed so far do not allow to distinguish between these two alternatives. In them either no particular instructions on relative timing were given as total duration was varied, or the instruction asked only to abandon the relative timing without specifying a particular new temporal pattern. Thus, although subjects possibly were unable to change the relative timing, it cannot be excluded that they only maintained it for convenience and could have changed it if they had really wanted to. The notion of a generalized motor program with invariant relative timing is more specific than the data with respect to the alternatives of a mandatory or strategic phenomenon. It posits that the tendency towards invariance is mandatory. When a motor pattern has been learned and a generalized motor program been acquired, relative timing cannot be changed easily by way of changing parameters. Instead, modification of the temporal pattern requires the acquisition of a new program. Whether or not invariant relative timing is a mandatory phenomenon can be tested easily. All that is needed is to really urge the subjects to modify the relative timing of a learned motor pattern in a specific way. Such experiments were run by Heuer and Schmidt (1988). Their subjects practiced a pattern of elbow flexions and extensions in the horizontal plane - similar to the task used by Armstrong (1970) -, and after the practice period they had to reproduce a visually presented pattern that was expanded in time by way of a proportional transformation of the time axis or a sinusoidal transformation which (relatively) compressed the initial and final parts and expanded the middle one. Except possibly for a minor transient difficulty, transfer performance on the pattern with the new relative timing was as good as in the control condition in which the relative timing of the practice period had been maintained during transfer. High performance levels in transfer tasks with a new relative timing have also been observed in some other experiments in which the role of practice conditions for transfer was examined (e.g. Langley & Zelaznik, 1984; Wulf & Schmidt, 1988; Carnahan & Lee, 1989). Although in these experiments the control condition in which the learned relative timing was maintained during transfer was lacking, the finding of a high performance level during transfer is suggestive; according to the data transfer performance was much better than initial performance in the acquisition period. The finding that the relative timing of a motor pattern can be changed quite easily when a new relative timing is explicitly requested suggests the conclusion that the tendency towards invariance is not a mandatory phenomenon but a strate-

Invariant Relative Timing in Motor-Program Theory

49

gic one. As will be discussed below, the ease of transfer to a new temporal pattern depends on the conditions of learning. However, according to the notion of a generalized motor program with invariant relative timing transfer to a new temporal pattern should never be easy; it always requires the acquisition of a new generalized program. Thus, the concept is clearly at variance with the available data.

Is relative timing categorical? The notion of a generalized motor program with invariant relative timing holds that relative timing characterizes discrete sets of movements, each one controlled by its own program. However, in principle relative timing is a continuous variable; the relative durations of the various segments of a motor pattern can be represented as the components of a vector, and each component is a real number between 0 and 1. Nonetheless, empirical observations could prove that only particular patterns can be produced so that relative timing would be continuous numerically, but discrete biologically. As far as I am aware, however, there is no evidence according to which discrete categories of relative timing exist in human movements. In contrast, the effect of accuracy requirements on rapid aimed movements suggests that, as accuracy requirements were varied in smaller and smaller steps, relative timing would probably also vary in a continuous fashion. Theoretically, the infinite (or very large) number of different temporal patterns corresponds to an infinite !or very large) number of generalized motor programs. Thus, taking relative timing as an essential characteristic re-introduces the "storage problem" (Schmidt, 1975) that the notion of a generalized motor program had been intended to avoid. The argument was that, if specific motor programs were required for all movements that humans can perform, this would overburden their storage capacity. Therefore, the number was reduced to a smaller set of categories. However, when categories are defined in terms of relative timing, their number is probably again too large. The evidence that is needed to defeat this argument is fairly straightforward; it corresponds to the type of evidence which supports the claim that the number of some filters in the perceptual system is limited (e.g. Beverley & Regan, 1973). For example, consider the effect of accuracy requirements on the relative timing of rapid aimed movements. For each level of accuracy a distribution of temporal patterns will be observed. However, the means of these distributions should not be graded in arbitrarily small steps as, for example, target width is graded finer and finer; rather the distributions should remain invariant for certain ranges of target widths. Such or similar evidence for a limited number of temporal patterns in human movements is lacking. As long as this is so, the "large-number argument" can be taken as valid. 2.3.

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3.

A NEW PERSPECTIVE ON GEN-IZED INVARIANT RELATIVE TIMING

MOTOR

PROGRAMS AND

The notion of a generalized motor program with invariant relative timing is attractive for its simplicity, but it encounters difficulties when confronted with experimental data. Contrary to predictions, the relative timing of a motor pattern can be changed easily. In addition there is no evidence that relative timing is a categorical rather than a continuous variable. In what follows I shall describe a modified perspective on generalized motor programs. It avoids those features which brought the notion into conflict with reality. Unfortunately, the modified concept is more complex than the original one, and its predictions are less specific. Nonetheless there are some data which support it, and these will be reviewed. Finally, the phenomenon of invariant relative timing will be re-considered. 3.1. A modified concept of a generalized motor program

There can be no doubt that autonomous central processes have to be invoked to account for the production of movements (e.g. von Holst, 1937; Lashley, 1951). The notion of a motor program serves to conceptualize them. Of course, trajectories do not only depend on central processes, but also on more peripheral parts of the system. With respect to timing this has been emphasized in this chapter and in several other places (e.9. Gentner, 1987; Heuer, 1988a). Although peripheral distortions of central timing do exist, they will be neglected in the following discussion. Stored commands and generative structures The concept of a motor program is strongly influenced by the computer analogy (e.g. Henry and Rogers, 1960), although other analogies of a more mechanical nature like a cam control (Taylor & Birmingham, 1948) or a phonograph record (Schmidt, 1982, p. 310-311) have also been used. As compared to the versatility of current computer programs, however, the typical description of motor programs is primitive. The program appears to be more a sequence of output commands as in the mechanical analogies than a real program which generates its output in an arbitrarily complex manner. There is nothing against bringing somewhat more complexity into motor-program conceptualizations of the autonomous central processes of motor control. Motor programs are mostly characterized in terms of the output that they produce. Depending on how movements are recorded, discrete and continuous descriptions of a program can be distinguished. Discrete descriptions, for example, are used for sequences of simple responses like key presses or strokes in handwriting (cf. Keele, 1986). The evidence 3.1.1.

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suggests that the internal representations for sequences of discrete responses are hierarchically organized whenever possible (Povel & Collard, 1982; Rosenbaum, Kenny & Derr, 1983). This evidence is based on the relative timing which can be predicted under the assumption that a hierarchical representation is read with a uniform clock rate ("tree-traversal process1#in the terms of Rosenbaum et al., 1983). Continuous descriptions of motor programs are used for simple movements for which kinematic variables are recorded continuously. An example are impulse-variability models of rapid aimed movements. The program here is described as a prototypical force-time curve that can be scaled on both axes. The operation of scaling is equivalent to reading the prototypical curve with a uniform clock rate, which varies across instances, and amplifying it with a certain gain factor which again varies across instances. Both types of motor-program descriptions can be characterized as reading stored commands which correspond to the output of the program. With this analogy in mind the concept of a generalized motor program with invariant relative timing obtains its attractive simplicity. However, when the analogy of reading simple command strings or more complex data structures at different rates is abandoned, things become different. In fact, there is no necessity to describe a motor program in this way. Instead it can be described in terms of generative structures. It has been argued that both kinds of description, output and generative structure, are essentially equivalent (Cruse, Dean, Heuer & Schmidt, 1990). This is true, however, only for a given set of constraints for which a unique output of a generative structure does exist. An analogy is a particular solution of a differential equation, given some initial conditions. Of course, the distinction between motor-program descriptions in terms of stored commands that are read with a certain clock rate and in terms of generative structures is somewhat blurred. A generative structure is also required when stored commands are read - a structure which realizes the reading and generative structures in general will also need some stored data as input. Nevertheless there is an important difference between both kinds of descriptions in how they account for different movements. In the one case different types of movements require different sets of stored commands, while the process of reading them remains essentially the same; different instances of a particular type are based on the same set of stored commands that are read at different rates or are amplified differentially. In the other case different types of movements require the implementation of different generative structures, while different instances of the same type come about through different parameter values. What these parameters are and how they affect the kinematics will depend on the particular generative structure. As an example for a description of a generalized motor

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program in terms of a generative structure, consider the VITE model proposed by Bullock and Grossberg (1988, 1990). This structure, in essence, is a central closed-loop system in which the difference between internal representations of target muscle length (which is an input signal) and actual length (which is the output signal) is low-pass filtered and integrated (cf. Heuer, 1990b). The system is made non-linear through a variable GO-signal (a second input signal). This signal multiplies the filtered error before it is integrated. Its effect is equivalent to changing the time-constant of the integrator during each single movement. A similar proposal, as far as the central level is concerned, has been made by Saltzman and Kelso (1987) in their tttask-dynamicll approach. In the task-space of their model the movement is characterized by a second-order differential equation which can be considered as a description of a central linear closed-loop system with a first-order low-pass filter and an integrator in the loop. Generative structures as those in the models of Bullock and Grossberg (1988, 1990) or Saltzman and Kelso (1987) have parameters like the gains and time constants of low-pass filters or the time constants of integrators. However, there is no particular reason to expect that variation of these parameters leaves the relative timing of the output of the generative structure unchanged. An example can be seen in Figure 20 of Bullock and Grossberg (1988) in which they illustrate how the relative timing is modified as the overall gain of the integrator in the VITE system is varied. As a matter of fact, variation of parameters will be associated with invariance of relative timing only in exceptional cases: relative timing will not in general be an essential characteristic of a certain generative structure. There is a second point that becomes obvious as soon as motor programs are described in terms of generative structures rather than stored commands. Parameters of different generative structures will affect their outputs in different ways. Thus, while the idea of reading stored commands suggests that invariant relative timing is an essential characteristic of a l l generalized motor programs, the description in terms of generative structures does no longer suggest that there is any invariance at all that is common to different generalized programs. To conclude, when the description of generalized motor programs in terms of stored commands is replaced by a description in terms of generative structures, the notion of a generalized motor program with invariant relative timing looses its intuitive appeal. There is no longer any obvious reason why motor programs should be parameterized in such a way that relative timing remains invariant when parameters are varied. There is not even any particular reason to expect that different generalized motor programs are characterized by the same kind of invariance. I am aware that my examples for a description of generalized

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motor programs in terms of generative structures will not always be appreciated as such. In fact, sharp distinctions have been drawn between models that assume I8prescriptions1l in terms of prestructured central commands and models according to which trajectories are emergent characteristics of a central (or central plus peripheral) structure (e.g. Kelso, 1981). However, the notion of a generalized motor program does not imply a particular way to characterize them. Only when one needs a strawman does one need a description of a motor program as a rigid set of commands that is read with variable rate. Central control of timing When a motor program is described in terms of stored commands that are read as the movement is executed, there is a simple factorization of "pattern and energy" (cf. Bullock & Grossberg, 1988). The I8patternf1, that is, the relative timing, is determined by the data structure, while *fenergyln, that is, average speed, is determined by the rate of reading. The simple factorization gets lost when motor programs are described in terms of more complex generative structures. The loss of simplicity, however, has to be accepted to bring the concept better in line with reality. It is likely that parameters of a generalized motor program not only serve to control average speed, but also relative timing. Thus, relative timing can be determined in a flexible way by choosing appropriate parameter values. The continuity and flexibility of relative-timing variations is one characteristic of human motor control that follows quite naturally from descriptions of generalized motor programs in terms of generative structures. In this section I shall turn to a second characteristic: The choice of parameters and thus of relative timing is not arbitrary but constrained in several ways. This follows from fairly simple considerations. As a start, consider a nlclosedll skill (Poulton, 1957) that does not require a more or less continuous adjustment to a variable environment. In spite of the Iffreedom of movement", at least three types of constraints on relative timing can be identified. First, there are laendogenous constraints". For example, some rhythms are easy to tap while others are hard. In skills like rhythmic tapping there are distinguished events, the timing of which has been studied extensively. Although in continuous movements like the patterns used by Armstrong (1970) or Heuer and Schmidt (1988) there are no obvious distinguished events, similar observations can be made. Some patterns seem to have an easy rhythm and are experienced as t8harmonic81, while others have a difficult rhythm and provoke the subjective experience of llawkwardnessll. Thus, the endogenous constraints on relative timing that have been identified for sequences of discrete taps do certainly also apply to continuous movement patterns. However, it is not exactly clear which events in such patterns correspond to the 3.1.2.

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discrete taps and, therefore, how to use the available knowledge about the constraints for predictions. Keele (1986) characterizes the endogenous constraints in terms of three principles which have been derived from studies of sequences of discrete taps. The first one is the principle of a 1:2 ratio that is most easily observed when long and short intervals between key presses alternate. Intervals with other ratios are not only harder to produce, but they are also biased toward 1:2. The second principle is that of beats. Most music obeys this principle. Beats are regular events, but the interval between successive beats can be subdivided in equal steps. For example, a sequence of 200, 200, 200, 600 ms obeys this principle, but a sequence of 200, 200, 600 ms does not. The final principle is that of an equal number of subdivisions at a given hierarchy level (with the exception of zero). For example, when the beat interval is 600 ms, the sequence 200, 200, 200, 300, 300 ms would be hard because the first beat is subdivided once but the second twice; however, the sequence 150, 150, 150, 150, 300, 300 ms is easier. In this sequence the beat interval is subdivided once on the second level of the hierarchy, and on the third level this is again subdivided once to obtain 150 ms, or not at all (300 ms). A second set of constraints for relative timing can be called 88spatia188.Theoretically such constraints are to be expected whenever the parameters of a generalized motor program affect spatial and temporal characteristics of a movement simultaneously. whatever the source for these constraints actually is, the fact that the temporal and spatial characteristics of a movement are interdependent cannot be debated. The relation has mostly been studied for drawing-like movements, where it was first noted by Derwort (1938); Derwort did not only observe that spatial characteristics affect temporal ones, but also the opposite influence that has been neglected in recent years. A more precise formulation of the relation between temporal and spatial characteristics has been proposed by Viviani and Terzuolo (1982b; cf. Viviani, 1986) but is subject to controversy (e.g. Thomassen & Teulings, 1985; Wann, Nimmo-Smith & Wing, 1988). Whatever the precise relation between spatial and temporal movement characteristics is, it is not a rigid relation but more a tendency toward a particular timing given a certain path. Similar to the endogenous constraints the spatial ones are rather soft and can be overcome with special effort, for example, when other relations between spatial and temporal characteristics are required in a pursuit-tracking task (viviani, Campadelli & Mounoud, 1987). Finally, there are peripheral constraints. The output of a central motor program is transformed by the peripheral structures of the human motor system, and the choice of parameters has to take these transformations into account. The basic concept in motor-program theory to deal with this problem is that of a “scheman8(Schmidt, 1975), a learned rule which

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specifies the parameter values that are needed to obtain the intended movement characteristics. The schema will frequently specify only a limited range of the possible parameter values: values outside this range may result in no movement at all. As an example, consider simple up-and-down movements of a finger. A central command for flexion will be subjected to a delay until the finger is actually flexed, and the same will be true for extensions. The peripheral delays result in a limited maximal frequency at which the peripheral system can work, and a higher-frequency output of a central program will probably result in no peripheral movement at all. Moreover, the central command must have a particular phase relation to the position of the finger; running out of this phase again would result in no overt movement. For example, a flexion command will produce no peripheral effect when the finger is already flexed. The requirement of a particular phase relation between central commands and peripheral kinematics suggests that central control must be somehow adjusted to short-term variations of the peripheral transformation which are caused, for example, by muscular fatigue. Peripheral constraints are probably more subtle than only limiting the range of parameter values that will produce overt movements. The peripheral system that is driven by the central motor program has its own dynamics. For example, arms and legs are similar to pendulums; once they are set into motion they tend to take a certain trajectory by themselves. Skillful movements appear to take advantage of tlpassive trajectoriestt; this is indicated, for example, by the decline of the integrated EMG in the course of practice (e.g. Metz, 1970: Person, 1960). Thus, the intrinsic characteristics of the peripheral system constrain central control in that they tend to become exploited. The several constraints on the central control of timing will have the joint effect that some temporal patterns are preferred over others. Formally this can be represented by a cost function that is defined - as far as theoretical concepts are concerned - on the parameter space and - as far as the observations are concerned on a "usable spacet1 (Heuer, 1990~). A usable space here is the set of all temporal patterns that can be produced, given certain spatial movement characteristics. Temporal patterns that are associated with minimal costs and are thus preferred have been called l1naturaltt by Heuer and Schmidt (1988). The general idea that movement trajectories are selected by minimizing some kind of costs has become somewhat popular recently. It has a history in biomechanics (cf. Marshall, Wood & Jennings, 1989), and over the last years several models of central motor control have been proposed according to which movements are performed as to minimize some cost criterion (e.g. Nelson, 1983; Flash & Hogan, 1985; Cruse, 1986: Uno, Kawato & Suzuki, 1989). A s far as the relative timing of simple and complex motor patterns is concerned, however, it is

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not yet possible to define an objective criterion like, for example, the minimum-jerk criterion for aimed movements. It appears even unlikely, given the several constraints which affect the costs, that a simple criterion exists. Even without an explicit definition of costs, however, some testable predictions can be derived that will be discussed in the following section. Before that, a final remark on the central control of timing is in order. So far I have talked about intrinsic timing in closed skills, that is, timing as determined by the real-time behavior of a generative structure. This, of course, is not the only kind of timing that motor-program theory has to account for. In open skills (Poulton, 1957), which have to be adjusted to a changing environment, timing of movements is frequently determined by external events. Well-studied examples are catching, hitting and similar motor patterns that have to be timed in relation to an approaching object (for review: Lee & Young, 1986). This kind of timing is inconsistent with the concept of a generalized motor program when the narrow perspective of a set of stored commands is taken that are read with a certain clock rate. With the wider perspective adopted here there is no difficulty to treat an extrinsic timing signal like, for example, the relative optical expansion, as an input of a generative structure (cf. Cruse et al., 1990). It seems likely that for extrinsic timing at least some of the constraints on intrinsic timing are effective as well. The continuity hypothesis on relative timing When the concept of a generalized motor program is modified along the lines outlined above, relative timing is no longer a categorical variable with a few discrete values that are the signatures of different programs, but a continuous variable that can be adjusted by way of parameters. In spite of its continuity, relative timing is constrained in several ways so that some temporal patterns are preferred over others. Together these two features - the continuous variation and the existence of natural patterns on the multidimensional continuum make up the llcontinuityhypothesis on relative timingtt (Heuer, 198833) that contrasts with the categorical hypothesis implied by the notion of a generalized motor program with invariant relative timing. The evidence in favor of the continuity hypothesis relates to its two features. With respect to continuity per se it rests mainly on some effects of the difference in relative timing between two motor patterns. Such effects are consistent with the continuity hypothesis because on a continuum differences are ordered in size, and they are inconsistent with the categorical hypothesis because for a categorical variable there are no graded differences; it is only defined whether two values are same or different, but not how different they are. As mentioned before, although the relative timing of a practiced motor pattern can be modified rather quickly in 3.2.

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general, there are some conditions which make the shift easier and others which make it harder. At least in part these differences are related to the difference between the relative timing of the practice and the transfer pattern. In addition to the general argument about the existence of graded differences on a continuous variable and their lack on a categorical variable, there is a more specific argument according to which certain differences in transfer performance on new temporal patterns should exist. According to motor-program theory, schemata are needed for the selection of the parameter values that will produce an intended outcome like a particular temporal pattern. Since a schema specifies a rule, its acquisition requires the experience of several parameter values and their kinematic effects. This is the basis of the variable-practice hypothesis, a major prediction of Schmidtls (1975) theory: practice on several variations of a motor pattern should result in better performance on new variants than practice on only one particular pattern. In spite of its plausibility the hypothesis has received only mixed support (Shapiro & Schmidt, 1982; van Rossum, 1987). One of the factors that contribute to the inconsistency of results seems to be the variability of reproductions even when only a single target pattern is practiced. Thus, even under constant-practice conditions subjects will experience different parameter values and their effects on kinematic characteristics. However, the schemata that are acquired during constant and variable practice will probably exhibit quantitative differences with respect to the ranges of program parameters and outcomes for which they specify a relation because different ranges of these variables have been encountered during practice. As far as relative timing is concerned, transfer to a new temporal pattern should deteriorate as the difference between practice and test pattern is increased. For a certain amount of variability encountered during practice, the probability that the new pattern is outside the range of acquired schemata will increase with an increasing difference; when the new temporal pattern is outside the range for which the schemata specify the appropriate parameter values, these cannot be selected immediately, but it will take some time to locate them. Some support for the hypothesized role of the difference between practice pattern and transfer pattern can be found in the results of Heuer and Schmidt (1988) and Heuer (198813). Heuer and Schmidt (1988) found perfect and almost immediate transfer to a new temporal pattern when the cross-correlation between practice and target pattern, after scaling them to the same total duration, was 0.68. In contrast, Heuer (198813) found less-than-perfect transfer when the cross-correlation between the two patterns was only 0.05. Supplementing the results on the difference between practice and transfer pattern for a certain variability during practice are some results on the role of variability during practice

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for a certain difference between practice and transfer pattern. The probability that the new pattern will be outside the range of the acquired schemata will decline as the variability during practice is increased; therefore, transfer to a new relative timing should improve. This prediction is nicely confirmed by the results of Wulf and Schmidt (1988). They found that transfer to a new relative timing of a sequence of discrete aimed movements was better when the subjects had practiced different temporal patterns instead of only one, which, however, had a variable total duration. In contrast, transfer to a new total duration was better after practice with variable duration than after practice with a constant total duration, but variable relative timing. An effect of the similarity of temporal patterns has also been found when switching between previously practiced patterns was studied rather than the switch to a new pattern. Heuer (198813, Exp. 2) found an essentially immediate change of the relative timing pattern when the cross-correlations between the target patterns were high (0.77 and 0.63), but a reduced initial performance level after the switch when the cross-correlation was low (0.05). This effect cannot be explained in terms of a limited range of the available schemata; however, when parameters of a generalized motor program have to be modified to produce a new temporal pattern, it is at least plausible to expect noticeable inaccuracies in the initial parameter settings after large changes of parameter values and less so after small changes. There is an important boundary condition for the expectation that initial;.er.rors should be observed after a large change of relative timing'and less so after a small change: the change must be accomplished by way of changing parameter values. In contrast, when successive movements are controlled by different programs, these movements differ categorically and, with respect to central control, it does not make any sense to talk about larger or smaller differences. The difficulty, of course, is that one cannot know whether or not the boundary condition is satisfied as long as the set of movements that is controlled by a certain generalized motor program is not precisely defined. As long as this theoretical gap is not closed, the precise definition must be replaced by intuition. Intuitively it is plausible that aimed movements with different amplitudes are controlled by a single generalized motor program, while to track a sine wave one needs another program. Thus one could expect that, in switching between different amplitudes of aimed movements, aftereffects will be observed in the temporal pattern which presumably result from slightly inaccurate parameter changes, while switching between sine tracking and aimed movements will not be accompanied by such inaccuracies. Corresponding results have been obtained by Heuer (1979). Heuer (1979) studied a particular aimed movement designated as the standard movement. when this was performed in alterna-

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tion with aimed movements of a smaller or larger amplitude (different start position but identical target position), the relative timing of landmarks in the acceleration-time curve of the standard movement was modified in complex ways as compared to a control condition in which only the standard movement was performed. In contrast, when the aimed movements of smaller or larger amplitude than the standard movement were replaced by watching a first period of a sine wave and then tracking a second one, no effect on the relative timing of the standard movement was seen. Thus, aftereffects of a motor pattern on the relative timing of another one that follows appear to be limited to patterns that are controlled by the same program: only then their relative timing is located on a single continuum (one program) rather than two different ones (two programs). The continuous variation of temporal patterns is only one ingredient of the continuity hypothesis on relative timing: the second one is the existence of natural patterns. One of the observations that led Heuer and Schmidt (1988) to propose the notion of natural temporal patterns were asymmetric biases in the reproductions of their target patterns. The reproductions of the one target pattern (A) were not only more accurate than those of the other one (B), but in addition reproductions of B were highly similar to target pattern A but not vice versa. Thus, reproductions of the less natural pattern B were biased toward the more natural pattern A, while reproductions of the more natural pattern A were not biased toward the less natural pattern B. Similar asymmetric biases have been observed by Heuer (1988b) even for patterns that were reproduced with essentially the same accuracy. Asymmetric biases are an immediate consequence of a cost function which is defined on a usable space of temporal patterns. Biases in the reproductions will depend on the gradients of the cost function at the target pattern, and whenever the gradients at two target patterns are different, biases will be asymmetric. The cost function thus offers a rather simple understanding of the constant errors that can be found when subjects have to produce a particular temporal pattern. For example, in the experiment of Carter and Shapiro (1984) the temporal pattern that the subjects produced deviated systematically from the one instructed. These systematic or constant errors are biases toward more natural patterns, as is strongly suggested by the results of Langley and Zelaznik (1984). In Langley and Zelaznik's (1984) experiments some subjects had to learn a particular relative timing for a sequence of three rapid aimed movements, while other subjects were only asked to produce a certain total duration and had a free choice regarding the temporal pattern. It is likely that a self-selected relative timing is associated with minimal costs and thus natural. The subjects who had to produce the instructed relative timing made constant errors, and these

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were biases toward the self-selected pattern of the other subjects. In addition to systematic biases in the reproduction of temporal patterns the notion of natural patterns suggests that differences in the transfer to new temporal patterns should exist which depend on how natural the old and new patterns are. Heuer (1988b) observed a tendency that transfer to a more natural pattern after practice on a less natural one was better than vice versa: the criterion for the "degree of naturalnessmm of the two patterns was the asymmetric bias in their reproductions during practice. Similarly, Langley and Zelaznik (1984) found that subjects who had practiced a particular non-natural pattern switched readily to the natural one as soon as specific instructions on relative timing were no longer in effect but only instructions for a certain total duration: in contrast, subjects who had practiced the selfselected relative timing showed very poor transfer performance when a particular non-natural temporal pattern was requested. Interestingly, the switch to a new non-natural pattern was rapid when another non-natural pattern had been practiced before: probably, during practice, these subjects developed means to overcome the tendency to produce a natural temporal pattern (cf. Carnahan & Lee, 1989). Taken together, the evidence on the continuity hypothesis appears suggestive but not conclusive. A variety of reasons for this not really satisfactory state can be found. For example, several of the data that I have reviewed are from experiments that addressed other problems than the one for which I have used them. More importantly, the continuity hypothesis has a certain conceptual softness which makes it hard to design stringent tests. One of the soft spots is the lack of an explicit definition of costs: however, it seems possible to go along without this because something about costs can be inferred from data like self-selected temporal patterns and than be used to predict other observations like reproduction biases. A crucially soft spot, however, appears to be that nothing can be said about the set of motor patterns for which the continuity hypothesis actually holds. Theoretically it is limited to patterns that are controlled by the same program, but the set of these patterns is undefined. The theoretical gap that had been closed when relative timing was suggested as an essential characteristic of a generalized motor program is re-opened. Without something to close it again the notion of a generalized motor program suffers from a lack of substance; it could even appear as a llsoup-stonell (cf. Navon, 1984), something that is not needed for the flavour of the soup, but also does no harm. Invariant relative timing re-considered Bearing in mind that this is a chapter on invariant relative timing in motor-program theory, I shall conclude it with a re3.3.

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consideration of relative-timing invariance. The phenomenon, of course, has a key status for the notion of a generalized motor program with invariant relative timing. What is its status for the modified concept? The brief answer to this question is Itnothing special1*. Under the modified perspective on generalized motor programs, relative timing will be approximately invariant when two conditions are satisfied. First, the relative timing of the motor pattern must be natural (or nearly so). Second, the natural relative timing must remain invariant when total duration or some other characteristic of the pattern is varied. Thus, relative timing can be invariant or not, depending on whether ancillary assumptions are met. I am not aware of data that allow an independent assessment of whether a natural temporal pattern changes when the total duration is varied. However, it is likely that it will remain constant in at least some skills. The endogenous constraints on relative timing in discrete sequences of taps, for example, are fairly independent of the overall speed. The same is true for the relation between spatial and temporal aspects of drawing-like movements as formulated in the Vwo-thirds power lawt1 (cf. Viviani, 1986), and thus at least part of the spatial constraints. There is some evidence to support the view that invariant relative timing is limited to motor patterns with a natural temporal structure. First, in many studies in which invariant relative timing has been found the temporal pattern was selfselected and thus probably natural. Second, when the relative timing was experimenter-imposed, it may also have been natural by chance or when the experimenter had tried it himself/herself before. In other cases subjects did not really produce the prescribed relative timing but deviated toward what was probably a more natural temporal pattern. Finally, in some experiments it was found that certain temporal patterns were maintained when the overall speed was varied and no explicit instruction on relative timing was in effect, while other temporal patterns were changed (e.g. Summers, 1975; Langley & Zelaznik, 1984). Similarly, Summers, Sargent and Hawkins (1984) found that some temporal patterns were maintained when a secondary task was introduced, while other patterns were modified. Summing up, approximate invariance of relative timing will be observed whenever the relative timing is highly comfortable, remains so as other movement characteristics vary, and no one requests seriously to do something less comfortable. Invariant relative timing is a phenomenon which reflects our (not necessarily conscious) likes and dislikes but not our abilities and inabilities.

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&know1 edgement :

The ideas that can be found in this chapter have profited very much from various discussions with Richard Schmidt in Bielefeld (at the occasion of the study year "Perception and Action" at the Center for Interdisciplinary Research) in 1984/85 and in Los Angeles in 1987; I want to express my gratitude to him. REFERENCES

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Carter,M.C. & Shapir0,D.C. (1984). Control of sequential movements: Evidence for generalized motor programs. Journal of Neurophysiology, 52, 787-796 Cruse,H. (1986). Constraints for joint angle control of human arm. Biological Cybernetics, 54, 125-132

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Cruse,H., Dean,J., Heuer,H. & Schmidt,R.A. (1990). Utilization of sensory information for motor control. In 0.Neumann & W.Prinz (Eds.), Relationships between perception and action. Current approaches. Berlin: Springer Derwort,A. (1938). Untersuchungen uber den Zeitverlauf figurierter Bewegungen beim Menschen. Pflugers Archiv fur die gesamte Physiologie, 240, 661-675 Fisk,J.D. L Goodale,M.A. (1989). The effects of instructions to subjects on the programming of visually directed reaching movements. Journal of Motor Behavior, 21, 5-19

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Flash,T. & Hogan,N. (1985). The coordination of arm movements: An experimentally confirmed mathematical model. Journal of Neuroscience, 5 , 1688-1703 Gentner,D.R. (1982a). Evidence against a central control model of timing in typing. Journal of Experimental Psychology: Human Perception and Performance, 8, 793-810 Gentner,D.R. (1982b). Testing the central control model of typing: Comments on the reply by Viviani and Terzuolo. Journal of Experimental Psychology: Human Perception and Performance, 8, 814-816 Gentner,D.R. (1987). Timing of skilled motor performance: Tests of the proportional duration model. Psychological Review, 9 4 , 255-276 Henry,F.M. & Rogers,D.E. (1960). Increased response latency for complicated movements and a "memory drum" theory of neuromotor reaction. Research Quarterly, 31, 448-458 Herman,R., Wirta,R., Bampton,S. & Finley,F.R. (1976). Human solutions for locomotion: I. Single limb analysis. In R.M.Herman, S.Grillner, P.S.G.Stein & D.G.Stuart (Eds.), Neural control of locomotion. New York: Plenum Press Heuer,H. (1979). Vber Bewegungsprogramme bei willkurlichen Bewegungen. Berichte aus dem Fachbereich Psychologie der Philipps-Universitat Marburg/Lahn Nr.76. Marburg Heuer,H. (1981). Fast aiming movements with the left and right arm: Evidence for two-process theories of motor control. Psychological Research, 4 3 , 81-96 Heuer,H. (1984a). Binary choice reaction time as a function of the relationship between durations and forms of responses. Journal of Motor Behavior, 16, 392-404 Heuer,H. (198413). On aiming movements.

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strategies in

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Pove1,D.J. & Collard,R.F.A. (1982). Structural factors in patterned finger tapping. Acta Psychologica, 52, 107-123 Rosenbaum,D.A. (1985). Motor programming: A review and scheduling theory. In H.Heuer, U-Kleinbeck 61 K.-H.Schmidt (Eds.), Motor behavior: Programming, control, and acquisition. Berlin: Springer Rosenbaum,D.A., Kenny,S.B. & Derr,M.A. (1983). Hierarchical control of rapid movement sequences. Journal of Experimental Psychology: Human Perception and Performance, 9, 86-102

Roth,K. (1987). Taktik im Sportspiel. Zum Erkldrungswert der Theorie generalisierter motorischer Programme fur die Regulation komplexer Bewegungshandlungen. Habilitationsschrift. Bielefeld: Fakultat fur Psychologie und Sportwissenschaft, Universitdt Bielefeld Saltzman,E. & Kels0,J.A.S. (1987). Skilled actions: A taskdynamic approach. Psychological Review, 94, 84-106

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Schmidtke,H. (1961). Uber die Struktur willkiirlicher Bewegungen. Psychologische Beitrage, 5, 428-439 Shapir0,D.C. (1977). A preliminary attempt to determine the duration of a motor program. In D.M.Landers & R.W.Christina (Eds.)! Psychology of motor behavior and sport, V o l . 1. Champaign, Ill.: Human Kinetics Publishers Shapir0,D.C. & Schmidt,R.A. (1982). The schema theory: Recent evidence and developmental implications. In J.A.S.Kelso & J.E.Clark (Eds.), The development of movement control and co-ordination. New York: Wiley Shapir0,D.C. & Walter,C.B. (1986). An examination of rapid positioning movements with spatiotemporal constraints. Journal of Motor Behavior, 18, 373-395

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van Rossum,J.H.A. (1987). Motor development and practice. The variability of practice hypothesis in perspective. Amsterdam: Free University Press Viv ani,P. (1986). Do units of motor action really exist? In H.Heuer & C.Fromm (Eds.), Generation and modulation of action patterns. Berlin: Springer Viviani,P., Campadelli,P. & Mounoud,P. (1987). Visuo-manual pursuit tracking of human two-dimensional movements. Journal of Experimental Psychology: Human Perception and Performance, 13, 62-78 Viviani,P. & Terzuolo,C.A. (1980). Space-time invariance in learned motor skills. In G.E.Stelmach & J.Requin (Eds.), Tutorials in motor behavior. Amsterdam: North-Holland Viviani,P. & Terzuolo,C.A. (1982a). On the relation between word-specific patterns and the central control model of typing: A reply to Gentner. Journal of Experimental psychology: Human Perception and Performance, 8 , 811-813

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Viviani,P. & Terzuolo,C.A. (198233). Trajectory determines movement dynamics. Neuroscience, 7 , 431-437 von Holst,E. (1937). Vom Wesen der Ordnung im Zentralnervensystem. Natumissenschaften, 25, 625-631,641-647 Vorberg,D. & Hambuch,R. (1978). On the temporal control of rhythmic performance. In J.Requin (Ed.), Attention and performance V I I . Hillsdale,N.J.: Erlbaum Wann,J., Nimmo-Smith,I. & Wing,A.M. (1988). Relation between velocity and curvature in movement: Equivalence and divergence between a power law and a minimum-jerk model. Journal of Experimental Psychology: Human Perception and Performance, 1 4 , 622-637 Wing,A.M. & Kristofferson,A.B. (1973a). Response delays and the timing of discrete motor responses. Perception and Psychophysics, 1 4 , 5-12 Wing,A.M & Kristofferson,A.B. (1973b). The timing of interresponse intervals. Perception and Psychophysics, 13, 455460 Wulf,G. & Schmidt,R.A. (1988). Variability in practice: Facilitation in retention and transfer through schema formation or context effects? Journal of Motor Behavior, 20, 133-149 Young, D.E., Schmidt, R.A. & Lange, L.A. (1990). Units of motor behavior: Modification with practice and feedback. In M. Jeannerod (Ed.). Attention and performance X I I I . Hillsdale, N.J.: Erlbaum Zelaznik,H.N., Schmidt,R.A. & Gielen,S.C.A.M. (1986). Kinematic properties of aimed hand movements. Journal of Motor Behavior, 18, 353-372

The Development of Timing Control and Temporal Or anization in Coordinated Action J. Fagard anfP.H. Wolff (Editors) Q Elsevier Science Publishers B.V., 1991

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R e l a t i v e timing f r o m t h e perspective of dynamic p a t t e r n theory: Stability a n d instability.1 P.G. Zanone and J.A.S. Kelso Program in Complex Systems and Brain Sciences, Center for Complex Systems, Florida Atlantic University, P.O. Box 3091, Boca Raton, Fla 33431 (USA) ABSTRACT. Unlike many approaches that use the relative timing invariance of skilled movements to invoke central, represented templates, the dynamical framework adopted here views relative timing as one (but not the only) entry-point that captures the cooperative processes underlying spatiotemporal organization of action. The study of temporal stability and loss of stability in bimanual movement patterns reveals the intrinsic dynamics of interlimb coordination. The adaptive mechanisms of the system, such as perceptual-motor coordination, entrainment, and learning, can be addressed operationally in terms of the interplay between these intrinsic dynamics and the behavioral constraints (e.g., environmental, intentional). Such dynamical principles a r e ultimately at the origin of behavioral stability and change at different levels of analysis and a r e active on several different time scales. 1 . INTRODUCTION

That movement may unfold in a coordinated, spatiotemporally organized fashion in spite of the tremendous complexity of the perceptual-motor system and the ever-changing external and internal constraints acting u p o n its components is one of the most amazing phenomena of everyday life. For the scientist, the challenging question is raised of what principles and mechanisms govern the achievement of such ordering in space and time. Fortunately (and deceivingly), action constitutes a macroscopic object of experimental investigation that may afford a way to unveil underlying organizational laws. Eventually, dynamical principles of movement coordination may be aradigmatic of the mechanisms in the central nervous system (CNS) that allow !or ordered (and disordered) behavior at this and other levels of description. Following this route, a great deal of research has been aimed at finding t h e algorithms for the spatiotemporal organization of skilled movement. Very generally, the prevailing idea emerged that motor behavior is best described in terms of i n v a r i a n c e : Some dependent variables seem to be rather insensitive -

The research was funded partly by NIHH qrant 1 4 2 9 0 0 , BRSG qrant NSS 1-SO7-RRO7258-01, and contract N00014-884-119 from the U.S. ONR. The first author was also supported by the Swiss National Science foundation, grant 8210-026064.

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to experimental changes in the independent variables, compared to other measures which covary more steadily. The movement invariance discovered most precociously was probably that of movement time (Bryan, 1892; Binet & Courtier, 1893; Freeman, 1914), the study of which culminated in Fitts' Law (Fitts, 1954) and the wealth of work that followed. The common belief was then that: "these invariances [...I have a great deal to sa about the underlying control processes for skills, in terms o how skilled movement behavior is represented in the CNS [...I" (Schmidt, 1985,

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In particular, timin between com arable events of a movement performed over a wide range o spatiotempora parameters (e.g., speed, amplitude) turns out to remain fairly constant relative to the total movement duration. In the area of human motor control alone, numerous examples su porting the relative timing invariance hypothesis have accumulated in intralim coordination (e.g., handwriting: Theulings, Thomassen & van Galen, 1986; Viviani & McCollum, 1985; prehension: Jeannerod, 1984; Wallace & Weeks, 1988; locomotion: Shapiro, Zernicke, Gordon & Diestel, 1981). Such results have led to the interpretation that there must be a temporal code, a general structure that controls the ongoing movement (a "motor unit", a "template", a "[generalized] motor program"), the parameters of which are mutable by the CNS in order to meet the actual task requirements. This code can then be played back a t different rates, keeping unchan ed the temporal patterning of movement over slight surface modifications pk.g., amplitude, force). Hence the "record metaphor" nicely captures the gist of the mechanism (Schmidt, 1987). The view of an abstract score setting the relative timing of movements finds also some support in the tight temporal coupling observed in interlimb coordination (e.g., typing: Viviani & Terzuolo, 1983; pointing: Kelso, Putnam &Goodman, 1983; Kelso, Southard & Goodman, 1979; in development: Fagard, 1987), although not always interpreted as such.

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As it often ha pens with any empirically derived principle, relative timing invariance su fers several experimental counterexamples as well as methodological and statistical flaws (e.g., Gentner, 1982, 1987; Heuer, 1988; Rumelhardt & Norman, 1982; Wann, Nimmo-Smith & Wing, 1988). Instead of entering here into a detailed discussion about the shortcomings inherent to such a prescriptive framework (e.g., Kugler, Kelso & Turvey, 1980, 1982; Zanone, 1990) or the methodological and statistical concerns that have arisen (Tuller & Kelso, 1990), we prefer to shed another light by posing a n essential question: How has the concept of (relative timing) invariance enhanced our understanding of the actual functionin of the CNS and its adaptability with respect to environmental constraints? %o answer this question, let us review several points of criticism which illustrate the limitations of the "invariance" approach as presently formulated.

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First, all the movements analyzed in the studies on motor invariance concern, explicitly or not, skilled performance. Thus, such invariance is perhaps observed but in highly trained behaviors. Even, (relative timing) invariance might constitute one of the clearest signs of skilled performance. Second, although the span of experimental variations within which invariance is observed seems large at first glance, it does not a p roach or go beyond the point at which the invariant pattern may be p e r t u r b e x o r even disrupted. Thus,

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seldom is there a basis upon which to compare the "invariance" of a pattern with another. Third, invariance remains an average behavioral feature within and across individuals, insofar as variability is considered to be noise, hence, unworthy of any interest. Fourth, several behaviors exhibiting various types of temporal invariance may be observed i n a similar situation. For instance, animals -humans included - can ado t different gaits of locomotion at the same speed (e.g., Hoyt & Taylor, 1981). n a slightly more provocative manner, one may argue that invariance is observed to the extent that the experimental conditions and the experimenter's frame of mind are set such that nothing else can be observed, leaving the question "invariant compared to what?" ignored.

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As far as understanding behavioral adaptation is concerned, it could be argued that a better window is offered when the mechanisms leading to invariance break down. As soon as the flexibilit allowed by such mechanisms is overridden, the full adaptability of the C d S appears. Therefore, we propose t o trade the static notion of invariance with the broader dynamical concept of s t a b i l i t y . Invariance refers to behavioral stationarity, that is, a fairly constant mean of some dependent variable over time. As we shall see, the concept of stability unites behavioral invariance with behavioral variability and change (continuous and abrupt) within a single metric. The reason why deviations from invariance are important is that fluctuations probe the stability of coordinated states and allow the system to explore and discover new ones. A well-grounded approach to (self-)adaptation comes from a field that originated i n physics concerned with the formation of spatiotemporal patterns i n nonequilibrium systems. Pattern formation is a common feature of m a n y physical, chemical, and, as we shall see, biological systems (see Haken, 1 9 8 3 a ; Kelso, Mandell & Shlesinger, 1988; Nicolis & Prigogine, 1989; Yates, 1987). Althou h the material substrates are different across these systems, the same p r i n c i c e s govern their (self-)organization. Such principles have been descri ed in synergetics, a theory of spontaneous pattern formation in open systems (see Haken, 1983a, 1983b, 1985). Self-organization results from the cooperative interplay of a large number of subsystems and pertains to the dissipative properties of the system's dynamics (Le., the e uations of motion of the system i n state space): The system will eventually reac a s t a b l e collective state (i.e., re roducible relations among interacting components) from a broad range of diherent initial states. Thus, if slightly erturbed, the system Ie in the local stability spontaneously relaxes to the stable state and is said to ! rkgime. Dissipative systems may also exhibit multiple stable collective states under the same boundary conditions. Then, the system can occasionally switch from one stable state to another on a much slower time scale, due to various types of noise acting on the system. A system "visiting" ts various stable states is in the global stability rkgime.

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In synergetics, specific and non-specific parameters act on the coordination dynamics, so that the system may b e led throu h instabilities. Under such circumstances, the system does not fall back to t e same stable state after a small parameter change, but instead switches (often abruptly) t o another stable state. At these points of p h a s e t r a n s i t i o n or bifurcation, the system reveals its basic organizational principle: A pattern exists as long as it is stable. Accordingly, loss of stability is instrumental in establishing the complete system's d namics, since it may lead t o behavioral change and the selection of new or difrerent patterns.

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According to this brief theoretical sket h, we can rephrase criticisms formulated about the search of invariances 2 and will propose a n alternative framework. Invariance reflects the existence of one stable collective state of the system in the local stability regime. As such, this is an important piece of knowledge. Yet, invariance provides no information about its global stability rbgime, that is, the system’s full dynamics remain concealed. Thus, the adaptive functioning of the CNS that permits a broad behavioral repertoire is never addressed, hiding principles that govern flexible switching among the (mu1ti)stable behaviors. Now, the concept of phase transitions suggests powerful methods to explore the system’s dynamics. In the framework of d y n a m i c p a t t e r n t h e o r y (Kelso & Schoner, 1987, 1988; Schoner & Kelso, 1988a, 1988b, 1988c), the paradigm for understanding self-organization and adaptation is to view behavior and behavioral change in terms of pattern stability and loss of stability.

In the following, the operational language of dynamic attern theory will be introduced, and its concepts illustrated through severa examples concerning relative timin among limbs in humans. It will become clear how such an approach she s light on laws of temporal ordering in interlimb coordination. Furthermore, such a framework captures adaptive mechanisms of coordination when the system is confronted with varied environmental constraints. We view the systematic treatment of these cases as a window into understanding some coordinative processes of the CNS commonly invoked in the field of motor behavior, psychology, and neurosciences.

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2. THE BASIC PHENOMENON: ADAPTATION TO NON-SPECIFIC CONSTRAINTS

When requested to move homoloBous fingers rhythmically at a common frequency (Kelso 1984), human subjects exhibit two patterns of coordination that are stable at various frequencies: in-phase (simultaneous activation of homologous muscles in both fingers) and anti-phase (alternated activation). The collective state of these two oscillating components can be captured through a pertinent collective variable, or o r d e r p a r a m e t e r , relative phase. The order parameter characterizes the observed b e h a v i o r a l p a t t e r n , which exhibits minimal variability at 0 and 180 deg. In the absence of any specific requirement in terms of relative phase between the components, the in-phase and anti-phase patterns are the only stable collective states toward which behavior is spontaneously attracted. In the field of human motor behavior alone, numerous examples of stable (less variable) in-phase and anti-phase patterns have been reported under quite different experimental conditions, We do not deny, however, the powerful concept of invariance for understanding the dynamics of coordination, especially when linked to m t r v p r ’ se (cf Kelso, in press). For example, symmetry has been used to classify coordination patterns (hand movements, locomotion gaits, etc.) and to restrict the functional form of the coordination dynamics, equations of motion that characterize the coordination activity of the CNS (Eaken, Kelso 6 Bunz, 1985; Schoner, Jiang 6 Kelso, 1990). Synmetries are expressed as invariance of the coordination pattern under a set or group of transformations. For example, the idealized walk, trot, gallop, and jump are member of the same symmetry group, namely, the only patterns that are invariant under left-right, front-hind and time inversion operations. Quantitative analysis of kinematic patterns on the other hand should in this view be fornulated in terns of the concept of stability and not (as in the motor control literature) invariance, because statistical fluctuations are a necessary part of the measurement process and prove to be conceptually important.

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either in interlimb coordination (e.g., Baldissera, Cavallari & Civaschi, 1982; Cohen, 1971; Tuller & Kelso, 1989, Yamanishi, Kawato and Suzuki, 1980) or intralimb coordination (Kelso, Buchanan & Wallace, 1990; Soechting & Terzuolo, 1986). If frequency is increased further, different phenomena are observed depending on the initial state of the system. Let us emphasize that the frequency parameter is unrelated to the col ective variable, relative phase, but acts as a non-specific cont ro l p a r a m e t e r - . If the system is set initially in the in-phase pattern, i t remains stable as such at all typical frequencies. In contrast, if the system is set originally i n the anti-phase pattern, it spontaneously switches t o the in-phase pattern above a given threshold. This is illustrated i n Figure 1. In Panel A (top of Figure l ) , the angular displacement of the right (solid line) and the left finger (dotted line) are plotted as a function of time, as the control parameter goes from 1.5 and 2.5 Hz. Finger abduction makes the curve move

4

A. TIME SERIES

-Position of

Right index Finger ____. Position of Left Index Finger

B. POINT ESTIMATE OF RELATIVE PHASE

-- -

..... .. ........ .............................. I

I

I 2sec I

I

Figure 1 : Typi cal phas e t r a n s i t i o n i n coor d i n a t e d f i n g e r m o v e m e n t s . Pa n el A p l o t s t h e m o t i o n of t h e i n d i v i d u a l f i n ers and P a n e l B t h e i r r e la t i ve p h a s e as a f u n c t i o n of t i m e , w hile t h e r r e q u e n c y of t h e f i n g e r o s c il l at i on is grad ually incr eas ed. S e e t e x t f or d e t a i l s.

It "controls" only in the sense of keeping the system in a stable operating range or by leading the system into instabilities where new patterns are formed.

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upward, and adduction downward. (Note that the same results are obtained with flexion/extension motion of the fingers or wrists.) A cycle-by-cycle pointestimate of the relative phase between movements is displayed on Panel B (bottom Panel). The switch from 180 to 0 deg (viz., 360 deg) is quite evident in the middle of the graph, preceded by a noticeable enhancement of the fluctuations of relative phase around 180 deg. In fact, by increasing frequency, the 180-deg pattern becomes unstable, so that the behavioral pattern is finally attracted to the 0-deg pattern. These features suggest that the in-phase pattern is more stable than the anti- phase pattern. An important step in building a theory in this model case of finger movements is to map the observed stable patterns onto attractors of the collective variable dynamics. Theoretically, attractors are asymptotically stable solutions of the equations of motion. The spontaneous switch from the anti- phase to the inphase pattern corresponds to a n o n e q u i l i b r i u m p h a s e t r a n s i t i o n from a bistable (at 0 and 180 deg) to a monostable rCgime (at 0 deg only) of the pattern dynamics. Such dynamics a r e called i n t r i n s i c d y n a m i c s , in that they exist independent of any specific constraints. The typical features of this phase transition have been extensively studied at the experimental and the theoretical levels (e.g., Haken, Kelso, & Bunz, 1985; Kay, Kelso, Saltzman, & Schoner, 1987; Kelso, Scholz, & Schoner, 1986, 1988; Scholz, Kelso, & Schoner, 1987; Scholz & Kelso, 1990; Schoner, Haken, & Kelso, 1986). The sharp change in behavior involved in the phase transition pertains to the n o n l i n e a r i t y of the system's dynamics, so that a slight difference in the control parameter near the critical value entails qualitative changes in the coordinative state, whereas elsewhere in p a r a m e t e r s p a c e , the system remains stable, insensitive to fairly large changes of the control parameter.

The relevance of this ensemble of data and theory to the questions raised about invariance in the previous section is threefold. First, behavioral pattern and stability are co-implicative concepts. Hence, it may be proposed that the mechanisms responsible for invariance ensure stability of behavior, and invariance is observed because the pattern of coordination is stable. As already pointed out, there is no way out of this kind of tautology as long as the system is maintained in one sin le stable state. Second, non-s ecific parameters can dramatically affect begavior, so that under certain Ioundary conditions, a coordination pattern may become very variable, transient, or eventually cease to be observable, if complete loss of stability is attained. This suggests that a given "invariance" might emerge only under a restricted range of boundary conditions, that is, a small region in parameter space. Third, once the system settles into a strong attractor, the odds are slim f o r the system t o exhibit other patterns due to hysteresis effects. Due to its inherent nonlinearity, the s stem is not only affected by the current boundary conditions (i.e., the ensemile of influences impinging onto the system), but also by its previous history (i.e., the state from which it comes). Practically, this means that the system may stay in a state A when a control parameter is manipulated in one direction and in the state B at the same value of the parameter, when it is scaled in the reverse direction. Thus, even though some parameter is manipulated experimentally, the presence of h steresis may limit the possible behavioral repertoire. Ultimately. these " h d d e n " behaviors may prove t o be those adopted when adaptation to larger system perturbations is required. The present "encoding" or mapping of ex erimental phenomena and theoretical modelling illustrates how knowledge o t t h e attractor layout of the coordination dynamics is crucial to

Relative Timingfrom the Perspective of Dynamic Pattern Theory

Phenomena

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Dynamics

IBoundary constraints I Specific parameters: e.g., oscillate fingers in a given fashion.. . Non-specific parameters: e.g., change frequency, spatial orientation.. .

Coordination dynamics

IOrder parameter1

V ( 4 )= -aces($) - 2bcos(24)

characterizes coordinated st at es, e.g., relative phase (4)

h Individual dynamics

nonlinear coupled oscillators

F i g u r e 2: W h a t " u n d e r s t a n d i n g " c o o r d i n a t i o n d y n a m i c s m e a n s o n a c h o s e n l e v e l of o b s e r v a t i o n : T h e b i m a n u a l c o o r d i n a t i o n e x a m p l e . S e e text f o r d e t a i l s . understanding the observed behavior in terms of adaptation to the current boundary conditions. I n Figure 2, we represent the conceptual nature of the relationship a ) between phenomena and theory (horizontal mapping); and b) between levels of description (vertical mapping), using the example of bimanual coordination The key-points can be highlighted as follows: A minimum of three levels is required to provide a closed-form description on any single level. There is mutability among levels. For instance, the component level here defined in terms of x , R for each component may be seen as a collective order parameter level for more fine grained descriptions, such as muscle activity. Model parameters a , b ma onto frequency in experiment; parameter a is non-ho onomic (non-integrable, rateindependent).

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The functional form of the component level is a ain determined based upon empirical considerations (e.g., ampfitude-frequency and velocity-position relations, phase resetting, dimension, etc.). Note that the dynamical law at the middle, coordinative level is derivable from the component dynamics. which may, o r may not be oscillatory. 3. A D A P T A T I O N TO S P E C I F I C C O N S T R A I N T S

The need to know the intrinsic dynamics is even more obvious to understand the behavior of the system under specific environmental constraints, that is, when boundary conditions affect the collective variable relative hase itself. In the first experiment briefly reported below, a given relative p ase is im osed by task requirements. In the second, the system is forced to execute p e r i o g c finger movements, each with different frequencies, so that the question of the validity of relative phase as an order parameter is raised. Both studies will show that the CNS is still subject to intrinsic dynamics, so that knowing these not only allows one to interpret the observed behavior a posteriori, but also to predict it.

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3.1. Producing a r e q u i r e d relative p h a s e Building on the previous results, the question arises of what happens when specific task requirements act as a force on the system’s behavior. In a situation similar to that of the study by Kelso (1984) described above, a visual metronome in front of the subjects displayed various relative phases, defined as the time relationship between the onsets of the two light-emitting diodes (LEDs). Subjects were asked to flex each finger synchronously with the onset of the respective left o r right LED. No other constraint was imposed on movement but to execute as smooth and regular motion as possible. So, sub’ects had to generate a coordinated pattern whose relative phase matched t e required phasing displayed by the metronome. In the terms of dynamic pattern theory, the required phasing constitutes b e h a v i o r a l in o r m a t i o n , in that it determines an attractor of the pattern dynamics. he task requirement is expressed by the same collective variable as behavior, namely, the relative phase defined by the metronome, toward which the system relaxes, were it not influenced by other factors, especially its intrinsic dynamics. In the current case, behavioral information I S defined by the environment, but it may represent as well a recalled pattern, o r intentional or purposeful needs. T h e metronome frequency was chosen below the threshold at which a phase transition is observed, so that multistability was expected.

h

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During an experimental trial, the relative phase required by the metronome was increased progressively from 0 (simultaneous blink of the two LEDs) to 180 deg (alternate blink) by steps of 15 deg, in thirteen plateaus lasting 20 s each. The rationale for this procedure is fairly straightforward. If no intrinsic dynamics were to come into play, the produced relative phase would perfectly match the required phasing. On the contrary, s stematic distortions with respect to the requested performance may reflect t i e presence of stable patterns attracting behavior elsewhere. Accordingly, these attractors must exhibit the smallest variability, since they are stable. In other words, the procedure is designed to

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probe the individual's intrinsic dynami s. that is, to provide a "snapshot" of their attractor layout o r p h a s e d i a g r a m . For the sake of simplicity, we shall report here results for some prototypical subjects (for more details, see Zanone & Kelso, 1990). The outcome of probin the dynamics a r e shown in Figure 3. In both parts, the upper curve (solid line? presents the mean within-plateau DELTA R P as a function of the required phasing. DELTA R P is the difference between the produced and the required relative phases, such that when the required phasing is overestimated, DELTA R P has a positive value, and conversely. Recall that if there were no intrinsic dynamics, the roduced relative phase would equal the required phasing, hence, mean DELTA R P would be a flat curve lying o n the zero line (dashed line). In the lower raphs (dotted lines) of each panel, the SD of DELTA R P within a plateau is i s p l a y e d as a function of the required phasing. For Subject TM (left part of Figure 3), mean DELTA R P (top curve) exhibits a humped shape as a function of required phasin , that is, it is lowest when the required phasing is 0 or 180 deg. The negative sfope below 180 deg of required phasing reflects attraction to the 180-deg pattern: The roduced relative phase departs from the required phasing in the direction of e!t 180-deg pattern, and the mismatch is roughly proportional to the difference between the required pattern and 180 deg. Attraction to the in-phase pattern, although much smaller, is also noticeable. The bottom curve shows that SD is lowest a t 0 and 180 deg, but it increases markedly at intermediate values, indicating that the 0- and 180deg patterns a r e stable, although the latter appears more variable than the former. Performance of Subject TM in this first probe can be described in a more intuitive fashion. The behavioral pattern stays around 0 deg of relative phase in the first two plateaus. Then, it becomes progressively unstable as attraction to the 180-deg attern develops, so that when 90-deg is required, the actual relative phase is a i o u t 180 deg. Once the pattern has "fallen" into this attractor, the variability drops steeply, and the 180 deg pattern is produced stably regardless of the required phasing. Such behavior and the attractor layout are those expected for the bistable dynamics reported in Kelso's original experiment. This picture is in tight agreement with the results of Tuller and Kelso (1989) and those of Yamanishi e t al., (1980), even though these authors used different methods and experimental situations t o probe the dynamics. In contrast, Subject SB (left part of Fi ure 3) exhibits a rather distinct attractor layout. Following the same scheme o interpretation, not only a r e the 0 and 180deg patterns stable and attractive, but the 90-deg pattern as well (negative slope of DELTA R P about this value and low SD).Thus, Subject SB is characterized by tristable dynamics in the span 0-180 deg.

B

The term '\phase diagram" derives fron thermodynamics. Hore generally, a phase diagram defines regions in parameter space that do not exhibit qualitative changes of the system's dynamics, as well as the boundaries across which such changes occur. In nonlinear dynamical systems, change can be continuous or qualitative depending on the region in parameter space occupied. We use the image \\attractor layout'l synonymously with phase diagram in this chapter in order to avoid confusion with the collective variable of our experimental system, $, which is a relative timing variable expressing the coordination between active components. Eowever, it is important to note that a typical \'attractor layout" or phase diagram nay contain attractive, repelling, and saddle points that occupy basins and separatrices (e.g., Abraham & Shaw, 1982).

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F i g u r e 3: E x a m p l e s of i n i t i a l p h a s e d i a g r a m s . T h e upper ( s o l i d ) g r a p h s p l o t t h e m e a n p r o d u c e d r e l a t i v e p h a s e a s a f u n c t i o n of t h e r e q u i r e d p h a s i n g . T h e l o w e r ( d o t t e d ) g r a p h s p r e s e n t t h e c o r r e s p o n d i n g SD. These results put into light two fundamental processes pertaining t o perceptual-motor behavior, which account for the observed differences in pattern stability as a function of the task requirements. When the re uired pattern corresponds to one of the intrinsic attractors (as for Subject T ), the attern d namics and behavioral information c o o p e r a t e to attract the ehaviora pattern to the same relative phase, so that the resulting state is highly stable. Conversely, when the required pattern does not coincide with a n attractor (as for Subject SB), the pattern dynamics and behavioral information com ete, fluctuations occur, and the resulting state is much less stable. In other worifs, the extent to which behavioral information cooperates or competes with the intrinsic dynamics determines the observed coordination pattern in terms of mean performance and variability.

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The question arises now as to how the system will adapt to environmental constraints on a longer run, given the differences in the individual intrinsic dynamics. In the same experiment, Zanone and Kelso (1990) had the subjects ractice the 90-deg pattern, so that the required pattern was eventually fearned. The learning procedure comprised fifteen trials per day, lasting 20 s each, €or five consecutive days. After each trial, knowledge of results was provided to the subjects. The pattern to be learned was set at 90 deg of relative

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phase, that is, in-between the 0 and 180 deg patterns that correspond t o attractive collective states of the coordination dynamics. From the very first trial on, Subject SB performed the required 90-deg relative phase i n a remarkably accurate and stable manner. This is little wonder, since, In our language, such a pattern corresponds to an attractor in our language. Instead, on the first trial, Subject TM produced a 180-deg pattern very consistently, in spite of the task requirements. The behavioral pattern fell almost immediately into one of the two intrinsic attractors, namely 180 deg. With practice, the produced relative phase tended gradually toward t h e required phasing across trials, until it matched 90 deg i n a stable fashion by the middle of the second day of practice. Nevertheless, during this process of learning, performance was highly variable, reflecting expected competition between the intrinsic dynamics pulling the behavioral pattern to 180 deg and behavioral information attracting it to 90 deg. For both subjects, practice entailed a substantial decrease in within- as well as across-trial variability. However, substantial fluctuations still remained across days. Now, if this interpretation is correct, it follows that when Subject T M finally performs the 90-deg required phasing, there m u s t be a n attractor of the pattern dynamics at that value, which did not exist in the original phase diagram. In order to trace this change, periodic probes of the attractor layout were carried out during the learning procedure. At the beginning and the end of each daily session, as well as twice in-between, the current phase diagram was established following the technique of scanning the required relative phase described above. Figure 4 displays the evolution of the attractor layout with practice for Subjects TM and MS. More specifically, the mean within-plateau relative phase coded A to 0 as the required phasing increases from 0 to 180 deg in each probe is plotted as a function the probe number. A cubic polynomial interpolation of these average values is drawn, such that the trend may be followed+ac_ross consecutive probes. If there were no influence of the intrinsic dynamics, the produced relative phase would match each required phasing between 0-180 deg in each probe. Thus, if no change in the dynamics occurred with practice, thirteen equidistant horizontal line would be plotted. On the other hand, clustered data points indicate the presence of an attractor. Changes with time in the attractor layout may be then observed over the time scale of the experiment, such as the drift of an attractor (fluctuation of a bunch of curves), the broadening or narrowing of a b a s i n of a t t r a c t i o n (convergence or divergence of curves, respectively). For Subject T M (left part of Fi ure 4), the salient phenomenon is the convergence of a large number !o "iso-requirement" curves toward 90 deg across successive probes. This illustrates very nicely how the attraction of this pattern is progressively built up with practice. Mostly, curves belonging to the 180-deg basin fall into that centered about 90 deg. Eventually, the 90- d e attractor temporarily "sucks in" the entire basin with t h e 180-deg pattern itself as observed at the end of Day 2 and the beginning of Day 3. These findings strongly suggest that the 180-deg pattern becomes unstable. Let us emphasize that there is close temporal coincidence between the moment at which the 90deg pattern is finally performed stably in the practice trials and the moment at which the corresponding attractor seems established, namely, in the middle of the second day of practice. Therefore, these results not only demonstrate the coherence of the dynamic pattern theory framework, but also permit us to

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PROBE NUMBER Figure 4: E v o l u t i o n of t h e phase diagrams with learning. S e e text f o r details formulate a basic insight into learning (Schoner, 1989; Schoner & Kelso, 1988d, 1988e): A pattern is learned to the extent that the intrinsic dynamics a r e modified in the direction of the to-be-learned pattern. In the case where there is initially competition between behavioral information and the intrinsic dynamics, as in Subject TM, learning involves a qualitative modification of the pattern dynamics: The required pattern emerges as a novel attractor in the phase diagram, and an originally stable pattern destabilizes. These are characteristic features of nonequilibrium phase transitions (for a detailed discussion of learning, see Schoner, Zanone & Kelso, in press). The right part of Figure 4 displays the evolution of the attractor layout with practice for Subject MS. Initially, the clustering of mean relative phases produced in adjacent plateaus around 0, 120, and 180 deg suggest tristable dynamics comparable with those of Subject SB above. With practice, all the isorequirement curves except 0 deg (coded A ) converge gradually toward 90 deg, as a huge basin of attraction evolves. Indeed, c o o p e r a t i o n between the intrinsic dynamics and behavioral information, both attracting the behavioral pattern toward 90 deg, concur to its further stabilization. As a result, the 90-deg pattern becomes a stron e r and stronger attractor, which eventually absorbs the 180-deg pattern itself. This alteration of the initial pattern dynamics also constitutes a nonequilibrium phase transition. Note that for all subjects the changes in performance and in the pattern dynamics were robust over a period of retention of one week, a necessary requirement for the conclusion that persistent changes, hence learning occurred.

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T o sum up, let us highlight some important points. If behavioral information is such t h a t it competes with the intrinsic dynamics (i.e., the required coordination pattern does not tap into the basin of an intrinsic attractor), two adaptive mechanisms aiming at reducing such competition come into play. On a short time scale, the behavioral pattern may be pulled into a nearby intrinsic attractor. On a longer time scale, the required pattern is progressively learned, to the extent that it actually becomes a behavioral attractor. One consequence of such a formulation is that altogether different initial pattern dynamics are observed between subjects under the same experimental settings. In fact, the study by Zanone & Kelso (1990) showed that some subjects exhibited tristable rather than bistable dynamics. This emphasizes the fact that the intrinsic dynamics a r e not simply hard-wired ri id, or preformed structures that constrain behavior, but rather constitute softfy- assembled, task-specific, and environmentally-attuned capacities that exist at the time a pattern is to be learned. Therefore, let us emphasize again t h e critical importance of knowing the system's intrinsic dynamics in order to understand how cooperative and competitive mechanisms lead to learning. The phase diagram allows one t o establish prior to learning which pattern is to be learned "from scratch", and to determine after learning to what extent this pattern has actually been learned. The phase diagram provides a probe of the long-term, sometimes qualitative modifications of the behavioral repertoire with learning, beyond quantitative changes in performance on a shorter time scale.

As indicated above, learning may lead to phase transitions, that is, qualitative modifications of the system's dynamics, depending on the distance between behavioral information and the intrinsic dynamics. Tentatively, we might want to juxtapose the two phenomena observed above in a common scenario. Starting from bistable intrinsic dynamics (cf. Subject TM), a first phase transition leads to tristable dynamics, establishing the to-be-learned pattern as an attractor (i.e., 90 deg). Then, loss of stability of the least stable among the original attractors ( 180 deg) entails a second phase transition, resulting in bistable dynamics (0 and 90 deg). Finally, a third phase transition could involve loss of stability of the most stable attractor too ( 0 deg). Although the latter transition was not captured on the time scale of the present experiment, the consistent drift of the 0-deg pattern toward 90 deg (see curves coded A in Figure 4)suggests that learning affects this pattern too. Eventually, even the inphase pattern might lose stability, leaving the 90-deg pattern as the only attractor. This evolution of the attractor layout to monostability with learning might correspond to a condition that psychologists refer to as overlearning. Finally, assuming that relative timing "invariance" expresses pattern stability, a monostability attained with learning across varied environmental constraints may explain why relative timing invariance is characteristic of learned and highly skilled actions. One has to keep in mind that such invariant behavior results from a long process which reduces the original multistability of the system. Interestingly, learning on a much slower time scale, namely, developmental time, show numerous examples of comparable reduction in the system multistability. An illustration may be found in babies who lose the discrimination between phonemes if these no longer belong to their native language (e.g., Strange & Jenkins, 1978; Werker & Lalonde, 1988). Such sharp reduction of a broad initial repertoire fits very well into the Chomskian framework (e.g., Chomsky, 1988) and selectionist ideas in general (e.g., Edelman, 1987).

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3.2. Producing different f r e q u e n c i e s In the foregoing, it has been shown that the pattern dynamics of coordination is adequately captured by the dynamics of a single collective variable, relative phase between the limbs periodic motion. As well, it has been claimed that the dynamical approach promotes a multilevel but theoretically coherent investigation of the system under study (cf. Figure 2 ) . As a n example, let us now examine the same bimanual system, but now one step below, namely, a t the level of the components. The individual finger's coordination dynamics can be modelled as a l i m i t c y c l e o s c i l l a t o r (e.g., Kelso, Holt, Rubin & Kugler, 1981). If perturbed, the system tends to recover its circular trajectory in the phase plane spontaneously, so that a well-defined phase relationshi between position and velocity is maintained over time. Such a natural inc ination of limbs to keep oscillating regularly was coined the "maintenance tendency" by von Holst (1939/1973). The two-finger system forms two nonlinear c o u p l e d oscillators. Their collective dynamics have been derived by Haken et al. (1985), so that the relative phase between the coupled oscillators exhibits a phase transition when oscillation frequency increases above a critical value.

P

A question posed by Kelso and DeGuzman (1988; see also DeGuzman and Kelso (in press) is what happens when the components oscillate at different frequencies, that is, what a r e the characteristics of the coupling between the two oscillators over time. Experiments were conducted in which subjects had to maintain the frequency of the right finger constant, while the other was mechanically driven by a torque motor a t another frequency. The results a r e very clear. For both frequencies to be kept constant by the right finger (i.e., 1.5 and 2.0 Hz), some frequency ratios turned out to be consistently more stable, namely, 3:2,2:l and 3:l. These correspond to m o d e - o r f r e q u e n c y - l o c k e d rkgimes of the dynamics. Accordingly, less stable patterns were attracted to these mode-locked patterns, since on the average, the observed ratios were biased in the direction of these simple integer frequenc ratios. Furthermore, a less stable behavioral pattern oftentimes shifted to t i e closest mode-locked regime in the course of a trial. A recent study by Pepper, Beek & van Wieringen (in press) which explored the relative stability of such frequency-lockings in drummers is very much in keeping with these results. When asked to maintain a given frequency ratio between hands as the tempo was increased gradually equivalent to Kelso's (1984)manipulation of a control parameter - transitions were obtained between mode-locking regimes whose sequence nicely followed the inverse Fibonacci series, that is, going from complex to simple frequency ratios. Numerous other examples of systems adopting various but limited lowinteger ratios, stable mode-locking regimes are reported in locomotion. A work by Thelen, Ulrich and Niles (1987)in human babies walkin on a split treadmill which runs a t different speed showed that the frequency o f t h e "fast" limb goes as a multiple of that of the "slow" leg. Comparable results a r e provided by Kulagin and Shik (1970) in the mesencephalic cat. Coupling between respiratory and locomotory rhythms showing the same henomena has been studied by Bramble and Carrier (1983)in human and q u a i u p e d a l gait.

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Far from behavioral sciences, nonlinear coupled oscillators represent a n object of extensive study in physics, mathematics and engineering, often modelled by the van der Pol equation (e.g., Abraham & Shaw, 1982, f o r a theoretical account). A very convenient way to capture the system's behavior is to probe the phase of the driven oscillator each time the forcing one accomplishes a complete cycle. Such r e t u r n m a p techniques imply mapping the circumference of a circle onto itself, hence the name of "circle map". The related equation depends on two parameters only, namely, the ratio between the frequencies of the driving and the forced oscillators and on the strength of their coupling. Yet, it is well known that this map captures the full dynamics of the system (reduction of its dimensionality). The regions in parameter space, namely, coupling strength (K) x frequency ratio Q, in which the system adopts a modelocked regime may be represented as "Arnold tongues" (Arnold, 1983), that is, the regions in parameter space in which each regime is stable and attractive. Examples of Arnold tongues for the model system of bimanual coordination a r e represented i n Figure 5. Two essential features are noticeable in all panels. First, with increasing coupling (K), the width of the tongues broadens, and so does the stability of the related mode (the frequency ratios corresponding to each tongue a r e indicated above the frame). Second, such a n increase in stability is quite compatible with the experimental results, the simplest modelockings exhibiting the widest tongue. This demonstrates the tight coherence between the model (i.e., the circle map) and the experimental findings. Starting from this model, DeGuzman and Kelso (in press) introduced into the circle map a parameter, A, representing the phase attractive property of the bimanual system, that is, the bistable dynamics of relative phase defined in the theory by Haken et al., (1985). Then, by iterating the map, all behaviors observed in the biological system were found, including: a ) transition from bistability to monostability as the frequency is increased, b) attraction from less stable to more stable frequency-locking mode, and c ) s ontaneous jumps from one phasing pattern to another within a given mode-loc!Iing regime. Even more important I S that the model allows f o r new predictions. Comparing the three anels of Figure 5, note that the width of the Arnold ton ues is modified as a Function of the parameter A (i.e., A = 0, 0.5, and -0.f in panels A to C, respectively). Thus, the stability of the various mode-locking rtgimes can be increased or decreased, depending on where the system "lives" in parameter space. Therefore, not only is relative phase a collective variable describing the system's dynamics, but phasing itself is a mechanism that governs the stability of multifre uency patterns. More recently (Kelso, DeGuzman & Holroyd, in ress, a a n 1 b), it has been shown that under conditions in which phase and Frequency synchronization are neither attained nor desirable, the system lives n e a r the mode-locked Arnold tongues, but n o t i n them. For example, if the system, due to the inherent variability of its components, is not exactly in a simple frequency-locked state (e.g., 1:l or 2:1), phase slippage is observed along with the insertion of additional cycles and hopping in and out phaselocked modes. Kelso et al. (ibid.) show that this relative o r sliding coordination corresponds to the intermittency regime of the phase-attractive circle map dynamics. Intermittency seems quite crucial because it affords a possibility to hase and frequency synchronize, but also provided the necessary mechanism For entering and exiting coherent states as well as exploring the full state space. It could well be important in the areas of vision (Gray, Konig, Engel &k Singer, 1989), neuronal pattern generators (Grillner, 1980), memory (Miller, 1989) and coordinated action itself not to get trapped in resonant, mode-locked states.

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Figure 5 : M o d i f i c a t i o n s of t h e A r n o l d t o n g u e s w i t h d i f f e r e n t v a l u e of A . Q is t h e r a t i o b e t w e e n t h e c o m p o n e n t s f r e q u e n c i e s a n d K t h e c o u p l i n g s t r e n g t h . S e e text f or d e t a i l s . The intermittency mechanism, which is a generic feature of dynamical systems such as circle maps, provides a vital mix of flexible yet coherent coordination. 4. DISCUSSION

This chapter reviewed several studies that illustrate the dynamic pattern approach to coordination in multidegree-of-freedom systems. A remarkable feature of the approach is the operational linka e between theoretical and experimental work, proven to be very fruitful in t e above examples. Probing the system's dynamics under varied boundary conditions allows f o r the

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identification of stable coordination states as attractors of the collective variable dynamics. Then, the theory may predict some aspects of the system’s behavior under boundary conditions not yet explored experimentally o r some features of the system’s dynamics that incorporate regulatory or adaptive mechanisms. Such theoretical expectations require experimental verification, the results of which may involve amending the model. T h e power of the approach stems from this interplay between experiment and theory. D namic pattern theory aims at generality, based on a multilevel approach. T i u s , we envisage other examples a t different levels of description where dynamical principles revealed by the present findin s may also apply. A t the behavioral level first, entrainment between periofic movements exhibiting stable low-integer frequency ratios is a pervasive phenomenon in perceptualmotor behavior. Indeed, nothing else happens when a child tries to keep up with the walking pace of a n adult, or when one has to perform complicated rhythms with one’s limbs: Inevitably, the slow cadence ends u p to be a sheer divider of the fast one. More generally, such ratios act also as grouping or stressing elements in roducing (e.g., Povel, 1981; Shaffer, 1982) as well as perceiving (e.g., Deutsc!, 1983; Fraisse, 1982) rhythmical patterns. On the other hand, the type of relative coordination described above was discovered long ago and coined the “magnet effect” by von Holst (1939/1975), which took t h e form of episodic coupling of two oscillating fins in swimming fish scattered among periods of weak uncoupling. Such phenomena may now be understood as intermittency in the mode-locking dynamics of the phase- attractive circle map (Kelso et al., in press a and b). At other levels, a lot of attention has recently focussed on cellular entrainment by periodic stimulation. Findings on different physiological substrates converge to show that cell oscillations happen t o stabilize at low- integer frequency ratios with respect to the forcing stimulus frequency, (for a review, see Glass & MacKey, 1988). Spontaneous phase-locking seems also to be a fundamental organizational mechanism at the level of neuronal assemblies. In cat visual cortex, several results show that columns activated by the same ob‘ect in the visual world show in-phase oscillations (e.g., Eckhorn et al., 1988; d r a y et a1 1989). Such cooperation of highly coherent neuronal activity seems tld correspond t o global features of the visual field, and may provide a general aradigm f o r perceptual mechanisms. Moreover, examples of collective ehavior at the neuronal level have recently been reported that relate quite directly to the topic of learning. Stanton & Sejnowski (1989) showed that longterm potentiation (LTP) or long-term depression (LTD) of a pyramidal cell of the hippocampus is obtained for up to 30 minutes, d e ending on whether a itioning input, whose frequency was that of the intrinsic fippocampal 0 rhythm (5-6 Hz), is administered in-phase o r anti-phase with respect to the test input. Work by Pavlides, not only is relative Phase a collective variable describing the system’s dynamics, but phasin itself is a mechanism that governs the stability of multifrequency patterns. d o r e recently (Kelso, DeGuzman & Holroyd, in press, a and b), it has been shown that under conditions in which Greenstein, Grudman & Winson (1988) suggests that such LTP is actually induced only if the conditioning signal is applied at the eak of the 0 rhythm, and not a t the trough. These findings strongly suggest t at relative timing is instrumental in understanding change in connective strength among neurons with learning. Thus, such patterns of neural activity may be ultimately those underlying selective mechanisms along longer time scales. During morphogenesis, there is a tremendous reduction of neural networking, leaving just a few of the possible

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connections functional (e.g., Changeux & Dehaene, 1989: Paillard, 1986). Certain relative timing patterns of activity, such as in-phase, may "reinforce" o r stabilize connections within neuronal assemblies, whereas other patterns may be detrimental to synapse formation (e.g., Barnes, 1986). A most exciting point is that such mechanisms of selection are very much alike those of competition and cooperation that have been described in the present paper (see Zanone & Kelso, in press). This striking convergence holds promise that there a r e very basic and eneral principles of coordination dynamics acting on various time scales and evels of description.

f

In this chapter, we have presented a theoretical framework which aims a t a lawful description the system's behavior when it is confronted with different constraints from the milieu. Such behavior cannot be meaningfully interpreted unless the intrinsic dynamics a r e known, that is, the ensemble of stable collective states and their dynamics. Such dynamics are (nonlinearly) affected by current boundary conditions, so that different coordination rCgimes may be observed under the same conditions and the same regimes observed in different situations. When specific constraints a r e applied, two mechanisms have been identified, competition and cooperation, that determine behavior depending on how such re uirements fit the current pattern dynamics. To recover stability under pertur ation, the system is endowed with adaptive mechanisms, among which three have been described here: a ) attraction, which drives behavior into the closest stable state: b) learning, which leads to a new attractor corresponding to the required pattern that has become part of the dynamics; and c) tuning, which modifies the region in parameter space in which the pattern is stable.

B

To conclude, the present framework encompasses the principle of behavioral invariance, but transforms it into the concept of stability: Invariance is but one of the spatiotemporal features of skilled movement that reflects behavioral stability, Nonetheless, the dynamical perspective also suggests several mechanisms that maintain stability under various kinds of perturbations. Somewhat paradoxically, even behavioral change is to be conceived of as one of the ways through which the system recovers stabilit . A unique appeal of the approach is to relate the notions of (marginally) stagle and unstable dynamics to that of behavioral change by means of unifying principles and to provide observables that allow one to operationally address the system's collective states and the influence of boundary conditions. 5. REFERENCES Abraham, R., & Shaw, C. (1982). D y n a m i c s - T h e g e o m e t r y of b e h a v i o r . P a r t 1 : P e r i o d i c b e h a v i o r . Santa Cruz: Aerial. Arnold, V. I. (1983). G e o m e t r i c a l m e t h o d s in t h e t h e o r y of o r d i n a r y d i f f e r e n t i a l e q u a t i o n s . New York: Springer. Baldissera, F., Cavallari, P., & Civaschi, P. (1982). Preferential coupling between voluntary movements of ipsilateral limbs. N e u r o s c i e n c e L e t t e r s , 34, 95-100. Barnes, D. M. (1986). Lessons from snails and other models. S c i e n c e , 2 3 1 , 1046- 1049.

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Kelso, J. A. S. (1984). Phase transitions and critical behavior in human bimanual coordination. A m e r i c a n J o u r n a l of Physiology: Regulatory, Integrative and C o m p a r a t i v e Physiology, 15, R1000R1004. Kelso, J. A. S. (in press). Anticipatory dynamical systems, intrinsic pattern dynamics and skill learning. H u m a n M o v e m e n t Science. Kelso, J. A. S., Buchanan, J. J., & Wallace, S. A. (1990). Order p a r a m e t e r s f o r t h e neural organization of single, m u l t i j o i n t l i m b m o v e m e n t patterns. Manuscript submitted f o r publication. Kelso, J. A. S., & DeGuzman, G. C. (1988). Order in time: How cooperation between the hands informs the design of the brain. In H. Haken (Ed.), N e u r a l and synergetic c o m p u t e r s (pp. 180-196). Berlin: Springer.

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Schoner, G. S., & Kelso, J. A. S. (1988b). Dynamic patterns in biological coordination: Theoretical strategy and new results. In J . A. S. Kelso, A. J. Mandell, & M. F. Shlesinger (Eds.), D y n a m i c p a t t e r n s i n c o m p l e x s y s t e m s (pp. 77-102). Singapore: World Scientific. Schoner, G. S., & Kelso, J. A. S. ( 1 9 8 8 ~ ) .A dynamic theory of behavioral change. J o u r n a l of T h e o r e t i c a l B i o l o g y , 135,501-524. Schoner, G. S., & Kelso, J. A. S. (1988d). A synergetic theory of environmentally-specified and learned patterns of movement coordination. I. Relative phase dynamics. B i o l o g i c a l C y b e r n e t i c s , 5 8 , 71-80. Schoner, G. S., & Kelso, J. A. S. (1988e). A synergetic theory of environmentally-specified and learned patterns of movement coordination. 11. Component oscillator dynamics. B i o l o g i c a l C y b e r n e t i c s , 5 8 , 81-89. Schoner, G. S., Zanone, P. G., & Kelso, J. A. S. (in press). Learning a s change of coordination dynamics: Theory and experiment. J o u r n a l of M o t o r Behavior. Shaffer, L. H. (1982). Rhythm and timing in skill. P s y c h o l o g i c a l R e v i e w , 89(2), 109-122. Shapiro, D. C., Zernicke, R. F., Gregor, R. J., & Diestel, J. D. (1981). Evidence f o r generalized motor programs using gait pattern analysis. J o u r n a l of M o t o r B e h a v i o r , 13,33-47. Soechting, J. F., & Terzuolo, C. A. (1986). A n algorithm for the generation of curvilinear wrist motion in an arbitrary plane in three-dimensional space. N e u r o s c i e n c e , 1 9 , 1395-1405. Stanton, P. K., & Sejnowski, T. J. (1989). Associative long-term depression in the hippocampus induced by Hebbian covariance. N a t u r e , 338,215-218. Strange, W., & Jenkins, J. J. (1978). The role of linguistic experience in the perception of speech. In R. D. Walk & H. L. Pick (Eds.), P e r c e p t i o n and e x p e r i e n c e (pp. 125-169). New York: Plenum. Thelen, E., Ulrich, B., & Niles, D. (1987). Bilateral coordination in human infants: Stepping on a split-belt treadmill. J o u r n a l of E x p e r i m e n t a l Psychology: H u m a n P e r c e p t i o n and P e r f o r m a n c e , 13(3), 405-410. Theulings, H. L., Thomassen, A. J. W. M., & v a n Galen, G. P. (1986). Invariants in handwriting: The information contained in a motor program. In H. S. R. Kao, G. P. van Galen, & R. Hoosain (Eds.), G r a p h o n o m i c s : C o n t e m p o r a r y r e s e a r c h in h a n d w r i t i n g (pp. 305-3 15). Amsterdam: North Holland. Tuller, B., & Kelso, J. A. S. (1989). Environmentally-specified patterns of movement coordination in normal and split-brain subjects. E x p e r i m e n t a l B r a i n R e s e a r c h , 75,306-316.

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Yamanishi, T., Kawato, M., C Suzuki, R. (1980). Two coupled oscillators as model for the coordinated finger tapping by both hands. B i o l o g i c a l C y b e r n e t i c s , 37,219-225. Yates, E. F. (1987). Self - o r g a n i z i n g systems. T h e e m e r g e n c e of o r d e r . New York: Plenum. Zanone, P. G. (1990). Perceptuo-motor development in the child and the adolescent: Perceptuo-motor coordination. In C. A. Hauert (Ed.), Developmental psychology: Cognitive, perceptuo-motor, and n e u r o p s y c h o l o g i c a l p e r s p e c t i v e s (pp. 309-338). Amsterdam: North. Holland. Zanone, P. G., C Kelso, J. A. S . (1990). T h e e v o l u t i o n of b e h a v i o r a l attractors with learnin : Nonequilibrium phase transitions. Manuscript submitted f o r putlication. Zanone, P. G., & Kelso, J. A. S. (in press). Learning and transfer as paradigms for behavioral change. In G. E. Stelmach & J. Requin (Eds.), T u t o r i a l in m o t o r b e h a v i o r I I . Amsterdam: North-Holland.

The Development of Timing Control and Temporal Or anization in Coordinated Action J. Fagard anfP.H. Wolff (Editors) Q Elsevier Science Publishers B.V.. 1991

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CENTRAL GENERATORS AND THE SPATIO-TEMPORAL PATIERN OF MOVEMENTS

Yu. I. Arshavsky*, S. Grillner**, G.N. Orlovsky***, Yu. V. Panchin*

* Institute of Problems of Information Transmission, Acad. Sci., Moscow, USSR

* * Nobel Institute of Neurophysiology, Karolinska Institute, Stockholm, Sweden * * * Moscow State University, Moscow, USSR

Introduction Animals and humans are capable of producing a great variety of movements with their body, limbs, eyes etc. These movements can be classified according to the role of corrections performed in the course of a movement. O n one extreme, there are movements which need continuous corrections like in the case of tracing a moving target. For these movements both information concerning the external world and that concerning the current state of the own motor apparatus are necessary. O n another extreme, there are movements which need no or minimal corrections during their execution either because they are very brief (like ballistic movements) or because they proceed under standard conditions (like swallowing and scratching movements). Some of these movements have rather complex spatial and temporal patterns of muscular activity. Most movements, however, are of a mixed nature, i.e. they can be performed in a rough way without any (or with minimal) information about the external world and about the current state of the own motor apparatus, but they become perfect if such information is available. The locomotor movements belong to this "mixed class. The basic pattern of locomotion is generated within the nervous system (see below), but when executed, the movements are adapted to the environment, and various sensory inputs (visual, proprioceptive) are used for these adaptations. Thus one can conclude that, for many movements, there is within the central nervous system (CNS) a "central representation" or a "program" of these movements. This program is realized as a result of the activity of a definite neuronal mechanism which is usually referred to as a "central pattern generator" or a "central generator" for a given movement. Deprived of sensory influences, the central pattern generator (CPG) produces the spatio-temporal pattern of activity of different muscles typical of a given movement (11,12,19,23,29,43,47,53).The neuronal structure of CPGs is genetically predetermined. In vertebrates, the CPGs for various movements are located at rather low levels of the CNS, in the spinal cord (CPGs for locomotion and scratching) and in the brainstem (CPGs for respiration, chewing, swallowing, eye movements, etc). The activation of CPGs and the control of various aspects of their activity is usually

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Fig. 1. Functional organization of the locomotor control system in mammals. A. Longitudinal section of the brainstem of the cat with the midbrain (mesenc) and the lower brainstem (pons and med. obl.). The midbrain locomotor region (MLR) is indicated and its connection to the lower brainstem locomotor region in Nuclei reticularis magnus and gigantocellularis (NRM & G). This area projects through the ventral quadrant of the spinal cord to the spinal pattern generators for locomotion. B. Schematic representation of the spinal network organizaiton. The spinal pattern generator circuitry is activated by the locomotor drive signal from the brainstem. This central pattern generator activates the different motoneurones and thereby muscles in sequence. During the ongoing movement, sensory signals arising from the movement can act at several different levels: the motoneurone, the spinal pattern generator, and various brain centres. Signals about activity of the spinal generator (efference copy) are also sent to the brain. Correcting signals from a variety of descending pathways can modify the activity of spinal mechanisms. c. The isolated spinal cord is capable of generating the basic locomotor pattern in all classes of vertebrates which proves the existence of locomotor CPG in the spinal cord. In this experiment, the spinal cord of a newborn rat was isolated together with two pairs of hindlimb muscles (left and right m. tibialis anterior, TA, and gastrocnemius, G). Bath application of the excitatory aminoacid (NMDA) evoked normal alternating flexor-extensor activity (recorded as muscle activity) typical of stepping, with a 180" phase shift between the two legs typical for walking (adapted from 34).

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performed by brain centres at a higher level. A typical example of such a motor organization is the system controlling locomotion in mammals illustrated in Fig. 1. This system has been extensively investigated during the last two decades (5,17,20,24,25,27,38,49,52).In mammals (and in other classes of vertebrates) locomotion can be initiated by stimulation in the upper part of the brainstem, in an area referred to as the midbrain (mesencephalic) locomotor region (MLR) (Fig. 1A). A local electric or pharmacological stimulation will give rise to locomotion (16,17,30,38,49). A weak stimulation elicits slow walking whereas stronger stimulation can elicit trot and gallop. Thus, the basic locomotor synergy with hundreds of muscles coordinated in a specific way comes into operation under the effect of a very simple command. This effect is mediated by special neuronal circuits located in the spinal cord which control the stepping movement of each limb, i.e. by the spinal CPGs (Fig. 1B). The brainstem command signals that activate the spinal CPGs can be substituted by certain drugs; Fig. 1C shows the rhythmic activity generated by the isolated rat spinal cord under the effect of the excitatory amino acid NMDA (34). The isolated spinal cord can not only generate the basic locomotor pattern underlying stepping movements in a single limb (alternating flexor and extensor activity) but also establish the reciprocal relation between left and right sides necessary for walking (Fig. 1C). This interlimb co-ordination is determined by a specific interaction between the CPGs controlling stepping in individual limbs. The spinal CPGs generate the basic locomotor pattern even in the absence of any sensory feedback, but during normal locomotion numerous sensory signals affect both motoneurones and CPG interneurones (Fig. 1B) to modify the motor pattern and adapt it to the current environmental conditions (1,20,35,40,46). The high level brain centres also participate in correcting the basic locomotor pattern. Their actions are based both on information coming from the spinal cord (sensory and efference copy signals) and on information coming from the visual, auditory and vestibular systems (Fig. 1B). The problem of neuronal organization and operation of CPGs in mammals is far from being solved, in spite of extensive studies in this field (8,14,17,20,23,41,51,52).In most cases we know neither the main neuronal groups constituting the CPG, nor the system of their interconnections, nor the properties of CPG neurones. This is why a question such as "How is the CPG organized?" is usually substituted by a question "How should the CPG be organized to fit some observations concerning the motor pattern that it generates?" However, if one turns to animals with a "simple" nervous system (lower vertebrates and invertebrates), the situation is much better, and a number of CPGs have been investigated at the level of "neuron-to-neuron interaction". We shall consider some of these CPGs and discuss the possible role of this knowledge for understanding the organization and operation of the CPGs in mammals. We shall start with rather simple neuronal mechanisms generating the basic locomotor pattern in the mollusc Clione and in the frog embryo. These two mechanisms have a lot features in common. Then we shall consider the locomotor generator of the lamprey. This generator, like the two mentioned above, belongs to the class of "symmetrical"networks, but it is capable of generating more complex efferent patterns. After this we shall consider the feeding rhythm generator of the snail Planorbis based on an asymmetrical neuronal network and producing an efferent pattern resembling those of respiration, visual nystagmus and scratching in mammals. We shall finish with the CPG for a defensive reaction in Planorbis which does not generate a rhythmical pattern but a single one. This pattern resembles that of rather complex arm movements like reaching.

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Locomotor CPG of Clione The pteropod mollusc Clione limacina is widely distributed over the northern seas. It is a plankton animal which maintains itself at a particular depth by continuous rhythmic (1-2 Hz) movements of two wing-like appendages. These "wings" move synchronously, similar to wings of a bird (Fig. 24B). The wing movements are controlled by the pedal

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Fig. 2. A. Schematic drawing of Clione limacina (a ventral view). B. Successive wing positions during a locomotor cycle (a frontal view): (1) the maximal ventral flexion, (2) the movement in dorsal direction, (3) the maximal dorsal flexion, (4) the movement in ventral direction. The interval between frames is about 100 ms. C.The CNS of Clione consisting of the buccal (BUC), cerebral (CER), pedal (PED), pleural (PL) and abdominal (ABD) ganglia. NW, the wing nerves. ganglia, each of which gives rise to the corresponding wing nerve (Fig. 2C). The basic efferent pattern of swimming can be recorded from the wing nerve. It consists of two bursts per cycle (2). One burst corresponds to the activity of motoneurones responsible for the dorsal flexion of the wing (D-phase of a swim cycle), the other reflects the activity of motoneurones responsible for the ventral flexion (V-phase). The same efferent pattern, with alternating activity of the D and V-phase motoneurones, is generated by completely isolated pedal ganglia. This rhythmical process, named "fictive swimming", is the manifestation of activity of the Clione locomotor CPG. The pedal ganglia contain about 1000 neurones, approximately 100 of which exhibit periodical activity during fictive swimming. About 50 of these "rhythmic"neurones are motoneurones sending axons into the wing nerve (Fig. 3A), others are interneurones with axons projecting to the contralateral pedal ganglion (Fig. 3B). Fig. 3C shows activity of two of the largest motoneurones, 1A and 2A, active in the D- and V-phases of a swim cycle, respectively. An EPSP and a burst of discharges in a given motoneurone is accompanied by IPSPs in its antagonist. Two groups of interneurones (7 and 8) play a crucial role in the operation of the locomotor CPG: they generate the locomotory rhythm and drive motorneurones (2,6). Each group contains about 20 cells. These cells generate action potentials of a long

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&.J. Motoneurones and interneurones of the locomotor CPG of Clione. Morphology of the largest wing motoneurones, 1A and 2A (A), and of the group 7 and 8 interneurones (B) was revealed by intracellular staining with Lucifer yellow. (The dorsal view of pedal ganglia is shown in A, and the ventral view in B). NW, Wing nerve; CPC, cerebropedal connective; PC, pedal commissure. Activity of these cells during "fictive" swimming generated by the isolated pedal ganglia is shown in C and Q, where the phases of a swim cycle corresponding to the dorsal (D) and ventral (V) wing flexion are indicated. duration (about 100 ms), one potential per swim cycle (Fig. 3D). Due to mutual electrical connections, all cells in the group fire synchronously. The interneuronal groups 7 and 8 exert a mutual inhibitory effect upon each other, and each action potential in a given group is followed by an IPSP in the antagonistic group of interneurones (Fig. 3D). Each cell in groups 7 and 8 is a pacemaker operating at a frequency of the locomotory rhythm range (4). This was demonstrated in experiments with isolation of single neurones; the method used is shown in Fig. 4 4 B . Fig. 4C shows initial activity of the group 7 interneurone recorded before extraction, and Fig. 4D activity of the same neurone after extraction from the ganglion. One can see that the rhythmic activity persisted in the isolated cell but the firing rate increased and the mid-cycle IPSPs (produced by the antagonistic group 8 interneurones) disappeared. Rhythmic activity of isolated cells strongly depended on the level of membrane potential. By varying the amount of current injected into the cell, one could cover the whole range of frequencies used by the intact Clione during swimming (0.55 Hz) (Fig. 4E). If the cell was inactive after extraction from the ganglion, its rhythmic activity could be restarted by depolarization (Fig. 4F, on the right). Thus, the generation of the locomotory rhythm in the Clione CPG is based on an

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for the rhythm generation. Ganglia were treated with proteolitic enzymes to destroy the mechanical connection between cells, after which a cell could be penetrated and extracted from ganglia by means of the microelectrode as shown in A and B. Activity of the group 7 interneurone before extraction is shown in 6 and after extraction, in R. In E is shown the effect produced by injection of various direct currents (the current value indicated on the left) in the isolated group 7 interneurone hanging on the tip of a microelectrode. If the neurone was not active after extraction from ganglia, a single action potential could be evoked in it on "rebound after the pulse of hyperpolarizing current, or rhythmic generation could be evoked by injecting a depolarizing current (E). endogenous rhythmic activity of interneurones of groups 7 and 8. The temporal efferent pattern underlying wing movements (a half-a-cycle shift between the D- and V-phase motoneurones) is determined by mutual inhibitory interactions between the two groups of interneurones: due to this interaction they Cannot fire simultaneously but only in succession. However, the pacemaker property of group 7 and 8 interneurones is not the only basis for the pattern generation: the CPG can generate the rhythmic pattern even when the interneurones of groups 7 and 8 are "below the threshold of their pacemaker activity. In this case, the "postinhibitory rebound is of crucial importance: both group 7 and group 8 cells are capable of generating a single action potential after they have been released from inhibition (Fig. 4F, on the left). This is why, by producing an IPSP in the antagonistic group of neurones, a given group will evoke activity of these neurones on the "rebound" after termination of the IPSP. A simplified scheme of the locomotor CPG of Clione is shown in Fig. 5A, and the

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m. Locomotor CPG of Clione (A) and a schematic pattern of activity of various cell groups in a swim cycle (B). The locomotor rhythm is generated by two groups of interneurones (7 and 8) with mutual inhibitory connections. These interneurones produce EPSPs and IPSPs in motoneurones of D-phase (groups 1and 3) and in those of V-phase (groups 2,4,6 and 10). Electrical connections between neurones are shown by resistor symbols, excitatory and inhibitory chemical synapses by white and black arrows correspondingly. pattern of activity in various groups of neurones, in Fig. 5B. Group 7 and 8 interneurones generate the locomotory rhythm with the proper (180") shift between the D- and V-phases of a swim cycle. They control the motoneurones of various groups by producing phasic EPSPs and IPSPs in them. The duration of the action potential generated by interneurones determines the duration of efferent bursts. As shown in Fig. 4E,F, the rate of rhythmic activity in the interneurones constituting the locomotor CPG strongly depends on the level of their tonic polarization. By varying the level of membrane potential in these neurones, one can easily control Clione's swimming, i.e. switch on and off the rhythm generator and regulate its frequency. Such a control is used, for instance, in a type of the motor behaviour named "vertical migrations". In the aquarium, and perhaps in the sea, Clione maintains itself at a definite depth by means of continuos oscillations of the wings. Sometimes the oscillations are terminated and in a few seconds the animal sinks by 20-30 cm. The oscillations then restart with an increased frequency and the animal returns to the initial depth. Clione repeats these short vertical migrations at intervals of about 1min. Presumed command neurones (PC) controlling the vertical migrations are located in the pedal ganglia. They exhibit spontaneous bursts of activity, one of them is shown in Fig. 6A. The neurone gradually depolarized and its firing rate increased. Then the membrane potential reached a plateau where it remained for many seconds. Finally, it spontaneously returned to the resting potential. Under the effect of the PC neuron, the group 8 interneurone as well as other neurones of the locomotor CPG became strongly depolarized which resulted in a burst of locomotor activity. Besides PC neurons, about

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neurone was capable of generating a plateau potential either spontaneously (A)or in response to a brief pulse of the depolarizing current (B). When excited, the PC neurone depolarized the group 8 interneurone (as well as other neurones of the locomotor CPG) and thus evoked the locomotor episode. Morphology of the PC neurone, located on the dorsal surface of the pedal ganglia is shown in C.

20 "command neurones were found in the pedal, cerebral and other ganglia; they could produce either de- or hyperpolarization of the CPG interneurons and thus mediate various types of influences on the locomotor activity. Locomotor CPG of Xenopus embrvo In spite of the great distance between molluscs and vertebrates, there is a striking similarity in organization of some CPGs in these two types of animals. This is clearly seen when comparing the locomotor CPGs of Clione with that of the embryo of the frog Xenouus laevis (44). The Xenopus embryos can swim if released from their egg membrane shortly before they normally hatch (Fig. 7A). The propulsive force during swimming arises due to laterally directed waves propagating along the body in the caudal direction. The CPG for locomotion is located in the spinal cord. In animals paralyzed with a myorelaxant, rhythmical discharges with a period length typical of locomotion, can be recorded in ventral roots. There is a half-a-cycleshift between the efferent discharges in the left and the right ventral roots of the same segment (Fig. 7B) while discharges in caudal roots are delayed in relation to those in more rostra1 roots, this delay increases with distance between the segments. A "local" (segmental) CPG consists of two symmetrical neuronal networks exerting mutual inhibitory action upon one another (Fig. 7D). The leading role in each of the networks is played by a group of excitatory interneurones (e) which generate one action potential per cycle (see Fig. 7C) and produce an EPSP in the inhibitory interneurone (i) and in motoneurones (m) forcing them to fire once per cycle (see Fig. 7B,C). The i-cells affect all the neurones in the contralateral network producing the mid-cycle IPSP in them (see Fig. 7B,C).

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The late embryo of the frog Xenopus moves due to the waves of bending that propagate along the body. In A are shown tracings of swimming movements of an embryo from film at 300 frames/s. Arrowheads indicate waves of bending which progress towards the tail. The CPG for swimming is located in the spinal cord. In B is shown a portion of the episode of fictive swimming evoked in an animal immobilized with dtubocurarine. Recordings were made from the right and left ventral roots of the sixth segment (R6 and L6) as well as intracellularly from the motoneurone located on the right side of the same segment (m). Excitation of a motoneurone is determined by the EPSP produced by ipsilateral excitatory (e) interneurones, while the mid-cycle IPSP is produced by contralateral inhibitory (i) interneurones. Rhythmic activity of the e and i cells from the same side of a spinal segment is shown in C together with activity in the ipsilateral ventral root (vr); the episode of fictive swimming was evoked by dimming the light. D.The local (segmental) CPG for swimming of the Xenopus embrio. The populations of the excitatory (e) and inhibitory (i) interneurones as well as motoneurones (m) are shown. Excitatory synapses are shown as white squares, and inhibitory ones as black circles. (Adapted from 44). Due to the inhibitory interaction between the two symmetrical networks, the segmental CPG of the Xenopus embryo produces a rhythmical efferent pattern with a half-cycle shift between symmetrical ventral roots. The left and right groups of e-cells are functionally equivalent to groups 7 and 8 in the locomotor CPG of Clione (Fig. 5A)

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except that the inhibitory action of e-cells upon the neurones of the antagonistic network is not direct but mediated by special i-cells. In the CPG, there are two reasons for excitation of group 7 (or 8) interneurones: the pacemaker properties of these cells and the postinhibitory rebound Both factors seem to play a role in excitation of e-cells in the Xenopus embryo CPG as well. The postinhibitory rebound was demonstrated directly (43,45) while pacemaker properties could be suggested on the basis of experiments in which the spinal cord was split along the midline, and each half of the cord could generate a rhythmic efferent pattern (31). Locomotor CPG of lamprey Lampreys swim due to alternating contractions of the two sides at any given segment. The frequency of the contractions can vary between 0.3 and 10 Hz. The intersegmental coordination is characterized by a delay between consecutive segments resulting in a wave propagating along the spinal cord h d , therefore, along the body. The motor pattern underlying locomotion can be produced in the brainstem-spinal cord h &Q preparation, and even in the isolated spinal cord, and can conveniently be recorded in the ventral roots along the spinal cord (Fig. 8A). The entire frequency range and the intersegmental coordination can be retained in in vitrQ conditions. The local (segmental) CPG for locomotion in lamprey is shown in Fig. 8B (21). It consists of two symmetrical networks exerting a mutual inhibitory action upon each other and, in this respect, it resembles the locomotor CPGs of Clione (Fig. 5A) and Xenopus embryo (Fig. 7D). A crucial role in the activity of this CPG is played by the excitatory interneurones (EIN). These cells generate bursts of action potentials lasting for about a half of the locomotor cycle. They produce excitation of different interneurones of the network as well as of motoneurones. An inhibitory action of EINs upon the contralateral network is mediated by commissural interneurones (CCIN) which produce inhibition of all types of neurones in that network. There are several reasons for bursting activity of the EINs. First, the cell membrane is capable of generating oscillations in the frequency range of locomotion. In this respect, the EINs are similar to the interneurones of groups 7 and 8 in the locomotor CPG of Clione. However, there is a principal difference between these types of cells: in Clione, the capability of generating oscillations is a permanent property of the cell membrane as demonstrated in experiments with cell isolation (Fig. 4), while in lamprey the cells are not capable of generating slow (locomotor rate) oscillations until their membrane is affected by a special mediator. This is illustrated in Fig. 8C,D. In C is shown fictive locomotion generated in the spinal cord and monitored by the rhythmic activity of one of the spinal neurones and by rhythmical discharges in a ventral root (VR).The rhythmic activity of the locomotor CPG was evoked by bath application of an excitatory amino acid (NMDA). Then spinal neurones were functionally isolated from each other by bath application of tetrodotoxin (which blocks the spike discharges and, therefore, synaptic interaction). One can see that the "isolated cell generates rhythmic oscillations (Fig. 8D); these oscillations do not arise in the abscence of NMDA receptor activition. Such an action of NMDA was found in various types of spinal neurones. Thus, the capacity of the cell membrane to generate slow oscillations is one factor contributing to the bursting activity of the CPG interneurones. The second factor is determined by the structure of the CPG which consists of two symmetrical networks with mutual inhibition (Fig. 8B). Due to several reasons (summation of spike afterhyperpolarization,

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and inhibition from LINs) the firing rate of neurones of a given network decreases with time in the course of a burst. The cessation of activity in one network will result in a "disinhibition" of the symmetrical network and, finally, in its excitation. This is why the lamprey CPG can generate the locomotory rhythm even without induction of oscillatory properties in its cells by NMDA. However, when both factors contribute to the rhythm generation, the CPG activity is much more stable as demonstrated both in experiments and in realistic computer simulations of the lamprey locomotor CPG (Fig. 8E) (21,22). The spinal locomotor CPG is activated by reticule-spinal axons which have excitatory synapses on different types of spinal neurones (Fig. 9A) (9). The reticulo-spinal EPSPs are due to activation of NMDA and kainate receptors as demonstrated in experiments

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for modifications of the locomotor pattern. (from the posterior rombensephalic reticular nuclei, PRRN) evokes excitatory postsynaptic potentials in different groups of spinal neurones located in different segments (in the comissural interneurone, CC; in the unidentified cell, UIN; in the motoneurone, MN; and in the lateral interneurone, LIN). The NMA receptor blocker (KYAC) abolishes the EPSP or decreases its amplitude. B. Excitation of a reticulospinal neurone from the right middle rombencephalicnucleus resulted in the disturbance of symmetry in the CPG activity. Fictive locomotion was evoked in the isolated spinal cord by NMA, activity of the ipsilateral (in relation to the reticulo-spinal neurone) and contralateral ventral roots of the same segment was recorded. Duration of the train of stimuli applied to the reticulo-spinal neurone, and its frequency is indicated. (Modified from 10).

with a blockade of the NMDA receptor action (Fig. 9A). Therefore, reticulo-spinal neurones produce two effects in the CPG neurones: they increase their excitability and transfer their membrane from a stable into an unstable (i.e. oscillatory) state. Besides activation of the CPG and regulation of the level of its activity the reticulospinal system may also exert more specific actions upon the CPG and considerably modify the locomotor pattern (Fig. 9B). Feeding CPG of Planorbis During feeding, the freshwater snail Planorbis corneus (Fig. lOA), like many other gastropod molluscs, performs rhythmic movementswith the radula (tongue-like structure)

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Fig. 1Q. Feeding movements in the pond snail Planorbis corneus. Crawling snail is shown in A. When contacting the food, the radula performs rhythmic movements. Retracted position of the radula is shown in B, and protracted one (when the radula scratches the food object), in C,D.Preparation consisting of the buccal mass and buccal ganglia (BG) is capable of rhythmic radula (RAD) movements. These movements are shown in E together with activity in two buccal nerves ( n l and n2). Quiescence protractor (P) and retractor (R) phases are indicated. The same efferent pattern can be generated in the isolated buccal ganglia (E).

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and other parts of its buccal apparatus (Fig. 10B,C). The movements are controlled by the buccal ganglia. Fig. 10D shows a preparation consisting of the buccal mass with the buccal ganglia capable of generating co-ordinated rhythmic movements (Fig. 10E). A cycle of the radula movement consists of three phases: quiescence ( a ) , protraction (P) and retraction (R). In intact animals, the radula is brought into contact with a food substrate (e.g. algae) during the P-phase. Then, in the R-phase, the radula scratches food pieces and transports them to the oesophagus (see Fig. 1OC). The activity recorded in the radular nerve (nl) corresponds mainly to the P-phase, and that in the dorsobuccal nerve (n2), to the R-phase (Fig.lOE). Similar activity is observed in these nerves in completely isolated buccal ganglia (Fig. lOF), which demonstrates the existence of a central network for feeding, that is a CPG (3).

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mot o n e u r o n s Fie. 11. A. Schematic pattern of activity of different neurone groups in a feeding cycle. Interneurones are marked by squares, other cells are motoneurones. Designations as in Fig. 10E,F. B, C.Morphology of interneurones of l e and 2 groups and their location in buccal ganglia. CBC, cerebro-buccal connective. 12. The feeding CPG of Planorbis. Designations as in Fig. 5A. About 100 neurones in the buccal ganglia are rhythmically active during the operation of the feeding CPG. Depending on their morphology, on the pattern of electrical activity and the phase of this activity in the feeding cycle, these neurones can be classified into 7 groups (Fig. 11A). Cells of group 1 (which consists of subgroups le and Id) and of group 2 are interneurones (Fig. 11B,C), other cells are motoneurones controlling the muscles of the buccal apparatus. Group 1 and 2 interneurones play a crucial role in the operation of the feeding CPG of Planorbis: they generate the feeding rhythm and drive motoneurones by producing rhythmic EPSPs and IPSPs in them. The neurones of both group 1 and group 2 are endogenous oscillators which was proved in experiments with cell isolation (3) (for methods see Fig. 4). The main features of the rhythmical pattern observed in these neurones before isolation persisted after they were extracted from the buccal ganglia. The subgroup l e neurones periodically generated a ramp depolarization

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Fig. 12. The main features of the firing pattern of interneurones from the feeding CPG of Planorbis persisted in isolated cells. A. Activity of le-cell in ganglia. B-D. Activity of the same cell after extraction from ganglia. E. Activity of the group 2 cell in the ganglia. E, G.Activity of the same cell after extraction. The value of a current injected into a cell is indicated in B-Q and E,8. accompanied by accelerating spike discharges (Fig. 12A-D). Group 2 neurones periodically generated a rectangular wave of depolarizing potential with oscillations on the top (Fig. 12E-G). The rhythmic activity in isolated cells depended strongly on the amount of current injected (Fig. 12B-D; F,G), which suggests that the CPG can be easily controlled by a tonic synaptic inflow to the generatory neurones. In contrast to all the CPGs considered above the feeding CPG of Planorbis is essentially asymmetrical (see Fig. 11D): group 1 neurones exert an excitatory action upon group 2 neurones, while group 2 neurones inhibit group 1 neurones. During the feeding cycle, the following events take place in the CPG. Due to the intrinsic properties of l e cells, their activity gradually increases in the Q and P phases. Because of the mutual electrical connections within group 1, le-cells provide an excitatory drive to ld-

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cells which get excited in the P-phase. The Id-cells exert an excitatory action upon group 2 neurones. Having reached the threshold, type 2 cells generate a rectangular wave of depolarizing potential and inhibit the group 1 cells, thus terminating the P-phase The duration of the wave generated by the group 2 cells determines the R-phase of the cycle. After termination of this wave, a ramp depolarization starts again in le-cells giving rise to a new cycle. Thus, the duration of a feeding cycle is determined by (i) the slope of depolarization in le-cells, (ii) the threshold of excitationof type 2 cells, and (iii) the duration of the rectangular wave generated by type2 cells. By varying these parameters, the duration of the entire feeding cycle and of the differentphases constituting the cycle can be regulated. All synaptic potentials in motoneurones in the P-phase (both EPSPs and IPSPs) are produced by Id-cells, while group 2 cells areresponsible for the PSPs produced in motoneurones in the R-phase. Due to combinationsof the two inputs, a variety of rhythmical patterns can be produced in the different groups of motoneurones (Fig. 11A). CPG for defensive reaction in Planorbis The locomotor and feeding CPGs considered above generate rhythmical patterns, each cycle giving rise to a new cycle. The CPG for adefensivereaction in the snail Planorbis corneus is an example of a mechanismgenerating a single pattern. The snail Planorbis, like other gastropod molluscs (see e.g. 7), exhibits a defensive reaction to various external stimuli. With a weak stimulus applied, for instance, to the head, the snail stops crawling and pulls the shell towards the head. This is the 1st phase of the defensive reaction. With stronger stimulation, the 1st phase is followed by the 2nd phase in which the whole body of the snail is pulled into the shell. Essential features of this movement can be observed in a simple preparation consisting of the CNS and the muscle pulling the shell. As shown in Fig. 13A, a weak stimulus applied to a peripheral nerve evoked a muscle contraction lasting for several seconds (the 1st phase, or component of the defensive reaction). With stronger stimulation (Fig. 13B), the 1st component increased considerably in amplitude, and it is now followed by an additional contraction which lasted for about 1 min (this 2nd phase corresponds to pulling the body of the snail into the shell). Both phases are graded, depending on the strength of the stimulus. Muscle contractions during this defensive reaction are controlled by numerous motoneurones. Different groups of motoneurones receive different inputs (excitatory and inhibitory) during the 1st and 2nd phases of the reaction (Fig. 13C), which ensures a coordinated movement of different parts of the body. The pattern of motoneurone activity typical for the defensive reaction can also be observed in the isolated nervous system of the snail. This pattern can either be obtained in response to stimulation of the skin or a peripheral nerve, or it can appear spontaneously. In the latter case, each of the components of the fictive defensive reaction appears either independently (Fig. 13D,E) or in a normal succession, i.e. the 1st component is followed by the second one (Fig. 13F). Thus, the essential features of the defensive reaction in the snail are determined by the CPG. This CPG is supposed to contain two groups of neurones generating the 1st and the 2nd phases of the reaction (Fig. 135). Numerous afferents eliciting a defensive reaction converge upon group 1 and 2 neurones and exert an excitatory action upon them. The proper sequence of phases (the 1st followed by the 2nd) in response to an afferent input is caused by the following conditions: (1) group 1 cells exert an

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Fig. 13. Organization of the defensive reaction CPG in Planorbis. A, B. In preparation consisting of the CNS and of the muscle pulling the shell, stimulation of the lip nerve (arrowhead) evoked the 1st phase of the muscle contraction (M). With stronger stimulation (B), the 2nd, long-lasting phase appeared. C.Activity of two motoneurones (MNl and MN2) during defensive reaction evoked in the same preparation. D-E. Spontaneous defensive pattern in two motoneurones (isolated CNS). The 1st and the 2nd components appeared either separately (QE) or in succession (E). G,H. Responses of the group 1 interneurone from the pleural ganglion (PLIN) to stimulation of the lip nerve in the isolated CNS. The lower trace shows the stimuli applied to the lip nerve, the number of pulses being indicated. When excited, the neurone generates a prolonged action potential. The upper trace shows that PLIN produces EPSP in the motoneurone (MN). As shown in H, excitation of PLIN by the current injection also evoked EPSP in the follower cell (MN). 1. Morphology of PLIN from the right pleural ganglion. (CerG, cerebral ganglia). J. Defensive reaction CPG of Planorbis. Designations as in Fig. 5A. excitatory action upon group 2 cells, (2) group 2 cells have a higher threshold for excitation, and (3) activity in group 2 cells increases slower than in group 1 cells. A gradual increase of the reaction with stronger stimuli is supposed to be caused by a recruitment of new neurones of the groups. Cells of groups 1 and 2 drive motoneurones by producing EPSPs and IPSPs in them. Fig. 13G-I shows an interneurone of group 1. When excited, it generates an action potential lasting for a few seconds (Fig. 13G,H). The duration of this potential determines the duration of excitation in motoneurones

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and, therefore, the duration of the 1st phase of the defensive reaction. The cellular properties of this neurone also determine some other essential features of the defensive reaction: the existence of a threshold and a long refractory period following excitation (Fig. 13H). Due to an extensive branching of its processes (Fig. 131) the neurone of group 1 will synapse on a great number of motoneurones responsible for the defensive reaction. Thus, the defensive reaction CPG of Planorbis, generating a single pattern, is based on the same principles as the rhythmic CPGs considered above. It consists of two groups of neurones, the cell properties of which determine the time course of the 1st and 2nd phases of the reaction. The sequential activity of the groups is mainly due to their made of interaction: the 1st group excites the 2nd one. This CPG differs from rhythmical ones in that there is no back action of the 2nd group upon the 1st group. An important feature of this CPG is that its pattern strongly depends on the initial stimulus. With stronger stimulus, not only the amplitude of the muscle contraction increases but also the 2nd phase of contraction appears. In this respect the defensive reaction cannot be considered as "a fixed action" (see 32). Discussion and conclusions A central pattern generator is a neuronal machinery capable of producing complicated time-dependent signals on its outputs (e.g. in motoneurones). In the motor system, such signals will determine the basic temporal and spatial characteristics of a given movement. The examples presented above have shown several common features in the organization of the CPG for various movements: 1) The output signal of a CPG can be divided into sequential phases. Within a given phase, the time course of a signal is determined, to a great extent, by specific membrane properties of a certain group of neurones. (2) A transition from one phase to another phase is determined mainly by an interaction between corresponding groups of neurones. (3) The pattern produced by a network of interneurones can be regulated in various aspects: the CPG can be switched on and off, the level of its activity can be changed, numerous afferent systems usually affect the CPG and its parts, etc. Below we shall consider these points in greater detail.

Role of specific membrane uroperties for CPG activity. The main features of the temporal patterns produced by different CPGs are determined by the patterns of activity of generatory interneurones which, in their turn, depend on the membrane properties of these cells. Thus, interneurones in the locomotor CPGs of Clione and of Xenopus embryo generate one action potential per swim cycle, and the duration of this potential (which is a specific property of the cell membrane) is the main determinant of the temporal characteristics of the motor pattern of swimming. The excitatory interneurones in the locomotor CPG of the lamprey, on the other hand, generate not a single action potential per cycle but a burst of such potentials, and the duration of this burst determines the duration of activity in each of the two symmetrical segmental networks. The main characteristic of the feeding CPG of Planorbis is a ramp-shaped and a rectangular-shaped waves observed in the P- and R-phases of a cycle in many CPG neurones. These waves are generated by interneurones of groups 1 and 2 due to specific properties of their membrane. Finally, the duration of locomotor episodes in Clione is determined by the duration of plateau potentials generated by "command PC neurones. These examples clearly show that both the duration of a definite phase of the movement and the temporal efferent pattern throughout this phase strongly depend on

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the characteristics of potentials generated by the membrane of the corresponding group of the interneurones. The capacity to generate potentials specifically depending on time is, in some cases, a permanent membrane property. For example, isolated interneurones of the locomotor CPG of Clione and of the feeding CPG of Planorbisgenerate patterns similar to those before extraction from ganglia. On the other hand, interneurones in the locomotor CPG of lamprey, for transition to the oscillatory state, are modified by the reticulo-spinal system. This system produces activation of certain types of receptors (NMDA), which induces oscillatory properties in the spinal neurones. Similarly, in the CPG controlling the pyloric rhythm in lobster, the "command neurones evoke changes in the membrane properties of some cells thus transferring them into oscillators (28,37,48). Types of eenerator networks. Both in the CPGs producing a single pattern (like the defensive reaction CPG of Planorbis) and in those producing a rhythmical pattern (e.g. locomotion), co-ordinated activity of generatory neurones is due to their interaction. First of all, the "synergistic" neurones are united into groups due to their mutual excitatory interaction. In molluscs, this action is mediated by electrical connections in many cases, while in vertebrates excitatory chemical synapses are more common. A proper sequence of phases of the movement is determined by a system of connections between the networks (interneurone groups) responsible for each of the phases. Inhibitory, excitatory and mixed interactions between the groups can be observed in different CPGs. In the feeding CPG of Planorbis, the group 1 neurones exert an excitatory action upon group 2, while group 2 inhibits group 1 neurones (Fig. llD). However, a mixed interaction is more common. Thus, in the locomotor CPGs of Clione, of Xenopus embryo and of lamprey the symmetrical (left and right) networks inhibit each other, but they produce a mutual excitatory action as well (in part, due to the rebound phenomenon). In some CPGs, consisting of several neuronal groups, the intergroup connections are rather complex (for review of CPG organization, see 18). There are a few examples of "re-organization'' of the CPG structure which allows the CPG to generate different efferent patterns. In the CPG controlling the pyloric rhythm in lobster, the efficiency of a particular synapse and therefore, timing of the output pattern can be affected by a special "command" neurone (48). In the locomotor generator of Clione, the principal network shown in Fig. 5A can be markedly modified during intense swimming when two additional groups of interneurones are involved (2). Finally, the spinal cord of lamprey usually generates forward swimming (there is a rostro-caudal delay between the segmental CPGs). However, the phase coupling between the CPGs can be modifed in such a way that backward swimming is generated (19). Organization of CPGs in mammals. The different CPGs considered above exhibit a number of similarities despite the fact that they are from widely different groups of animals. It may therefore be relevant to consider the possible mechanisms in mammals. The biphasic pattern with gradually increasing activity in the first phase and with a rather short burst in the second phase is a characteristic of some motor patterns in mammals, e.g. of respiratory movements (Fig. 14A), of chewing movements (Fig. 14B), and of the scratch reflex (Fig. 14C). One can suggest that, for producing this pattern, a CPG similar to the feeding CPG of Planorbis (Fig. 11D) can be used (CPG with a "switch-off' mechanism, see 13). It seems very likely that interneurones generating the ramp depolarization (like le-cells in Planorbis, Fig. 12A-D) are responsible for the first phase of a movement and interneurones generating a short burst or a rectangular-shape

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A

0.3 s

0.1 s

Fie. 14. A number of CPGs in mammals generate biphasic rhythmic pattern, with the activity gradually increasing in the 1st phase and rapidly falling in the 2nd phase. Three examples are illustrated: A. Integrated EMG of the phrenic nerve during the respiratory cycle (cat) (15). B. Integrated EMG of the digastric muscle during rhythmical chewing (monkey) (33). c. Total activity in two groups of spinal interneurones durin, the cycle of fictive scratching (cat). The two groups are supposed to reflect the activity of a CPG with the "switch-off mechanism" (8) similar to that of Planorbis (Fig. 11D). depolarization wave (like group 2 cells in Planorbis, Fig. 12E-G) are responsible for the second phase. The CPG located in the spinal cord and controlling stepping movements of a limb produces a rather complex efferent pattern (26,4). As a first, very rough approximation, this pattern can be considered as a biphasic one, i.e. as the alternating activities of the two main groups of muscles, i.e. extensors (the support phase of the step) and flexors (the swing phase). The pattern of stepping is asymmetrical in the sense that the stance phase is usually longer and varies directly with speed of locomotion but the swing phase remains fairly constant. Such a pattern could be produced basically by two groups of interneurones. Recordings from non-identified spinal interneurones during locomotion have shown that the total number of active neurones increases in the course of the swing phase and decreases towards the end of the stance phase (39). This finding suggests that the activity of CPG neurones responsible for the swing phase increases towards the end of the phase. On the contrary, the efferent activity in the stance phase seems to be controlled by interneurones generating a gradually decreasing activity, like that in the locomotor CPG of lamprey. In the lamprey, activation of excitatory amino acid receptors of the NMDA type (produced by the reticulo-spinal neurones) transforms the spinal interneurones into oscillators operating within the frequency range characteristic of swimming (Fig. 8C,D). The fact that application of NMDA to the isolated spinal cord also evokes fictive

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locomotion in mammals (34), (see Fig. 1C) may suggest that some of the neurones constituting the CPG for stepping may be "conditional" oscillators activated by the reticulo-spinal fibres coming from the brainstem locomotor centres. There is some data indicating a possible inhibitory interaction between the interneuronal networks responsible for the swing and stance phases of a step cycle (36). An excitatory interaction probably exists as well, at least in the form of postinhibitory rebound which is a property of many types of neurones in mammals. Though the biphasic pattern is usually considered as a basis for stepping and scratching limb movements in mammals, in real movements there is some phase shift between, for example, flexor muscles of different joints of a limb (26,41). For explaining this finding, an idea that each of the joints is controlled by its own CPG, and that the CPGs of different joints are interconnected, was advanced (20). Examination of this problem can be easily carried out on the lamprey which has numerous segmental CPGs working with some phase shift in relation to one another. Besides such "automatic" movements as locomotion, respiration, etc, the central programming is also extensively used in those movements which are traditionally called voluntary (e.g. reaching or pointing arm movements). Though these movements are characterized by a great variety of motor patterns, each given pattern is determined, to a great extent, by initial information concerning the relative positions of the hand and the target (SO). One can thus suggest that these movements are also controlled by CPGs like that for defensive reaction in Planorbis (Fig. 13J), in which the output pattern strongly depends on the initial stimulus. In this chapter we did not deal with the sensory regulation of the central networks. It is of crucial inportance, however, to recall that in most instances in vertebrates and invertebrates, the sensory input can modify the duration of a given phase of a movement and the amplitude of the output signal. References 1 Andersson O., Grillner S. Acta Physiol. Sand., 113 (1981) 89. 2 Arshavsky Yu.I., Beloozerova I.N., Orlovsky G.N., Panchin Yu.V., Pavlova G.A. Exp. Brain (1985) 255. Res., 3 Arshavsky Yu.I., Deliagina T.G., Orlovsky G.N., Panchin Yu.V. Exp. Brain Res., 70 (1988) 310. 4 Arshavsky Yu.I., Deliagina T.G., Orlovsky G.N., Panchin Yu.V., Pavlova G.A., Popova L.B. Exp. Brain Res., 63 (1986) 106. 5 Arshavsky Yu.I., Gelfand I.M., Orlovsky G.N. Cerebellum and Rhythmical Movements. Springer-Verlag, Berlin, 1986. 6 Arshavsky Yu.I., Orlovsky G.N., Panchin Yu.V. Exp. Brain Res., 3 (1985) 203. 7 Benjamin P.R., Elliot C.J.H., Ferguson G.P. In: Model Neural Networks and Behaviour, A.I. Selverston (ed.), Plenum Press, N.Y., (1985) 87. 8 Berkinblit M.B., Deliagina T.G., Feldman, A.G., Gelfand I.M., Orlovsky G.N. J. Neurophysiol., 41 (1978) 1040. 9 Brodin L., Grillner S., Dubuc R., Ohta Y., Kasicki S., Hokfelt T. Arch. Ital. Biol., 126 (1988) 317. 10 Buchanan J.T., Cohen A.H. J. Neurophysiol., 47 (1982) 948. 11 Cohen A.H., Rossignol S., Grillner S. (eds.) Neuronal Control of Rhythmic Movements in Vertebrates. John Wiley and Sons, New York, 1988. 12 Delcomyn F. Science, 210 (1980) 492. 13 Euler C., von In: Neural Origin of Rhythmic Movements, A. Roberts, B. Roberts (eds), Cambridge University Press, (1983) 469.

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14 Feldman J.L., Grillner S. The Physiologist, (1983)310. 15 Feldman J.L., Speck D.F. J. Neurophysiol., (1983) 472. 16 Garcia-Rill E., Skinner R.D. In: Neurobiology of Vertebrate Locomotion, S. Grillner, P.S.G. Stein, D.G. Stuart, H. Forssberg, R.M. Herman (eds.), Macmillan, London, 77 (1986). 17 Gelfand I.M., Orlovsky G.N., Shik M.L. In: Neural Control of Rhythmic Movements in Vertebrates, A.H. Cohen, S. Rossignol, S. Grillner (eds.), J.Wiley and Sons, New York, 167 (1988). 18 Getting P.A. In: Neural Control of Rhythmic Movements in Vertebrates, A.H. Cohen, S. Rossignol, S. GriUner (eds.), J. Wiley and Sons, New York, 101 (1988). 19 Grillner S. In: Function and Formation of Neural Systems, G.S. Stent (ed.) Dahlem Konferenzen, Berlin, 197 (1977). 20 GriUner S.In: Handbook of Physiology, Sect. 1. The Nervous System Vol. II. Motor Control. V.B. Brooks (ed.) Waverly Press, Maryland, 1179 (1981). 21 Grillner S., Buchanan J.T., WdBn P., Brodin L. In. Neural Control of Rhythmic Movements in Vertebrates. A.H. Cohen, S. Rossignol, S.Grillner (eds.) J. Wiley and Sons, New York, 1 (1988). 22 Grillner, S.,Lansner A., Walldn P., Brodin L., Ekeberg O., TravBn H., Christenson, J. In: Cell to Cell Signalling: From Experiments to Theoretical Models. Academic Press, 77 (1989). 23 Grillner S.,Science, 228 (1985) 143. 24 Grillner S.,Stein P.S.G., Stuart D.G., Forssberg H., Herman R.M. (eds.) Neurobiologyd Vertebrate Locomotion. Macmillan, London, 1986. 25 Grillner S., Wallen P., Ann. Rev. Neurosci., (1985)233. 26 GriUner S.,Zangger P., Brain Res., & (1975)367. 27 Herman R.M., GriUner S.,Stein P.S.G., Stuart D.G. (eds.) Neural Control of Locomotion. Plenum Press, New York, 1976. 28 Hinzel H-G. In: Neural Mechanisms of Behavior. Erber J. et al. (eds.), N.Y., 61 (1989). 29 Holst E. Brit. J. h i m . Behav., 2 (1954) 89. 30 Jordan L.M. In: Neurobiology of Vertebrate Locomotion. S. GriUner, P.S.G. Stein, D.G. Stuart, H. Forssberg, R.M. Herman (eds.) Macmillan, London, 21 (1986). 31 Kahn J.A., Roberts A., Phil. Trans. R. SOC.B., 296 (1982)229. 32 Kandel, E.R. The cellular bases of behavior. Freeman, San Fransisco, 1976. 33 Kubota K., Niki H. In: Oral-Facial Sensory and Motor Mechanisms. R. Duber and Y. Kawamura (eds.) Appleton-Century-Crofts, N.Y., 365 (1971). 34 Kudo N., Yamada T. Neuroscience Letters, 75 (1987)43. 35 Loeb G.E. In: Neurobiology of Vertebrate Locomotion. S. Grillner, P.S.G. Stein, D.G. Stuart, H. Forssberg, R.M. Herman (eds.), MacMillan, London 547 (1986). 36 Lundberg A. In: Symp. lect. of XXVIII Int. Congr. Physiol. Sci., AkadBmiai Kiado, Budapest, 155 (1981). 37 Marder E.In: Neural Mechanisms of Behaviour. J. Erber et al. (eds.), N.Y., 55 (1989). 38 Orlovsky G.N., Shik M.L. In: International Review of Physiology. Neurophysiology II, vol. 10,281 (1976). 39 Orlovsky G.N., Feldman A.G. Nejrofiiilogia, 4 (1972)410. 40 Pearson KG., Duysens J. In: Neural Control of Locomotion. R.M. Herman, S. Grillner, P.S.G. Stein, D.G. Stuart (eds.), Plenum Press, New York, 519 (1976). 41 Perret C. In: Neural Origin of Rhythmic Movements. A. Roberts, B.L. Roberts (eds.), SOC. Cambridge University Press, 405 (1983). Exp. Biol. Symp. 42 Roberts A. In: The Computing Neuron. R. Durbm, C. M i d , G. Mitchison (eds.), AddisonWesley, Woringharn, 228 (1989). 43 Roberts A., Roberts B.L. (eds.) Neural Origin of Rhythmic Movements. SOC. Exp. Biol. Symp. 22. Cambridge University Press, Cambridge, (1983).

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44 Roberts A., Soffe S.R., Dale N. In: Neurobiology of Vertebrate Locomotion. S. Grillner, P.S.G. Stein, D.G. Stuart, H. Forssberg, R.M. Herman (eds.), Macmillan, London, 279 (1986). 45 Roberts, A,, Tunstall M.J., Europ. J. Neurosci., 2 (1990) 11. 46 Rossignol S.,Lund J.P, Drew T. In: Neural Control of Rhythmic Movements in Vertebrates. A.H. Cohen, S. Rossignol, S.Grillner (eds.), J. Wiley and Sons, New York, 201 (1988). 47 Selverston A.I., Behavioral Brain Sci., 2 (1980) 535. 48 Selverston A.J., Moulins M.The crustacean stomatogastric system. Springer, Berlin, (1987). 49 Shik M.L., Orlovsky G.N., Physiol. Rev., 3 (1976) 465. 50 Soechting J.F., Flandres M., J. Neurophysiol., 62 (1989) 582. 51 Stein P.S.G. Ann. Rev. Neurosci., l(1978) 61. 52 Stein P.S.G. In: Neural Origin of Rhythmic Movements. A. Roberts, B.L. Roberts (eds.), Exp. Biol. Symp., 22, Cambridge University Press, 383 (1983). (1961) 283. 53 Wilson D.M., J. Exp. Biol.,

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SECTION 11: Current research on temporal patterns of movements in early motor development Chapter 5

ENDOGENOUS MOTOR RHYTHMS IN YOUNG INFANTS P.H. Wolff

Chapter 6

EVIDENCE AND ROLE OF RHYTHMIC ORGANIZATION IN EARLY VOCAL DEVELOPMENT IN HUMAN INFANTS R.D. Kent, P.R. Mitchell, and M. Sancier

Chapter 7

THE ROLE OF REFLEXES IN THE PATTERNING OF LIMB MOVEMENTS IN THE FIRST SIX MONTHS OF LIFE P.M. McDonnell and V.L. Corkum

Chapter 8

DEVELOPMENT OF INFANT MANUAL SKILLS: MOTOR PROGRAMS. SCHEMATA. OR DYNAMIC SYSTEMS? G.F. Michel

Chapter 9

TIMING IN MOTOR DEVELOPMENT AS EMERGENT PROCESS AND PRODUCT E. Thelen

Chapter 10

SOFT ASSEMBLY OF AN INFANT LOCOMOTOR ACTION SYSTEM E.C. Goldfield

Chapter 11

TIMING INVARIANCES IN TODDLERS’ GAIT B. Bril and Y.Brenitre

Chapter 12

THE DEVELOPMENT OF INTRALIMB COORDINATION IN THE FIRST SIX MONTHS OF WALKING J.E:Clarkand S.J. Phillips

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The Development of Tmin Control and Temporal Or anization in 8bordinated Action J. Fagard anjP.H. Wolff (Editors) 8 Elsevier Science Publishers B.V., 1991

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Endogenous motor rhythms in young infants Peter H. Wolff The Children's Hospital, 300 Longwood Avenue, Boston, MA 02115, USA INTRODUCTION The spontaneous fluctuation of physiological and behavioral processes is a fundamental attribute of all living things that maintain complex organisms in a marginally stable but far-from-equilibrium state (Rapp, 1987; Schoener & Kelso, 1988; Sollberger, 1965; Turvey, 1990), and regulates their spontaneous behavior and inputoutput relations (Yates, 1987). Yet, theories of psychological development have traditionally proceeded on the premise that humans behave like steady state systems, and that their behavioral processes and developmental transformations can ultimately be reduced to a few fundamental interactions in terms of linear deterministic laws (Davies, 1988). Therefore, all moment-to-moment fluctuations of behavior are usually treated as random noise and partialled out by statistical smoothing procedures. Complex organisms do in fact behave like steady state systems over a limited range of conditions. However, outside these boundaries, minor changes in one or more parameters can precipitate a radical reorganization of the entire organism; and they can sometimes induce irreversible developmental transformations that are neither preprogrammed in the genome nor specified by environmental contingencies (Prigogine & Stengers, 1984). Stable and quasi-periodic oscillations are therefore a fundamental characteristic of human behavior and development. The systematic study of endogenous motor rhythms should help to resolve some of the obvious contradictions implied by these fundamentally different perspectives on behavioral organization and development. Because infants frequently exhibit spontaneous motor rhythms in a relatively simple form that has not been significantly modified by experience or cognitive development, the period of early infancy should also be an ideal entry point for investigating the functional characteristics of rhythmic behavior. However, the actual mechanisms of rhythmogenesis are rarely well understood and often controversial even in relatively simple biological systems (Glass & Mackey, 1988). Moreover, infants are "noisy" systems whose frequent and unpredictable changes of behavioral state radically alter their spontaneous behavior and responses to environmental events (Prechtl & O'Brien, 1982; Wolff, 1987). Finally, there is no a priori reason to assume that the organizational principles of motor behavior are necessarily simpler during infancy than in later stages of development (Fentress, 1976; Kelso, Tuller & Harris, 1983). Despite these limitations, the important functional characteristics of endogenous motor rhythms can frequently be described qualitatively without detailed knowledge of their underlying mechanisms (Glass & Mackey, 1988; Kugler & Turvey, 1987), particularly when discrete motor rhythms can be manipulated experimentally by simple non-invasive procedures.

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FUNCTIONAL CHARACTERISTICS OF NEONATAL MOTOR RHYTHMS

Nearly all human motor patterns that are repeated at more or less regular intervals have at one time or another been classified as motor rhythms (Kravitz & Boehm, 1971; Thelen, 1981; Wolff, 1967), but such indiscriminate usage tends to obscure the potential explanatory power of the concept for investigating and understanding processes of motor coordination and behavioral development (Stratton, 1982). A meaningful investigation of endogenous motor rhythms requires operational definitions that can distinguish incidental repetitions from behavioral events that qualify as rhythms; and it requires formal criteria that will distinguish among the various types of linear and nonlinear oscillators. The term endogenous refers to the fact that some repetitive movement patterns (usually in a frequency range of seconds and minutes) are produced by the organism's intrinsic dynamics rather than by temporal cues from the environment (Delcomyn, 1980; Prechtl, 1990; Rapp, 1987). Isolated segments of the central nervous tissue of vertebrate embryos can generate spontaneous electro-physiological pulses even after all sources of sensory input have been experimentally eliminated (Corner, 1978; Crain, 1976; Delcomyn, 1980). These pulses, in turn, may generate spontaneous movement patterns that vary in type from random fibrillations to species typical coordinated motor patterns including quadrupedal gait, swimming, and flying movements (Braendle & Szekely, 1973; Gottlieb, 1983; Hamburger & Balaban, 1963; Rapp, 1987; Weiss, 1969). Such observations have given rise to the generic hypothesis that most rhythmic behaviors of complex organisms are produced by specialized ensembles of central nervous system neurones or central pattern generators (CPG) that determine the spatio-temporal characteristics of coordinated motor behavior in a hierarchic topdown mode. Peripheral information may introduce adaptive variability in the otherwise stereotyped motor behavior, but the fundamental patterns of behavioral coordination are specified a pion' by a given CPG (Grillner, 1980; Selverston, 1980; see also Arshavsky et al., this volume, for a more detailed discussion). In principle, the concept of CPG should therefore have immediate relevance for the investigation of endogenous motor rhythms. However, the concept of CPG can usually not be tested experimentally in humans or other intact mammals. For example, there is general consensus that CPG are always the arbitrarily defined fragments of larger functional systems (Anokhin, 1975; Grillner, 1977), and the exact boundaries of any given CPG can usually not be defined precisely. Therefore, it is also difficult to demonstrate experimentally that a given CPG does in fact control a given motor rhythm independent of other CPG, other central nervous system structures or peripheral variables (Glass & Mackey, 1988). The notion of CPG also fails to address the fundamental question how a limited (even if large) number of hard-programmed neural mechanisms can selectively generate temporal structures that will achieve the functionally specific goal in face of the organism's constantly fluctuating initial conditions and environmental requirements (Schoener & Kelso, 1988; Turvey, 1990; see also Michel, this volume, for a discussion of a more flexible central motor programming models). The dynamical systems perspective on spontaneous pattern formation was advanced in part to address the question whether the timing of coordinated behavior

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is centrally programmed, or the emergent property of motor coordination itself (Schmidt, 1982). It recognizes that the coordination of directed movements ultimately depends on a neural substrate, but challenges the conventional wisdom that a neurally oriented or "reductionist" analysis is either the only valid, or necessarily the preferred, strategy for investigating motor coordination. Instead, it assumes that even the most exquisitely detailed knowledge about the molecular machinery driving a motor rhythm will not elucidate how a nearly infinite number of potentially independent degrees of freedom cooperate to induce rhythmic motor behavior at a macroscopic level; or how the temporal characteristics of such rhythmic behavior will switch systematically with changes in the organism's initial conditions and functional requirements (Kugler & Turvey, 1987; Schoener & Kelso, 1988). A research strategy based on this perspective therefore identifies collective variables or order parameters that emerge when many component variables induce dynamically stable but structurally unstable ensembles; and then tests formal predictions about the stability of the collective variables by perturbation experiments designed to dislodge a given motor rhythm from its temporal trajectory (Jeka & Kelso, 1989; Kugler & Turvey, 1987; Schoener and Kelso, 1988). The potential explanatory power of the strategy was first explored by von Holst (1935) when he experimentally demonstrated that two or more separate neuromotor automatisms may be "attracted" to each other to induce novel motor patterns with qualitatively different temporal characteristics without losing their individuality when acting singly, so that they remain free to interact with other motor rhythms to induce different synergies. Many experiments since then have formally tested the generic hypothesis that coordinated behavior emerges from the spontaneous cooperation among many nonlinear oscillators, to induce marginally stable low dimensional ensembles whose characteristics cannot be reduced to their components elements (Kelso, Tuller, & Harris, 1983; Kugler & Turvey, 1987). Breathing rhythms

The phenomenology of rhythmic behavior in human infants has been described i n several recent reviews, and need not be repeated here (Stratton, 1982; Thelen, 1981). As a point of departure for examining how endogenous motor rhythms might contribute to the development of coordinated behavior, I will therefore describe two well studied and easily recognized neonatal motor rhythms that are fully operational at birth. Ultrasound imaging studies have shown that by 20 weeks of gestational age the human fetus makes repetitive breathing movements organized as irregular bursts that range in frequency from 30-100/minute and are separated by long apneic periods. Two months later, fetal breathing movements show a more consistent and continuous rhythmic pattern; and at term, all healthy infants breathe in stable rhythms at a constant amplitude and frequency while they are in stable state 1 sleep (Prechtl & O'Brien, 1982; Wolff, 1987). A n extensive body of clinical and experimental investigations has examined the neurological, physiological, and anatomical mechanisms that contribute to various aspects of respiratory control during early infancy (see, for example, Schulte, 1979), but the detailed findings are not immediately pertinent for our description of breathing rhythms at a macroscopic level. The breathing movements of healthy infants during state 1 sleep (also referred

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to as non-REM, regular or quiet sleep) are typically organized in a smooth, symmetrical alternation of inspirations and expirations of equal duration, with a period of 30-40 cycles per minute that fluctuates only slightly over an episode of stable state 1 sleep. Spontaneous startles (Wolff, 1987), sighing inspirations (Thach & Taeusch, 1976), tickling the infant's face with a cotton wisp (Wolff & Simmons, 1967), and other endogenous or exogenous perturbations will produce a brief apnea and transient change in the amplitude and rhythm of breathing. However, the basic breathing rhythm usually returns spontaneously to its pre-stimulus trajectory after a "relaxation time'' that may extend over three or four breathing cycles. Biological rhythms that fluctuate naturally around a stable period, resist change, and return spontaneously from nearly all neighboring trajectories to the same "attractor basin" after mild perturbations rather than shifting to a different trajectory, are formally defined as stable limit cycles (Oatley & Goodwin, 1971; Winfree, 1980). They constitute an essential mechanism by which organisms are maintained in a far-from-equilibrium, but marginally stable, state (Glass & Mackey, 1988), and by which organisms form novel motor patterns whose temporal characteristics differ qualitatively from those of their component oscillators. This propensity for spontaneous pattern formation also has major implications for any theory of behavioral coordination, by suggesting an elegantly simple mechanism for developmental transformations that are not prescribed a pn'on' by any central nervous system instructions. For example, adult speakers typically organize the segmental flow of spoken phrases and sentences by partitioning their speech patterns over "breath groups" by controlling the cycle of inspirations and expirations to maintain the subglottal air pressure and speech prosody of conventional speech at a more or less constant level throughout an extended utterance. The adult speaker's intent, rather than the intrinsic dynamics of the breathing rhythm, elastic recoil forces of the lungs, or anatomical characteristics of the rib cage and the like, therefore determine how expiratory subglottal air pressure will be allocated over a vocalizations (Lieberman, 1984). Infants acquire this ability only gradually during the early months after birth. The so-called basic or rhythmic cry of the full term infant, for example, is organized as a regular alternation of expiratory phonations (crying proper) with a mean period of approximately 0.6 sec, followed by a brief aphonic pause, an abrupt inspiratory whistle, and another expiratory vocalization (Wasz-Hoeckert, Michelsson, & Lind, 1985; Wolff, 1967, 1969). Active crying alters the basic breathing rhythm as well as ratio of expiratory and inspiratory half cycles. However, within each expiration the acoustic pattern of crying is determined by the intrinsic dynamics of the respiratory apparatus as it expresses subglottal air over the vocal cords. The dependence of cry vocalizations on the breathing cycle is visualized on the sound spectrograph as an inverted U-shape corresponding to each expiration, with an initial smooth increase of amplitude and fundamental frequency followed by a smooth decrease of about the same duration, amplitude and fundamental frequency being phase-locked. In three-month-old infants, this balance of forces has shifted. On the sound spectrograph, non-cry vocalizations are now often represented as extended plateaus with a constant fundamental frequency that may be elaborated by a terminal increase of fundamental frequency (Wolff, 1969). In other words, infants can now "hold back on the mechanical flow of subglottal air pressure to create variations on the basic cry

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sound pattern at most points during an expiratory cycle. This shift in the locus of motor control for sound production culminates in the adult speaker’s ability to control how subglottal air pressure within each breath group will be allocated to produce the desired speech prosody. The example is prototypic of the developing interactions among many groups of motor rhythms that begin as an initial decoupling of intrinsic motor synergies, followed by the subsequent reassembly of the same components to achieve more differentiated functional goals. SUCKING

A large body of clinical and experimental studies on human sucking behavior has demonstrated the same theoretical issues in a different domain of motor coordination. All mammals initially depend on a competent sucking apparatus to survive, but nutritive sucking patterns have only a peripheral function thereafter (Crooke, 1979). A developmental analysis of sucking rhythms from the neonatal period through childhood may therefore provide important information about the long term contributions of congenital motor rhythms to behavioral coordination by clarifying, for example, the often debated question whether endogenous rhythms are embodied in central timing structures, or whether the timing of naturally occurring motor rhythms is an emergent property of the behavior itself (Schmidt, 1982). I will begin the description of sucking rhythms in infants with the assumption that nutritive and nonnutritive sucking involve qualitatively different motor rhythms, and will leave until later whether such distinctions are justified by the evidence (Crooke, 1979; Stanley, 1972). Nutritive sucking (NS)

Healthy human infants have at their disposal three separate oral motor mechanisms for taking milk from the feeding nipple. These include 1) the expression of milk by rhythmic compression and relaxation of the mouth muscles that is recorded on the polygraph as positive pressure changes inside a modified feeding nipple (Bruner, 1962); 2) the creation of a partial vacuum inside the mouth, or sucking proper that is recorded as intra-oral changes of negative pressure; and 3) stripping the nipple by periodically moving the tongue from the base to the tip of the nipple (Bosma, 1972; Crooke, 1979; Peiper, 1963). When the infant is hungry and excited at the start of a meal, the three components are usually combined in a single collective variable. With partial hunger satiation, the other components may drop out, and alert infants will continue sucking by periodically compressing the nipple alone, but the mean frequency of sucking movements remains the same. Spontaneous alerting or nonspecific environmental stimuli such as jiggling the infant, can reinstate all three component sucking mechanisms without altering the mean frequency of nutritive sucking. Neither the level of hunger nor environmental stimulation per se determine how the coordinated behavior will be manifested, but either control parameter can lead the infant from one pattern of NS to the other without altering the basic sucking frequency. At the start of a meal, NS is typically organized as long sequences of continuous sucks separated by occasional short pauses; the length of sucking bursts decreases progressively during the course of the meal, ahd the frequency and duration of pauses

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increases (Crooke, 1979). The changing pattern of burst-pause sequences of NS appears to be a direct consequence of gastric loading rather than of motor fatigue. Sham feeding experiments in animals by an artificial esophageal fistula that siphons off all orally ingested nutrient, indicate that the length of sucking bursts remains constant throughout the feeding as long as no nutrient reaches the stomach (Peiper, 1963). The same point can be demonstrated in human infants with esophageal atresias and tracheo-esophageal fistulas who, after surgical repair, may be fed either by gastrostomy tube or by mouth. When they are fed primarily by gastrostomy tube while oral nutritive sucking is recorded intermittently, the progressive decrease in length of NS bursts is the same as during oral feedings. By contrast, when they are fed entirely by mouth and the stomach contents are continually aspirated by the gastrostomy tube in a sham feeding paradigm, the NS pattern does not change, at least until motor fatigue sets in (Wolff, 1972). Some investigators have further concluded that the mean rate of nutritive sucking movements within each burst also decreases from the start to the end of a meal (Crooke, 1979); others have reported that the sucking frequency increases slightly toward the end of the meal (Crooke, 1979; Stanley, 1972), and we find no systematic change of sucking frequency within bursts during the course of a meal. Differences in calculating mean sucking rates probably account for some of the conflicting results. For example, a calculation based on total amount of sucking across bursts and pauses in time units of 30 or 60 seconds would be expected to show a gradual decrease of sucking frequency, because gastric loading increases the number and duration of pauses between sucking bursts. In infants with surgically repaired esophageal atresias, we have found that whether infants are fed entirely by gastrostomy tube or fed orally while the stomach contents were constantly aspirated from the gastrostomy tube, the mean frequency of NS movements remains constant over a meal. Our results therefore suggest that the length of NS bursts is regulated by linear homeostatic mechanisms directly from the stomach or by glucostatic mechanisms, but that the base period of NS movements within each burst is regulated by very different mechanisms. Possible reasons for the sometimes reported slight increase of NS frequency near the end of a meal are more complex and will be considered below. Because other exogenous variables such as the rate of milk delivery, the composition and sweetness of the nutrient, and the haptic characteristics of the nipple may also influence the total amount of NS (Crooke, 1979), some investigators have concluded that NS is controlled entirely or primarily by peripheral variables. The remarkable consistency of NS patterns and sucking rates within and across healthy infants has suggested to other investigators that sucking rhythms are primarily controlled by central pattern generators with a time structure either in the NS range of 1 Hz, or in the NNS range of 2 Hz and slowed down during a feeding by feedback signals from periodic swallowing movements (Burke, 1977; Halverson 1938). Both interpretations posit autonomous CPG that are conceptually distinct from, but causally related to the observed motor rhythm of NS. By contrast, a dynamical systems perspective might assume that the timing of endogenous motor rhythms is the emergent property of cooperation among component movements as they induce low dimensional ensembles; and that the differences in base frequencies of NS and NNS are determined by the intrinsic dynamics of their

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respective collective variables. Partial support for this view comes from experiments in which the sucking patterns of infants are tested by a modified artificial feeding nipple that controls the flow of milk while recording changes of negative pressure in the mouth and positive pressure in the nipple (Bruner, 1968; Wolff, 1972). During the early part of a feeding, the mouth usually forms a tight seal around the nipple; sucking is organized in a continuous stream; and positive pressure peaks are tightly coupled with negative pressure peaks in a stable 1:l frequency ratio of 1 Hz. When milk flow is experimentally increased to a rate that does not elicit a gag reflex, the negative pressure component may drop out, but the feeding rhythm continues at about the same mean sucking frequency of 1 Hz. On the other hand, when the milk flow is experimentally blocked, the negative pressure component also drops out, but the positive pressure component shifts abruptly to a stable alternation of bursts and pauses, and the mean intra-burst sucking frequency doubles to about 2 Hz. When the milk flow is reinstated, the motor system shifts back to the NS pattern. By turning the milk supply on and off repeatedly during the early part of a meal, it can be demonstrated experimentally that milk flow acts as one control parameter that leads the motor system from one stable motor pattern to another without prescribing how these patterns will be realized. The same switching occurs spontaneously when the infant shifts from an alert state to drowsiness or light sleep near the end of a feeding. Such state transitions are associated with unstable and easily reversible switches from the slower to the faster rhythm, so that infants sometimes suck at approximately 1 Hz and sometimes at 2 Hz. Transient shifts in sucking rate with changes of state may therefore account for a slight overall increase of NS frequency near the end of a meal. The rate variables of sucking behavior not only highlight some formal differences between NS and NNS rhythms, but may also be of interest from an evolutionary perspective. By definition, all infant mammals depend on nutritive sucking for their survival and growth, so that nutritive sucking is homologous across mammalian species. Species differences in the rate of NS rhythms may therefore provide a convenient behavioral window on the question whether endogenous motor rhythms are regulated by domain general central timing structures that determine the rate of other homologous motor rhythms as well; or whether sucking rhythms are an emergent property of synergy formation whose rate differences across species are specific to a particular motor pattern. To address this question, we examined various species of felines, canines, ungulates, rodents, pachyderms and primates, but limited the observations to captive hand-reared mammals who were accustomed to taking nourishment from artificial nipples adapted to each species, and could therefore be tested by the same experimental technique as humans. Most generally, the comparison indicated that all mammals started by sucking in a continuous stream of sucks separated by brief pauses, and they showed a similar progressive decrease in length of sucking bursts near the end of the feeding as human infants. More specifically, infant mammals of the same species sucked at essentially the same basic frequency, and species from the same taxonomic family sucked at frequencies that were more nearly the same than those of species from different taxonomic families. The relative specificity of sucking rates within taxonomic families was independent of body size. Domestic kittens and Siberian tiger cubs sucked at about the same frequency while

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kittens and rodents or rodents and tiger cubs sucked at very different frequencies. Except for chimpanzees, gorillas, and orang-utans who sucked in the same frequency range of 1 Hz as human infants (Wolff, 1968; see, also Brown & Pieper, 1973), all mammalian species sucked 2-4 times as fast as human infants. Blurton-Jones (1976) has speculated on the possible survival value of species differences of NS rate, but we were unable to demonstrate any association between NS rates and species differences in the frequency of other periodic motor patterns - in large part because the relevant data were not available for any meaningful comparisons with the mean frequency of other motor rhythms, basal metabolic rates, breathing rates and the like (Eisenberg, 1981). The data on NS rates therefore did not clarify the independence or interdependence of endogenous rhythms and their expression in coordinated behavior. Non-nutritive sucking

All healthy full term and many premature human infants respond to a pacifier (i.e., a nipple that delivers no milk) by rhythmic mouthing movements that differ qualitatively from NS rhythms, and are here defined as non-nutritive sucking (NNS). The rhythm is typically organized as a stable alternation of bursts and pauses, with a stable mean frequency of 1.9-2.2 Hz of individual sucks within each burst that is stable over repeated recordings in the same or in different behavioral states. The mean number of sucks in a burst (7.8; SD 2.3, range 4-13), and the mean duration of pauses between bursts (6.6/sec; SD 4.9, range 3-11 sec) are more sensitive to state fluctuations, but they are also relatively constant across infants within state. By using a soft and pliable pacifier, one can elicit NNS rhythms in premature infants by 35-36 weeks of gestational age; and in full term neonates the rhythm is fully competent within five minutes after birth. While NS is always the direct response to a feeding nipple, NNS patterns may be manifested either as the response to a pacifier or as a spontaneous phenomenon. The pacifier increases the amplitude of sucks, prolongs the length of bursts, and facilitates the expression of NNS in all behavioral states except crying but the temporal characteristics of burst-pause patterns and mean sucking frequencies within a burst are essentially the same in spontaneous and pacifier induced NNS rhythms (Salzarulo et al., 1980; Wolff, 1987). Peripheral stimulation may increase the total amount of NNS and reduce the sensitivity to state fluctuations, but it does not affect the form in which the rhythm will be realized. Simple perturbation experiments can be used to test the dynamic stability of the NNS rhythm. Any exogenous or endogenous perturbation such as tickling the face or spontaneous startles will temporarily disrupt the basic burst-pause cycle, and the point in the sucking cycle when the perturbation is presented will determine how the rhythm is altered. Regardless of such local effects, however, the burst-pause rhythm nearly always returns to its original phase-space after a variable relaxation time, behaving like a self-correcting non-linear oscillator. NNS rhythms may also interact with other periodic motor patterns such as breathing rhythms to induce novel temporal patterns that are not characteristic of either component rhythm when it is acting alone. For example, the onset of each burst of non-nutritive sucking during stable state 1 sleep is

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associated with a transient increase of breathing rate relative to mean breathing frequency without a pacifier; and the end of each burst is associated with a transient decrease of breathing frequency (Dreier et al., 1979). The two neuromotor automatisms with different base periods therefore interact to induce a qualitatively different motor rhythm. Yet, each rhythm returns to its original phase-space when it acts alone. The endogenous motor rhythms of complex organisms rarely act as isolated units but interact to form higher order synergies (Glass & Mackey, 1988). When two or more separate limit cycles interact to induce a qualitatively different pattern, the previously independent periods may phase-lock in a number of different combinations, depending on the nature of the rhythms and the infant's initial condition. Sometimes the motor rhythm with the higher base frequency "wraps around" the temporal trajectory of the slower period in a simple ratio, forming a globally stable "torus attractor" with a three-dimensional phase space. This appears to be the case for NNS rhythms. Within a given behavioral state, the burst-pause pattern conforms to a stable limit cycle over extended periods, but the frequency of individual sucks decays systematically from the beginning to the end of each burst, and then resets spontaneously to the initial frequency at the start of each new burst. Thus, motor rhythms that behave like torus attractors may represent another important mechanism by which organisms are maintained in a marginally stable condition, and by which they sometimes induce novel patterns of behavioral coordination that are not prescribed a prion.

NNS rhythms may also be of interest from an evolutionary perspective. The observations summarized above indicate that human infants exhibit two rhythmic patterns of sucking that correspond to the nutritive and non-nutritive functions, and that they shift discontinuously from the NS to the NNS rhythm whenever the milk flow is experimentally blocked. Other mammalian species also continue to suck when the milk supply is turned off, but never exhibit two qualitatively different patterns of sucking as they shift from a nutritive to a non-nutritive function. Instead, they maintain essentially the same rate and temporal pattern whether the nipple does or does not supply nutrient. In short, only human infants demonstrate the discontinuous shift in temporal sucking pattern with changes of function (Wolff, 1968). The theoretical significance, if any, of these species differences remains unknown, but a developmental comparison of NS and NNS rhythms in humans may provide some of the information necessary to examine the question empirically. THE DEVELOPMENT OF ENDOGENOUS MOTOR RHYTHMS Most psychological theories of human development take it on faith that the events of infancy necessarily shape the course of subsequent development, this assumption motivating most longitudinal studies in behavioral development (Werner & Kaplan, 1968). One widely accepted version of the formulation assumes that primitive reflexes are the basic building blocks of development, and that more complex behavioral forms are constructed from these units under the influence of experience and contingent reinforcement. From this formulation it should follow that complex behavioral forms can ultimately be reduced to their elementary structural units (Reed, 1986). The

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plausibility of this formulation depends on the extent to which the reflex concept can be stretched without perverting its heuristic intent (Easton, 1972; Thelen, 1989; see also McDonnell & Corkum, this volume, for a detailed discussion). If the reflex is defined rigorously as a fixed stimulus-response sequence determined by hard-programmed neuro-anatomical structures, the formulation as applied to endogenous motor rhythms is almost certainly wrong (see below). A very different perspective on the relation between antecedent and consequent behavioral events during ontogenesis follows from animal experiments demonstrating that some coordinated behavior patterns serve a vital function during infancy, but disappear entirely from the animal's repertoire after they have completed their functionally specific task; at the same time, the neural substrates that presumably regulate the behavior in question are structurally eliminated (Hamburger & Balaban, 1963; Oppenheim, 1981). The concept of "ontogenetic adaptations" based on such experiments does not exclude the possibility that antecedent behavioral characteristics may be linked with more differentiated behavioral forms, but it calls attention to the lack of well documented examples that would support the widely accepted epigenetic formulation of normal development and its clinical corollary that deviant development outcomes are causally related to deviant antecedent conditions (Oppenheim, 1981; Wolff, 1989). Once it has been shown that at least some behavioral characteristics emerging during ontogenesis are not derived from remnants of the past, it can no longer be accepted as self evident that all later appearing behavioral forms are necessarily derived from specific antecedent conditions. Each developmental sequence of interest must therefore be investigated empirically in its own right, but the experiments required to demonstrate any causal epigenetic dependence are usually very difficult to perform. A still different, and now rarely accepted, viewpoint holds that the infant's "primitive reflexes" are phylogenetic residues; that they serve no particular function; and that they must be inhibited during normal development to make way for more differentiated behavioral forms controlled by higher cortical centers. By assuming that primitive reflexes are inhibited rather than dismantled during ontogenesis, the formulation further predicts that they remain a part of the organism's latent behavioral repertoire, and can reemerge in their original form when extensive destruction of higher cortical control mechanisms releases them from inhibitory influences (Jackson, 1878). Although clinical neurology has adduced a large number of clinical observations to support this "maturationist" perspective (Paulson & Gilbert, 1968), most of the examples turn out on closer examination to be superficial analogies of form with very different structural characteristics and functional properties than the primitive reflexes of the young infant (Prechtl, 1988). To examine whether any of the extant formulations on antecedent-consequent relations during ontogenesis can be applied meaningfully to the natural history of endogenous motor rhythms, I have selected sucking patterns rather than breathing rhythms, because they undergo extensive developmental transformations during the early months (Crooke, 1979), whereas breathing patterns remain relatively unchanged throughout the life cycle. In most technological societies, children generally stop feeding from the breast or bottle sometime between 6-12 months after birth, this decline in function probably being determined by cultural conventions rather than

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cortical inhibition or ontogenetic adaptations. For example, children who grow up in traditional cultures where breast and bottle feeding in older children are socially accepted, will continue to show essentially the same NS rhythm on an artificial nipple as young infants. Even normal adults who have long given up the bottle or breast can quickly learn to suck efficiently on a feeding nipple, and their recorded NS rhythms do not differ significantly from those of young infants (Wolff, 1972). In short, the NS rhythm is neither dismantled nor neurologically suppressed during ontogenesis; nor is it significantly affected by "atrophy of disuse". NNS rhythms have a very different developmental history. Infants who do not acquire a psychological dependence on the pacifier, generally stop sucking on it sometime after the third or fourth month. When offered a pacifier while awake, they typically chew on it in a random pattern, although they may continue to generate a stable NNS rhythm while falling asleep or during the induction phase of (rectal) anesthesia (Wolff, 1972). By contrast, normal adults, including individuals who are thoroughly familiar with the expected pattern of NNS because they have analyzed many newborn sucking records, can reproduce only crude and grossly irregular copies of the burst-pause pattern; they fatigue rapidly, and show little if any improvement with practice. The neuromotor mechanisms for producing stable NNS rhythms therefore seem to be dismantled during ontogenesis, but it is not clear whether the disappearance of NNS rhythms meets the criteria of an ontogenetic adaptation. To test the apparent developmental decline of NNS rhythms more objectively, we examined adult neurological patients with different degrees of cortical damage, and used the same modified feeding nipple to record the sucking patterns. Ten elderly persons with senile dementia who were alert and socially responsive during conversation, produced a continuous stream of sucking movements as long as the nipple delivered a palatable fluid. They sucked at a stable mean frequency of about 1 Hz (range, 0.8-1.3 Hz) and showed the same coupling of positive and negative pressure changes as alert infants during the early part of a feeding. However, when the flow of fluid was blocked, they did not switch to the NNS pattern, but either chewed in an erratic pattern or rejected the nipple. Three comatose neurological patients between 50-65 with extensive diffuse cortical damage but no facial or oropharyngeal muscle weakness were examined by the same procedure. As long as a palatable fluid was delivered at a controlled slow rate to avoid a gag reflex, they also sucked in a continuous stream at a stable mean frequency of 1.0-1.3 Hz, and they showed the expected simple phase coupling between positive and negative pressure. However, when the flow of fluid was blocked they, in contrast to senile patients, switched discontinuously to the typical burst-pause pattern of NNS with a stable mean intra-burst sucking frequency of 2.2-2.4 Hz; and they maintained that rhythm for extended periods without evidence of fatigue. Furthermore, experimentally turning the fluid supply on and off caused them to switch back and forth between NS and NNS rhythms. The apparent similarities between the NNS rhythms of healthy infants and of comatose adults might suggest that the rhythm is in fact inhibited during ontogenesis, and subsequently released by extensive cortical damage (Jackson, 1878; Paulson & Gilbert, 1968). However, the earlier descriptions of young infants suggested that NNS rhythms are the emergent property of self-organizing and self-equilibrating dynamical

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patterns that may be manifested either as a spontaneous motor event in the absence of all sensory input, or as responses to functionally specific stimulation; and they will sometimes combine spontaneously with other motor rhythms to induce transiently stable novel motor synergies whose characteristics cannot be inferred from their component rhythms. In other words, NNS rhythms exhibit none of the characteristics of a reflex except in its loosest sense. On the other hand, the similarities of NNS patterns in comatose adults and newborn infants cannot be dismissed outright as superficial analogies of form. The question therefore remains how the endogenous motor rhythms of young infants might be related to the very similar coordinated behavior patterns of older individuals. A dynamical systems perspective on pattern formation suggests that stable nonlinear oscillators such as NNS rhythms are realized only when the temporal parameters of relevant subsystems favor spontaneous synergy formation. Such boundary conditions evidently obtain during early infancy. However, the differential physical growth and neuromotor development of the oro-pharyngeal motor system apparently alters its biomechanical characteristics irreversibly (Bosma, 1972); and as the component movements couple with other motor rhythms to induce more differentiated oro-pharyngeal motor patterns, development interferes with the spontaneous formation of NNS rhythms (see also Thelen, 1989). The clinical investigation of adult neurological patients indicates that differentiated patterns of motor coordination, including later acquired oro-pharyngeal synergies, are frequently dismantled by extensive cortical damage. Under very limited conditions, such structural impairment may, however, create the conditions necessary for the induction of NNS rhythms that obey the same principles of spontaneous pattern formation as young infants, but that now operate with units of behavior no longer coupled as stable higher order synergies. What is preserved during the growth years are therefore neither primitive reflexes nor stereotyped patterns of coordinated behavior, but the dynamicdl rules that promote spontaneous pattern formation and that avail themselves opportunistically of existing units of movement. In this restricted, but theoretically important, sense the experimental study of endogenous motor rhythms of infants may be a strategic entry point for investigating the mechanisms of rhythmogenesis of periodic motor patterns that cannot be so easily studied in older individuals where anatomical and physiological changes, and cognitive or other “higher cortical” influences have significantly altered patterns of coordinated behavior. REFERENCES

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The Development of Tmin Control and Temporal Or aniZation in 8mrdimted Action J. Fagard anc!P.H. Wolff (Editors) @ Elsevier Science Publishers B.V., 1991

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Evidence and Role of Rhythmic Organization in Early Vocal Development in Human Infants Ray D. Kent*, Pamela R. Mitchell** and Michele Sancier*

*Waisman Center, University of Wisconsin-Madison, 1500 Highland Avenue, Madison, Wisconsin, 53705-2280, U S A . **Department of Communication Disorders, Smith Hall, 400 Hal Greer Blvd., Marshall University, Huntington, West Virginia 25755-2675, U.S.A. Abstract Well before infants are thought to be using language, they typically produce striking sequences of apparently rhythmic vocalizations. These sequences, called babbling, may be one foundation for the development of spoken language. This paper considers the evidence for rhythmic organization in these and other early vocalizations and offers suggestions for their possible roles in the development of speech and language. 1. SPEECH AND RHYTHM Speech is often asserted to be a rhythmically organized motor behavior. The literature on the production and perception of speech is replete with comments on its rhythmicity (Allen, 1975; Condon, 1986; Fowler, 1983; Gee and Grosjean, 1983; Hoequist, 1983a; Levelt, 1989; Warner and Mooney, 1988). However, there is no generally accepted account of the exact nature of speech rhythm. The issue is complicated by the fact that languages may differ in their temporal characteristics. Some languages, such as English, are said to be stress timed, or temporally structured in relation to the stressed syllables of an utterance. One of the simplest characterizations of the rhythmicity of English is an alternating pattern of strongweak syllables. Other languages, such as Spanish, are syllable-timed languages, in which syllables tend to have uniform durations. Japanese has still another impressionistic rhythm, this one based on the mora. The beginning of a mora, a timing unit, is not necessarily coincident with the beginning of a syllable. These differences in language rhythm are reflected in the temporal adjustments of speech (Hoequist, 1983b), and there is reason to believe that they may influence infant vocalizations even in what has been called the "prelinguistic" babbling period (De Boysson-Bardies, Sagart and Durand, 1984) The dimensions that underlie speech rhythm often are simultaneously involved in other phonological contrasts. As a result, "the rhythmic structure of the utterance, and the pattern of correspondence between that rhythmic structure and its measurable physical and physiological correlates can become quite complex" (Allen and Hawkins, 1980, p. 230). Part of the difficulty, then, of studying rhythmic processes in early speech development is that the maturational end-product, adult speech, is itself not fully understood in respect to its rhythmic organization.

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At a general level, rhythm may be defined as "the structure of a sequence" (Allen and Hawkins, 1980). The evidence of rhythmicity in infant vocalizations can best be viewed by examining the structure of relationships among units of vocalization. An immediate question to be answered in undertaking such an analysis is: What is the appropriate unit of behavioral analysis? Most conceptions of rhythm in speech refer to a temporal pattern that extends over some grouping of syllables. In fact, the syllable may be the optimum unit of behavioral analysis, because it can be fairly reliably identified and because the use of a syllable unit does not presume the existence of adult linguistic units such as words, morphemes or phonemes. In addition, the syllable can potentially be defined at several levels of analysis, such as the phonological, perceptual, physiologic and acoustic levels. This is not to say that the correlates of syllable structure are unerringly identified at each level. All units of speech organization, syllables included, present interpretive difficulties across and within levels of observation. A major factor in these difficulties is the attempt to impose segmentation on what is often a continuous motor pattern. But of all the candidates for behavioral analysis of vocal development, the syllable appears to be the most practical and the most commonly used. Bloom (1988) suggested that "speechiness" (the attribution of speechlike quality to an utterance) is strongly related to the perception of syllables, as opposed to, for example, vocalic sounds. She went on to conclude that "speechiness," as judged by the adult listener, has its beginnings "with sporadic occurrences during the third month of life" (p. 471). It may not press the issue too much to say that speech as a signal is recognized by its syllabic structure. Syllable analysis offers other advantages. Particularly important is the capability of the syllable to address different processes of speech development, including segmental (phonetic), prosodic, and paralinguistic. Segmental attributes pertain to elemental sound units (phonetic inventory and phonetic combinations); these are intrasyllabic components of an utterance and, in fact, their distributional properties within a language are largely described in reference to syllable position (e.g., permissible syllable-initial consonant clusters). Prosodic, or suprasegmental, features subsume vocal regulations typically expressed within and across syllables. These include intonation (vocal pitch levels and riseslfalls), stress pattern, utterance rate, loudness, pausing and related variables. Paralinguistic properties include vocal expression of emotion or other aspects that parallel linguistic organization but are not necessarily included within linguistic theory per se. The segmental-prosodic linkage is especially critical in the analysis and interpretation of infants' vocal patterns. Baltaxe, Simmons and Zee (1984) drew attention to the importance of prosody by noting that: (1) Prosodic development often is more advanced in early language acquisition than phonological, syntactic or semantic development; (2) Early prosodic units may facilitate both perceptual and productive aspects of language and may function as ''frames'' for other units of language; (3) These early prosodic "frames" seem to be more stable than accompanying segmental characteristics; (4) Evidence indicates that control proceeds in the developmental order of fundamental frequency first, then timing, and lastly segmental contrasts; and (5) The development of the prosodic system interacts with the development of other aspects of language and appears to reach adult refinement only at puberty. Analysis by syllable units may be the means by which rhythmic patterns in developmental data can be related to rhythmic patterns in adult speech data. That is, syllables are one of the few analysis units that can be used in life-span studies

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without making strong assumptions about linguistic organization. Indeed, syllables also have been the analysis units used in studies of bird song (Marler, 1981) and nonhuman primate vocalizations (Bauers, 1989). For the purposes of the present chapter, the syllable figures prominently as the fundamental unit of which rhythmic behavior is formed. The syllable is a grouping of motor adjustments, highly variable in composition from one syllable to another, that is associated with the auditory perception of a fundamental prosodic unit. The relationships between physiologic and auditory correlates are not straightforward. For example, listeners (and linguists) generally agree that the word "wrestling" has two syllables, each associated with a vowel. But if the acoustic waveform of this word is altered by deletion of the part of the signal corresponding to the suffix "-ing," the remaining word, which sounds like "wrestle," still is judged to have two syllables. If nothing else, this result indicates that syllabicity is a relational phenomenon. The syllable is a means to describe behavior, but caution always is in order when dealing with so-called "units" of behavior, for the reasons given above and by Fentress (1984). 2. RHYTHM IN INFANT CRY The importance of considering both cry and comfort-state vocalizations in the role of rhythm in early vocal development is predicated on functional and structural continuities that have been demonstrated between these two types of vocal behavior (Stark, 1978; Kent and Murray, 1982; D'Odorico, Franco and Vidotto, 1985). Crying is often the infant's first experience in postnatal vocalization, and the rhythmic structure of cry behavior may have implications for the development of social, cognitive and communication patterns that emerge within the first year of life. Rhythms in infant cry have been noted to occur in three modes (Lester, 1985): (1) long-term periodicities, such as when or how often the infant cries; (2) shorter periodicities within the cry, for example, coordination of cry with expiratory phase of the respiratory cycle; and (3) short-term periodicities such as changes in the fundamental frequency of cry. The value of long-term rhythmicities in infant cry may be to establish predictability within the interaction routines between infant and caregivers. Lester (1984) found that acoustic measures of neonate cries were correlated with the rhythmic structures (synchrony) of infant-mother face to face interaction at three months of age. Synchrony scores were further correlated with Bayley mental scores at the age of 18 months. The infant's caregiver often responds to crying by providing the infant with rhythmic stimulation (e.g., rocking, singing, patting, etc.) designed to soothe the infant, which helps to establish temporal patterning for social interactions and turntaking (Lester, 1985). Shorter term rhythmicities may reflect the status of respiratory, phonatory, and central nervous system organization of the infant. Investigations of acoustic characteristics of cry have provided a descriptive framework within which the temporal patterning of cry and cry sequences can be viewed. A "spontaneous" cry sequence follows a rhythmic pattern, beginning with a cry, then a break of 0.2 sec., then a short inspiratory whistle, another break, then another cry (Wolff, 1969). This basic temporal pattern within the cry is observable 30 minutes after birth and remains constant until about the second month of life, at which point greater variability occurs. Wolff (1967) reported that masking noise did not effect rhythms or sounds of cries, and postulated the existence of intrinsically regulated time sequences in cry. Prechtl, Theorell, Gramsbergen and Lind (1969) observed cry rates of 50-70 utterances per minute in "spontaneous cry," with durations of each cry unit in the range of 0.4-0.9 seconds.

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Pain cries have been structurally described as consisting of an inspiration, then a long expiratory cry, then an inspiration, then expiratory cries of variable duration (Wolff, 1969). The average duration of pain cries has been described as about three seconds (Wolff, 1969), with the first unit of the cry longest (4.1 to 5.2 seconds), and succeeding units decreasing in duration (Langlois, Baken and Wilder, 1980). Very early in life, the infant demonstrates highly precise coordination between cry and respiration (Bosma, Truby and Lind, 1966), with a consistently similar pattern of respiratory volume displacement associated with separate cry cycles. Maturational changes in respiratory activity result in changes within the rhythmic pattern of the cry (Zeskind, 1985). The duration of the expiratory portion within "steady" cries increases with age through the first eight months of life (Prescott, 1980), while the duration of the inspiratory period remains fairly constant (Wilder and Baken, 1978). Silences within the expiratory portion of the cry are long, highly variable and without predictable rhythms within the first ten days of life (mean durations of 150 msec, standard deviation of 70 msec), but show more stability by six to nine months of age (mean durations of 73 msec, standard deviations of 43 msec) (Prescott, 1980). Within the first nine months, within-utterance silences in cry increase in frequency, decrease in duration, and decrease in variability of duration with age (Prescott, 1980). This increase in the consistency of temporal patterning of cry at 6-9 months corresponds with similar timing changes in the infant's speech-like (non-cry) vocalizations. A primary feature of Oller's (1980) Canonical Babbling Stage (7-9 months) is an increased consistency in syllable timing, which results in timing characteristics of this stage appearing more like mature speech than previous stages. This developmental period from approximately 7-9 months is characterized by a major biobehavioral shift which consists of changes in cognition and affect thought to reflect reorganization of the central nervous system (Lester, 1985). It is also within this general time frame in development that rhythmic patterns such as "rhythmic stereotypies" (Thelen, 1981) and multisyllable babbling typically emerge. 3. PHONETIC DATA ON RHYTHMIC PATT'ERNS IN INFANT VOCALIZATIONS Several investigators have reported evidence of rhythmic behavior in the developing infant's babble, or vocalizations that precede spoken language. Although studies in this area differ in method, number of subjects, and data analysis, they have contributed to a general understanding of patterns of vocal development in infancy. A summary of developmental patterns and stage models is given in Kent and Hodge (1990). Commonly, the syllable is taken as the most basic unit of analysis, progressing in form from a simple phonation (vowel-like phonation or nasal murmur), to a simple articulation (involving a combination of a single consonant, C, and vowel, V, in a CV syllable), to complex articulatory combinations produced together with cross-syllable periodic patterning and phonatory variations (such as pitch or loudness changes). Oller (1978) proposed a stage description of phonetic development in which the "canonical syllable" assumed a particularly important role. The canonical syllable, defined in terms of acoustic parameters relating to vocal-tract opening and closing, was proposed as the basic unit of reduplicated (repetitive) babbling. That is, the canonical syllable was the basic unit for the composition of repetitive sequences, such as "ba ba ba ba." It is these multisyllabic sequences, often, but not always, repetitive

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in structure, that commonly are associated with the term "babble." Because this word is used inconsistently, the terms "repetitive canonical syllables", "reduplicated babble," "repetitive babble" and "multisyllabic babble" have been introduced to refer to productions of syllable trains. Whatever term is used, there is general agreement that this kind of vocal pattern typically emerges between 6-10 months of postnatal life. The emergence of this vocal behavior is closely timed with the appearance of what Thelen (1979) has called "rhythmic stereotypies" in other motor systems, such as the limbs. In view of this temporal congruence, Kent (1984) suggested that multisyllabic babble is a specific example of a more general motor pattern in which repetitive or alternating movements are performed rhythmically. Another example of a stage description of phonetic development in infants is a report by Elbers (1982). She concluded from observations of her infant son over the period of 6-12 months, that there is a developmental sequence based on three core types of babble: single, repeated, and concatenated. A single babble is the occurrence of a single sound or syllable; a repeated babble is the repetition of a sound or syllable; and concatenated babble is a variation in place or manner of articulation across a syllable train. Although the proposal has intuitive appeal, subsequent investigations of infants in English-speaking homes have not confirmed the sequence of repeated and concatenated babble. The data of Smith, BrownSweeney and Stoel-Gammon (1989) and Mitchell and Kent (1990) indicate that repeated and concatenated babble can be co-emergent. In keeping with these data, it seems better to use the terms "repetitive canonical syllables" or "multisyllabic babbling" to refer to the syllable trains that typically emerge during the second half of the first year of life. These trains do not appear to be exclusively, or perhaps even typically, repetitive in nature. Therefore, the more general terms, canonical or multisyllabic, are preferable. The term "multisyllabic babbling" will be used in this chapter to refer to these vocalizations of syllable trains. Whether the multisyllabic babbling is repetitive, variegated, or some combination of the two, the syllables often are judged to have a rhythmic structure. The following conclusions can be drawn from phonetic studies of multisyllabic babbling: 1. It appears typically between 6-10 months of postnatal life. This period coincides with the general appearance of "rhythmic stereotypies," or repetitive movements of body structures. (Kent, 1984; Kent and Bauer, 1985). 2. It incorporates different types of segmental (phonetic) composition, ranging from strictly repetitive (e.g., [ba ba ba ba ba]) to variegated (e.g., [ba ba di di de de gal). These types can be co-emergent; that is, one type does not necessarily precede the other (Mitchell and Kent, 1990). 3. It can be accompanied by a variety of prosodic patterns, involving variations in voice quality, pitch, loudness, syllable rate and pausing (Oller, 1978; Stark, 1979). 4. The syllable pattern frequently is judged to have a rhythmic character (Kent and Bauer, 1985). 5. Its phonetic aspects are largely continuous with the phonetic characteristics of early word production (Oller et al, 1978). This segmental carryover indicates the relevance of the motor experience of babbling to the infant's attempts to produce first words. 6. It is shaped in some respects by the ambient language and by the infant's sensorimotor abilities. That is, this type of babbling assumes certain characteristics of the parent language and is affected by infant characteristics such as hearing impairment and orofacial anomaly (Kent and Hodge, 1990).

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R D.Kent, R R Mitchell and M. Sancier However, there is no strong evidence that it is impeded by cognitive impairment, such as would be expected in infants with Down syndrome (Dodd, 1972; Smith, 1984).

4. ACOUSTIC AND PHYSIOLOGIC DATA ON RHYTHMIC VOCAL PATTERNS Acoustic data are not as abundant as perceptually derived phonetic data on infant vocalizations. However, an acoustic data base is rapidly growing. It is likely that perceptual and acoustic methods will be the major sources of data for at least the near future. Physiological methods are more difficult to use, although some data, especially on respiratory activity, have been reported. Indeed, the physiological data on respiration are an appropriate starting point for discussion. A fact of immediate relevance is that infants have a faster breathing rate than older children and adults. Because vocalization is generated on egressive or ingressive transglottal air flow, the rate of breathing may set limits on the duration of the inspiratory or expiratory phase for vocalization. This issue is of particular concern to rhythmic vocalizations because respiratory support is needed over a grouping of syllables. Unlike general body movements, such as those of the arms and legs, the movements that result in vocalization disrupt the normal pattern of respiration. Any vocalization that extends beyond some minimal duration is a modification of the rest breathing pattern. Acoustic data usually take the form of segment durations, fundamental frequencies, and selected spectral measures, but these are not equally informative for present purposes. The acoustic measures that provide the most information on rhythmic structure of vocalization are the intensity envelope, the fundamental frequency contour, and segment and syllable durations. Papousek and Papousek (1989, using sound spectrography, observed an increasing duration of vowel sounds in the vocalizations of their infant subject over the first three months of life. These vowels were noted to occur frequently in rhythmic sequences of four to eight units per expiration. Rate of vocalization in these rhythmic sequences was reported to range from 40 to 80 vowel sounds per minute. Vowel durations varied in the range of 150-1100 msec. The authors also noted that a new, faster articulatory rhythm developed within respiratory cycles beginning in about the third month. Zlatin-Laufer and Horii (1977) also reported a general increase in the duration of nonreflexjve vocalizations over the period from birth to 24 weeks. They remarked that the infants seemed to engage in systematic manipulation and practice of different durations of vocalizations. In another study of early vowellike sounds, Stark (1978) determined that "cooing" sounds occur in single units at first emergence (8-12 weeks), with each unit having a duration of about 500 msec. Shortly after, the sounds began to be produced in series, with no more than one sec between successive units of the series. Other types of rhythmic vocal behavior have been reported at later points in infancy. Oller (1980) noted the presence of ingressive-egressive sequences within a stage that he termed the Expansion Stage (roughly extending from 4 to 6 months). These sequences were alternating vocalizations on ingressive and egressive phases of the breath cycle. He did not provide information on the temporal organization of these sequences. Vocalizations of 4-8 month-olds were studied by D'Odorico, Franco and Vidotto (1985). They segmented vocalizations into vocal sequences (each sequence being separated from temporally adjacent sequences by a silent period of at least 2 sec duration. A further segmentation was determined for Units of Vocalization (UV).

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Each UV was defined by an interruption of phonation having a duration of at least 50 msec. The number of UVs per sequence was in the range of 1-16, but fewer than ten percent of the sequences contained more than six UVs. The average sequence length for non-cry calls was 1.56 UVs per sequence, and the average pause duration between non-cry UVs was in the range of 627-693 msec. The authors concluded that the durations of infant vocalizations were influenced by a number of factors, including type of voicing (voiced, half-voiced or unvoiced), manner of phonation and melodic pattern. In addition, the communicative context of vocalization affected the temporal parameters of voiced sequences. Several writers on infant vocalizations identify the onset of a major stage at about 6 months of life. This stage is called variously the Canonical Babble Stage, the Reduplicated Babble Stage, the Repetitive Stage or the Multisyllable Babble Stage. One of the distinguishing characteristics of this stage is the relatively frequent occurence of syllable trains, These trains invite a number of inquiries into their temporal organization. One feature that has been studied by several investigators is Final Syllable Lengthening (FSL). FSL is a phenomenon in which the final syllable of an utterance is lengthened. Such lengthening is common in adult speech at major syntactic boundaries and is sometimes called prepausal lengthening. In one of the first studies of FSL in infants, Oller and Smith (1977) did not find significant evidence of this feature in the multisyllable productions of 8-12 month-olds. However, Zlatin-Laufer (1980) reported the occurrence of FSL in the first half year of life. Mitchell (1988) also reported significant differences between final and nonfinal vowels in bisyllable productions of 7-, 9- and 11-month-old infants. These differing results may be explained in part by differences in overall utterance properties. In adult speech, FSL is less apparent in longer utterances or connected discourse (matt, 1976; Umeda, 1975). A similar effect may obtain in infant multisyllable babbling. Acoustic measures of relative timing were used by Hodge (1989) to infer movement events in reduplicated CV chains of the form [dae dae dae dae]. Her infant subjects were 7-9 months old. One measure of relative timing was based on a ratio of two intervals: (1) the interval from the release burst of one consonant to the closure for the following consonant, and (2) the interval between the second and third stop bursts (representing a full cycle from opening to opening movements). Another measure was based on the ratio of the duration of formant transition (representing articulatory movement) to the duration of the entire CV syllable. The first ratio was not significantly different in comparison across five age groups (infants, 3-year-olds, 5-year-olds, 9-year-olds and adults). Thus, a constancy in relative timing was preserved from infancy through adulthood. The second ratio did vary significantly across age groups, with the smallest values recorded for the infants. The differences in the ratios indicated that the youngest subjects spent relatively less time in movement and relatively more time changing direction or initiating the next movement cycle. The effect of maturation, then, was to increase the actual ovement proportion of an alternating movement sequence.

THE ROLE OF RHYTHMIC ORGANIZATION IN SPEECH DEVELOPMENT A model of the processes involved in infant vocalizations is given in Fig. 1. This model is based on observations of infant sounds and on various concepts represented in stage descriptions of infant vocalizations (Kent and Hodge, 1990). It shows how developmental events contribute to the form of vocalizations over approximately the 5.

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RESPIRATORY/ LARYNGEAL FUNCTION

SUPRAGLOTTAL FUNCTION

Phonation

Prima ily vocalic

+Grunts, cries, coos 4 Possible combination -+ Coos, goos, trills

'-

'

optional interruption

-'

VOCALIZATION TYPE

with velar or uvular closures

+ +

Phonatory variations

Vocalic nuclei with possible closant(s)

+ Yells, growls,

Improvements in coordination of phonation with supraglottal events

Possible combination with front closants

+ Marginal syllable

Prosodic control grossly adjusted to ambient language

ClosaGt-vocant -&

+

Canonical syllable

+ sequences with

articulatory dynamics roughly matched to adult syllables

+

4

Sustained phonation with p ossib1e interruption for phonqic segments Refinement of prosodic patterns

--+ Repetitive

Trains of repeated closant-vocant syllables

+ +

Mixed closant-vocant syllable sequences

*

1

squeals

Improved ambient language -p of phonation with supraglottal events

+ Variegated

Adjustment to selected

+ features of ambient

*

canonical babble canonical babble

+ Babble

combinations

language Continued adjustments+ to possible first words

Jargon and coordination

Figure 1. Scheme of vocal development for the first year of life, showing respiratoryflaryngeal events, supraglottal events, and vocalization types. Development proceeds from top to bottom.

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first year of life. The processes in the left column reflect respiratory and laryngeal function; those in the center reflect supraglottal function, and the resulting vocalization products are shown at the right. Vocal development is based on several different accomplishments, including (1) regulation of respiration to insure a prolonged expiratory phase, (2) control of phonation to permit momentary interruption within an overall expiratory phonatory pattern, (3) movements of articulatory structures to produce vocants (vowellike sounds) and closants (consonantlike sounds), (4) regulation of intrasyllabic movement timing to produce canonical syllables, (5) coordination of phonatory and articulatory events within a rhythmic syllabic organization. Rhythmic organization in early vocalization can be discussed with respect to two general issues, one being the role of rhythm in motor behavior, and the other being the role of rhythm in relation to speech development. Because rhythmic structure is by no means unique to vocal behavior, and because the appearance of rhythmic vocalizations is developmentally linked with the more general appearance of rhythmically organized motor behavior, the rhythms of vocalization probably should be considered in terms of a larger picture of developmental rhythms. But because rhythms in vocalization may contribute to the unique properties of speech and language, it is also appropriate to consider the role that these temporal patterns may play in the acquisition of spoken language. In recent literature that takes a dynamical biological perspective on behavior, evidence has been presented for an emerging rhythmicity during ontogenesis, in animals and human alike, that may provide the basis for more complex, coordinated movements later in life. Whiting (1980) suggested that movement in early behavior is mechanical, allowing the organism to go through the motions of complex coordinated actions, or parts of these actions, before they are actually needed. Various bird species exhibit preening behavior before the development of feathers (Barraud, 1961; Nice, 1943). Rat pups, after being injected with milk, exhibit motor patterns of grooming (Hall, 1979). In a study of junglefowl development, Kruijt (1964) noted early, fragmented fighting movements without cause, and also observed pecking movements used in fighting that were not distinct from feeding movements. For both animals and humans, early rhythmic behavior may be a foundation for the development of subsequent coordinated behavior. One feature that infant babbling shares with speech is a serial structure of movements, apparently organized into syllables. The CV syllable commands particular attention, because of its primacy in babbling and early words. Trains of CV syllables give the infant a rich sensorimotor experience. These vocalizations provide the opportunity for the infant to produce CV movements in a larger prosodic structure, which may be modulated to produce changes in component durations, vocal intensity, or fundamental frequency. The early co-existence of repetitive and variegated CV syllables in babbling indicates that the infant may gain valuable motor experience. The production of CV trains also gives the infant a corresponding sensory experience based on tactile, kinesthetic, barometric and auditory feedback. Interestingly, perceptual experiments have shown that infants are better able to make auditory discriminations for sounds that occur in repeated, rather than variegated, syllables. This result indicates that the repetitive syllable structure that occurs commonly in babbling offers a stable pattern for the discrimination of sound patterns.

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What is the origin of the apparent rhythmicity of infant vocalizations? A first consideration is that biomechanics of the speech system tend to yield a particular cyclicity. Sorokin, Gay and Ewan (1980) suggested that the normal syllable rate in natural languages (5-6 per second) is a reflection of articulatory (especially mandibular) biomechanics. At this syllable rate, the movements are associated with a muscle energy minimum. If infants tend to produce multisyllabic sequences largely by jaw movement (Kent and Hodge, 1990), then a modal frequency determined by biomechanical factors of the mandible would be expected. This is not to say that only one frequency can occur, but that syllable rate is strongly influenced by peripheral properties to occur at rates around a preferred value (see, for example, the analyses of rhythmic behavior described by Porges et al, 1980). As Lindblom (1983, p. 238) explains, "the average duration of a syllable...is not an arbitrary but to a significant extent a biomechanically and physiologically conditioned figure." By this reasoning, the syllable becomes a relatively fixed time frame within which consonant(s) and vowel production is accomplished. Central pattern generators (CPGs) are another possibility for rhythm control. As discussed by Grillner (1981): "In analogy with the control of limb movements, the innate programs to control different sound sequences in animals may be generated through a control of the activity in the respiratory brainstem pattern generator and fractionation of the central pattern generators (CPG) for mastication and swallowing" (p. 227). To produce vocalizations of varying duration with rhythmic organization, the primary requirement for respiratory function is a prolongation of the expiratory phase. The primary requirement for the upper airway (supraglottal) musculature is the performance of a rhythmically organized movement performed during the prolonged expiratory phase. Both lesion and stimulation studies suggest that the lateral nonprimary motor area activates the patterned movements of swallowing, mastication and lapping (Larson et al., 1980; Lund and Lamarre, 1974; Luschei and Goodwin, 1975). Fractionation could be achieved by cortical influences on brainstem CPGs controlling orofacial movements. Recalling the infant's reliance on jaw movement, it can be suggested that the infant could produce sequences of bilabiaValveolar consonants and vowels primarily by rhythmic movements of the mandible, on which the lower lip and the tongue can ride passively. Fractionation selecting the mandibular musculature could contribute to babbling rhythm. Another way of conceptualizing the role of rhythmic processes in speech and language development is in terms of the theory of neuronal group selection (Edelman, 1987, 1989). This theory involves three mechanisms--developmental selection, experiental selection and reentrant mapping. Developmental selection is a mechanism for the diversification of local neuronal connectivities. The processes of cell division, cell death, cell migration, process extension and elimination contribute to developmental selection, which yields a primary repertoire of large numbers of variant neuronal groups within a given brain region. These repertoires come about through genetic and epigenetic regulation. In experiental selection, behavior results in a dynamic selection of neuronal groups; populations of synapses are strengthened or weakened so that secondary repertoires are formed through an action akin to differential amplification. Perceptual categorization develops as maps are generated in relation to receptor sheets. The interaction between maps and receptor sheets with one another is accomplished through a signal exchange called reentry. Reentrant mapping is a parallel signaling through ordered anatomical connections between separate maps. Phasic or continuous signaling across reentrantly connected maps contributes to temporal correlations among the neuronal selections within the maps.

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Applied to infant vocal behavior, these ideas could take a form such as the following. The orofacial system is richly endowed with sensory receptors, so that stimulation through contact or movement generates a variety of sensations, including static and kinetic cutaneous stimulation, muscle spindle activation, and joint mechanoreceptor stirnulation. In addition, baroreceptors and other specialized receptors monitor air pressures and flows generated by the action of the respiratory and laryngeal structures. (For a review of these sensory systems, see Kent, Martin and Sufit, in press.) Thus, oral movements activate a number of receptor sheets. If sound also is generated by these movements, then additional sensory information is present in the form of audition. These various types of sensory stimulation give rise to maps for particular modalities. The production of even a relatively simple sound, such as a single syllable, causes neuronal activation in several receptor sheets and their associated maps. The maps, in turn, are reentrantly connected. As vocal movements are performed, temporal correlations of neuronal activity are established across the various maps. A given movement, such as the movement for the consonant [d] in “do,” can be associated with cutaneous stimulation of the tongue tip and alveolar ridge, stimulation of the muscle spindles and deep mechanoreceptors in the tongue and jaw, and stimulation of the barometric receptors in the tracheobronchial tree. This sensory information is related to the auditory sensations produced by the acoustic signal through reentrant signaling. The sensory neuronal activity, in turn, is related to motor neuronal activity in a motor map (or maps). In this way, a correspondence is established between sensory consequences and motor activity. Perceptual categorization of self-produced vocalizations results from the reentrant signaling among the maps. Sounds produced by others, such as the infant’s parents, are also represented in the auditory receptor sheet and associated map. Global maps, or dynamic structures containing multiple local (sensory and motor) maps, then relate the various selections accomplished through the local maps. Reentrant signaling of this kind could lead to phonetic, and eventually phonemic, categorization. Categories are not defined by specific activity in any single receptor sheet or map, but rather by correlations and relationships in several sheets, local maps and global maps. A primary advantage to this formulation is that it avoids the necessity of identifying invariant motor or sensory correlates of a given sound. Lack of invariance is a persistent problem in the study of speech. It has been extraordinarily difficult to specify invariant acoustic or physiological correlates for a given phoneme. But such invariant correlates need not exist in the local (sensory and motor) maps if the appropriate correlations among selected neuronal populations are represented in the global maps. Rhythmic processes could be involved in two major ways. First, Edelman suggests that rhythm arises from the reentrant signaling itself. Second, rhythm arising from other sources, e.g., subcortical generators or biomechanical efficiencies, could provide a temporal pattern for the reentrant signaling among maps. As a child engages in repetitive babble, highly predictable patterns of motor and sensory activity would result. The rhythm of the babbling movements should facilitate the spatiotemporal statistical analyses among the selected neuronal populations. The production of both repetitive and variegated babbling in the second half-year of life would give the infant numerous opportunities to derive coordinated patterns among sensory and motor maps associated with vocalization. Preferred rhythms might be identified by considerations of the sensory and motor mechanisms involved. As noted above, the syllable rate of natural languages seems to be determined largely by biomechanical solutions that minimize energy expenditure (Sorokin, Gay and

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Ewan, 1980). On the sensory side, Riesz (1928) reported that sensitivity to amplitude-modulated tones is greatest at a rate 2-4 Hz, which corresponds to a change every 250 msec, which is close to the average syllable durations of speech. The 4 Hz modulation sensitivity may facilitate the infant’s auditory processing of the syllabic pattern, which in turn could assist the infant to recognize phonetic elements within the syllables. Thus, a hand-shaking arrangement between mandibular biomechanics and auditory sensitivity may facilitate the infant’s entry into the sensorimotor experience of speech. The rhythms so defined may then contribute to the rhythms of reentrant mapping in the theory of Neuronal Group Selection. 6. REFERENCES Allen, G.D. (1975). Speech rhythm: Its relation to performance universals and articulatory timing. Journal of Phonetics, 3, 75-86. Allen, G., and Hawkins, S. (1980). Phonological rhythm: Definition and development. In G. Yeni-Komshian, J. Kavanagh and C. Ferguson (Eds.), Child Phonology. Vol. 1: Production. Baltaxe, C., Simmons, J., and Zee, E. (1984). Intonation patterns in normal, autistic and aphasic children. In Van den Broecke and Cohen (Eds.), Proceedings of the Tenth International Congress of Phonetic Sciences (pp. 713-718). Barraud, E.M. (1961). The development of behaviour in some young passerines. Bird Study, 8, 111-118. Bauers, K.A. (1989). The role of vocal communication in the intra-group social dynamics of stumptailed macaques (Macaca arctoides}. Unpublished Ph.D. dissertation, University of Wisconsin-Madison, Madison, WI. Bloom, K. (1988). Quality of adult vocalizations affects the quality of infant vocalizations. Journal of Child Language, 15, 469-480. Bosma, J., Truby, H., and Lind, J. (1966). Cry motions of the newborn infant. Acta Paediattica Scandinavica (Suppl.}. 163, 61-92. Condon, W.S. (1986). Communication: Rhythm and structure. In J. R. Evans and M. Clynes (Eds.), Rhythm in Psychological, Linguistic, and Musical Processes (pp. 55-78). Springfield, I L Charles C. Thomas. De Boysson-Bardies, B., Sagart, L., and Durand, C. (1984). Discernible differences in the babbling of infants according to target language. Journal of Child Language, 16, 1-17. Dodd, B.J. (1972). Comparison of babbling patterns in normal and Down-syndrome infants. Journal of Mental Deficiency Research, 16, 35-40. D’Odorico, L., Franco, F., and Vidotto, G. (1985). Temporal characteristics in infant cry and non-cry vocalizations. Language and Speech, 28, 29-46. Edelman, G.M. (1987). Neural Darwinism: The Theory of Neuronal Group Selection. New York: Basic Books. Edelman, G.M. (1989). The Remembered Present. New York: Basic Books. Elbers, L. (1982). Operating principles in repetitive babbling: A cognitive continuity approach. Cognition, 12, 45-63. Fentress, J.C. (1984). The development of coordination. Journal of Motor Behavior, 16, 99-134.

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Fowler, C.H. (1983). Converging sources of evidence on spoken and perceived rhythms of speech: Cyclic production of vowels in monosyllabic stress feet. Journal of Experimental Psychology: General, 112, 386-412. Gee, J.P., and Grosjean, F. (1983). Performance structures: A psycholinguistic and linguistic appraisal. Cognitive Psychology, 15, 411-458. Gracco, V.L., and Abbs, J.H. (1988). Central patterning of speech movements. Experimental Brain Research, 71, 515-526. Grillner, S. (1981). Possible analogies in the control of innate motor acts and the production of sound in speech. In S. Grillner, B. Lindblom, J. Lubker and A. Persson (Eds.), Speech Motor Control (pp. 217-230). New York Pergamon Press. Hall, W.G. (1979). Feeding and behavioral activation in infant rats. Science, 205, 206-208. Hodge, M.M. (1989). A comparison of spectral-temporal measures across speaker age: Implications for an acoustic characterization of speech maturation. Ph.D. dissertation, University of Wisconsin-Madison. Hoequist, C.E. (1983a). The perceptual center and rhythm categories. Language and Speech, 26, 367-376. Hoequist, C.E. (1983b). Syllable duration in stress-, syllable-, and mora-timed languages. Phonetica, 40, 203-237. Kent, R.D. (1984). The psychobiology of speech development: Co-emergence of language and a movement system. American Journal of Physiology, 246, R888R894. Kent, R.D., and Bauer, H.R. (1985). Vocalizations of one-year-olds. Journal of Child Language, 12, 491-526. Kent, R.D., and Hodge, M. (1990). The biogenesis of speech: Continuity and process in early speech and language. In J.F. Miller (Ed.), Progress in Research on Child Language Disorders. Austin: Pro-Ed. Kent, R.D., Martin, R.E., and Sufit, R.L. (in press). Oral sensation: A review and clinical prospective. In H. Winitz (Ed.), Human Communication and Its Disorders. Vd. 3. Norwood, New Jersey: Ablex. Kent, R.D., and Murray, A. (1982). Acoustic features of infant vocalic utterances at 3, 6, and 9 months. Journal of the Acoustical Society of America, 72, 353-365. Klatt, D.H. (1976). Linguistic uses of segmental duration in English: Acoustic and perceptual evidence. Journal of the Acoustical Society of America, 59, 1208-1221. Kruijt, J.P. (1964). Ontogency of social behavior in Burmese red junglefowl (Gallus gallus spadeceus Bonnaterrs). Behavior, Suppl. 12. Langlois, A., Baken, R., and Wilder, C. (1980). Pre-speech respiratory behavior during the first year of life. In T. Murry and J. Murry (Eds.), Injiarif Communication: C y and Early Speech. Houston: College-Hill. Larson, C.R., Byrd, K.E., Garthwaite, C.R., and Luschei, E.S. (1980). Alterations in the pattern of mastication after ablations of the lateral precentral cortex in rhesus macaques. Experimental Neurology, 70, 638-651. Laufer, M.Z. (1980). Temporal regularity in prespeech. In T. Murray and J. Murray (Eds.), Infant Communication: Cry and Early Speech. San Diego: College-Hill Press. Lauter, J.L., and Hirsh, I.J. (1985). Speech as temporal pattern: A psychoacoustical profile. Speech Communication, 4, 41-54. Lester, B. (1984). A biosocial model of infant crying. In L. Lopsitt (Ed.), Advances in Infancy Research. New York: Academic Press.

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Lester, B. (1985). Introduction: There’s more to crying than meets the ear. In B. Lester and C.F.Z. Boukydis (Eds.), Infant Crying: Theoretical and Research Perspectives. New York Plenum Press. Levelt, W.J.M. (1989). Speaking. Cambridge, MA: M U Press. Lindblom, B. (1983). Economy of speech gestures. In P.F. MacNeilage (Ed.), The Production of Speech (pp. 21 7-245). New York: Springer-Verlag. Lund, J.P., and Lamarre, Y. (1974). Activity of neurons in the lower precentral cortex during voluntary and rhythmical jaw movements in the monkey. Experimental Brain Research, 19, 282-299. Luschei, E.S., and Goodwin, G.M. (1975). Role of monkey precentral cortex in control of voluntary jaw movements. Journal of Neurophysiology, 38, 146-157. Marler, P. (1981). Birdsong: The acquisition of a learned motor skill. ZYends in Neuroscience, 4, 88-94. Mitchell, P. (1988). Phonetic variation and final syllable lengthening in multisyllable babbling. Unpublished manuscript, University of Wisconsin-Madison. Mitchell, P.R., and Kent, R.D. (1990). Phonetic variation in multisyllabic babbling. Journal of Child Language, 17, 247-265. Nice, M.M. (1943). Studies in the life-history of the song sparrow. 11. Transactions of the Linnean Society of New York, 5, 1-328. Oller, D.K. (1978). Infant vocalizations and the development of speech. Allied Health and Behavioral Science, 1, 523-549. Oller, D. (1980). The emergence of speech sounds in infancy. In G. YeniKomshian, J. Kavanagh and C. Ferguson (Eds.), Child Phonology. Vol. I. Production. New York: Academic Press. Oller, D., and Smith, B. (1977). Effect of final-syllable on vowel duration in infant babbling. Journal of the Acoustical Sociey of America, 62, 994-997. Oller, D.K., Weiman, L.A., Doyle, W.J., and Ross, C. (1976). Infant babbling and speech. Journal of Child Language, 3, 1-11. Papousek, M., and Papousek, H. (1981). Musical elements in the infant’s vocalization: Their significance for communication, cognition, and creativity. In L. Lipsitt (Ed.), Advances in Infancy Research. Norwood, NJ: Ablex. Porges, S.W., Bohrer, R.E., Cheung, M.N., Drasgow, F., McCabe, P.M., and Keren, G. (1980). New time-series statistic for detecting rhythmic co-occurence in the frequency domain: The weighted coherence and its application to psychophysiological research. Psychological Bulletin, 88, 580-587. Prechtl, H., Theorell, K., Gramsbergen, A., and Lind, J.A. (1969). Statistical analysis of cry patterns in normal and abnormal newborn infants. Developmental Medicine and Child Neurology, 11, 142-152. Prescott, R. (1980). Cry and maturation. In T. Muny and J. Murry (Eds.), Infant Communication: Crv and Ear& Soeech. Houston: College-Hill. Riesz, R.R. (1928). Differential Sensitivity of the ear for PUGtones. P/zysics Review, 31. 867-875. Smith, B.L. (1984). Implications of infant vocalizations for assessing phonological disorders. In N.J. Lass (Ed.), Speech and Language: Advances in Basic Research and Practice (Vol. 11). Orlando, FL: Academic Press. Smith, B.L., Brown-Sweeney, S., and Stoel-Gammon, C. (1989). Reduplicated and variegated babbling. First Language, 9. Sorokin, V.N., Gay, T., and Ewan, W.G. (1980). Some biomechanical correlates of jaw movement. Joiinial of the Acoustical Sociey of America, 68(Sl), S32 (A).

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Stark, R. (1978). Infant speech production and communication skills. Allied Health and Behavior Sciences, 1, 131 -151. Stark, R.E. (1979). Prespeech segmental feature development. In P. Fletcher and M. Garman (Eds.), Language Acquisition (pp. 15-32). Cambridge: Cambridge University Press. Sumi, P.S.G. (1969). Some properties of cortically-evoked swallowing and chewing in rabbits. Brain Research, 15, 107-120. Thelen, E. (1979). Rhythmical stereotypies in normal human infants. Animal Behavior, 27, 699-715. Thelen, E. (1981). Rhythmical behavior in infancy: An ethological perspective. Developmental Psychology, 17, 237-257. Umeda, N. (1975). Vowel duration in American English. Journal of the Acoustical Society of America, 58, 434-445. Warren, R.M., and Mooney, K. (1988). Individual differences in vocal activity rhythms: Fourier analysis of cyclicity in amount of talk. Journal of Psycholinguistic Research, 17, 99-111. Whiting, H.T.A. (1980). Dimensions of control in motor learning. In G.E. Stelmach and J. Requin (Eds.), Tutorials in Motor Behavior. Amsterdam: North Holland. Wilder, C.N., and Baken, R.J. (1978). Some developmental aspects of infant cry. Journal of Genetic Psychology, 132, 225-230. Wolff, P. (1969). The natural history of crying and other vocalizations in early infancy. In B.M. Foss (Ed.), Determinants of Infant Behavior (Vol. 4). London: Methuen. Wolff, P. (1967). The role of biological rhythms in early physiological development. Bulletin Meninger Clinic, 31, 197-218. Zeskind, P. (1985). A developmental perspective of infant crying. In B. Lester and C.F.Z. Boukydis (Eds.), Infant Crying: Theoretical and Research Perspectives. New York Plenum Press. Zlatin-Laufer, M. (1980). Temporal regularity in prespeech. In T. Murray and A. Murray (Eds.), Infant Communication: Cry and Early Speech. Houston: CollegeHill. Zlatin-Laufer, M., and Horii, Y.(1977). Fundamental frequency characteristics of infant nondistress vocalization during the first 24 weeks. Journal of Child Language, 4, 171-184.

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The Development of Tmin Control and Temporal Or anization in C!oordinated Action J. Fagard aniP.H. Wolff (Editors) Q Elsevier Science Publishers B.V., 1991

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The role of reflexes in the patterning of limb movements in the first six months of life P.M. McDonnell and V.L Corkum Department of Psychology University of New Brunswick Fredericton, NB Canada, E3B 6E4

Abstract This chapter examines the interrelationships of reflexes and the motor skills of infants developing in the first six months of life and the implications for motor development beyond this period. Different theoretical positions on the nature of this relationship are considered. Arguments are advanced in favor of a theoretical position called "motor-genre theory" which views reflexes as distinct from other innate patterns of movement and argues that primitive reflexes are not behavioral ancestors of voluntary behaviors. The importance of postural stability and control has often been overlooked in discussions of developing motor skills. We explore the contributions of mature postural reflexes in developing motor control. It is argued that mature postural reflexes are necessary but not sufficient conditions for voluntary motor functions. A specific example is given in a detailed discussion of the evidence that the stepping reflex develops into unaided voluntary walking. It is proposed that the evidence should be re-evaluated. As an aid to researchers, the final section of the chapter provides a review of some of the key tests used to assess both primitive and mature reflex patterns

1.THEoRJEs The extent to which reflexes contribute to o r interfere with the development of normal patterns of movement is a major theoretical question. A more specific form of the question asks what is the nature of the relationship between the neonate's array of primitive reflexes and emerging voluntary motor activities. One possible view is that primitive reflexes are the behavioral ancestors of adult motor behaviors or that they are the building blocks of voluntary motor functions. This connection has been described by Twitchell (1970) and Easton (1972). An example would be that the grasp reflex is a primitive form of mature grasping. Still another example would be that the stepping reflex is directly related to mature walking. This latter relationship

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has been postulated and empirically tested with some success by Zelazo, Zelazo and Kolb (1972). Other researchers (e.g., Easton, 1972;Peiper, 1963;Piaget, 1952) seem to have assumed without very strong evidence that voluntary behaviors were behavioral descendants of reflexive behaviors. This viewpoint might be termed the "motor-continuity''theory. A recent example of the motor continuity approach is the work of Sheppard and Mysak (1984). They examined the developmental course of mature chewing movements and concluded that a set of orofacial reflexes, available at birth and maintained until 35 weeks of age, are organized into functionally specific chewing actions with food. Also, Fogel and Hannan (1985)looked at the correlations between facial expressions and specific manual actions (e.g., point, spread, curl, grasp) in infants ranging from 9 to 15 weeks of age. The presence of correlations encouraged them to conclude that "early hand actions are reflexive coordinations similar to orofacial movements" (p. 1278). Since one of the major difficulties with these and other papers is the definition of a reflexive pattern of movement, the problem of definition will be discussed in detail below. Major support for the motor-continuity point of view comes from Zelazo (1976,1983)who claims that his research on the effects of active exercise on reflexive stepping in newborns provides some evidence that reflexive stepping is the behavioral antecedent of voluntary walking. However, Thelen (1983)and McDonnell, Corkum, and Wilson (1989)have provided alternative explanations for Zelazo's findings and this debate will be discussed later in this article. An alternative viewpoint, termed "motor-genre theory", has been advocated by McDonnell (1979;McDonnell et al., 1989) which states that primitive reflexes are neurologically and developmentally distinct from developing voluntary motor functions. From their point of view the apparent connection derives primarily from the fact that mature motor functions gradually emerge as primitive reflexes decline giving the illusion of continuity. That is, primitive reflexes follow a course of development which is parallel but is causally independent of emerging voluntary control. Any given muscle group may take part at different times in many reflexes and in other movement patterns. All of these movements must finally funnel their impulses through the same motor system and this common part is called the final common path (Sherrington, 1947). Reflexes and other movement patterns which share a final common path may facilitate one another or may inhibit one another. For example, the stretch and extensor thrust reflexes are compatible and help support an infant against gravity. In contrast, the grasp reflex and hand placing reflex are antagonistic so that a toy is usually released when a child falls. In this sense there are important interactions between reflexes and other action patterns. In contrast, another view is that primitive reflexes interfere with emerging voluntary behaviors. Many of the earlier theorists, in fact, argued that reflexes had t o be inhibited before voluntary walking could develop (Humphrey, 1969). For example, Gesell and Amatruda (Knobloch and Pasamanick, 1974)and McGraw (1966)argued that the stepping reflex had t o be inhibited before voluntary walking could begin. In their view, anything done to strengthen a reflex might delay the development of voluntary motor

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skills. This kind of argument seems to support a continuity position since it implies direct linkages between reflexes and voluntary behaviors with superficial similarities. It also seems to imply that primitive reflexes are actively inhibited by the cortex, however, Prechtl (1981)has argued that the evidence for cortical inhibition of infantile reflexes is scant and indirect. A less sanguine interpretation might be that strong tonic and postural reflexes simply make it difficult to perform certain movements because they severely restrict body and limb positions. A motor-genre position can accept that primitive reflexes in general interfere with achievement of voluntary behaviors, however, there must be other reasons why neonates and young infants have such a limited range of voluntary movements. From our point of view primitive reflexes decline because of corticoneuromotor maturation which through myelinization a n d synaptic development favours cortical control over behaviors especially i n the pyramidal tract. I n addition, two developments are essential for the performance of many voluntary behaviors. There must be sufficient perceptual and cognitive functions t o motivate action and there must be adequate postural control. The former requirement has been described by others Won Hofsten, 1989; Zelazo, Weiss, & Leonard, 1989). The latter specification includes achievement of trunk stability (especially head and shoulder stability) and achievement of righting and equilibrium reactions. We believe primitive reflexes neither develop into voluntary behaviors nor do they automatically exclude voluntary behavior. Capute, Shapiro, Accardo, Wachtel, Ross, and Palmer (1982)compared the development of several reflexes with several voluntary behaviors. They found significant association of all reflexes with all motor actions. The clear implication is that no single reflex determines a particular motor activity a s is implied by a continuity position. Instead, their research seems to support a motor-genre position that reflexes are a distinct class of behaviors which undergo rapid developmental change in the first half of the first year and, a s such have differential effects on on-going behavior. Our view is that full-term neonates are capable of some cortically controlled limb movements and that these are enhanced by providing the infant with firm postural support. This question of the role of reflexes in motor development is important since it has a bearing on whether or not newborns are capable of successful reaching a s had been claimed, originally, by Bower, Broughton, and Moore (1970). If the motor repertoire of newborns consists exclusively of reflexes, then we should not expect them to be able to reach for visual targets. Since 1970, a number of people have investigated Bower, Broughton, and Moore's claims (Dodwell, Muir, & DiFranco, 1976; Ruff & Halton, 1978; McDonnell, 1979;and Von Hofsten, 1982). While most investigators failed to confirm the totality of their claims, neonatal reaching was observed in every study albeit with lower frequency and lower accuracy. More recently these movements have been termed "prereaching" movements (Bushnell, 1985;Von Hofsten, 1984) which clearly distinguishes them from reflexively derived movements but also from true intentional reaching.

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2. DEFINITION AND CLASSIFICATION: THE ROLE OF REFLEXES IN

MOTOR DEvEulpMENT Despite some of the controversy described above, theories of motor development have not had to be overly concerned with these issues. In general, motor reflexes have been given very cursory treatment by developmental psychologists. The term "reflex" is used very casually in many textbooks without any attempt to define, classify, or distinguish them from other forms of behavior. In addition most developmental texts leave one with a very simplistic view of motor development. The impression is that primitive reflexes characterize the first few months of life and are subsequently replaced by voluntary motor activities. There is little or no discussion of the possible connections between them. The implication is that mature behavior is not influenced by reflexes at all instead of recognizing the role of mature postural reflexes which are integral parts of mature motor behaviors. For example, maintenance of upright posture while sitting or standing requires fine control of righting and equilibrium reactions which provide corrective weight shifts as the body moves forward and backward. From our perspective, mature postural reflexes provide a behavioral background upon which voluntary behavior can be projected. A good starting point then is to review what we mean when we talk of reflexes. It is not easy to distinguish reflexes from more complex behaviors but there are several criteria. These include: (a) a relatively short latency following the onset or offset of a stimulus; (b) involvement of a single group of muscles or, at least, a specific set of muscle groups rather than the whole body; (c) they are characterized by stable, low thresholds for specific stimuli; and (d) they tend to resist habituation (Manning, 1972). Thus, infants turn their heads in response to perioral tactile stimulation and in a neurologically normal infant this response is easily elicited, short in latency, and resists habituation. Despite these criteria some researchers have used the term reflex to refer to other behavioral reactions. For example, elicitation of a headturn orienting response to sound (Muir & Clifton, 1985; Zelazo, Weiss, Randolph, Swain, & Moore, 1987)requires carefully controlled conditions and the response shows a relatively long latency and habituates quickly. Primitive reflexes are prenatal in origin and can be divided into three classes: segmental, intersegmental and suprasegmental. Segmental and intersegmental reflexes are organized in the spinal cord while suprasegmental reflexes are primarily organized in the brain stem or higher centers. Myotatic o r myogenic reflexes are segmental reflexes which respond to stimuli arising in a muscle or its antagonist. They serve to compensate for changes in external load especially when limbs are used to support the body against gravity. An example is the patellar tendon reflex. In contrast the cutaneous segmental reflexes are initiated by stimuli applied to the skin's surface. Two familiar examples are the Babinski and grasp reflexes. Examples of suprasegmental reflexes are breathing, swallowing, pupillary reactions, facial expressions, and postural reflexes (Sherrington, 1947;Peiper, 1963). Postural reflexes can in turn be divided into classes. First , there are tonic reflexes which are concerned with controlling the orientation of one body

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part in relation to another (but not in relation to gravity). The second type of postural reflexes are the righting and equilibrium reflexes which develop postnatally. These attempt to maintain the body in a constant orientation to gravity (righting reaction) o r to restore the body to an upright posture if it is lost (equilibrium reaction). An example of an early righting reaction would be the Landau reflex which develops around 3 to 4 months. Relaxation of the tonic labyrinthine prone reflex permits voluntary, perpendicular righting of the head from prone which triggers the Landau and enables the infant t o maintain a position against gravity (Capute, Wachtel, Palmer, Shapiro, & Accardo, 1982).

3. Fu"AI,ROLES OF REFLEXESIN DEVEUIPIMENT: INTHE NORMAL COURSE OF DEvELoplMENT In the normal course of development the infant begins with a number of primitive reflexes (e.g., respiration, sucking, rooting, palmar grasp, moro), mediated by different levels of the brain stem and spinal cord, and without which the infant would not be viable. Motor development is greatly influenced by the postural reflexes which are organized in the pontine, medullary, and midbrain regions. Examples would be the tonic labyrinthine and asymmetrical tonic neck reflexes. Some of these decrease in potency within a few months of birth and are effectively replaced by more complex postural reflexes which are essential preconditions for the development and maintenance of normal voluntary control. However, primitive reflexes are not the sole way to describe the motor repertoire of the neonate. There now seems to be good evidence that there are other forms of behavior which like reflexes are prenatal in origin. For example, Thelen (1983) has described innate patterns of movements which are initially organized at a brain stem level, low in frequency, and weak in amplitude, but which eventually come to characterize the response repertoire of the infant as physical strength and cortical control increase. Bushnell(1985) and Von Hofsten (1984) have labelled the directed swiping reactions of young infants when exposed to attractive stimuli as prereaching movements. McDonnell (1979) described these movements as instrumental responses to distinguish them from reflexive and voluntary movements. An example may be the hand to mouth or hand to face movements of newborns which appear to vary in location, duration, and type of stimulus control (Rochat, Blass, & Hoffmeyer, 1988). One of the sources of confusion in discussion of continuitylmotor genre theory has been the failure to distinguish the development of leg functions from arm functions. As a result of Zelazo's work, the evidence that reflexive walking is related to voluntary walking is somewhat stronger (although we do not accept this view) than the evidence for reflexive antecedents for reaching skills. Nevertheless, the notion that manual motor skills undergo a gradual transition from reflexive grasping to voluntary reaching has been a commonly held view (Fogel & Hannan, 1985; Twitchell, 1970). While it may be that the pattern of development for lower limbs is similar to the pattern of development for upper limbs, it is essential to demonstrate their similarities empirically. Therefore, Zelazo et al.'s work on the walking reflex cannot be applied t o

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reaching without considerable qualification. Although the stepping reflex has been reasonably selected as a likely antecedent of walking, no one has identified the reflexive antecedents of reaching skills. One can think of several candidates among the primitive reflexes (e.g. ATNR, palmar grasp, moro, startle, etc.) but the relationship to voluntary patterns of reaching is less obvious than the relationship of the stepping reflex to walking. Postural reflexes regulate the delicate changes of muscle tone needed t o maintain balance when body position changes or t o fix certain body parts to provide support for other moving body parts. For example, the tonic labyrinthine reflex is a primitive postural reflex which accounts for the neonate's predominantly extensor tone in supine and predominantly flexor tone in prone, which effectively prevents the newborn from raising the head off the supporting surface (Scherzer & Tscharnuter, 1982). In the pull-to-sit manoeuvre (Brazelton, 19841, as the infant's body approaches a vertical posture, extensor tone gives way to a total flexor pattern which facilitates its movements against gravity. In contrast, the dominant flexor pattern in prone prevents extension of the neck and thus prevents the infant from raising the chest (Scherzer & Tscharnuter, 1982). This limitation, in turn, prevents the infant from rolling from stomach to back until about the third month. Extension of the neck and arms is required for the infant to move from the stomach to side-lying or to supine. A month or so later, the infant achieves rolling from the back to the stomach by flexion at the neck and shoulders. In these achievements we see the weakening of the tonic lab reflex with control of extension developing earlier than flexion. Thus, infantile postural reflexes impose severe limits on the infant's opportunities t o exercise non-reflexive patterns of movement. Mature postural reflexes are clearly essential for the development of voluntary motor skills since they provide stability, a balance of extensor and flexor tone, and allow a broader range of motion. These are especially evident in development in the second half of the first year. Paillard (1986)has suggested that the emergence of postural control depends on the development of the pyramidal tract which takes place a t that time. McDonnell (1979)and McDonnell et al. (1989)proposed that reflexive behaviors and voluntary behaviors may be developing concurrently. In general, reflexive behaviors are declining while voluntary behaviors are increasing. Neurological maturation underlies both trends but the former are controlled at subcortical and brain stem levels while the latter are primarily controlled and initiated at a cortical level. Cortical inhibition of reflexes is not needed to account for development except in so far as two functional systems are competing for the same final common path. Some primitive reflexes may pre-empt available control of the final common path to the extent that other forms of movement may be precluded until neurological development weakens control by these reflexes. Clearly this position differs from one which claims that reflexes are ancestors of voluntary behaviors although the pattern of behavioral development would not necessarily appear different for either position. If an infant's movements are dominated by powerful reflexes (e.g., tonic labyrinthine reflex), voluntary behaviors are necessarily excluded. A young infant lying in supine is limited in movements by the presence of the tonic lab reflex (e.g., reaching to midline).

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9Fu”ALRO~S0FREFLExESINDEvELopMENT: DEVELOPMENTAL OUTCOME FOR ATYPICAL DEVELOPMENT Another situation of such conflict is clearly evident in the case of a n adult with cerebral palsy (a disability characterized by persistence of primitive reflexes) whose attempts a t voluntary reaching may trigger a palmar-grasp reflex preventing the hand from opening and closing on a desired object (Milani-Comparetti & Gidoni, 1967). Similarly, if an infant attempts to bring hand to mouth, uncontrolled movements of the head may elicit a reflexive pattern of movement which prevents completion of a cortically initiated movement. Greater postural control and stability would eliminate this problem. Traditionally, persistence of a reflex has been taken to signify central nervous system dysfunction (Peiper, 1963) and neurodevelopmental therapies are directed a t promoting mature postural reflexes as a way to facilitate motor development. Prechtl (1981),however, argues that there is only a superficial resemblance between infantile reflexes and pathological reflexes. Nevertheless, Prechtl would have to explain the fact that these pathological reflexes, although transformed, are characteristic of the individual with congenital neurological damage throughout development. It also must be said that primitive reflexes, although transformed, are not totally absent in the neurologically normal adult. Respiration is an example of an enduring primitive reflex while the typical pattern of yawning and stretching frequently results in the classic ATNR “fencing“posture. Although commonly thought to disappear by 6 months, recent research suggests the ATNR can be demonstrated in neurologically normal children (Zemke & Draper, 1984). 5. FROM REFLEXTO INSTRUMENTALBEHAVIOR ADEBATE

As mentioned above, Zelazo and colleagues have advocated the view that reflexes develop into instrumental behaviors (Zelazo, Zelazo, & Kolb, 1972; Zelazo, 1983). They reported that with the use of daily practice sessions the infant‘s stepping reflex (which peaks at six weeks) did not disappear as it usually does by four or five months. In fact, they found that extended practice of the stepping reflex resulted in earlier independent walking as well. Thus, it was clear that cortical inhibition was not a factor in the development of walking skills and it also seemed that the stepping reflex was indeed the behavioral ancestor of normal walking. Zelazo (1983)has argued that in addition to the benefits of regular exercise, the reflex is converted to an instrumental activity because of the infant‘s growing cognitive skills and the reinforcing effects of being upright. While we disagree that the stepping reflex is converted we do agree that growth in cognitive abilities is an essential feature in achievement of voluntary motor functions. Among neurologically impaired children, one can find many examples of children with apparently normal motor systems but who fail to develop voluntary motor functions. The reasons for their failure to walk are not known although it may well be that their cognitive deficiencies deny them curiosity about objects and places. In a

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word, they have no place t o go. This is a question which clearly needs more research. Thelen (1983)and Thelen, Fisher, and Ridley-Johnson (1984)using a dynamical approach have proposed an alternate explanation of Zelazo's work. They argue that the disappearance of the stepping reflex is a result of peripheral rather than central factors. Specifically, they argue that the infant's body mass increases faster than muscular strength. The rapid increase in weight of the legs in the first few months makes it difficult for the infants to step, especially in the upright posture. Zelazo's finding of persistence of stepping is therefore explained as an increase in muscle strength resulting from the daily practice. Thelen et al. (1984)found that the frequency of infant stepping was closely affected by infants' overall arousal level and other peripheral factors such as weight and buoyancy. They found that : (a) those infants who gained the most weight stepped less frequently, (b) when artificial weights were added to their legs stepping rates decreased and, (c) they found that stepping rate increased when the infants' legs were submerged in water. Thelen et al. (1984)conclude that stepping should not be considered a reflex at all but rather should be considered an innate pattern of movement, an automatized and stereotyped behavior controlled a t a subcortical level. This behavior will gradually come under cortical control as a function of neurological maturation at several levels including the motor cortex, the pyramidal tract, subcortical structures, and the cerebellum. This demonstration that peripheral factors such as muscle strength are important determinants of motor behavior may provide some support for a motor-genre theory. A motor-genre theory proposes that the essential features of motor development are central factors, especially the increasing cortical control of movements supported by the development of mature postural reflexes. It should therefore be possible to reveal the full extent of cortical control by carefully supporting the infant's body in such a way as to overcome the influence of reflexes and minimize the effects of gravity. Fentress (1978) has shown that providing young rodents with appropriate postural support enables a precocious display of patterned grooming and locomotor movements. Neurodevelopmental techniques developed by Bobath and Bobath (1975)for neurologically impaired children facilitate movement through the use of reflex inhibiting positions and activation of postural reactions. Indeed, Bower (1974)argued that inappropriate positioning (e.g., supine) would preclude demonstration of certain behaviors (e.g., reaching) by very young infants. Most researchers investigating reaching in neonates or young infants have arranged for the infants to be tested in upright or semi-upright positions. A young infant of 3 months in supine is more likely to show kicking than arm movements because the upper body is stabilized by the head and arms. The more stability in the upper body, the more freedom the infant will have to kick. Similarly if the same infant is held in an upright posture and must use all its muscle tone to maintain head control, there can be no possibility of arm movements in space since they would threaten that balance. In the original Zelazo studies (Zelazo, Zelazo, & Kolb, 1972)the experimental subjects received extensive experience in an upright (or semi-upright posture). None of the control subjects did. Parents of experimental subjects

The Role of Refreres in the Patterning of Limb Movements

159

"practiced walking" their infants. None of the control subjects did. Zelazo (1983) argued that the infants enjoyed the upright posture. Thelen (1983) suggested that, when tested for stepping reflexes, infants do not appear to enjoy the experience. It is quite possible that young infants do not "enjoy" the experience initially but repeated experience of this kind may become pleasurable because of the interaction with their parents and especially as their strength increases. Thus, the situation may have become one with some intrinsic pleasures and social rewards which in turn may have increased the infant's interest in pulling to standing. There is another potential confound in the research by Zelazo et al. (1972). While their research did provide a number of suitable control groups, they did not control for the extent to which their experimental subjects developed upright postural control. Their experimental subjects were the only subjects to have 8 weeks of daily experience in the upright posture (while practicing the stepping reflex). It is clearly possible that this experience led t o an enhancement of their stability in the upright position. Increases in postural control could account for the earlier onset of independent walking. A similar suggestion has been made by Forssberg (1986). Of course, additional research needs to be done to determine if this is a valid criticism. In summary, it appears that there are a t least three alternative explanations of Zelazo et al's motor-continuity demonstration. First, as Thelen pointed out there is the possibility of increased muscle strength in the legs, Second, experience in being upright is initially aversive but becomes more desirable with practice. Third, there is the possibility that their treatment enhanced postural control. There are other reasons for doubting that the stepping reflex is functionally related to normal walking. For example, if the stepping reflex is directly related to unaided walking it is not clear why it disappears for several months in normal development. In addition, despite myoelectric data provided by Forssberg showing some similarities across ages, there are very substantial differences in the qualitative appearance of the neonatal walking reflex and the appearance of walking at the end of the first year. Consider the following contrasts. In the reflex, the infant's weight is on the whole sole of the foot with the ankle in slight dorsiflexion. In the first stages of supported standing, weight bearing is on the toes. To elicit the stepping reflex, it is necessary to support the infant's upper torso in flexion whereas in supported standing the older infant attempts to maintain the center of gravity aligned over the feet. The initial gait pattern is characterized by a pronounced extension of the trunk combined with a high guard position of the arms. In the stepping reflex, the legs are fully adducted and a t times scissored. In the initial standing pattern, the infant assumes a broad-based stance with both legs in abduction and external rotation. These are readily observable and substantial differences in form. Righting and equilibrium reflexes are not easily distinguished in the adult as they tend to blend together. Every time one takes a step forward, equilibrium reactions are necessary to re-establish balance. This is done smoothly and without difficulty under normal walking conditions. In addition, righting reactions are continuously operating during locomotion in

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maintaining erect head and body posture. The broad based, high guard walking stance, and stride of the 14 month old is an example of walking without fully developed equilibrium reactions. The infant's righting reactions struggle to maintain erect posture but if it is lost by moving too rapidly or tripping, equilibrium reactions are insufficient to allow the infant to regain control. Thus, from a qualitative viewpoint the components of the stepping reflex and the initial phases of standing and walking are quite dissimilar. In our view, then, the form and substance of voluntary walking seen at 12 months is more likely a direct result of achievement of postural control and cognitive growth than the developments of the stepping reflex pattern. The importance of Zelazo's work, then, might be that it is a clear demonstration that experience in the upright posture facilitates achievement of voluntary walking and it raises the question as to whether or not similar treatments would be effective for infants at risk for cerebral palsy (Zelazo et al., 1989). It seems that experience in the upright posture may stimulate protective extension, righting, equilibrium, and postural control which should facilitate independent movement but it is unlikely that it results from persistence of primitive reflexes.

6.NEW DIRECI'IONS FOR REFLEXTHEORY IN DEVELOPMENTAL

RESEARCH

In summary, we have argued that there is little evidence to support a motor-continuity position. A motor-genre position recognizes that there can be qualitatively different forms of innate movement systems not all of which neatly fit accepted formulations for reflexes. They also are not in any sense purposive. It is probable that they provide kinesthetic and proprioceptive information for orientation. In addition, we have argued that developmental researchers need to examine, more critically, the role played by mature postural reflexes in the establishment of voluntary motor functions. The first requirement for achievement of voluntary motor activity is stability of the trunk, the head, and the shoulders. The second requirement is the development of cognitive abilities which provide the motivational bases of movements. Determining the origin and developmental course of cortically controlled (purposive) movements is a major enterprise which cannot be settled in a few papers. Despite the excellent descriptive accounts of the 30's and ~ O ' S ,even more detailed accounts of developing motor skills in the first six months of life will be of value. We have attempted to show in the above review that there are important interactions between reflex systems and other action systems in this age range. Since reflexes are such a prominent part of the response repertoire of the neonate, developmental researchers need to include them as dependent measures. We have found it difficult to find any adequate review of tests of reflexes and early motor behavior in the literature. Consequently, in the last section of this chapter, we have provided a short review of current methods for assessing and quantifying primitive reflexes in young infants.

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7.THE ASSESSMENT OF 7.1 Purpose

Assessment of reflexes in the neonate affords us our very first opportunity to evaluate fully the maturation and functional integrity of the developing nervous system (Prechtl, 1982). Of primary focus is the localization of central nervous system (CNS) abnormality and an evaluation of the integrity of peripheral nerves (Taft & Cohen, 1967). Initial assessment identifies infants who require immediate interventions as well as those who may be a t risk for future complications. Charting reflex development through the infancy period permits areas of neurological involvement to be more accurately documented, the effectiveness of therapeutic interventions to be evaluated, and the likelihood of future developmental problems to be predicted.

7.2 TypesofReflexTests There are a large number of infant assessment devices available that permit the evaluation of reflexes. However, these tests differ greatly in both scope and focus due in large part to the professional orientation of the originators and, consequently, the purpose for which the tests were constructed (Self & Horowitz, 1979). Two main groups exist. By far the majority of reflex assessments are medical in nature and have been created for the purpose of assessing the neurological integrity of the infant. A subset of these tests includes the screening devices designed to identify those infants who have suffered some degree of neurological damage. The other subset of medical tests is comprised of more comprehensive neurological examinations designed to assess fully the functioning of the developing nervous system. These tests go beyond the normaVabnorma1 classification to detail areas of dysfunction and often provide a specific diagnosis. The second body of tests to incorporate evaluation of infant reflexes is more psychological in nature. These tests are designed to document the behavioral and interactive style as well as the sensory capabilities of the infant. Unlike the medical tests, their aim is to uncover the uniqueness or individuality of the infant while they serve only a secondary purpose of screening for neurological dysfunction (St. Clair, 1978). The remainder of this section is devoted to providing an overview of the tests currently available for assessment of infant reflexes. The tests have been divided into three categories based upon their nature and purpose: Comprehensive Neurological Examinations, Neuromotor Screening Tests, and Behavioral Tests. Only one test of each type will be fully reviewed although titles, age ranges, and sources are provided for all tests. The tests chosen for review were selected simply to be representative of their categories. In addition, the motor reflexes and the observed and elicited motor behaviors assessed by each test are listed in Table 1.

x

w

x

w

x x

x

Brazelton (NBAS)

Graham/Rosenbl it h

Gesell

Bayley

Nickel et al. (IMS)

Neuromotor screening

x

Kliewer et al. (MC) x

Amiel-Tison et al. (NACS)

Wilson

Capute et al. (PRP)

Prechtl (screening exam)

Parmelee

Fiorentino

Dubowitz & Dubowitz (NAPI)

Chandler et al. (MAI)

Saint-Anne Dargassies

x

x

x

Prechtl

Amiel-Tison

Neurological examination

x

x

x x

x x

56

x x x x

x

we

;;f

Test item

x

ankle clonus ankle jerk asymmetrical tonic neck reflex Babinski reflex balance/equilibrium Bauer's response c3

Table 1

Motor reflexes and motor behaviors assessed by each test. Test type Behavioral test

X

x

x

x

x x x

x

w

wxw

x

x x

w w w

w

x x

w

x

x

x

w

x

x x w

x

x

x

X

xw

X

x

x

x

w w

x

w

wx

W X H

x

x

w x

x x

x w x x x

w

w

w

x x

x

x w x

x

w

x x

w

x

wwx

wxw

x

w

biceps reflex body angle adductors dorsiflexion of foot popliteal square window crossed extension reaction defensive reaction definitive walking Galant's reflex heel jerk knee jerk Landau reflex lateral propping reaction magnet response Moro reflex movements athetoid clonic crawling creeping defensive power of active range recoil (arms & legs) resistance to passive spontaneous tremor muscle tone arms and legs head and neck consistency (symmetry) extensibility passivity

Table 1 R n

P

W m Q) m

9

Motor reflexes and motor behaviors assessed by each test.

Test type

5-

s

.-a,

4-

.-

a

8

c1 m

.!-I

2

Test item

muscle tone trunk palmar grasp parachute placing response plantar grasp

E

C

c

cd

x x

x x X

x x

x x

?!

a

X X

C

C

L

x

4-

-0

a

x

.-

a, -

0 0

x x

0 C

L

a a

I

z

a

a,

5 .-

a

a,

a P a n C

0

X

v) v)

0

Behavioral test

h

v)

z

Neuromotor screening

'cd5

m8



%$Neurological examination

0 .lL

x

X X

a,

a c

a, a, c

3 Q

([I

0

a

0

4-

.-

0

Ia,

z

a

x

x

C

-

L v)

L

a, v)

0

a,

X X

%

-a,

%

E

a m

x x X

X

m

z

a C 0 c - E a a, r a N \

u) .-

x x

za

v)

m sf 0 m I

X

X X X

postures asymmetrical athetoid global straightening opisthotonic prone prone suspension resting sitting standing supine supine suspension vertical suspension precipitation reflex prehension pull to sitting reflex irritability righting reaction rolling response scarf sign staggering reaction startle reaction stepping movements symmetrical tonic neck reflex supporting reaction tilting reaction tonic fingerhe flexion tonic labyrinthine reflex traction response withdrawal reflex

x

x x

x x

x

x x x x x

x x x

x x

x

x

X X

x x

x

X

X

X

X

x x x

X

x

x x

x

X

x

x

X

x

x x

x

X

X X

x x

x

x

x X

X

x x

x x

X

X

X

X

X

x

X

X

x

x

X

x

x x

x x

x

x

x

X

x

X X

x

x

X

X

X

x X

X

x

x

x

X X

x

X

x x

X X

X

X

X X

x

X

X

x x x x

x

x x

x x

x

x

X

X

X

x

x

X

X

x

x x

x

X X

x

x x

X

X

X

x x

x

x x

x

X

X

166

P.M. McDonneN and KL. Corkum

72.1 ComprehensiveNemlogical Examhatiom

The Neurological Examination of the Full Term Newborn Infant (Prechtl, 1977) Purpose. To assess the integrity of the central nervous system. Age range. Full-term infants who are 38-42 weeks gestational age (GA) and preterms who have reached this GA. Test administration. The test requires approximately 40-60 minutes to administer. Examiners require extensive experience for administration and interpretation of the examination. The test is comprised of two parts: observation and examination. Specific guidelines are provided in the manual with respect to the following examination parameters: behavioral state of the infant, postprandial time, body posture, light, and temperature of the test environment, intensity of the stimulations, and handling of the infant. Photographs and descriptions of the manipulations necessary for each test item are provided. Scoring. A variety of techniques are employed for scoring. Some test items require written descriptions of infant behavior or sketches of body positions. Others involve rating infant behavior on a 4-point scale which typifies responses as: absent (-1, weak (+), medium (++I, or exaggerated(+++). A section is provided for overall summary and appraisal of the infant. Diagnoses of the presence of hemisyndrome or any of three syndromes of reactivity (hyperexcitable, apathetic, and comatose) is possible. In addition, description of results in terms of optimalityhonoptimality is suggested although no guidelines are provided. Standardization. Standardization of the original examination (Prechtl & Beintema, 1964)was conducted on 1500 children with a history of obstetrical

complications. Possible responses and their developmental significance are noted with respect to each test item.

Reliability. No reliability data is provided for the most recent version of this examination (Prechtl, 1977). However, Prechtl(1963) reported inter-rater reliability for the original version (Prechtl & Beintema, 1964) to be between r = .80and r = .96. Test-retest reliability was assessed by Beintema (1968) in a series of examinations conducted with the same 49 infants over the first 9 days of life. Correlations for 20 items administered on Days 1 and 2 were significant at p < .001 while correlations for an additional 6 items were significant at p < .05. However, in correlating scores from Days 1and 9 only 9 items were significant at p < .01 while 6 more were significant at p < .05. Validity. Bierman-van Eendenberg, Jurgens-van der Zee, Olinga, Huisjes, and Touwen (1981) assessed predictive validity of the Neurological

The Role of Reflexes in the Patterning of Limb Movements

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Examination of the Full Term Newborn Infant by re-examining at 18 months a group of infants who were found to be neurologically abnormal at term. Of the 79 infants re-assessed via Touwen's (1976) procedure 13 retained an abnormal classification while the other 66 were normal. Of the 80 infants in the control group at 18 months only 2 showed signs of neurological abnormality. Although the difference between experimental and control groups was significant at p c.01, the high rate of false positives generated should be noted. Other comprehensive neurological examinations currently available include: the Neurologic Evaluation of the Newborn and the Infant (AmielTison, 1973), The Neurological Examination of the Infant (Saint-Anne Dargassies, 19771, the Movement Assessment of Infants (MAI) (Chandler, Andrews, & Swanson, 1980), and The Neurological Assessment of the Preterm and Full-Term Newborn Infant (NAP0 (Dubowitz and Dubowitz, 1981). All of these tests are appropriate for assessment during the neonatal period; birth (38-42 weeks GA) to 4 weeks. In addition, with the exception of the N M I , they are also capable of evaluating infants up to 12 months of age. 7.2.2 NeummotorScreening Tests

Infant Motor Screen (ZMS) (Nickel, Renken, & Gallenstein, 1989) Purpose, To evaluate the quality of infant motor patterns and to identify those infants in need of a comprehensive neuromotor examination. The IMS is adapted in part from the Milani-Comparetti Motor Development Screening Test (Pearson, 1975) and the Movement Assessment of Infants (Chandler et al., 1980). Age range. 44 to 56 weeks GA. Test administration. The test requires approximately 5-10 minutes to administer. No specific guidelines for examiner background or preparation are provided. However, the IMS was designed to be easily and reliably employed by such health professionals as nurses, physical, and occupational therapists, and physicians, Test items are administered in a standard sequence but no specifics are provided with respect to standardization of other aspects of the administration. The score form contains sketches and brief descriptions of possible responses to each test item and the corresponding score. Scoring. Each test item is scored on a 3-point scale that typifies responses as: absent (01,intermediate (11, or complete/obligatory (2). An overall diagnosis of normal, questionable, or abnormal is obtained by totalling individual item scores.

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P.M. McDonnell and KL. Corkzm

Standardization. Nickel et al. (1989) tested 134 infants with the IMS:111 at 4-month, 58 a t 8-month, 35 a t both ages. Infants were admitted to the study on the basis of having received Neonatal intensive care services and having been judged "at risk' by one o r more biological or social criteria. All infants were followed up a t approximately 12 months corrected age. Reliability. Nickel et al. (1989) reported inter-rater reliability for evaluation of 44 infants with either the 4-month or 8-month IMS. When administered by pediatriciadphysical therapist examiners, item agreement ranged from r = .84 to r = .90 while overall test rating agreement was r = 1.00. When administered by pediatriciadnurse examiners, item agreement ranged from r = .81 to r = .87 while overall test rating agreement ranged from r = .91 to r = .93. Validity. Nickel et al. (1989) reported predictive validity of the 4-month IMS for cerebral palsy in terms of sensitivity (co-positivity, r = .93) and in terms of specificity (co-negativity, r = .as). Comparable values for the 8-month IMS were: sensitivity (r = 1) and specificity (r = .96). Other neuromotor screening tests currently available include: the Fiorentino Reflex Test (Fiorentino, 19701, the Newborn Neurological Examination (Parmelee, 1974 cited in Self & Horowitz, 19791, the Neurological Screening Examination of the Newborn Infant (Prechtl, 19771, the Primitive Reflex Profile (PRP) (Capute, Accardo, Vining, Rubenstein, & Harryman, 1978), the Developmental Reflex Test (Wilson, 19781, the Neurologic and Adaptive Capacity Scoring System (NACS) (Amiel-Tison, Barrier, Shnider, Levinson, Hughes, & Stefani, 19821, and the Milani-Comparetti Motor Development Screening Test (MC) (Kliewer, Brucek, & Trembath, 1987). Only the MC, the PRP, and the Fiorentino Reflex Test have been designed to assess infants from birth (38-42 weeks, GA) to 2 years (CAI. The remainder are appropriate for assessment strictly during the neonatal period. '72.3 BehavioralTests

Neonatal Behavioral Assessment Scale (Brazelton, 1984) Purpose. The primary purpose of the NBAS is to evaluate the coping and adaptive capacities of the infant in an interactional context. A secondary purpose is the screening for neurological abnormality. Age range. Full term infants from 38 to 44 weeks GA and healthy preterms who have reached this GA. Test Administration. The test requires approximately 20-30 minutes to administer. Background knowledge of child development and experience working with neonates as well as extensive training in administration and scoring of the NBAS is required for test scores to be considered meaningful. The exam consists of an observation period, a set of reflexive/elicited items

The Role of Reflexes in the Patterning of Limb Movements

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designed to screen for neurological abnormality, and a set of behavioral items. Very specific guidelines (including photographs) are provided in the manual regarding: the behavioral state of the infant, the proper procedure for handling the infant and for administering each test item, the conditions of the test environment, and the procedures to be employed to comfort the infant should helshe become upset during testing. The aim of capturing the infant's best rather than average performance on all items is also stressed.

Scoring. Elicited behaviors and reflexes are scored on a 4-point scale typifying responses as absent (01, or of low (l),medium (2), or high (3) intensity. Behavioral items are scored on a detailed 9-point scale. Guidelines for employing this scale are specific to each test item and are outlined in the manual. However, the midpoint of the scale represents the expected behavior of a normal 3-day old infant. A scheme for grouping items into meaningful clusters (i.e. habituation, orientation, motor performance range, autonomic regulation, and reflexes) is provided. S t a n d a r d i z a t i o n . To date, the NBAS has not been formally standardized. However, it is commonly used in clinical settings as well as in a wide variety of research. Francis, Self, and Horowitz (1987) report that normative data are currently being collected by Horowitz and her colleagues. Reliability. Using agreement within 1-point a s criteria for percentage agreement, Als, Tronick, Lester, and Brazelton (1979) reported interrater reliabilities of greater than or equal to 90%. However, test-retest reliability of the NBAS has been found to be moderate to poor. In a sample of 104 infants, Horowitz, Sullivan, and Linn (1978) found Pearson correlations for repeated examinations ranging from r = .20 to r = .50. However, in correlating Day 2 and Day 3 item scores for a group of 35 infants, Sameroff, Krafchuk, and Bakow (1978) failed to find significant test-retest reliability for nearly half of the NBAS items. Further, Kaye (1978) failed to find any significant correlations between factor scores for NBAS examinations on Days 2 and 15. However, Lester (1984) suggests that employing a traditional Pearson r statistic may not be the best way to evaluate the test-retest reliability of the NBAS. Instead, he suggests that a n "individual stability measure" (p. 86-87) may be more reflective of true NBAS scale stability. Validity. Lester (1984) evaluated 20 term and 20 preterm infants a t 40, 42, and 44 weeks gestational age with the NBAS and a t 18 months with the Bayley Developmental Scales. Bayley mental and motor scale scores were predicted from four NBAS cluster scores yielding multiple correlations ranging from RZ = .42, p < .05 to Rz = .63, p < .01. Other behavioral tests currently available include: the Bayley Scales of Infant Development (Bayley, 1969) which are designed to assess children from 4 weeks to 30 months (CA), the Gesell Developmental Schedules (Knobloch & Pasamanick, 1974) which are appropriate for children from 4 weeks to 36 months (CA), and the Graham IRosenblith Scales (Rosenblith, 1975) which are designed for neonatal assessment only.

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References Als, H., Tronick, E., Lester, B. M.,e.g., Brazelton, T. B. (1979). Specific neonatal measures: The Brazelton neonatal behavioral assessment scale In J. Osofsky (Ed.), Handbook of infant development (pp. 185-215).New York: Wiley. Amiel-Tison, C. (1973). A method for neurologic evaluation within the first year of life. Current Problems in Pediatrics, 7 , 3-50. Amiel-Tison, C., Barrier, G., Shnider, S., Levinson, G., Hughes, S. C., & Stefani, S. J. (1982). A new neurologic,adaptive capacity scoring system for evaluating obstetric medications in full-term newborns. Anesthesiology, 56,340-350. Bayley, N. (1969). Manual for the Bayley scales of infant development. New York: Psychological Corporation. Beintema, D. (1968). A neurological study of newborn infants. London: National Spastics Society. Bierman-van Eendenberg, M. E. C., Jurgens-van dor Zee, A. D., Olinga, A. A., Huisjes, H. H., & Touwen, B. C. L. (1981). Predictive value of neonatal neurological examination: A follow-up study a t 18 months. Developmental Medicine and Child Neurology, 23,296-305. Bobath, B., & Bobath, K. (1975).Motor development in the different types of cerebral palsy. London: Heinemann. Bower, T. G. R., Broughton, J., & Moore, M. (1970). Demonstration of intention in the reaching behavior of neonate humans. Nature, 228, 679-681. Bower, T. G.R. (1974).Development in infancy. San Francisco: Freeman. Brazelton, T. B. (1984).Neonatal behavioral assessment scale. Philidelphia: Lippincott. Bushnell, E. (1985). The decline of visually guided reaching during infancy. Infant Behavior and Development, 8,139-155. Capute, A. J., Accardo, P. J., Vining, E. P. G., Rubenstein, J., & Harryman, S. (1978).Primitive reflex profile. Baltimore: University Park Press. Capute, A., Shapiro, R., Accardo, P., Wachtel, R., Ross, A., & Palmer, F. (1982). Motor functions: associated primitive reflex profiles. Developmental Medicine and Child Neurology, 24,662-669. Capute, A., Wachtel, R., Palmer, F., Shapiro, R., & Accardo, P. (1982). A prospective study of three postural reactions. Developmental and Child Neurology, 24,314-320. Chandler, L. S., Andrews, M. S., & Swanson, M. W. (1980). Movement assessment of infants: A manual. Rolling Bay: Infant Movement Research. Dodwell, P., Muir, D., & DiFranco, D. (1976).Responses of infants to visually presented objects. Science, 194,209-211. Dubowitz, L., & Dubowitz, V. (1981). The neurological assessment of the preterm and full-term newborn infant. London: National Spastics Society. Easton, T. (1972). On the normal use of reflexes. American Scientist, 60, 591-599.

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Fentress, J. C. (1978). Mus muscius: The developmental orchestration of selected movement patterns in mice. In G. M. Burghardt & M. Bekov (Eds.1, The clevelopment of behavior: Comparative and evolutionary aspects (pp.161-178).NewYork: Garland Press. Fiorentino, M. R. (1970). Reflex testing methods for evaluating CNS development. Springfield: Charles Thomas. Fogel, A., & Hannan, T. E. (1985). Manual actions of nine- to fifteen-week-old human infants during face-to-face interaction with their mothers. Child Development, 56,1271-1279. Forssberg, H. (1986). Development and integration of human locomotor functions. In M. E. Goldberger, A. Gorio, & M. Murray (Eds.), Development and plasticity of the mammalian spinal cord (Vo1.3) (pp.545-552). Padova: Liviana Press. Francis, P. L., Self, P. A., & Horowitz, F. D. (1987). The behavioral assessment of the neonate: An overview. In J. Osofsky (Ed.), Handbook of infant development (2nd ed.,pp. 723-7791, New York: Wiley. Horowitz, F. D., Sullivan, J. W., & Linn, P. (1978). Stability and instability in the newborn infant: The quest for elusive threads. Monographs of the Society for Research in Child Development, 43(5-6), 29-45. Humphrey, T. (1969). Postnatal repetition of human prenatal activity sequences with some suggestions of their neuroanatomical basis. In R. J. Robinson (Ed.),Brain and early behavior (pp.126-157). New York Academic Press. Kaye, K. (1978). Discriminating among normal infants by multivariate analysis of Brazelton scores: Lumping and smoothing. Monographs of the Society for Research in Child Development, 43(5-6), 60-80. Kliewer, D., Brucek, W., & Trembath, J. (1987). The Milani-Comparetti motor development screening test. Omaha,NB: Meyer Children's Rehabilitation Institute. Knobloch, H., & Pasamanick, B. (Eds.) (1974). &sell, & Amatruda's developmental diagnosis: the evaluation of normal and abnormal neuropsychologic development in infancy and early childhood (3rd. ed.). New York: Harper & Row. Lester, B. M. (1984). Data analysis and prediction. In T. B. Brazelton, Neonatal behavioral assessment scale (pp. 85-96). Philadelphia: Lippincott. Manning, E. (1972). An introduction to animal behavior. London: William Clowes. McDonnell, P. M. (1979). Patterns of eye-hand coordination in the first year of life. Canadian Journal of Psychology, 33,253-267. McDonnell, P., Corkum, V., & Wilson, L. (1989). Patterns of movement in the first 6 months of life: New directions. Canadian Journal of Psychology, 43, 320-339. McGraw, M. (1966). The neuromuscular maturation of the human infant. New York: Hafner. Milani-Comparetti, A., & Gidoni, E. (1967). Routine developmental examination in normal and retarded children. Developmental Medicine and Child Neurology, 9,631-638.

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Muir, D., & Clifton, R. (1985). Infant's orientation to the location of sound sources. In G. Gottlieb & N. Krasnegor (Eds.), Measurement of audition and vision in the first year of postnatal life: a methodological review (pp.171-194). New Jersey: Ablex. Nickel, R. E., Renken, C. A., & Gallenstein, J. S. (1989). The infant motor screen. Developmental Medicine and Child Neurology, 31, 35-42. Paillard, J. (1986). Development and acquisition of motor skills: A challenging prospect for neuroscience. In M. G.Wade & H. T.Whiting (Eds.), Motor development in children: Aspects of coordination and control (pp.83-106). Holland: Marinus Nijhoff. Pearson, P. H. (1975). A manual of the Milani-Comparetti testing procedures. Omaha,NB: University of Nebraska Medical Center. Peiper, A. (1963). Cerebral function in infancy and childhood. New York: Consultants Bureau. Piaget, J. (1952). The origin of intelligence in children (2nd ed). New York: International Universities Press. Prechtl, H. F. R. (1963). The mother-child interaction in babies with minimal brain damage (A follow-up study). In B. M. FOBS (Ed.), Determinants of infant behavior II (pp.53-66). New York Wiley. Prechtl, H. F. R. (1977). The neurological examination of the full term newborn infant. London: National Spastics Society. Prechtl, H. F. R. (1981). The study of neural development as a perspective of clinical problems. In K. J. Connolly, & H. F. R. Prechtl (Eds.), Maturation and development: Biological and psychological perspectives (pp. 198-215) London: National Spastics Society. Prechtl, H. F. R. (1982). Assessment methods for the newborn infant: A critical evaluation. In P. Stratton (Ed.), Psychobiology of the human newborn (pp. 21-52). New York Wiley. Prechtl, H. F. R., & Beintema, D. (1964). The neurological examination of the full term newborn infant. London: National Spastics Society. Rochat, P. Blass, E., & Hoffmeyer, L. (1988). Oropharyngeal control of hand-mouth coordination in newborn infants. Developmental Psychology, 24,459-463. Ruff, H., & Halton, A. (1978). IS there directed reaching in the human neonate? Developmental Psychology, 14,425-426. Rosenblith, J. F. (1975). Prognostic value of neonatal behavioral tests. In B.Z. Friedlander, G.M. Sterritt, & G.E. Kirk (Eds.), Exceptional infant: Vol. 3. Assessment and intervention (pp. 157-172). New York: Brunner/Mazel. Saint-Anne Dargassies, S. (1977). Neurological development in the full-term and premature neonate. New York ElsevierhJorth Holland. Sameroff, A. J., Krafchuk, E. E., & Bakow, H. S. (1978). Issues in grouping items from the Neonatal Behavioral Assessment Scale. Monographs of the Society for Research in Child Development, 43(5-6), (Serial no. 177). Schemer, A., & Tscharnuter, I. (1982). Early diagnosis and therapy in cerebral palsy. New York: Marcel Dekker. Self, P. A., & Horowitz, F. D. (1979). The behavioral assessment of the neonate: An overview. In J. Osofsky (Ed.), Handbook of infant development (pp. 126-164). New York Wiley.

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Sheppard, J.J., & Mysak, E.D. (1984). Ontogeny of infantile oral reflexes and emerging chewing. Child Development, 55, 831-843. Sherrington, C. (1947). The integrative action of the nervous system. New Haven: Yale University Press. St. Clair, K. L. (1978). Neonatal assessment procedures: A historical review. Child Development, 49,280-292. Taft, L. T., & Cohen, H. J. (1967). Neonatal and infant reflexology. In J. Hellmuth (Ed.), Exceptional infant:Vol. 1. The normal infant (pp. 79-120). New York: Brunnerhlazel. Thelen, E. (1983). Learning to walk is still an "old' problem: A reply to Zelazo (1983). Journal of Motor Behavior, 15, 139-161. Thelen, E., Fisher, D., & Ridley-Johnson, R. (1984). The relationship between physical growth and a newborn reflex. Infant Behavior and Development, 7, 479-493. Touwen, B. C. L. (1976). Neurological development in infancy. London: National Spastics Society. Twitchell, T. (1970). Reflex mechanisms and the development of prehension. In K. Connolly (Ed.), Mechanisms of motor skill development (pp.25-60). New York:Academic Press. Von Hofsten, C. (1982). Eye-hand coordination in the newborn. Developmental Psychology, 18,450-461. Von Hofsten, C. (1984). Developmental changes in the organization of pre-reaching movements. Developmental Psychology, 20, 378-388. Von Hofsten, C. (1989). Motor development as the development of systems: Comments on the special section. Developmental Psychology, 25, 950-953. Wilson, J. (1978). A developmental reflex test. In S . G. Vulpe, E. I. Rollins, & J. Wilson (Eds.), Vulpe assessment battery (pp. 342-358). Toronto: National Institute on Mental Retardation. Zelazo, P. R. (1976). From reflexive to instrumental behavior. In L.P. Lipsitt Ed.), Developmental psychobiology: The significance of infancy (pp.87-iO8). New York: Wilev. Zelazo, P. R. (1983j. The development of walking: New findings and old assumptions. Journal of Motor Behavior, 15, 99-137. Zelazo, P., Zelazo, N., & Kolb, S. (1972). Walking in the newborn. Science, 176, 314315. Zelazo, P., Weiss, M., & Leonard, E. (1989). The development of unaided walking: The acquisition of higher order control. In P. Zelazo & R. Barr (Eds.),Challengesto developmental paradigms (pp.1-43). Hillsdale, N J L. Erlbaum Associates. Zelazo, P., Weiss, M., Randolph, M., Swain, I., & Moore, D. (1987). The effects of delay on neonatal retention of habituated headturning. Infant Behavior and Development, 10,417-434. Zemke, R., & Draper, D. (1984). Notes on measurement of the magnitude of the asymmetrical tonic neck reflex response in normal preschool children. Journal of Motor Behavior, 16,336-343.

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The Development of Thin Control and Temporal Or anization in &ordinated Action J. Fagard anfP.H. Wolff (Editors) CP Elsevier Science Publishers B.V., 1991

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D e v e l o p m e n t of I n f a n t M a n u a l Skills: M o t o r Programs, S c h e m a t a , or Dynamic Systems?l George F. Michel Psychology Department, De Paul University Chicago, IL 60614

The hands are used in an enormous range of actions involving feedin , locomotion, body maintenance (cleaning, soothing and protection!, communication, p a , social cohesion, and emotional regulation. However, in the contexts of b o d evolution and civilization, the manipulation of inedible environmental objects is the most im ortant use of the hands. Most human characteristics depend, directly or in irectly, on the manual skills needed to use implements and construct tools (Parker, 1974). Effective manual action in these skills requires refined control of the shoulder, elbow, wrist and finger joints a s well as specific postural adjustment of the trunk and legs. Indeed, failure to achieve the appropriate postural “set”can preclude the expression of a manual skill (Fentress, 1987). The execution of manual actions has a special priority in the organization of central nervous system activity, co-opting a diverse set of neuroanatomical structures that are involved in a wide range of functions (Goodwin & Darian-Smith, 1985). Prehension is arguably t h e most fundamental of manual skills (Napier, 1956). Prehensile movements involve the successful seizure of a n object and its secure retention within the com ass of the hand. The a r m maneuvers the hand to the position of the object so t at grasping may occur. Once securely grasped, the object ma be manipulated in a variety of ways, constrained by the pattern of the grasp (Jlliott & Connolly, 1984). Reaching and grasping are prehensile skills established during infancy and serve as the basis for most of the infant’s manipulatory actions. Intelligent behavior almost always involves acts of prehension and manipulation (e.g., searching for hidden objects, usin tools). Accordingly, processes involved in the acquisition of various manua skills during infancy may serve t o either facilitate or constrain cognitive development, and manual skill is often used as a means of assessing the co nitive ability of infants (e.g., Uzgiris & Hunt, 1976). For these reasons, an for the insight it provides about the functional development of the nervous system, psychologists have been interested in describing and explaining the development of prehensile and manipulatory skill during infancy.

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Preparation of this chapter was supported in part by NICBliD grant number 5R01 HD22399. I would like to thank Celia L. Moore for colments on earlier versions.

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A prehensile skill depends upon central neural networks f o r its regulation and precise timing and for its integration with manipulation and tactile exploration. These networks a r e qualitatively different from those involved in postural maintenance and locomotion (Phillips & Porter, 1977; Smith, Frysinger, & Bourbonnais, 1983). Manipulatory actions often involve movement of the object within the hand itself, achieved by the temporal and spatial coordination of the actions of the digits (Elliott & Connolly, 1984). The control of the isometric and dynamic forces of arm, wrist, and finger muscles durin gras ing and ob'ect manipulation also depend on neural mechanisms that fiffer from those !or posture and locomotion (cf., Goodwin & DarianSmith, 1985). Since prehension and manipulation involve neural mechanisms that are quite different from those involved with locomotion and posture, investigation of the development of locomotion and posture (common foci of infant behavioral research) will provide little information of relevance to understanding the development of prehension and mani ulation. Traditionally, there have been two accounts of t e development of the infant manual skills: maturational and cognitive. Both cognitive and maturational accounts assume that the manifestation of each pattern of skill represents the availability of specific rules (programs, schemas, etc.) f o r the actions. That is, a representational system (symbolic o r otherwise) is assumed to specify the kinematic details of a movement se uence and the nature of that system is discerned from the invariant aspects of t e sequence. The specifics of these invariant aspects are embodied in motor program theory and schemata theory and will be presented later. In contrast to the maturational and cognitive accounts, recent investigations of adult manual skill have emphasized a d namic systems perspective. This perspective im lies that musculoskeleta variables a r e constrained to function as units o!'action called "synergies" or "coordinative structures" which are sensitive to the environmental context, especially in the form of task constraints (Kelso, Holt, Kugler, & Turvey, 1980). According to this perspective, manual skills and other manifest action categories a r e emergent properties of the ways in which response dynamics are channelled by organismic (neuroanatomical, biomechanical, etc.), environmental, and task constraints. Rather than reflecting some representational system, the patterning of any action reflects a region of stability for coordination, according to the nature of the organismic, environmental, and task constraints. Althou h the otential range of patterns for any given skill may be very large, only a ew wil be manifested because the various constraints limit the regions in which action will be stable. The motor program, cognitive schema, and dynamic systems perspectives each seek evidence of invariant features in the execution of a n action. However, only the dynamic systems perspective seems to account for the immediate coordination of new movement forms as a function of changes in constraints to action (Jordan, 1990). Yet, dynamic systems theory seems to require a fundamental reorganization of the study of the development of manual skill, especially during infancy. This chapter will compare the motor program, cognitive schema, and dynamic systems erspectives for the acquisition of manual skill. Then, the characteristics o! manual skill and its development during infancy will be described. Finally, an attempt will be made to provide a developmental account of infant manual skill which integrates the three perspectives.

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Motor Programs, S c h e m a s a n d Dynamic Systems As originally conceived, a motor program was a movement-specific, temporally structured collection of parameter values (force, velocity, duration, muscle sequencing) that, when transmitted directly to the motor system, would initiate and carry through a specific action (Keele, 1968; Adams, 1971). Motor programs were capable of explaining both the coordination inherent i n speciestypical, evolutionarily adaptive, behavior patterns and the coordination of skills acquired with the practice of complex movements. In unskilled performance, corrective processes (usually visual feedback) operate continuously and make the performance slower, jerkier, and temporally less structured (Pew, 1966). The unskilled performer makes part of the overall movement (a submovement), evaluates the result, makes another submovement, reevaluates, etc. The movement becomes skilled when the submovements are coordinated with one another and seem to anticipate or coincide with the events i n the environment. Because the time between submovements i n a skilled action is often less than the time it would take to rocess feedback and initiate new commands, the submovements making up the Full movement are inferred to have been stored as a program. This allows the submovements to be se uenced and executed without stimulus-response chaining or the extensive Ieedback processing required during the unskilled., acquisition phase of performance. Once a motor program has been acquired and stored, skilled performance depends on the retrieval of the appropriate program via environmental or internal elicitors. Of course, it is not clear whether the different versions of the action, manifest during practice, are stored separately or over written by subsequent versions. Recently, motor programs have been characterized as collections of eneralized instructions representing not one, but a class of related movements Schmidt, 1985). Before being transmitted to the muscles, certain movement parameters contained in the generalized instructions a r e replaced by specific values appro riate for the particular movement to be made (Bernstein, 1967; Schmidt, 197P). In this manner, generalized motor program theory explains how novel variants of previously learned movements are produced by changing the value of variables in the program, thereby providing direct transfer of learning and obviating the need for a new program each time a new element is introduced within a class of "similar" movements. Both motor program and generalized motor program theory make a conceptual distinction between actions (sequences of movements) and elementary movements which also involve sequential action of a variety of muscles over time. It is not clear that the same principles of sequencing always apply to both levels. At the level of action it may be appropriate t o talk of motor programs whereas at the level of movement, other concepts (e.g., massspring systems) may better explain t h e sequence (trajectory) of the movement over time. Interestingly, examination of the development of manual skills during infancy often focuses o n movements (e.g., reaching) rather than actions (e.g., reach-grasp-examine-discard). However, the well studied phenomenon of infant prehension (reach and grasp) may be an action appropriate for the concept of programming. In order to describe a motor program, invariances i n t h e kinematic data must be identified across a variety of conditions (Hollerbach, 1990; Schmidt, 1985). Kinematic data a r e t h e geometry of motion. Thus, for reaching, the position of the objects i n space (goal object and potential obstacles) and the osition of the hand need to be specified so that the geometric transformations getween the hand and object can be made. Those aspects of the transformation

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that remain invariant across different movement speeds, different loads (weights) to the hand, different target positions, etc. identify a motor program. If a set of lanning variables and coordination strategies can be provided which describe t e movement across all of these conditions, it is usually interpreted that the motor control system uses these variables to plan the movement. Coordinates f o r the positions of the hand, objects and the angles of the joints of the arm are the kinematic variables reflecting movement. However, to make limbs move, muscles must exert torque about joints. This is the dynamics of movement. Motor programs include variables for muscle activation to create force at joints. However, there is a complex interaction of forces in moving a joint. These forces include inertia, reaction tor ues (e.g., elbow flexion induces shoulder acceleration), gravity torques, corio is torques, etc. Somehow, the rogram must allow for such interaction. Moreover, some of the invariant Features of the kinematics of the movement will be the byproduct of the dvnamics of the movement. Therefore. thev need not be suecified in the piogram and would easily fit the dynamicsystims perspective (gugler, Kelso, 8z Turvev, 1982). The evidence f o r generalized motor programs is the presence of such kinematic features as: invariant relative timin of the component acts comprised by the sequence, the positive relation etween reaction time f o r initiation of the sequence and the degree of complexit of the sequence, and the effector independence of the action (Schmidt, 1985y. Effector independence means that once a program is established for a articular movement, it can be used to control performance of that movement g y any number of muscle-joint systems, although some loss of precision may occur. The choice of effector may be represented by variables that a r e replaced by specific values a t the time of the movement. In the case of manual skill in infants, effector inde endence could only be discerned from comparison of the right and left hand. TKis would make investigation of handedness and its development during infancy a n essential pre-requisite for the assessment of effector independence f o r infant manual skills. As will be demonstrated later, there has been little evaluation of effector inde endence using right and left hand comparisons in studies of infant manuarskill. A r b i b ' s S c h e m a Theory. Recently, Arbib (1989) proposed a theory in which hi h-level analyses of cognitive processes can be described with elements low-levef enough to indicate how they could be implemented by neural networks or computer programs (Cervantes-Perez, 1989). Within this theory, a schema is a unit of knowledge composed of a erceptual schema, a motor schema, a goal state, and a program. Perceptual sc emas a r e units of knowledge representing the environmental situation with which the individual can interact. They identify, locate, and generate parametric representations of the various stimuli in a situation. This information may be used by motor schemas, but need not activate them. Motor schemas a r e units of motor control that can use information obtained by one o r more perceptual schema to direct action that copes properly with the current situation. Programs are processes that select information from activated perceptual schemas in order t o activate proper motor schemas in accord with the individual's goals. A program relates perceptual schema processes to motor schema processes and coordinates the motor actions in space and time. According to Arbib (1990), a set of basic motor schemas provides sensorimotor neural activity corresponding to simple, prototypical patterns of movements. These "building blocks" combine with perceptual schemas to form coordinated control programs which interweave their activations in accordance with the current task and sensory environment. Different perceptual schemas

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may be active a t the same time so they may cooperate o r compete with each other to provide the necessary parameter information to activate motor schemas. Motor schemas may be either basic o r built from other schemas as coordinated control programs. Schema activations a r e largely task driven, reflecting intention-related goals of the individual and physical and functional requirements of the task as revealed by the perceptual schemas. New schemas are formed as assemblages of old schemas; but once formed, a schema may be tuned into a unified whole much as a skill is honed into a unified whole from constituent pieces. Tunability allows schemas to start as composites of simpler schemas but to emerge as units with organizational characteristics equivalent to those of sim ler schemas. Tunability transforms a composite of schemas into a unit that can ecome a com onent in the formation of other composite schemas. According to Arbib ( 1 9 h ) , tuning may reflect processes similar to those revealed in adaptive network mechanisms. Arbib’s schema theory promotes the study of sensorimotor behavior within the context of a perception-action- cle. A n individual perceives in order to act and may act in order t o perceive. y e w stimuli update the individual’s internal model of the world thereby modifying perception of the spatio-temporal relation between the individual and the environment. This relation directs t h e action that would lead successfully to the goal. P i a g e t ’ s S c h e m e T h e o r y . In many ways, both Arbib’s schema theory and generalized motor proeram theory a r e like Pia et’s theory of the development of sensorimotor intelligence during infancy. iaget (1952) argued that infants construct their knowledge of the world, not from perception or information provided by others, but from motor activity. Mental representations (ideas, plans, images, thoughts) are internalized motor activity. For Pia et, the basic element of knowledge was the scheme, a way of acting on the wor d. For infants, schemes are skilled motor activities (sucking, eras ing, reaching, looking, hearing, etc.) used to process o r acquire information rom the environment. These schemes and others allow assignment of function and meaning to stimuli. Adaptation is the process by which schemes a r e altered through experience in Piaget’s theory. When information may be processed according t o a n existing scheme (assimilation), the ex erience is meaningful. This is analogous to Gibson’s (1966) notion of affor8ance. If a n existing scheme cannot process some information, then either another scheme is activated o r the existing scheme/action is modified (accommodation) and the information is processed. Task constraints would be an important contributor to scheme accommodation. Like Arbib ( 1990), Piaget argued that schemes can combine (mutually accommodate) to form new schemes. As schemes become more com lex, they take on the characteristics of operations, a more generalizable inte ligence. Piaget considered manual action to be both a n expression of knowledge and a means of acquiring it. Performance of manual actions rovides new or additional sensory information (visual, auditory, tactual), whic can b e used t o maintain, modify, o r curtail further action and influence the organization of future actions. Investigation of the development of manual skill during infancy was essential for the construction and demonstration of Piaget’s theoretical notions about the sensorimotor basis of intellectual development. Therefore, it would seem likely that such investigation would prove relevant f o r refining notions of internalized schemata and motor pro rams. D y n a m i c S y s t e m s T h e o r y . Traditionalyy, theories of action that posit an internal control structure have had difficulty dealing with the flexibility and adaptability of action. Motor program structures d o not deal adequately with

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the degrees of freedom problem and the context-sensitive nature of action patterns (Jordan, 1990). Some (e.g., Saltzman & Kelso, 1987) have argued that these failures result from the s ecification of action units in terms of kinematics or muscle variables. I f the units of action a r e specified by the mathematics of dynamical systems theory, then action is a matter of setting up interaction between biomechanical variables and environmental variables so that the resulting nonlinear dynamical system is characterized by multiple stable manifolds of low dimensionality, a vector field. It is this vector field (or its mathematical representation) that is the dynamical structure of action. Saltzman and Kelso (1987) have shown how task dynamic theory can account for both trajectory shaping and the immediate com ensation (motor equivalence) for perturbation in movement. They argue t at task dynamic theory and a notion of network-couplin create a conception of sensorimotor organization that can generate bota invariant trajectory patterns for unperturbed movements and spontaneous, compensatory behaviors for perturbed movements. Although there are formal differences between the task dynamic, generalized motor programs, and schemata perspectives, there are many conceptual similarities. All agree that in order to successfull execute manual tasks, three kinds of information are required: information a 8l out the position, orientation, size, form, substance and texture of the object(,) to be manipulated; information about the position and movements of arms and hands relative to subject's own body; information about the positions and movements of the arms and hands relative to object to be manipulated. Visual, proprioceptive, and haptic-tactile input contribute to efficiency of manual action. Haptics provide information about the object substance and how the object is deformed during grasping. It also contributes to the regulation of gri force by monitoring microslips between hand and object (Johansson Westling, 1990). Also, like Arbib (1990), Saltzman and Kelso define action units abstractly in a functional task specific manner spanning a n ensemble of muscles and joints. Once a given functional organization is established over a muscle joint collective, the system achieves its goal with minimal voluntary intervention. Also, skill acquisition requires the designing of a n action unit (coordinative structure) whose underlying dynamics are appropriate to the skill. During the acquisition of a skill "... one is establishing a one-to-one correspondence between the functional characteristics of the skill and the dynamical regime under1 ing the performance of the skill" (Saltzman and Kelso, 1987, pg. 86). Tgese notions compare nicely to Arbib's description of prehensile movements. The "hand" is defined abstractly as consistin of three virtual fingers. A large variety of prehensile movements can be fescribed by three types of abstract opposition patterns o r schemata of the virtual hand. In the ad opposition schema, the pad of the first virtual finger (potentially the thuml! of the real hand) is opposed to the pad of the second virtual finger (one o r any combination of fingers of the real hand). In the palm opposition schema, a group of fin ers (excluding the thumb) form the second virtual finger which is opposed to t i e first virtual finger (the palm). In the side o position schema, the pad of the thumb (virtual finger 1) is opposed to side of i n g e r s (virtual finger 2). Not all manual activities are captured by this vocabulary (stroking, sign language, piano playing, etc.) but it reduces many complex grasps to simple parametized forms. A major use of vision in grasping is to determine the opposition space embedded in the object to allow preshaping. Preshaping forms the hand so the opposing surfaces of the virtual fingers will be correspondingly separated.

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One aspect of task dynamic theory sharply distinguishes it from schema and motor program theory. Schema and motor program theory require modular synergies of acts automatically triggered by appropriate distinctive features of input. These synergies are re resented by output patterns stored somewhere in the CNS. In contrast, task jynamic theory postulates synergies as emergent properties; they are not represented anywhere. If patterns of movement a r e not stored in the CNS, then this has profound consequences not only for the acquisition of skill but also for the relation between sensorimotor development during infancy and subsequent intellectual ability. What develops, if not internal re resentations, during infancy? Let us examine the phenomena of manual s k i i during infancy. Hand-to-mouth Actions

In spontaneous activity, the arm movements of newborn infants may result in hand contacts with the head, face, and mouth. Some of these movements result in the hand entering the mouth. However, are they directed to the mouth? Older infants appear to employ a hand-to-mouth strategy as a means for self-regulation of state. Moreover, hand-to-mouth action becomes a frequent component of the manipulative phase of prehension. Reach, grasp, and then retrieval of the object to the mouth precedes, developmentally, the post-grasp object-elicited manual actions (shaking, pal ating, fingering, intermanual transfer, etc.) and forms the foundation of sePf-feeding actions. Also, hand-to-mouth movements ma serve as a kind of tactual self exploration (Kravitz, Goldenberg, & Neyhus, 1g78) and mouthing of objects can provide tactual information about an object's properties (Gottfried, Rose, & Brid er, 1977). Therefore, hand-to-mouth may be as important a n aspect of infant prehension as is hold and manipulate for visual and/or haptic inspection. Hand-to-mouth r e uires that the hand be transported t o the position of the mouth. Visual in ormation would be relatively unimportant in the coordination of this action. However, the infant could make use of roprioceptive information about hand and head position. Hand-in-mouth is a Prequen: attern of prenatal behavior (Birnholz, 1989). Therefore, it is conceivdb e that a rudimentary pattern of hand-to-mouth coufd be acquired during prenatal development that depends on proprioceptive information. Within schema and motor program theory, hand-to-mouth actions would imply stored information about the output needed to produce the correct trajectory which, in turn, would depend upon stored information from proprioceptive and other sources about the positions of the hand and the mouth. Task dynamic theory would consider the hand-to-mouth pattern to occur as a consequence of biomechanical, neural, and environmental constraints. Butterworth (1986) reported that newborn infants, a few hours after birth, were capable of directing arm movements to bring the hand to the mouth. Althou h for most arm movements the hand often failed to contact any part of the bofy or contacted other parts of the face first, there were instances when the hand moved "immediately in the direction of the mouth" (p. 28). Since the mouth was significantly more likely to be o e n before and during the a r m movement when the hand entered the mouth &an when it did not, Butterworth considered it to be an intentional movement. However, in a study of infants 12 to 30 hours after birth, Michel, Meserve, and Canli (in prep.) found no evidence of directed hand-to-mouth actions. T h e hand was more likely t o enter the mouth if it was open than if it was closed, but it was just as likely to contact the closed and the open mouth. Also, when the head was turned toward one side, the hand on that side was more likely to touch

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the face and mouth. The likelihood of newborn hand movements coalescing into hand-to-mouth actions seemed to depend on the constraints created by the neonate's asymmetrical posture, flexion patterns of the arms, and associated movements involving mouth and arm. These associated movements are likely the result of an over production of corticospinal axon collaterals and synapses on spinal interneurons and motoneurons serving the hand and mouth. These observations support the notion that newborn hand-to-mouth movements need not imply any co nitive ability. Such actions seem to be an instance of posture constraining f i n a very low-level sense) arm movement instead of arm movement invoking a supportive posture. This is not to say that such movements in older infants and adults d o not depend upon some sort of representational-intentional system. Nor should it negate the possibility that newborn hand-to-mouth movements a r e affected by prenatal hand-mouth experience.

Reaching and Grasping According to Napier (1956, 1976), the hand evolved specifically for rehension and according to Simpson (1976) the arm evolved to osition the [and relative to the body. Therefore, from the perspective o evolution, reaching and grasping are basic functions of human forelimbs. Accordingly, Na ier (1956) distinguished prehensile movements of the forelimb (reaching) a n g grasping) from non-prehensile movements. In prehensile movements the object is seized and secured by the hand. In non-prehensile movements the object can be manipulated by pushing or lifting motions of the arm as a whole or of the individual digits. Pointing, touching, and hitting a r e examples of nonprehensile movements. Both prehensile and non-prehensile actions reflect the coordination of multijoint movements, integrated with visual and kinesthetic information, to place the hand at a point in body-centered space. This coordination involves not only eye and hand movements but also head and trunk postures. In prehension, there is adjustment of the hand configuration during reaching to allow immediate grasping o r manipulation of the object according to its size, shape, weight, etc. Napier (1956) classified all prehensile grasp patterns as variants of two main configurations. In the precision gri the inter-phalangeal joints a r e extended and the terminal ad of the t h u m i opposes the terminal pad of the index or other fingers for felicate control of prehensile force. This grip also allows for independent ad'ustment of the fingers at the expense of strength. In the power grip the t h u d buttresses the other fingers and flexes the interphalangeal joint for moderate to strong grippin forces a t the expense of mobility and independent motion of the fingers. k i t h this grip the agonistic muscles of wrist, fingers, and thumb co-contract to provide a stiff postural sup ort. Landsmeer (1962) objected to the use of 'grip" for the precision configuration, although he retained Na ier's power/precision dichotomy, preferring instead the term "precision han ling" because of the dynamic aspect of the action. Elliott and Connolly (1984) argued that the ower/precision dichotomy should not be confused with that of grip/handling. h e noted that if an object is held immobile so that i t cannot be moved within the Eand, then movement of the object can only be achieved by some combination of movement of wrist, arm, and trunk. These movements can be very precise, even delicate. However, if an object is held so that it can be manipulated within the hand itself, then a greater variety of movements is available. Digital grips encourage delicacy and precision of movement simply as a consequence of the variety of possible

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movements. Palmar gri s immobilize objects in the hand by maintaining them in contact with the pafm. As a result, greater force can be applied with the object. Nevertheless, palmar grips can be controlled as precisely as digital grips. Prehensile actions have been divided into three movement components (Prablanc, Eschallier, Komilis, & Jeannerod, 1979; Paillard 1982). First, eye and head movements a r e directed toward the tar et. Then, the a r m is propelled toward the target, beginning with a rapid, possib y ballistic (but see Prablanc & Pellisson, 1990), movement followed by a slower phase in which visual information is used to direct the hand to the target. The prehensile action ends with grasping and/or manipulation in which haptic-tactile and kinesthetic information is important. The three movement components a r e integrated in skilled prehensile action. This integration is revealed by the decrease in accuracy of pointing if head and eyes are not free to move in the direction of target (Biguer, Prablanc & Jeannerod, 1984). The integration is revealed also by the relation of the configuration of the hand to the movement of the arm (Jeannerod, 1984). T h e fingers extend in preparation for gras ing until the peak velocity of the transport phase is achieved; then, the Angers close during the low velocity phase. This second phase of the approach seems to be part of the rasp act. T h e degree of initial finger extension and subsequent finger closure f e p e n d on the perceived size of the object to be rasped (Jeannerod, 1984). However, vision during reaching is not essential o r the association of the change in hand configuration with the change in arm velocity. Jeannerod and Biguer (1982) reported that a t the same time re-acceleration began the hand started t o close. A smooth prehensive action requires that the grasp is adequately timed relative to the encounter with the object, especially if the object is moving, so that the object is securely retained within the compass of the hand. T h e hand should start to close in anticipation of, rather than in reaction to, the encounter with the target. If closure is late, the ob’ect just bounces off the alm. If closure is too early, the object hits the fingers. Jrecise timing requires t l a t the gras be planned for and initiated in anticipation of the encounter with the object. !his implies visual control. Tactual control of grasping would interrupt the reach and grasp act. The preparatory adjustments of prehensile movements seem to involve visual information about the properties (orientation, size, and form) of the object (Jeannerod, 1981). However, Rosenbaum, Marchak, Barnes, Vaughan, and Jorgensen (1990) reported evidence that adults adjust their gri patterns according to what they plan to d o with the objects being grasped. &at is, the hand shaping occurring in late phases of reaching were in anticipation of a later manipulatory task, not the one to be performed immediately. Rosenbaum, e t al. (1990) reported that these prehensile patterns are constrained by the avoidance of extreme joint angles and the exploitation of extreme joint angles when they can not be avoided. Reaching and grasping may constitute separate perception-action systems. Hofsten (1990) proposed that the descending ventromedial pathway of the spinal cord is concerned with reaching movements and maintenance of balance during reaching and the dorsolateral pathway is involved in grasping. Although this may be true for monkeys, reaching in humans and other great apes is very much dependent on the dorsolateral system {Kuypers, 1982). Therefore, if reachin8 and rasping a r e separate systems, it is not because of some simple anatomical diherence. The organization of reaching and grasping into a smooth prehensile action is one of the main issues of infant behavioral development.

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Reaching. Are neonatal arm movements controlled by motor programs or schemas? Neonatal arm movements have been characterized as random thrashing (White, Castle, & Held, 1964). However, recent accounts have considered the neonate's arm movements to represent patterns of eye-hand coordination controlled by motor programs formally equivalent to those proposed to control arm movements in older individuals. The neonatal arm movements have been called intentional reaches (Bower, Broughton, & Moore, 1970), preada tations for reaching (Bruner, 1973), prefunctional reaches (von Hofsten, 19827, prereaching (Trevarthen, 1975), reaching-like arm movements (Rader & Stern, 1982), and visually elicited reaching (Bushnell, 1985). In contrast, some have questioned the resence of e e-hand coordinated reaching in very young infants (Coryell & Miciel, 1978; Rurf & Halton, 1978). E e hand coordination is said to involve visual localization of the target, visual localization of the hand, and proprioce tive or kinesthetic localization of the hand (Bushnell, 1985; Hofsten, 1990). &e mapping of the hand position (visual or "felt") with the target position is used to coordinate the movement. Unlike investigation of adult reaching, however, information about gaze and head orientation is missing from the account of infant eye-hand coordination. It has been proposed that neonatal eye-hand coordination depends on some sort of neural visuo-proprioceptive or visuo-motor spatial coordination (Bushnell, 1985; Hofsten, 1990). In contrast, eye-hand coordination of older infants is accomplished by monitoring and progressively reducing the gap between seen target and seen hand. This type of coordination is characteristic of unskilled, unprogrammed actions. Piaget (1952) argued that the acquisition of skilled eye-hand coordination depended upon mutual assimilation of visuomotor schema of looking at the hand and looking at the object and the tactual motor schema of feeling with the hand. It is generally agreed that 1 to 4 monthold infants spend a good deal of their time visually regarding their hands and it has been proposed that this experience contributes to the development of handedness as well as eye-hand coordination (Michel, 1987). Evidence for visually guided reaching IS first obtained between the a es of 3 and 5 months (Bower, 1974; Bruner, 1969; Bushnell, 1985; McDonnefl, 1979; Piaget, 1952; White, Castle, & Held, 1964). According to Bushnell (1985) three characteristics distinguish eye-hand coordination of older infants from neonatal eye-hand behavior. Firstly, the neonatal behavior is less accurate than reaching at later ages. Infants over 20 weeks of age (5 months) contact the tar e t more than 80% of the time (Bower, 1974) whereas neonates contact the o\'ect less than 10% of the time (von Hofsten, 1982; Ruff & Halton, 1978). indeed, Dodwell, Muir, & DiFranco (1976) reported only a 3 % contact rate. Secondly, neonatal arm movements a r e thought to be ballistic whereas the movements of the older infant a r e visuallyguided. Finally, neonatal arm movements are said to be "based on some sort of pre-wired visuo-proprioceptive or visuo-motor spatial coordination" (Bushnell, 1985, p. 142). Perhaps the most striking aspect of neonatal arm movements, in contrast to those of older infants, is that they a r e not corrective. Bower (1976) reported that infants younger than 26 weeks routinely missed targets when wearing prism glasses that laterally displaced seen object and seen hand. Older infants used midreach corrective movements or corrected their movements between reaches. Also, younger infants did not show any alteration of arm movements that failed to achieve contact with a "virtual" object as created by special lenses. Thus, it seems that the younger infants were not using information from seen

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hand/seen object relations or feedback from tactual senses in executing their arm movements. Many consider von Hofsten’s (1982) descriptions of neonatal a r m movements to authenticate the presence of eye-hand coordination. H e re orted that extended arm movements came closer to a target (off by 32 degreesrwhen the newborn fixated it than when the infant either looked elsewhere (off by 52 degrees) or had closed eyes (off by 54 degrees). However, the neonates did not get as close to the target as did the older infants. There is some question about whether von Hofsten adequately controlled for the neonate’s head orientation during testing. This control is essential because it could account for why hand movements came closer to the target during fixation without assuming visuallydirected reaching. When supine o r seated, neonates prefer to orient their heads to one side, most often the right side (Michel, 1981, 1987; Michel & Harkins, 1986). This head orientation differentially affects the pattern and frequency of movement of the two hands, with the face side hand being more active and extending more frequently. The preferred head orientation also creates a lateral asymmetry in the pattern of sensitivity of the neonate’s visual field (Bullinger, 1984; Mellier & Jouen, 1984). Turning the head to fixate a moving tar et when it was to one side o r the other would lead to more arm extensions on t at side and hence the hand would come closer to the target. D e Schonen (1977) reported that neonatal reaching with one arm is associated with flexion of the other arm toward the body (in the manner of a n asymmetric tonic neck reflex - ATNR) which may he1 maintain postural equilibrium during transport of the reachin8 arm. The A T k R is also expressed during s ontaneous head turning but declines during the 6 to 12 week age period o!(yrel & Michel, 1978). According to de Schonen (1977) accurate and well-coordinated reaching is associated with the disappearance of the ATNR. Thus, postural patterns may affect arm movements and may create the impression of visual1 -directed reaches. Neonates show rather limited coordination of reac ing with eye and head movements and limited compensation of tra‘ector of reaching with postural changes (Trevarthen, Murray, & Hubley, 1dSl). Jherefore, neonatal reaching may b e coordinated by biomechanical characteristics of posture. Until postural positions a r e adequately controlled, it is uncertain whether neonatal arm movements a r e controlled by any means other than posture. This may be another instance in neonates of posture constraining (in a low sense) arm movement instead of the arm movement invoking a supportive posture. Although there is no critical evidence that the neonate’s arm movements are ballistic, the subjective descriptions (swipes, flings, explosive) suggest that they are rapidly executed. Hofsten (1982) reported that neonatal extensions came closest to the target in 1.04 seconds but that 4 1/2 to 5 1/2 month-old infants came closest to the target in 1.8 seconds (von Hofsten, 1979), documenting a difference in speed. However, timing corn arisons depend on identical start and stop positions. There is no evidence t PI a t neonates began their movements from the same position as did the older infants. The tem oral aspect of neonatal arm movements reveals a succession of elements wit[ the fundamental cadence of saccades of visual scanning (Trevarthen, Murray, & Hubley, 1981). Perhaps, some neonatal arm movements are driven by motor processes similar to those affectin eye movements. According to Hofsten (19847, prefunctional reaches decline by 7 weeks and there is a period of no eye-hand behavior. Beginning at about 4 months, reaching behavior reappears. Reaching after 4 months appears to be guided during its performance or upon completion (Bushnell, 1985). T h e arm’s

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approach to the target seems to be monitored and adjusted during the reach. McDonnell (1975) reported that infants as young as 4 months adapted to wearing prisms that laterally displaced the visual field, indicating that they were using visual information to guide the movements of the hand during reaching. However, these infants were reaching with sweeping movements em loying the shoulder only. By 7 months, the reaches were parabolic refrecting shoulder and some elbow control. Only by 9 months were the reaches straight. Interestingly, there was less adaptation to the effect of the prisms in the older infants. This has been interpreted to mean that the older infant is employin a more ballistic reach (McDonnell, 1979). Finafly, von Hofsten (1979) reported that 4 to 5 month old infants' approaches to targets were slow with many zig-zag movements consisting of several elements of about the same duration and often containing elements directed away from the target. Over 60% of reaches of 18 week-old infants consisted of three or more elements whereas by 36 weeks over 75% of reaches consisted of one or two elements with more of the duration, distance, and force of the reach associated with the first element. Hofsten (1990) proposed that infants between 4 and 8 months of age make trajectory adjustments and visually attend to the target-hand relation when reaching whereas both younger and older infants d o not. This would imply that the younger infant's reaching does not involve the execution of a motor program o r schema. Interestingly, even skilled reaching in normal adults consists of a series of "virtual positions" which a r e used to gradually shift the arm equilibrium ("stiffness" of antagonistic muscles) between initial and final positions (Bizzi.& Mussa-Ivaldi, 1990). Arm movement consists of a series of sequentially implemented postures or staggered joint positions. The onset of one joint position is staggered in time to onset of another. "Knowled e" of the appropriate staggerin delay is built with experience using f e e back from vision or contact with t e environment. The nervous system transforms a trajectory into a sequence of postures equilibrium positions and muscle stiffnesses). The schema or motor pro ram Ior reaching may be the sequencing of these virtual positions. Infeed, sequencing a series of intermediate virtual postures may provide better adaptation to changes in external conditions, especially if the program is open to additional input. Indeed, additional input (proprioceptive feedback) may be used to control the "open loop" phase of reachin (Prablanc & Pelisson, 1990). That is, movement of the arm appears to be fefined initially in body related coordinates and then later in ob'ect related coordinates. Prablanc and Pelisson (1990) reported that retinal Ieedback from a visual tar et, displaced (during the first saccade of eye orientation to the target) 10% urther from the center of the position a t initiation of the reach, could influence ongoing limb motor output. They roposed that an initial set of information about target osition from the perip era1 retina is used to direct eye and hand movements. d w e v e r , after the initial saccade, input from retinal and other sources is used to update information about target position to "fine-tune" hand trajectory. Since this modification can be achieved without visual feedback about limb position, the target position feedback must combine with information about the current trajectory of the hand derived from non-visual sources (proprioceptive feedback and/or efference co y of the signals sent to neurons controlling the hand trajectory). It is difficuyt to understand how the adjustment to target changes could have occurred if skilled reaching was not coordinated as a series of ostural positions. It is interesting that neonatal reaching movements seem to e exaggerated (unskilled?) versions of the coordination of arm movements

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that might be expected if the theoretical notions of Bizzi and Mussa-Ivaldi (1990) and Prablanc and Pelisson (.I990) were combined. By the end of the first year, infants exhibit shapin of the hand before and during reaching in preparation for grasping (Newelf, Scully, McDonald, & Baillargeon, 1989) and can make detours to reach around a transparent barrier €or objects (Lockman, 1984). Such prehensile patterns have been considered as evidence of motor programming of prehension in adults (Jeannerod, 1986). Since the specific forms of infant prehensile skill depend extensively on both task constraints and infant state, it is not known whether the infant’s performance can be taken as reflecting internal representation. Infant prehension has not been examined for its response to perturbation, effector independence (comparison of right and left hand performance), or reaction time in relation to the complexity of the action. Grasping. Studies of the development of manipulative patterns sug est that there is improvement throughout the first five years (Connolly & Elkot, 1972; Connolly, 1973). However, the patterns used do not readily fit the power grip/precision handling dichotomy. During infancy, Halverson (1931, 1932, 1937) reported a regular and orderly sequence in the onset of grip configurations. The progression begins with a primitive grasp reflex involving circle clawin . By 20 weeks a power rip squeeze is observed, then at 32 weeks a superior pa m grasp appears fol owed by a precise index finger-thumb opposition grasp at 52 weeks. However, Newell, et al. (1989) argued that infant grip configurations reflect task dynamic synergies that are a function of the size and shaQe of the object and the size of the infant’s hand and not some neuromaturational process associated with the infant’s age. In an earlier study, Newell, Scully, Tenenbaum, and Hardiman (1989) found that when object size is scaled to hand size for a given set of tasks, the grasping patterns and limb orientations during reaching will be similar for both adults and three year-olds. Moreover, a common set of five ,configurations accounted for the majority of grip patterns for both age groups. They concluded that the prehensile pattern is a consequence of task constraints, including the object properties (size, shape, texture, mass, etc.) that constrain the dynamics of the action, rather than age. Therefore, Newell, et al. (1989) predicted systematic grip differentiation as a function of differences in object size and shape in 4 to 8 month-old infants. As in the earlier study, Newell, et al. (1989) found that five grip configurations accounted for most patterns of gras . These were: thumb and index finger of same hand; thumb, index, and middre finger of same hand; all five digits of the hand; thumb, index, middle, and ring finger of same hand; all ten digits of both hands. The presence of precision thumb-index opposition grip was dependent on the task constraints. Nevertheless, there were some age differences. Four month-old infants were more variable in their grip configurations than infants 5 to 8 months old. Also, four month old infants shaped their hand only after contact with the object. Shaping the hand during reaching, in accordance to the visually perceived properties of the objects, increased with each age group until it predominated (60% of reaches) at 7 months. Thus, Newell, et al. proposed that the regular and orderly se uence in the appearance of grip configurations observed in earlier studies resu ted from assessment with a narrow range of task constraints. Thus, their results support the task dynamic theory of motor coordination. Although Newell, et al. (1989) can account for the appearance of rather sophisticated grasp patterns durin early infancy, they do not offer an explanation as to why grip atterns o differ with age when a narrow range of task constraints are used. &hen grasp patterns for the same task constraints

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change with age, then something must be developin character of the tasks in Halverson’s studies ( a pill-s cube), it is unlikely that hand size differences with changes in grasp pattern. Clearly, the task dynamic theory must be adjusted if it is to accommodate the em irical evidence provided by the study of the development of manual skill uring infancy. Newborns d o not grasp objects during arm extensions because as the arm is extended the hand is opened (Trevarthen, 1974; Hofsten, 1982). There is a synergy of arm movement and hand configuration and that synergy is affected by postural asymmetries including direction of head orientation (Michel & Goodwin, 1978; Michel & Harkins, 1986). Twitchell (1965) demonstrated that grasping at one month can occur as a consequence of stretching the shoulder adductors and flexors. In response, all joints, includin the digits, flex. After two months the syner begins to break and the han may be fisted during extension (Hofsten 1$i4). After 3 months the hand begins to open during extension and reaching attempts increase. Lockman, Ashmead, & Bushnell (1984) observed 5 and 9 month-old infants as they reached for horizontally and vertical1 oriented dowels. T h e younger infants adjusted the orientation of the hand efore contact with the object (see also, Morron iello & Rocca, 1986). The preparation was done i n the early phase of the reacfi before the start of the approach. After 6 months, adjustments a r e performed continuously during the approach. Hofsten and Ronnqvist (1988) reported that at 9 and 13 months, but not 5 months, infants adjusted the distance between the thumb and index finger according to the s u e of the object. Hofsten (1990) speculates that the younger infants may be using a different grasp.

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Bimanual Prehension: Reaching and Grasping. During the second half of the first year, infants show bimanual coordination of arm movements in a number of activities ( e ., crawling, reaching, manipulating). In adults, coordinated use of the arms an hands often involves the temporal and spatial linkage of their movement (Kelso, Putnam, & Goodman, 1983). Such linkage is thou4ht to allow the nervous system to more easily control the actions of several joints during complex movement patterns (Bernstein, 1967). For infants, the formation of temporary linkages in the coordination of bilateral reaching changes as a function of age and handedness status. Goldfield and Michel (1986a) showed that spatial and temporal linkage of bilateral reaching movements is present in infants. By using a large, transparent, toy-filled box, bilateral reaching was reliabl elicited by 7 months of age. Although it occurred with equal frequency at 7 andYll months of age, the spatial and temporal linkages of the movements were not the same. The timin of the movement of one arm was more ti htly linked to that of the other for than for 11 month old infants. Also, a t months, the hands tended to move together i n isomorphic directions (i.e., if one hand moved to the left the other also moved left). At 11 months, the hands tended to move in complementary directions (i.e., one moved left and other moved right) to converge on the target. Moveover, at 11 months there was more inde endence in the timing of the movement of the two hands than at 7 months. ‘rphus, the spatial-temporal coordination of movement of the two hands i n bilateral reaching was quite different at these two ages. The infant’s handedness status affects some aspects of bilateral reaching (Goldfield & Michel, 1986b) both when there is no obstacle in the reaching

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ath and when there is a low (8cm hi h) opaque barrier in the ath of one of the pands. For those infants with a han -use preference, the pre erred hand leads during obstacle-free, bilateral reaching. The presence of the low barrier disrupted the bilateral character of reaching for infants younger than 11 months; they tended to reach first with one then the other hand. Also, the younger infants were more likely to hit the barrier when it was in the path of their non-preferred hand than when it was in the path of their preferred hand. For 7 to 9 month old infants, the obstacle disrupted the coordination of bilateral reaching more for infants with a handuse preference than for those without a preference. For 10 t o 12 month old infants, the obstacle disturbed coordination of bilateral reaching more for infants without a hand-use preference than f o r those with a preference. Thus, the ability of the infant to cope with the obstacle depended on the infant’s age and handedness status. It should be noted that the character of infant hand-use preferences begins to include complementary bimanual manipulatory skill in the older a e group (Michel, Ovrut, & Harkins, 1986; Ramsey, Campos, & Fenson, 1975). Fagard and Jacquet (1989) point out that bimanual manipulation may involve successive or simultaneous movements of the hands and that the movements may be symmetrical o r asymmetrical. They found that infants as young as 10 months can coordinate bimanual movements as long as the movements a r e not substantially different between the hands. Simultaneous asymmetrical bimanual actions a p eared between 13 and 18 months of age. Of course, the younger infants were a&le to hold a n object in one hand as the other hand explored it, indicating that this is a special form of asymmetrical bimanual action. The development of bilateral coordination of manual action during infancy deserves further investigation.

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L a t e r a l D i f f e r e n c e s i n H a n d - u s e a n d Skill. Handedness is not an immediately obvious characteristic of infants, but it can be revealed by appropriate assessment procedures (e.g., Michel, e t al. 1986). There is some evidence of differential usage of the hands in infants under 6 months of age. Hopkins, Lems, Janssen, Butterworth (1987) reported that hand-face contacts in newborns were equally likely to involve right and left hands, hand-mouth contacts were more common f o r the right than left hand f o r 10 of 12 infants. The remaining two infants showed a left hand preference. By 3 months, visual stimulation elicits more frequent movements by one hand than the other and it is the right hand f o r most infants (Coryell & Michel, 1978). By four months, infants are showing a hand-use preference in reaching and they remain consistent in their preference throughout the following 14 months (Michel & Harkins, 1986). Moreover, the right versus left hand-use preference of infants can be predicted from knowledge of their preferred direction (right versus left) of head orientation as newborns (Konishi, Mikawa, & Suzuki, 1986; Michel, 1981; Michel & Harkins, 1986). During the period from 6 to 18 months of age, infants will exhibit hand-use preferences (the right hand f o r most infants) in precision graspin and handling (Mebert, 1983), in the unimanual manipulation of toys (Michef e t al., 1986; Ramsay, 1980), and f o r ointin and gesture (Young, Lock, & Service, 1985). Moreover, Ramsay, et a f (19797 reported that by 10-11 months of age, infants preferred to hold to s in one hand and manipulate them with the other. This preference r e m a i n e J s t a b l e throughout the following 5 months. For infants 14 to 16 months of age, 7 1 per cent used the right hand t o manipulate, 14 per cent

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used the left hand, and 15 e r cent showed no preference. Thus, handedness is manifest in infant bimanua as well as unimanual actions. During infancy, a preferred hand will be more successful in rehension and the investigation of object properties. Indeed, the hands may d i k e r in skill because of the infant’s hand-use reference. Therefore, hand-use preferences could play an important role in e!lt organization of infant sensorimotor skills. Certainly, knowledge of handedness and its develo ment during infancy would b e essential if comparison of left and right hand ski 1was used as a n indicator of the effector independence of generalized motor rograms. Although the issue of hand-use preference has been relatively negkcted in both empirical and theoretical accounts of motor skill acquisition, it is a pervasive feature of infant manual actions.

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Discussion. As the review of the literature on the manual skills of infants demonstrated, most investigations provide on1 accounts of what the infant’s manual skill can accomplish at different ages. l o m e studies provide systematic descriptions of the kinematics of the skills, but very few experimentally challenge the infant’s erformance in order to reveal the processes that create the pattern of action. ithout the latter information, we cannot address such important develo mental questions as: what role early skills lay in the acquisition of su!I se uently appearing skills; how environmenta conditions (task constraints) an8organismic factors (biomechanical variables and state of neuromotor and neuroperceptual systems) combine t o create the pattern of movement; what aspects of movement control contribute to the development of the individual’s social and cognitive skills; and what types of ex erience (e.g., task specific or more general) a r e important for the acquisition o skill, transfer between skills, and the developmental transformations in manual ability. Infant manual actions a r e complex enouBh to convince many researchers that they a r e the consequence of some sort of internal representation system. If the infant’s performance is the result of schemata or motor programming, then questions about the relation of this internalized representation system to other, more cognitive, systems may be raised. Unfortunately, the review showed that many researchers often have inferred the characteristics of the infant’s representational system from inappropriate o r weak evidence. Neonatal arm movements (hand-to-mouth, reaching) need not imply any sort of representational system. Several studies have shown that infant manual actions, especially in ve young infants, could emerge from postural, biomechanical, and tas constraints. If infant manual skill was simply the consequence of task constraints and biomechanical properties, then changes in skill with age would result from rather low-level, cognitively irrelevant, processes. These rocesses mieht include changes in ratios of muscle and bone mass, growth of imbs and digits of the hand, growth of corticospinal tracts allowing individuated movements of the digits, growth of refined detection of visual, haptic-tactile, and proprioceptive input, etc. However, there would be no internal representation of action that could serve as a source for, or aspect of, knowledge. The infant would successfully exhibit skillful actions, but not because of any symbolic re resentation of the skill or the context. Notions of planning, intentionality, cpoice, understanding, problem-solving, and such would be less relevant to accounts of the patterns in performance. Can these alternative perspectives be reconciled? Is it possible to create a model of motor skill that incorporates the evidence acquired from the task-

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dynamic perspective and provides for a n internal representational system that does not manipulate symbols via rules (cf., Ku ler, 1986)? Moreover, the model's internal system should allow possib e transfer of motor skill representation to performance of actions usually described as cognitive abilities. Jordan (1990) proposed a model f o r the serial ordering of movements that seems to incorporate the strengths of the schemata, generalized motor rograms, and task dynamic perspectives. T h e model system is a sequence reaming and production system that uses a connectionist architecture (Rummelhart & McClelland, 1986). I t allows the same elements to occur in different orders in different contexts. Also, when wrong output occurs, the error results in changes in the network model so that stabilization is reached only when inputs lead t o correct outputs. After extensive ractice, the system is dynamic. That is, once a sequence starts, it becomes sef-perpetuating and if a movement is perturbed successive movements a r e automatically attracted back to the normal course. However, the system is not modular. Sequence learning is bound to a particular effector system. Practice tunes sequence performance to details of articulators, suggesting that sequential representation a t low levels of skill is effector independent. Indeed, effector inde endence may not be a n appropriate criterion for internal representation or skill. Wright (1990) recently argued that it is difficult to reconcile the notion of a motor rogram as a repository of information acquired as the skill developed a n f the notion that a motor program is a form of representation containing no specific information about muscles and joints. For example, consider writin a sentence with a pen' on paper versus with chalk on a board. The joints anfactivating muscles used for movements made with fingers and wrist differ radically in geometry and number of degrees of freedom of movement from larger scale, similar movements made with elbow and shoulder joint-muscle activation. These differences a r e so great it is difficult to see how the low-level plans for movements made for o n e combination could be transformed to control the other combination. Therefore, modularity and effector independence may not be necessary criteria for generalized motor programs. The success of Jordan's model depends on a learned internal mapping that allows the system to predict t h e results it expects to obtain, given the state of the environment and the output of the motor program. This "forward model" allows the system to "find" a motor program that produces a desired result. Like schemata and generalized motor program theories, Jordan's model postulates internal representations of action sequences. However, the network architecture of the model involves sets of connections whose wei hts a r e changed with experience. Memory is implemented by the weights whic means that particular experiences a r e integrated rather than stored separate1 the network is a dynamical system and changes in connection strength fect the local vector field rather than store particular trajectories o r movement sequences. The network need not be a device f o r rule governed manipulation of symbols. Jordan (1990) describes his model of motor learning as a n optimization of procedure embodying two kinds of constraints: explicit task specifications and intrinsic constraints that apply to a range of tasks. When constraints a r e expressed in distal coordinate systems (the environment), a n internal forward model is re uired so that they can be transformed into motoric coordinate systems. W i h n this model, the environment can set limits and experience can constrain development. Also, there can be generalization from one prototypical trajectory to all straightline motions.

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Jordan’s model does not address all of the important developmental questions, but it does demonstrate how internal re resentation can be reconciled with the dynamic systems perspective. Also, t e model would treat rehension as a perception-action s stem. Sensory and motor processes a r e Elended in the achievement of ski1 ed performance. It is not necessary to explain how the motor processes become linked with sensory processes during development because both are always aspects of any action. However, it is necessary to ex lain how the geometry of the environment is transformed into the geometry o movement of the arms and hands that is appropriately serially ordered. One interesting developmental question that Jordan’s model does not address is how new organizations might emerge as parts of the system (especially the perceptual and motor domains) undergo differentiation or refinement by experience and other influences. However, Jordan’s model does show how the stud of the development of manual skill during infanc can contribute to, and genefit from, cognitive-neuroscience investigations o skill acquisition.

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The Development of Thin Control and Temporal Or anization in &odited Action J. Fagad anf P.H. Wolff (Editors) Q Elsevier Science Publishers B.V., 1991

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T i m i n g in M o t o r D e v e l o p m e n t as E m e r g e n t P r o c e s s a n d P r o d u c t Esther Thelen Department of Psychology, Indiana University, Bloomington, IN 47405 Abstract A dynamical systems approach to motor behavior and motor develo ment proposes that t h i n emerges from the autonomous dynamics of the bo y and the constraints of t i e task and the environment. In particular, the limbs of newborn and youn infants act much like mass-springs and produce wellcoordinated and often oscillatory movements. During development, these intrinsic properties must be ada ted to task and intention. The process of acquiring skill may involve tRe multimodal exploration of generated movements and their perceptual concomitants. One mechanism that makes this possible is co-contraction of muscles, which gets t h e organism into the approximately correct space f o r discovering stable movement solutions. I illustrate this developmental se uence using spontaneous and elicited leg movements in infants. The deveYopmenta1 evidence suggests that timing is discovered perceptually rather than imposed by structural clocks.

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1. THE O R I G I N S OF T I M I N G As many i n this volume have noted, timing is the essence of motor skill. Much like the oft-quoted canard that it is aerodynamically impossible for hummingbirds to fly, the timing precision attained by very highly skilled performers almost defies explanation in terms of known properties of the nervous and skeletomuscular systems. For example, professional cellists can produce ra id reversals of the bow accurately and consistently within error margins we{ under 10 msec. (Winold, Thelen, & Ulrich, 199.1). Developmentalists a r e faced with the task of explaining the origins of motor skill timing, not just for elite performance, but f o r the everyday activities of locomotion, ob'ect manipulation, tool use, and sport, which depend on contracting and relaxing the muscles of the body with exquisite precision. It is continually tempting, when faced with actions that play out with clock-like precision, to assign causality to a clock. Indeed, there a r e a number of structures within the central nervous system- the spinal cord and the cerebellum in particular-- that are admirably designed to encode timin relations (Houk, 1990), and ve likely play a n integral role in this aspect o coordination and control. How these presumed timing mechanisms come t o reside in these structures? In a traditional structure- leads-to-function approach, brain structures are believed to "mature" and carry function along with them. For example, locomotion is a product of innate locomotor generators and maturing cortical control (Forssberg, 1982) and accurate grasping may reflect maturation of the appropriate corticospinal tract (Jeannerod, 1988).

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On purely logical grounds this level of explanation alone is deficient because it carries no account of the processes by which neural structures change and because of the strong nativist conclusions that inevitably follow. That is, that structure is contained in the initial state and merely needs to somehow unfold during ontogeny. A developmental analysis must beyond neural causation alone to ask about not only the nature of the initia state, but also about the agents and processes of change.

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2. DYNAMICAL APPROACHES TO MOTOR TIMING Fortunately, theory and research on adult motor behavior evolving over the last decade or so provides us with a rich and generative alternative. The tenets of what is variously called dynamical systems or dynamical pattern theory, the natural- physical perspective, or ecological perception-action theory are now well-known in the motor control and motor development fields and constitute an important challenge to the mainstream paradigm (Kugler, Kelso, & Turvey, 1980; 1982; Ku ler & Turvey, 1987; Schoner & Kelso, 1988). Dynamical the0 rests on very ifferent assumptions from traditional motor coordination a n 7 control approaches. At the heart is whether the problem of the generation action patterns is solved by the body acting as a machine-that is as a controller (the nervous system) imposing control signals on the energyconverting skeletomuscular system, or as a physical system which enerates patterns from the autonomous coo eration of components, w‘i,ere the distinction between the controlled and t\e controller is not simply dichotomous (Beek, 1989; Ku ler, et al., 1982). The two views lead to distinct1 different conclusions on t e origins of timing in motor performance. In t e former, timing is explicitly encoded in the programs or schemas of the controller. In the latter, in contrast, timin is a property emerging from the confluences of constraints arising from t8e nature of the task, the physical environment, the neural and mechanical linkages of the body, and the particular flow of energy through the body as it acts as a thermodynamic engine.

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3. DYNAMICS OF DEVELOPMENT

Dynamical systems principles have far-reaching implications, and wide explanatory powers, I believe, for understanding not only motor development, but developmental processes in general (Kugler, et al, 1982; Thelen, 1986a; 1989; Thelen, Kelso, & Fogel, 1987; Thelen 19Ulrich, in press; Wolff, 1987). In particular, such principles can help resolve the logical problem of the origins of timing -- is the “clock” encoded in the genes? Specifically, I propose that motor timing in skilled actions is discovered in onto en (as well as in adult skill learning) through perceptual exploration of the o y’s intrinsic or autonomous dynamics within a changing task and fhysical space. Infants are born with neural and skeletomuscular systems t at produce patterned and sometimes well-timed movements from the cooperative interactions of the anatomical substrate and its energy status within a particular physical environment. These autonomous dynamics are progressively modified by infants’ intentions within a task and social environment. The rocess of modifying the body’s dynamics involves exploring many possib e movement configurations and their perceptual consequences multimodall . Adaptive configurations which optimize the fit between the action a n d the perceived task are dynamically selected from this wider explored universe. The action-perception fit is itself an

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emergent and dynamic process: the organism does not "know" ahead of time the end-point of the developmental process (Edelman, 1987).

4. TIMING IN THE DEVELOPMENT OF LOCOMOTION These abstractions are best illustrated by a concrete example. Adult human locomotion is a precisely timed, seemin ly automatic cycle of movements, characterized by stable patterns of musc e activation within each limb and between the limbs. It is also an efficient movement, with the muscle contractions timed exquisitely to take advantage of the natural pendular movements of the legs and the body, so that muscles need not work when the passive (elastic and ravitational) forces can produce art of the movement cycle. It is widely hekd, based on animal studies, that t l! e patterned timing of locomotor movements is controlled by networks of neurons, likely in the spinal cord. These c e n t r a l p a t t e r n e n e r a t o r s are capable of producing locomotorlike muscle atterns in the atsence of sensory information, althou h in the intact anima , peripheral information appears to always play a role (brillner, 1980). Whether human locomotion is controlled b central pattern generators can never be known by direct experimentation. ?yhe developmental evidence, however, suggests that even timing patterns as universal and stereo ped as those in locomotion are not prescribed but discovered, or carved out rom an initial d namics. The atterns represent solutions to the multiple constraints imposedYby the naturafsprin -like and resonant properties of the body and the task of maintaining upright falance while propelling forward (see also Clark; Goldfield; Roberton, all in this volume). Although the onset of independent, erect locomotion is a seemingly discreet event at the end of the first year, infants have produced patterned movements of the legs since birth, and likely even in utero. Over the past decade, my colleagues and I have tried to understand the relation between these spontaneous and elicited early patterns and learning to walk alone. Clearly, a neuromuscular and ener etic substrate must be in place at the time of that first toddle that or anizes t i e behavior. But this substrate cannot have fully anticipated the specific and dynamic requirements of each ste is the nature of infant leg patterning, and especially its timing, t atWhat allows independent walking to appear when and how it does?

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We have studied patterned le movements that infants spontaneously generate as kicking actions, and also t ose movements elicited when infants are placed on a treadmill. This combination has allowed an understanding both of the autonomous dynamics of the legs when there is no specific intention or task, and also of a central-peripheral interaction that is essential for later locomotion. I discuss spontaneous kicking first. 5.1 Infant kicking

The coordination and control of infant kicking is, in my opinion, compelling evidence, that motor timing is an emer ent proper of the motor system as a whole and not just of an executive cloc (Thelen, elso, & Fogel,

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1987). Especially in the first few months of life, infant kicks a r e wellcoordinated, seemingly stereotyped, and often highly rhythmical. Movement durations, especiall of the flexion phase of the kick, where the hi , knee, and ankle simultaneous& flex toward the body, a r e clustered around 3 d msec., and intra-and interindividual variability is reater in the pauses between the movement phases than the movements t emselves. Bilateral coordination is often seen as legs alternate or move simultaneously in phase. It was tempting, on first examination, to ascribe these re ularities to a "central locomotor program" (Thelen, Bradshaw, & Ward, 19817. As we studied these movements in greater detail, however, the notion of a simple network oscillating between flexors and extensors became no longer tenable. First, the muscle activity underlying kicking did not follow the aeonistantagonist alternations seen in isolated animal preparations. Even in t h e absence of s ecific phasic inputs, kick movements were initiated b strong, coactivation o leg flexors and extensors, with flexor strength evident y dominant. We saw little o r no muscle activation in the extensor phase-- extension was presumably passive until about five months of age, when forceful extensions were produced--but again by co-active muscle contractions (Thelen & Fisher, 1983; Thelen, 1985). Since the nervous system can produce movement only through the timing of muscle contractions, there was clearly no simple one-toone correspondence between the muscle patterns and the movement patterns. What accounted f o r the regularity of the timing as well as the smooth, coordinated trajectories of the joints? There was indeed more regularity of coordination and rhythmicity than provided by the pattern of muscle contraction. The system, in its dynamical assembly, ained in complexity. Clearly, other components in addition to neural signak contribution to this increase in information, and we suggested earlier that this self-organization was, in part, a result of the passive and elastic properties of the leg (Thelen, Kelso, & Fogel, 1987). Recently, we have begun to look at these deceptive1 simple movements not only in terms of the kinematics and their underlying E L G patterns, but of the forces that actually produce the movements of the leg segments. T h e forces that move limbs o r body segments can arise from several sources. We conventionally think about the contraction of muscles and the forces that arise from the elastic qualities of muscle. But limbs may also move because of gravity (if all muscles a r e relaxed, we collapse!), and f r o m the passive, motiondependent forces that act on any one segment and arise from the movement of the other, mechanically linked se ments (picture pulling a sinele string on a jointed marionette). The effects o f t h e muscles, gravity, and motion-dependent forces a r e not static during a movement, but va continually and dynamically as a function of the posture and orientation of z e body part, the vigor of the movement, and the system's stiffness. The mathematics of inverse dynamics allowed us t o calculate the three sources of torques--muscle, gravitational, and motion-dependent--acting to move the joints of the leg during infant s ontaneous kicks from measured kinematics and body mass parameters (gchneider, Zernicke, Ulrich, Jensen, & Thelen, 1990). Using these technques, we confirmed earlier hypotheses that the space and time configurations of infant kicking could not be a product of a specific, dedicated clock in the CNS, but a systems assembly of the neural and energetic components. In particular, we found that while the flexion phase of the kick was initiated by flexor muscle torque, the forces acting to produce the extensor phase were largely passive, and especial1 gravitational. Indeed, the predominant influence of the muscles remainedrflexor during both flexion and extension of the leg. We also showed that motion-dependent forces played an

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im ortant role in determining the movement trajectory (Schneider, et al., 19fO). Most importantly, our anal sis revealed that the dynamic organization of infant kicks was similar to that o a sim le spring with a mass (Jensen, Ulrich, Thelen, Schneider, & Zernicke, 1991). fmagine imparting potential energy to the spring by stretching it, and then letting 0. The spring will exhibit a stable trajectory and timing---and will continue to o so as long as you periodically tug it. The particular time and space behavior of the spring depends on its intrinsic stiffness and how strongly you tug it, but whatever the force you impart, there will be a lawful relationship between t h e position of the spring and its potential energy. It may well be that in these spontaneous movements, the anatomical and elastic qualities of the legs dissipate energy in a manner similar to the spring. The nervous system can set the stiffness of the spring by the relative tonic contraction of the muscles and can regulate the pulse of energy delivered to the spring. But once these energy parameters a r e set, the details of the movement emerge from the constraints, and these details include the oscillatory timing of the movement. These dynamic properties may not be limited to the lower limbs. Our preliminary data on spontaneous arm movements in young infants also oints to these sprin$-like qualities. The view that the young i n i n t ma be a torso with four oscillating springs attached is not so strange considering t i e rather pervasive use of mass-springs and pendulums to describe adult limb movements (e. . Feldman, 1980; Kelso & Tuller 1984; Kugler & Turvey, 1987; McMahon, 19th and see also Clark and Roberton, this volume). The im ortant question, it seems, is when and especially how these initial spring-Eke qualities become adapted to functional and task-specific ends (Bingham, 1988). To answer this question, I refer again to qualities of the initial state which constrain the coordination patterns of the legs.

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These important qualities are best illustrated here b the phenomenon of t r e a d m i l l - e l i c i t e d stepping in infants. As described by J h e l e n (1986b), when

7-month- old infants were su ported so that their feet rested on a motorized treadmill, they produced welfcoordinated, a l t e r n a t i q steps in a n apparently nonintentional manner. Treadmill ste s were kinematically much more similar to adult locomotion in terms of intrairnb coordination than t o supine kicking or step ing without the treadmill in the same infants. Most importantly, treadmi 1 steps alternated between the legs in a remarkably stable fashion. To accomplish this selection process, infants must be sensitive to the multiple sensory consequences of their own actions, and must use that information to further select and refine behavioral patterns. Accordin to Edelman (1987) such a selective rocess is consistent with what is nown about neural architecture and levelopment. In brief, as a result of prenatal e ieenetic processes, the brain at birth is organized into highly overlapping, inchidually variant networks or neuronal groups. Especially important is that the local networks receiving input from a particular sensory modality have multiple and redundant connections with other local areas. In this way, eve motor action generates multiple and simultaneous sensory maps which are lin ed, in parallel

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Recall that the defining property of treadmill stepping is the stable alternation of the legs. If each leg has characteristics of a mass-spring, how is this bilateral coordination accomplished? Treadmill stepping suggests that one characteristic of the autonomous dynamics of the legs, probably in place at

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birth or earlier, is an informational linkage between the legs such that each limb is informed of the dynamic status of the o osite limb, and that movement is coordinated through this information. is means that movement is assembled by an intrinsic perception-action loop which detects the distribution of forces as the limbs move and adjusts the muscles to maintain a preferred coordinative mode, alternation in this case. The treadmill-leg system is in many ways analogous to the bilateral coordination of the wrist-pendulums of Kugler and Turve (1987). When these researchers instructed subjects to swing a hand-held pen ulum about the wrist in a comfortable mode, individuals settled on characteristic cycles that was a function of the mass of the pendulum. When given pendulums of different weights in both hands to coordinate, subjects discovered a comfortable frequency different from each preferred frequency alone. The frequency depended on the dissimilarity of the pendulum weights in a lawful manner governed by the ph sical principles of coupled pendulums. Kugler & Turvey concluded that the leformation of the tissues that resulted from the pendulum wei hts set up a continual "haptic flow field" in the nervous system that coupled thelftinetic interaction between the limbs. Further evidence that such cou lin is present early in life comes from Thelen, Skala & Kelso's (p9877 demonstration that the bilateral kinematic patterns of spontaneous kicking in 3-month-old infants were affected by the weighting of only one leg; a ain, the dynamic status of the moving limbs appears to be transmitted across t!i e pelvic girdle.

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6. TASK AND INTENTIONAL MODIFICATION OF AUTONOMOUS DYNAMICS

What is the relation, then, between the autonomous dynamics of these early limb movements and well-timed and task appropriate skilled movements? First, these studies emphasize that timing is not an arbitrary imposition, but a composite creation of a neuromotor/skeletal/vascular system working within a physical and task space. These autonomous dynamics are the substance from which all other timing skills are carved. Indeed, I follow the theories of Edelman (1987) in sug esting that timing (as other aspects of skill) is d namically selected by the &S as individuals move and perceive their wor ds. In particular, this approach sug ests that in early life, more patterns are generated than are eventually used. ome become stable and are retained; other behavioral combinations are lost. What determines this selection is a fit between the action and the demands of the periphery. To accomplish this selection process, infants must be sensitive to the multiple sensory consequences of their own actions, and must use that information to further select and refine behavioral patterns. Accordin to Edelman (1987) such a selective rocess is consistent with what is nown about neural architecture and levelopment. In brief, as a result of prenatal e ieenetic processes, the brain at birth is organized into highly overlapping, inchidually variant networks or neuronal groups. Especially important is that the local networks receiving input from a particular sensory modality have multiple and redundant connections with other local areas. In this way, eve motor action generates multiple and simultaneous sensory maps which are lin ed, in parallel to form higher order global maps. In other words, both the movement and its visual, proproprioceptive, auditory, and tactile consequences continuously converge and are correlated. As each slightly different variant of a movement combination is generated in presumably slightly different contextual

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conditions, the resulting features a r e fed back into this global mapping so that they may become associated with their motor responses. This type of reiterated feature correlation process alone can produce stable categories of action; certain elements become reliably associated with each other. Computer simulations of such systems show learning and generalization by this reentry procedure without a n explicit instructor and without traditional reinforcement mechanisms (e. g. Ku erstein, 1988, among others). T h e action categories selfassemble because of t i e dynamic interplay of the components. T h e autonomous dynamics of the neuromotor system serve therefore, to set up the constraints of the space the infant multimodally ex lores in order to discover adaptive timing for a articular motor skill. Goldfierd's (this volume) work on rocking-to-crawling il ustrates this process well. When infants assume the hands-and- knees posture and rock back and forth, this intrinsic oscillation (its frequency and amplitude a r e not intentionally timed) provides the infant with a sense, not only of the haptic, vestibular, and roprioceptive "feel" of the self-generated movement, but also its visuaf and perhaps auditory consequences. When the intentional as ect of crawling is realized (the hand reaches forward), this must be t i m e f to use and optimize the intrinsic oscillations of the body. The forward propulsive force must be applied at the right time and amplitude to rovide the correct, alternating pattern. Newly crawlin infants a r e less welfcoordinated than practiced crawlers (Benson, 1990), Further suggesting that timing must be discovered through exploration (practice) in multiple modalities. In terms of upright locomotion, the task is to adapt the autonomous dynamics of the legs (s ring-like, bilaterally coupled) t o the difficult conditions of dynamic balance o?the bod , which itself acts like an inverted pendulum. The nervous system cannot "{now" ahead of time the particular intrinsic stiffness qualities of the legs and the height, stiffness, and mass distribution of the body, which determine the physical substrate for the movement dynamics. Thus, as Bernstein (1967) suggested decades ago, this d namic fit must evolve as the system is used. The task sets the problem that the ZNS must solve. Both biomechanical and neurophysiological evidence support the contention that locomotor timing is discovered rather than imposed. First, EMG studies have consistently shown that newly walking infants d o not have the consistent a onist- antagonist alternations characteristic of mature walking (Forssberg, 198f; Okamoto & Goto, 1985). Rather, early walkers use mostly cocontraction, a muscle strategy common in the early stages of skill acquisition. What does co-contraction accomplish? Here t h e biomechanical data provides a clue. There is now stron evidence that many of the characteristic postures and movements of new walfers are a consequence of their instability, which in turn, may be due to their lack of extensor strength. Recall that in order to remain upright while movin forward, the walker needs to transfer all the weight to a single leg without t f e leg buckling. If the extensor muscles cannot yet provide the stron pillar that can support the body as the weight is shifted over the swing leg, infants can he1 provide stability by co-contraction. With a stiffer le then, infants can stil move forward by adoptin compensatory patterns. F h e s e include a wide base of support (high step width!, and especially short, rapid steps that minimize the time balanced on one le (Thelen, 1984). Note here that infants adjust the timing of their steps to fit t t e i r autonomous dynamics What of the temporal invariances seen in mature locomotion, specifically the proportional changes of swing and stance that occur with chan es in speed? By three months of walking experience, toddlers showed re ative timing proportions of step cycles similar to that of adults (Clark & Phillips (1987). As

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Clark & Phillips note, however, these invariances probably result from the energy demands of locomotion and the pendular swing, not from a pre-existing program. Indeed, compelling evidence of the importance of these biodynamic considerations comes from the work of Bril and Breniere. The show that durin the first phases of independent walking, infants literally "?all" a t each step. t h a t is, they d o not effectly reverse the acceleration of the foot before contact, but rather allow the pendular action of the le to car the foot to the round. (Mature walkers, in contrast, actively brake t e foot efore contact). !art of the inability to brake the foot may derive from lack of time to ad'ust the muscles, since the step must be short to prevent falling (Breniere, b r i l , & Fontaine, 1988; Bril & Breniere, 1989). In addition, these workers found that their is little temporal invariance in the phase of double sup ort (in contrast to single leg swing and stance) in the early months, and that t k s double support hase is probably most important at this time f o r balance control (Bril & reniere, 1988). Co-contraction is important during the period of learning to walk because it gets the leg-body system in the right "ball park" for locomotion, that is upright and moving forward. It is neither graceful nor efficient, but it is a muscle timing strategy that puts infants into the a proximately correct exploratory space. Once infants are up and moving, t e dynamic selective process, as described above, can be used to refine the movement and best optimize the natural dynamics of the le and body springs and pendulums. My colleagues and I have shown that a simifar process- contraction to get into the "ball park" in order to perceptually ex lore the ractice s ace- may be the mechanism of early reaching as well [Thelen, L r n i c k e , {chneider, Jensen, Kamm, & Corbetta, in press).

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7. SUMMARY I have argued that the origins of motor timing arise from a confluence of intrinsic o r autonomous d namics of a neuromotor system and the imposition of specific task demands. T e early motor system can produce timed behavior-often oscillatory-- and intentional activities use these dynamics as a substrate for carving out more adaptive, goal-corrected atterns. One initial strategy for moving from the intrinsic dynamics of the Body t o task-specific actions is stiffening by co-contraction to get the system into the approximate space. The infant can then multimodally explore this space to gain strength and accuracy. Finally, we would expect this exploration to lead to an optimization of the intrinsic dynamics to produce graceful and efficient movement. It is difficult to imaBine how an intrinsic neural clock such as a spinal locomotor generator can impose timing on a system that does not know its dynamics a riori. These dynamics can only be discovered perceptually, and in this sense, t i i s perceptual-motor process must be the source of real timing for real tasks.

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8. ACKNOWLEDGEMENT This research was supported by rants from the National Institutes of Health and the National Institutes of d e n t a l Health. I thank Dexter Gormley, Jody L. Jensen, Kathi Kamm, Michael Schoeny, Klaus Schneider, Beverly Ulrich and Ronald Zernicke for their contributions to the research described here and Kathi Kamm for her comments on the manuscript.

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9.REFERENCES Beek, P. J. (1989). J u g ling d y n a m i c s . Amsterdam: Free University Press. Benson, J. B. (1990). #he significance and development of crawling in human infancy. In J. E. Clark & J. H. Humphrey (Eds.). A d v a n c e s i n m o t o r d e v e l o p m e n t r e s e a r c h ( V o l u m e 3 ) New York: AMS Press. Bernstein, N. (1967). C o o r d i n a t i o n a n d r e g u l a t i o n of m o v e m e n t s . New York: Pergamon Press. Bingham, G. P. (1988). Task specific devices and the perceptual bottleneck. H u m a n M o v e m e n t S c i e n c e , 7, 225-264. Breniere, Y., Bril, B., & Fontaine, R. (1988). Analysis of the transition from u right stance to steady state locomotion f o r children with under 200 days o autonomous walking. J o u r n a l of M o t o r B e h a v i o r , 20,41-60. Bril, B., & Breniere, Y. (1988). D o temporal invariances exist as early as the first six months of independent walking? In A. Berthoz & F. Clarac : Development, adaptation and (Eds.), P o s t u r e and m o d u l a t i o n . Amsterdam: lsevier. Bril, B., & Breniere, Y. (1989). Steady-state velocity and temporal structure of K i t during the first six months of autonomous walking. Human ovement Science, 8,99-122. Clark, J. E., & Phillips, S. J. (1987). The ste cycle organization of infant walkers. J o u r n a l of M o t o r B e h a v i o r , I f , 421-433. Edelman, G. M. (1987). N e u r a l D a r w i n i s m . New York: Basic Books. Feldman, A. G. (1980). Superposition of motor programs. I. Rhythmic forearm movements in man. N e u r o s c i e n c e , 5,81-90. Forssberg, H. (1985). Ontogeny of human locomotor control. I. Infant stepping, su ported locomotion, and transition t o independent locomotion. & p e r i m e n t a l B r a i n R e s e a r c h , 57,480-493. Grillner, S. (1980). Control of locomotion in bi eds, tetrapods, and fish. In V. B. Brooks (Ed.), H a n d b o o k of p h y s i o r o t y , Y o 1 3: M o t o r c o n t r o l . Besthesda, MD: American Physiolo ical Society. Barto, A. G. (1990). An a d a tive Houk, J. C., Singh, S. P., Fisher, C., sensorimotor network inspired by the anatom and physiology o the cerebellum. In W. T. Miller, R. S. Sutton, & P. Werbos (Eds). N e u r a l n e t w o r k s f o r c o n t r o l . Cambrid e: MIT Press. Jeannerod, M. (1988). T h e n e u r a l a n c f b e h a v i o u r a l o r g a n i z a t i o n of g o a l d i r e c t e d m o v e m e n t s . Oxford: Clarendon Press. Jensen, J.L., Ulrich, B. D., Thelen, E., Schneider, K., & Zernicke, R. F. (1991). Adaptive dynamics of leg movement patterns of human infants: T h e effects of posture on spontaneous kicking. Manuscript submitted f o r publication. Kelso, J. A. S., & Tuller, B. (1984). A dynamical basis f o r action systems. In M. S. Gazzaniga (Ed.), H a n d b o o k of c o g n i t i v e n e u r o s c i e n c e . New York: Plenum Press. Kugler, P. N., Kelso, J. A. S., & Turvey, M. T. (1980). O n the concept of coordinative structures as dissipative structures. I. Theoretical lines of convergence. In G . E. Stelmach & J. Requin (Eds.), T u t o r i a l s i n m o t o r b e h a v i o r . New York: North Holland. Kugler, P., Kelso, J. A. S., & Turvey, M. T. (1982). O n the control and coordination of naturally developing systems. In J. A. S. Kelso & J. E. Clark (Eds.), T h e d e v e l o p m e n t of m o v e m e n t c o n t r o l and c o o r d i n a t i o n . New York: John Wiley.

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Kugler, P. N., & Turvey, M. T. (1987). I n f o r m a t i o n , n a t u r a l l a w , a n d t h e self - a s s e m b l y of rhythmic m o v e m e n t . Hillsdale, NJ: Erlbaum. Kuperstein, M. (1988). Neural network model for adaptive hand-eye coordination for single postures. S c i e n c e , 239, 1308-1311. McMahon, T. A. (1984). M u s c l e s , r e f l e x e s , and l o c o m o t i o n . Princeton, NJ: Princeton University Press. Okamoto, T., & Goto, Y (1985). Human infant pre-independent and independent walking. In S. Kondo (Ed.), P r i m a t e m o r p h o p h y s i o l o g y , l o c o m o t o r analyses and h u m a n b i p e d a l i s m . Tokyo, Japan: University of Tokyo Press. Schoner, G., & Kelso, J. A. S. (1988). Dynamic pattern generation in behavioral and neural systems. S c i e n c e , 239,1513-1520. Schneider, K., Zernicke, R. F., Ulrich, B. D., Jensen, J. L., & Thelen, E. (1990). Understanding movement control in infants through the analysis of limb intersegmental dynamics. J o u r n a l of M o t o r B e h a v i o r , 22,493-520. Thelen, E. (1984). Learning to walk: Ecological demands and phylogenetic constraints. In L. P. Lipsitt (Ed.), A d v a n c e s in i n f a n c y r e s e a r c h , V o l . 3. Norwood, NJ: Ablex. Thelen, E. (1985). Developmental origins of motor coordination: Leg movements in human infants. D e v e l o p m e n t a l P s y c h o b i o l o g y , 18, 122. Thelen, E. (1986a). Development of coordinated movement: Im lications for early human development. In M. G. Wade & H. T. A. Wgiting (Eds.), M o t o r s k i l l s a c q u i s i t i o n . Dordrecht, Netherlands: Martinus Nijhoff Publishers. Thelen, E. (1986b). Treadmill-elicited stepping in seven-month old infants. C h i l d D e v e l o p m e n t , 57,1498-1506. Thelen, E. (1989). Self-organization in develo mental processes: Can systems approaches work? In M. Gunnar & Thelen (Eds.), S y s t e m s i n d e v e l o p m e n t : T h e M i n n e s o t a S y m p o s i a in C h i l d Psychology, V o l u m e 22. Hillsdale, NJ: Erlbaum. Thelen, E., Bradshaw, G., & Ward, J. A. (1981). Spontaneous kicking i n monthold infants: Manifestations of a human central locomotor program? B e h a v i o r a l and N e u r a l Biology, 32,45-53. Thelen, E., & Fisher, D. M. (1983b). The organization of spontaneous leg movements in newborn infants. J o u r n a l of M o t o r B e h a v i o r , 15, 353377. Thelen, E., Kelso, J. A. S., & Fo el, A. (1987). Self-organizing s stems and infant motor develo ment. j e v e l o p m e n t a l R e v i e w , 7, 39-6l. Thelen, E., Skala, K., & kelso, J. A. S. (1987). The dynamic nature of early coordination: Evidence from bilateral leg movements in young infants. D e v e l o p m e n t a l P s y c h o b i o l o y , 23, 179-186. Jensen, J. L., Kamm, K., & Corbetta, D. Thelen, E., Zernicke, R.Schneider, (in press). The role of intersegmental dynamics in infant neuromotor development. In G. Stelmach & J. Requin (Eds.), T u t o r i a l s i n m o t o r b e h a v i o r 11. Amsterdam: North Holland. Thelen, E., & Ulrich, B. D. (in press). A d y n a m i c a l systems analysis of t r e a d m i l l stepping i n t h e f i r s t y e a r . M o n o g r a p h s of the S o c i e t y f o r Research in Child Development. Thelen, E., Ulrich, B., & Niles, D. (1987). Bilateral coordination in human infants: Stepping on a split-belt treadmill. J o u r n a l of E x p e r i m e n t a l Psychology: H u m a n P e r c e p t i o n and P e r f o r m a n c e , 13,405-410.

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Wolff, P. H. ( 1 9 8 7 ) . T h e d e v e l o p m e n t of b e h a v i o r a l s t a t e s a n d t h e expression of e m o t i o n s in e a r l y i n f a n c y : N e w p r o p o s a l s f o r i n v e s t i g a t i o n . Chica 0 : University of Chicago Press. Winold, H., Thelen, E., & Ufrich, B.D. (1991). Coordination and control in the bow arm movements of highly skilled cellists. Submitted for publication.

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The Development of Timin Control and Temporal Or anization in e[oordinated Action J. Fag& anfP.H. Wolff (Editors) Q Elsevier Science Publishers B.V., 1991

Soft assembly of an infant locomotor action system Eugene C. Goldfield Child Development Department, Connecticut College, Box 5352, 270 Mohegan Avenue, New London, Connecticut, USA, 06320-4196

Abstract An ecological and dynamical approach is adopted to examine the development of prone locomotion during human infancy. Data is presented in support of the hypotheses that infant rocking is a consequence of a mechanical system in an equilibrium state, and that postural asymmetries redistribute gravitational and elastic potentials to move the system away from equilibrium. 1. INTRODUCTION 1.1.

Assumptions of an ecological and dynamical approach

The ubiquity of behavioral rhythms during infancy (see, for example, Kravitz ti Bohm, 1971; Thelen, 1981; Wolff, 1967) and the persistence of behavioral rhythms in atypically developing children (see, e.g., Pohl, 1977; Wolff, 1968a) remain as puzzles for developmentalists and clinicians alike. A common theme in both the developmental and clinical literatures is that body rhythms such as kicking, rocking, waving, bouncing, scratching, banging, and rubbing, sometimes called llstereotypiesll(Thelen, 1981; Wolff , 1968a) , reflect an intrinsic patterning of movement by the central nervous system. Moreover, it is assumed that such patterning is the temporal substrate out of which functional activities are carved. In this chapter, I consider both the source of patterning and the transformation of temporal patterns into function during infant development. I do so by examining the implications of a style of motor control in which the nervous system exploits the natural resonant properties of the body in order to minimize energy expenditure in motor activity. The ideas expressed here build upon the work of Peter Kugler, Michael Turvey, and Scott Kelso, who have placed questions about adult motor control and coordination in the context of an ecological and physical biological approach to self-

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organizing systems, and on Peter Wolff's insights into the applications of these ideas in infant development. Central to the synthesis of the adult and infant work is the understanding of the role of the nervous system in coordination: The nervous system is seen as the medium supporting the causal agencies of coordination. The burden of explanation is shifted from modular anatomical units that are ascribed a special causal function a prior to very general physical principles that coordinate both animate The purpose of an ecological and inanimate things analysis is to determine the degree to which coordination phenomena can be understood in terms of lawful regularities and principles at the ecological scale, the scale at which the physical entities of animal and environment are defined (Schmidt & Turvey, 1989, pp. 124-

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125).

The ecological research program with adults has been guided in part by efforts to better understand the systematic linking together of neural, vascular, circulatory and muscular microstructures (Bingham, 1988) into a much larger functional collective in order to solve what Bernstein (1967) called the "degrees of freedom problemll (i e. , too many individual parts to be regulated independently). The key to the ecological approach is that these collectives can be given a lowdimensional physical redescription, and thus general organizational principles may be studied in behavior (cf. WolffIs approach to the study of behavioral state, e.g., Wolff, 1987). Kugler et al. (1980) propose that these collectives, or coordinative structures, behave like other collections of physical atomisms: they are marginally stable steady-states maintained by a flux of energy, that is, by metabolic processes that degrade more free energy than the drift a thermodynamic engine that draws toward equilibrium energy from a high potential source, rejects some to a lower potential energy sink and does work in a periodic limit-cycle fashiont1 (p.17) Coordinative structures are considered as open multistable systems, i.e., systems which, as visualized in qualitative geometry, are capable of self-organization into state space regions with multiple equilibrium points, or attractors. Multiple attractors arise because a "flow of energy through a field of loosely coupled, fluid-like operational components give(s) rise to a set of soft-molded constraints that temporarily organize the field" (Kugler & Turvey, 1987, p. 121). Kugler & Turvey argue that the mechanical linkages of the skeletomuscular system behave like a pendular system, and the energy gating function of the nervous system functions as the escapement for the pendular system: energy flow through the escapement allows the system to operate in a limit-cycle fashion.

.

...

.

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The concept of soft-molded neural energy gating (escapements) provides a distinctive perspective on posture and movement as well as on the process underlying developmental change in behavior. Posture may be thought of as a mechanical embodiment of the geometry of softly-molded neural steady states or attractors (see below), and movement as the dynamics of trajectories which tend toward these steady states. Developmental change in the soft-assembly of multiple attractors may be understood with respect to growth-related changes in the link-segment, musculotendon, circulatory and nervous systems. Development of each of these subsystems influences the flow of energy through the system as a whole. For example, an increase in tissue mass and a lengthening of the bones results in greater resistance to movement owing to gravity (Thelen, 1984). At the same time, change in the elasticity of the tendinous elements and in impulse transmission in the nervous system make it possible to increase muscular resistance to gravitational and other forces (Bingham, 1988). To make matters even more complicated at the level of microstructure, these subsystems interact in different ways during development, e.g., in the interaction between the link-segment system and the musculotendon system, mechanical energy can be returned to as well as derived from the muscles (McMahon, 1984). Due to the nonlinear properties of muscle and circulatory flow, the response of muscle to neural impulse varies widely (Bingham, 1988). HOW, then, is it possible to study the complex interaction of these subsystems undergoing change in order to understand the emergence of order in behavior? One solution is to adopt an ecological and dynamical research strategy summed up by Bingham (1988) as follows: The strategy is to describe, within specific functional contexts, the reduced dynamics of the human action system assembled from its diverse dynamic resources for the performance of a task. The challenge is to work backwards from a description of the reduced dynamics to an understanding of the manner in which sub-system dynamics couple and co-constrain one another to produce the observed dynamical system (p.13). The steps in this strategy are summarized by Jeka and Kelso (1989) as follows: (1) Characterize the observed relation between the microcomponents of the system by low dimensional collective variables or order parameters (2) Identify the type of dynamics which best characterize the macroscopic behavior of the order parameter, i.e., whether the dynamics fit one of four fundamental types of attractor: point, limit-cycle, torus (bifurcating), and strange or chaotic (Thompson & Stewart, 1986). (3) Identify the parameters which move the system through different collective states, i.e., the control parameters.

216

1.2.

E.C. Gola'field Timing laws and sealing laws

In the ecological approach adopted by Kugler and Turvey, the microstructural resources of a single limb during locomotion are modeled (i.e., examined as an order parameter) by a mass-spring pendular system in a gravitational field with a linear spring attached (Schmidt & Turvey, 1989; Turvey, Schmidt, Rosenblum & Kugler, 1988). Their modeling approach emphasizes two kinds of laws: a t i m i n g l a w (the pendular clocking mode) which remains invariant under transformations, and a s c a l i n g l a w , a geometry created by a layout of potentials which transforms the energetics of the atomisms governed by the timing law without changing the timing law itself. This approach assumes that timing is governed by mechanical processes and that a function of the nervous system is to transform (or, I1tune1l) the mechanical (dynamical) processes governing timing. The timing law is a statement of how elastic and gravitational potentials sustain the oscillation of a mechanical system (the musculotendon and link-segment systems). That is, the limb is hypothesized to oscillate as a function of two potentials (where a potential is defined as any local concentration of a conserved quantity), gravity and the restorative forces of the limb musculature and its associated metabolism (Schmidt & Turvey, 1989). The restorative forces are based upon both the inherent elasticity of muscle and the elastic stiffness assembled temporarily during active co-contraction (see, e.g., Feldman, 1986). The lawful relation between the variables in the equation of motion for the mass-spring pendulum system has been used in order parameter to model absolute coordination of a wristpendulum system in adults as follows: period = 2Pi [M*12 1 (M*L*g+kb2)] ' I 2 where M is the mass of the pendulum, L is its length, g is the acceleration due to gravity (a constant), k is the elastic stiffness of the attached spring, and b is the distance from the spring to the center of rotation of the pendulum (Turvey, Schmidt, Rosenblum & Kugler, 1988). By contrast with the high-energy musculotendon and linksegment potentials governing the timing law, the nervous system is envisioned as a geometry patterned by the layout of potentials arising from neural flow. This neural field of potentials, thus, envelops the potentials governing the timing laws and regulates energy flow. The signal difference between neural and muscular potentials is that the former are governed by laws of thermodynamics (i.e. , laws of irreversible flow) and the latter by mechanical laws (i.e. , where kinetic and potential energy are reversible). For this reason, the coordinate space of the nervous system is described by a scalinq law. The scaling law is an allometric one, based on the insights of D*Arcy Thompson (1942) on the relation between

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energy and form. It attempts to capture the way in which the nervous system is a transformational system, one that can, for example, transform articulator coordinates into task coordinates (Saltzman & Kelso, 1987). It rests, in part on the tensor network theory of the cerebellum and other brain structures (see, e.g., Churchland, 1986; Pellionisz & Llinas, 1979). While a description of the tensor network theory of the nervous system is beyond the scope of this chapter, the way in which neural potentials create a curvature in the geometry of the coordinate spaces of the nervous system may be described by the analogy between the trajectory of a single-point mass (a mechanical system) and the line connecting systems in an allometric plot (i.e., a plot in log coordinates), described by Kugler and Turvey (1987): Suppose that the motion of a particle in a field is examined and its trajectory in [displacement (X), displacement (Y), potential (V)] coordinates determined on three separate occasions is designated y1, y2 , and y3. In identifying the location of the particle in the field, (xi! yi, vi! it will be assumed that each location defines a minimum of a potential well. The resulting trajectory of points defines the layout of potentials in the field. If the potentials were uniformly distributed throughout the field, the particle would exhibit a straight line trajectory ...(the line connecting the minima). The nervous system, as an enveloping layout of potentials, transforms the mechanical timing law according to the curvature of logarithmic space in a plot relating period to that curvature. It identifies a trajectory of the same particle, under the influence of the same natural law, but in a different field. The new trajectory is to be attributed to the symmetry of the new field, not to a change in the symmetry of the law (p.222). This complementary relationship between the mass-spring pendulum system as a mechanical process, and the nervous system as a softly molded energy transformation process (escapement) is illustrated in Figure 1. A limit-cycle is created by the transformation from potential to kinetic energy and kinetic energy t o heat, and at the same time, the mechanical atomisms of the musculotendon and link-segment systems are softly assembled into a coordinative structure. The assumption that macroscopic order emerges in this way follows from the laws of thermodynamics, i.e., that there is a degradation of energy from microscopic to macroscopic states which results in increasing order in the latter (Kugler & Turvey, 1987; Wicken, 1988).

E.C. Goki’eki

218

S o f t Assembly of Macroscopic mechanical processes (mass-spring pendular system)

--___-Potential energy to kinetic energy

Kinetic energy to heat

Microscopic chemical-thermal process ( t h e nervous system) acts as s o f t l y molded escapement for pendular clocking)

Figure 1. Energy flow resulting from coupling of a neural (thermodynamic) field and the mechanical components of the link-segment and musculotendon systems. Modified after Kugler & Turvey, 1987. To summarize, it may be useful to distinguish two kinds of terminology in the ecological and dynamical approach, a language of natural laws (timing and scaling laws) (Kugler & Turvey, 1987) and a set of dynamical descriptors (e.g., Jeka & Kelso, 1989). In the former, coordination is considered as a soft assembly of microcomponents (coordinative structures), and in the language of dynamics, this is equivalent to studying the constraints that hold among variables in an equation of motion (i.e., an order parameter). The coordinative structure which emerges as a macroscopic mechanical (mass-spring pendular) system is assembled as a consequence of the energy flow between potentials in a patterned field (neural, environmental, etc.). The alternative dynamical description of a coordinative structure (using the geometric representation of phase space) is a layout of attractors and gradients, the shape of the oscillations towards which all trajectories tend. And finally, a softly assembled coordinative structure may dissolve and reassemble with changing values of the potentials in the patterned field, or, in alternative dynamical language, that microscopic variable in an equation of motion which changes the macroscopic order parameter is considered a control parameter.

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2. AN ECOLOGICAL AND DYNAMICAL APPROACH TO THE STUDY OF INFANT

LOCOMOTOR DEVELOPMENT 2.1.

Hypotheses

I next use the ecological research strategy to examine the following hypotheses in support of a theory of locomotor development based upon coordinative structures: (1) Infant prone rocking during early locomotor development exhibits limit cycle behavior because it reflects a soft assembly of gravitational and elastic potentials into a mechanical system in an equilibrium state (identifying an order parameter), (2) Infant prone rocking exhibits limit cycle behavior (identifying attractor dynamics), and (3) Postural asymmetry in head orientation and use of the hands to support the body against gravity reflects an asymmetrical layout of neural potentials which redistributes the symmetrical layout of skeletomuscular gravitational and elastic potentials into an asymmetrical layout compatible with crawling (identifying a control parameter). 2.2. Roaking as a layout of potentials in equilibrium.

gravitational and

elastic

I examine the first of these three hypotheses here with respect to data I collected in a longitudinal study of 15 infants (some of this data are reported in Goldfield, 1989; 1990). I was able to record 11 of the 15 infants (73%) on videotape while they rocked (and mothers reported that the other 4 infants rocked as well). The mean age of rocking was 222 days, and this was significantly earlier than the mean of first observation of crawling at 265 days, t(23) = 3.09, E < .05. In other words, none of the infants crawled without first exhibiting rocking at an (albeit transitory) earlier period. I conducted kinematic analysis of rocking in two dimensions as the basis for exploring the dynamics of the rocking trajectory. This analysis was based upon ten consecutive halfcycles of rostro-caudal motion for each of the infants and ten additional half-cycles for one infant who sustained his rocking for long periods. To examine whether rocking is governed by the reversible exchange of energy between gravitational and elastic potentials, I used the procedure proposed by Kugler and Turvey (1987) to identify whether the timing law proposed for a mechanical pendular clock holds for infant limb oscillation during rocking. If the timing of rocking is governed by a soft molded pendular system, then for each of the periods observed for each infant, there should be a unique amplitude. This follows because the amplitudes are not determined by a global

220

E.C. GokzJeU

distribution of forces, but rather, by the potential energy depots carried in the local muscle chemistry (Kugler & Turvey, 1987). To examine whether rocking is governed by a soft-molded pendular system, therefore, I examined whether all infants rock at the same period, and whether for each period there is a different amplitude. Table 1 presents the mean periods and amplitudes of rocking for each of the infants. The data indicate that infants do not rock with the same period, and for each period there is a different amplitude. This supports the claim that rocking is governed by a soft-molded clocking function. But why do infants rock at different periods? Another assumption about softly molded clocks is that they are sustained by two potentials, gravity and elastic potential. If so, then infants of different mass and with different elastic potentials would be expected to rock at different periods. It was difficult to evaluate this claim, because I did not have a direct measure of elastic potential (gravity is a constant). Table 1 Mean Period and Amplitude of Rocking Period .62 .75 .69 .59 .74 .90 .78 .80 .68 .71 .69

Amp 1itude 35.2 47.2 26.5 23.5 38.6 79.7 40.6 43.1 16.9 35.9 33.0

To circumvent this problem, I first computed an average elastic potential for the eleven infants by solving the PCM equation for elastic potential. I then used this value to derive an adjusted value of period. A regression analysis was then used to examine the relation between adjusted period, predicted by the PCM equation, and observed period. There was a significant R-square, R2 = . 4 8 , Q = .0163, supporting the claim that infants rock at different periods because rocking is sustained by gravitational and elastic potentials. The second step in the methodology of an ecological and dynamical approach involved identifying the scaling law: the geometry of the layout of potentials that makes it possible to

Soft Assembly of an Infant Locomotor Action System

22 1

sustain this period. Kugler and Turvey (1987) have proposed that a particular curvature of logarithmic space describes the layout of gravitational and elastic potentials. This curvature is created by the graph in logarithmic coordinates relating log period to log (MA1/16*LA1/2)(see Kugler & Turvey for the rationale underlying this equation) If , as is hypothesized here, gravitational and elastic potentials are in equilibrium during rocking, then the curvature of the logarithmic coordinate space relating log period to log (MA1/16*LA1/2) should identify whether the potentials are uniformly distributed in that space. (In other words, a straight line would be the expected outcome in a regression analysis if the potentials were in equilibrium). Figure 2 presents a plot in log coordinates of the relation between log period and log (MA1/16*LA1/2). As predicted, the regression coefficient indicates that a straight line describes the curvature of the logarithmic coordinate space created by the relation of these variables, R2= .832, < .01. Rocking does seem to be a layout of potentials in equilibrium.

.

-0.10

:

-0.12

-

-0.14

.

1 y = - 0.10674 + 2.5026~ R”2 = 0.832

-0.18 -0.20 -0.16

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1

.

-0.03

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-0.02

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Figure 2. Log period of rocking plotted against log (M”’6*L’”)

2.3.

Rocking as a limit-cycle process.

In order to identify the attractor dynamics of rocking, I used the kinematic data to construct phase-plane plots (Kelso, Vatikiotis-Bateson, Saltzman & Kay, 1985) of rocking by each of the infants. Figure 3 presents a representative plot. As is apparent by inspecting its geometry, the plot conforms to what is expected for limit-cycle oscillation: a steady closed oscillation in phase space that attracts all adjacent motions (see Abraham & Shaw, 1987 for discussion of attractors). The implication of this phase-plane plot is that potential

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(chemical) energy in neural microstructures is being converted into time-dependent kinetic energy:

This process drives the trajectory through phase space in an outwardly spiraling manner. The outward spiraling motion is prevented from growing indefinitely by a second energy-converting process that converts the outwardly spiraling kinetic energy into a micro heat mode (Newell, Kugler, van Emmerik & McDonald, 1989, p. 105).

0

100

200

300

DISPLACEMENT

Figure 3. A phase-plane portrait of infant rocking.

Postural asymmetry as a means of redistributing the layout of potentials in a state of equilibrium.

2.4.

To test my final hypothesis, that postural asymmetries evident at the stage of crawling redistribute the layout of potentials which were in equilibrium during the stage of rocking, I examine the role of lateral asymmetry in hand use in the transition from rocking to crawling. 1 specifically examine whether changes in lateral asymmetries in hand use during rocking and at subsequent stages provide evidence that hand u s e i s a control p a r a m e t e r d u r i n g p r o n e l o c o m o t i o n . Stated in another way, hand use reflects neural potentials which redistribute the gravitational and elastic potentials of the link-segment system so they are no longer in equilibrium. Hand preference data was collected with respect to performance on a maximum of six trials of reaching for a toy (a rattle or a set of keys) at each observation (see Goldfield & Michel, 1986 for details of the procedure). Figure 4 presents the proportion of times the preferred hand made initial contact with the toy during five weeks after the

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strongest hand preference. As has been reported in other studies (e.g., Ramsay, 1985), hand preference fluctuated between strong unimanual preference ( a score of 1.00) and ambilaterality (a score of .50): there was a significant

0

1

2

3

4

5

Weeks of Obsewatlon

Figure 4 . Periodic fluctuations in hand preference relative to peak of unimanual preference. Modified after Goldfield, 1989. difference over observations, E (6, 104) = 47.45, E < .001. Thus, hand preference fits the expected character of a control parameter, namely that its value changes in a regular way during the transition between stable states (i.e. , stages) But does lateral asymmetry drive the system into new states? Figure 5 presents the mean proportion of initial contacts by the preferred hand at the first observations of rocking,high creep, and crawling. During the period of first

.

,

5

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0.6

Rocking High Creep

2=

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Figure 5. Infant hand preference at three stages during the acquisition of crawling. Modified after Goldfield, 1989.

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E.C. Cokzfield

rocking, the seated infant was, on average, equally likely to use the right or left hand to make initial contact with a toy presented at midline. This was also true during the stage of high creep. However, at the first observation of crawling, the infant was significantly more likely to use the same hand on successive trials to make initial contact with the toy, E ( 2 , 30) = 11.41, E < .0002. If hand preference acts as a control parameter underlying the transition from rocking to crawling, how does it actually manifest itself as the infant uses the hands to attempt to locomote? Prior to crawling, infants use both hands to support the body as the legs attempt to propel it forward (transport). In order to actually displace the body forward along the support surface, though, one hand must be free to reach ahead to something which affords approach. Thus, in a sense, these two functional capabilities of the hands compete with each other when the infant tries to perform both at the same time: if he tries to reach he falls, and if he uses both hands for support he doesn't get anywhere. The hands (as articulators), in other words, are a limited macroscopic resource (i.e. , we have only two). This limited resource acts as a constraint on selecting the functional possibilities for use of the hands in particular tasks (see Goldfield, in preparation, and Reed, 1985 for a discussion of the impact of limited resources in selection of action modes). Lateral asymmetry in the use of the hands may resolve this competition for limited articulatory resources by providing an adaptive solution: division of labor between the hands. Instead of performing the functions of support and transport at the same time, reaching out with one hand is temporally sequenced with the other to maintain support (with the legs, an adequate tripod stance). The temporal alternation between support (stance) and transport that we refer to as crawling may result from the selection (by self-organization) of the use of one hand for reaching and the other to catch the fall precipitated by reaching. To examine this possible functional significance of lateral asymmetry in tlselectingtl the functions of the hands, 1 observed each of fifteen seated infants during a condition in which they were encouraged by the mother to approach an object. The overall hand preference (mean over observations) was used to classify each infant as either right or lefthanded. A second coder, blind to this classification, scored the hand on which the infant landed as he or she fell forward onto the hands. If hand preference determined the sequencing of the hands in performing support and transport functions, then there should be a close association between which hands lands on the support surface and the infant's preferred hand for reaching.

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225

Figure 6 presents the number of trials on which infants fell onto their preferred or non-preferred hand (they never landed on both hands simultaneously). There was a significant association between the infant's preferred hand and the order

60 I

I

Landing Hand Relative to Hand Preference

Figure 6. The association between hand preference and the lllandingll hand in falling from a seated posture onto the hands to begin to crawl. of hand contact with the support surface during falling onto the hands, a (1, N=ll) = 7 2 . 9 5 , E < .001. Infants with a right hand preference landed first significantly more often on their left (non-preferred) hand, and infants with a left hand preference landed significantly more often on their right (non-preferred hand). Thus, in falling from upright into a crawl posture, infants appear to be landing in a way that leaves their preferred hand free to reach ahead of them and begin to crawl (an interpretation supported in a study by Kamm & Thelen, 1989). If one adopts the assumption of an ecological approach that the nervous system does not control, but only complements the mechanical forces generated by the limbs, how might we understand the role of lateral asymmetries in brain organization for the development of hand use in tasks such as reaching and prone locomotion? Earlier, I described how the assembly of the mechanical degrees of freedom of the skeletomuscular system into a massto spring pendular system is accomplished relative gravitational and elastic potentials. The nervous system, for its part, functions as a soft molded escapement which transforms the mechanical system into a soft-molded clock. Implicit in the notion of an escapement is that by means of

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the the gating of neural energy flow, it is possible to 98tune19 elastic potential of the muscles (Kugler & Turvey, 1987). This suggests that lateral asymmetryin brain organization may make it possible to differentially tune the muscles on the right and left sides of the body so that their elastic potential is different. Differential elastic potential on the left and right sides of the body would result in different lengthtension relations for the muscles on each side (Feldman, 1986). If so, then one would expect to observe a difference in relative velocities of the right and left hands as infants alternate the hands as they reach out during crawling. I explored the possibility of asymmetry in the velocity of the hands during the first observations of infant crawling by comparing the mean off-surface time (in msec) of the right and left hands during crawling (a measure of velocity). A Friedman ANOVA indicated that the infant's preferred hand took less time to break contact with the support surface and then land again than did the non-preferred hand, X2 (1, N=ll) = 3.80, E < . 0 5 . Thus, as the infant first begins to fall forward onto the hands and locomote, it appears as if the hands alternate support (stance) and transport because one hand gets to the support surface first. As the second hand lags behind the first during the forward fall, it is placed slightly behind on the support surface, and a de facto sequencing begins. 3.0.

CONCLUSIONS: WHAT IS ASSEMBLED?

The ecological and dynamical approach is a functional one, i.e., it assumes that the dynamical systems which are assembled by thermodynamic flow processes have an emergent function. How are we to understand the emergence of function? In this concluding section, I briefly describe a model which I developed to explain the pattern of stages I observed in early locomotor development, of which the transition from rocking to crawling is a part (Goldfield, 1989). I propose that at any point in development, an infant uses whatever means he or she has available to satisfy an intention (e.g., locomoting) (see shaw & Kinsella-Shaw, 1988, for a discussion of intentionality in self-organizing systems). As the individual elements change, the organized behavior as a whole changes. Such fluidity in the composition of elements may be what gives behavior its inherent variability. A stage of behavior, in this view, may reflect a stable (albeit transitory) state resulting from a particular interaction of components, each with its own rate of growth. What are the locomotion-relevant capabilities of the young infant which both exhibit variability and interact functionally with each other? Goldfield (1989) proposes three capabilities: (1) orienting, the use of the eye-head system to maintain balance when the chest and abdomen are lifted off the support surface, ( 2 ) propulsion, use of the legs to push the body forward by kicking against the support surface, and (3)

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steering, use of the hands to change direction of body movement. Observed stages of locomotion, I argue, reflect the way in which the infant uses these three capabilities together in order to accomplish a particular task: steering the body through the environment with all four limbs while supporting the body against gravity. Goldfield (in press) has shown that the sequence of stages classically observed by Gesell and Ames (1940) and McGraw (1945) could be accounted for by specific combinations of these three capabilities (see Table 2). The stage of rocking Table 2 Stages according to their functional achievement Stage Pivot Low Creep Rock High Creep Crawl

Orienting No No Yes Yes Yes

Propulsion

steering

No Yes No Yes Yes

Yes Yes No No Yes

for example, is one in which the infant is able to orient to the environment in order to support the body against gravity, but is unable to either propel the body forward or steer it in a desired direction. Crawling, by contrast, accomplishes all three functions. What may hold the sequence together is the combination of three kinds of constraints: the infant's intention to locomote, the organismic constraints of the body (e.g. , body size, muscle strength, etc. ) , and the task demands of the environment (objects in the environment which afford approach). 4.

REFERENCE8

Abraham, R.H. & Shaw, C.D. (1987). Dynamics: A visual introduction. In F.E. Yates (Ed.), Self-organizing systems: The emergence of order (pp. 543-597). New York: Plenum Press. Bernstein, N.A. (1967) The control and regulation of movements. London: Pergamon Press. Bingham, G.P. (1988). Task-specific devices and the perceptual bottleneck. Human Movement Science, 7, 225-264. Churchland, P. (1986). Neurophilosophy. Cambridge, MA: MIT Press, Feldman, A.G. (1986). Once more on the equilibrium-point hypothesis (lambda model) for motor control. Journal of motor behavior, 18 , 17-54. Gesell, A. & Ames, L. (1940). The ontogenetic organization of prone behavior in human infancy. Journal of Genetic Psychology, 56, 247-263.

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Goldfield, E.C. (1989). Transition from rocking to crawling. Developmental Psychology, 25, 913-919. Goldfield, E.C. (1990). Early perceptual-motor development: A dynamical systems perspective. In H. Bloch & B. Bertenthal (Eds.) , Sensory-motor organization and development in infancy and early childhood. Dordrecht: Kluwer Academic. Goldfield, E.C. (in press). Dynamical systems in development: Action systems. In E. Thelen & L. Smith (Eds.), Dynamical approaches to development: Applications. Cambridge: MIT Press. Goldfield, E.C. (in preparation) Development of action systems. Oxford University Press. Goldfield, E.C. & Michel, G.F. (1986). The ontogeny of infant bimanual reaching during the first year. Infant behavior and development, 9 , 81-89. Jeka, J.J. & Kelso, J . A . S . (1989). The dynamic pattern approach to coordinated behavior: A tutorial review. In S.A. Wallace (Ed.), Perspectives on the control of movement, (pp. 3-45). Amsterdam: Elsevier. Kamm, K. & Thelen, E. (1989). Sitting to quadruped: A developmental profile. Paper presented at the annual meeting of the Society for Research in Child Development, Kansas City, Kansas. Kelso, J.A.S., Vatikiotos-Bateson, E., Saltzman, E.L. & Kay, B. (1985). A qualitative dynamic analysis of reiterant speech production: Phase portraits, kinematics and dynamic modeling. Journal of the Acoustical Society of America, 77, 266-280. Kravitz, H. & Bohm, J. (1971). Rhythmic habit patterns in infancy: Their sequence, age of onset, and frequency. Child Development, 42, 399-413. Kugler, P.N. & Turvey, M.T. (1987). Information, natural law, and the self-assembly of rhythmic movement. Hillsdale, N.J. Erlbaum. Kugler, P.N., Kelso, J.A.S. & Turvey, M.T. (1980). On the concept of coordinative structures: I. theoretical lines of convergence. In G. E. Stelmach & J. Requin (Eds.) Tutorials in motor behavior, (pp. 3-47). Amsterdam: NorthHolland. McGraw, M. (1945). The neuromuscular maturation of the human infant. New York: Hafner. McMahon, T . A . (1984). Muscles, reflexes, and locomotion. Princeton: Princeton University Press. Newell, K.M. , Kugler, P.N. , Van Emmerik, R . E . & McDonald, P.V. (1989). Search strategies and the acquisition of coordination. In S . A . Wallace (Ed.), Perspectives on the coordination of movement (pp. 85-122). Amsterdam: Elsevier. Pellionisz, A. & Llinas, R. (1985). Tensor network theory of the metaorganization of functional geometries in the central nervous system. Neuroscience, 1 , 245-273. Pohl, P. (1977). Tempo change during body rocking. Developmental Medicine and Child Neurology, 19, 485-488. Prechtl, H.F.R. (1974). The behavioural states of the newborn infant (a review), Brain Research, 76, 1304-1311.

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Ramsay, D . S . (1985). Fluctuations in unimanual hand preference in infants following the onset of duplicated syllable babbling. Developmental Psychology, 21, 318-324. Reed, E.S. (1985). An ecological approach to the evolution of behavior. In T. Johnston & A. Pietrewicz (Eds.), Issues in the ecological study of learning (pp.357-383). Hillsdale, N. J. : Erlbaum. Saltzman, E. & Kelso, J.A.S. (1987). Skilled actions: A taskdynamic approach. Psychological Review, 94, 84-106. Schmidt, R.C. & Turvey, M.T. (1989). Absolute coordination: An ecological perspective. In S.A. Wallace (Ed.), Perspectives on the coordination of movement (pp. 123-156) Amsterdam: Elsevier. Shaw, R. & Kinsella-Shaw, J. (1988). Ecological mechanics: A physical geometry for intentional constraints. Human Movement Science, 7 , 155-200. Thelen, E. (1981). Rhythmical behavior in infancy: An ethological approach. Developmental Psychology, 17, 237257. Thelen, E. (1984). Learning to walk: Ecological demands and phylogenetic constraints. In L.P. Lipsitt (Ed.), Advances in infancy research (Vol. 3, pp. 213-250). Norwood, N. J. : Ablex. Thompson, D. (1942). On growth and form. London: Cambridge University Press. (Original work published 1917). Thompson, J.M.T. &I Stewart, H.B. (1986). Nonlinear dynamics and chaos. Chichester: Wiley. Turvey, M.T., Schmidt, R.C., Rosenblum, L.D. & Kugler, P.N. (1988). On the time allometry of co-ordinated rhythmic movements. Journal of theoretical biology, 130, 285-325. Wicken, J.S. (1988). Thermodynamics, evolution, and emergence: Ingredients for a new synthesis. In B.H. Weber, D.J. Depew & J.D.Smith (Eds.), Entropy, information, and evolution: New perspectives on physical and biological evolution. Cambridge, MA: MIT/Bradford. Wolff, P.H. (1967). The role of biological rhythms in early development. Bulletin of the Menninger Clinic, 31, 197-218. Wolff, P.H. (1968a). Stereotypic behavior and development. The Canadian Psychologist, 9, 474-484. Wolff, P.H. (1987). The development of behavioral states and the expression of emotions in early infancy. Chicago: University of Chicago Press.

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The Development of T h i n Control and Temporal Or anization in 800rdhatei-lAction J. Fagard an%PH.Wolff (Editors) 8 Ekvier Science Publishers B.V., 1991

23 1

Timing invariances in toddlers' gait Blandine Bril & Yvon BrenKre Laboratoire de Physiologie du Mouvement, UA CNRS 631, UniversitC Paris XI, F-91405 Orsay (France)

INTRODUCTION There are many ways of considering the temporal structure of gait. Gait movement can be "divided up" into phases according to diverse parameters. Figure 1 clearly shows that gait movement appears, at the level on which behavioral observations are made, as a succession of unipodal and bipodal stance phases. A single step is then defined as the succession of a double support phase and a single stance phase. A step cycle is generally defined as the movement camed out between two successive foot contacts of the same foot; this is equivalent to two successive single steps. Many studies that focus on the gait of adults or children give the duration of phases in percentages, for double-support as well as for swing or stance. The authors implicitly consider the relative invariances of gait movement even if they do not openly discuss its temporal structure. Values for the relative duration of the different phases vary greatly from one study to the other. For example, Jansen, Vittas, Hellberg & Hansen (1981) find 36% for the duration of the double support phase at a fixed velocity (1.1 d s ) , whereas Kirtley, Whittle & Jefferson (1985) find an average of 8.5% for an average velocity of 1.45 m/s. When velocity is taken into account, most of these studies attribute smaller values (in relative terms) to double-support duration for higher velocities (Grieve and Gear, 1966; Larsson, Odenrick, Sandlund, Weitz & Oberg, 1980; Murray, Kory, Clarkson & Sepic, 1966). Some studies state that double-support decreases down to zero as speed increases - at which point walking switches on to running (Grieve & Gear, 1966; Larsson et al., 1980). Whereas many studies give information concerning the relative duration of the stance phases of gait, very few, to our knowledge, explicitly discuss the theoretical implications of the temporal structure of gait movement, and of its invariances in particular. Furthermore, when temporal patterns are analyzed, segmental kinematics of the lower limbs are chosen to determine the phases of gait rather than more global parameters such as unipodal or bipodal support (Shapiro, Zernicke, Gregor & Diestel, 1981; Clark & Phillips, 1987). These

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two studies place more emphasis on the temporal relative invariances than on the differences, even though the published data may question these invariances. The authors of these two studies each have completely different theoretical viewpoints. Shapiro et al. (1981) conclude that their data support the generalized motor program theory. According to this view, relative timing is an invariant of motor program which is "called up" prior to the execution of the movement. The opposite view is held by Clark & Phillips (1987). They favor an interpretation stemming from the dynamical perspective (Kugler et al., 1982) in which relative timing invariances result from the use of a given "coordinative structure". A coordinative structure is defined here as "a unit of motor control which governs a group of muscles as it operates over one or more body joints" (Clark, 1982: p 165). They state that step cycle organization in the infant gait is similar both in absolute and relative timing to that of the adult, and conclude that as early as three months after onset of independent walking, toddlers "exhibit step organization that is remarkably similar to that of the mature walkers" (Clark & Phillips, 1987: p43).

step cycle

1111111

l e f t foot right foot 1111111

Figure 1. Descriptive schema of gait cycle and stick diagram of a child 12 months after onset of I.W. (On the rigth of the stick diagram, the Philippson step cycle defined from the flexion-extension of the knee: phase E2, from FC to deep knee flexion (DKF); E3 from DKF to T O F from TO to DKF, El from DKF to FC).

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However, both studies implicitly consider that the temporal structure of gait as defined by the Philippson phases (fig. 1) is a good way to describe the organization of adult and child gait. In a developmental study of another locomotor movement, hopping, Roberton & Halverson (1988) explore the question of relative timing in relation to developmental qualitative changes in segmental coordination. They find very few relative timing invariances which span the entire duration of the longitudinal study. Only the time elapsed between the ground-touching and the deepest knee flexion appears to stay invariant in relative values from 3 to 18 years of age. The interesting point is that the authors suggest that the same event exists in walking (E2 phase of Philippson). Different possible explanations are discussed, and the issue is far from been settled (see chapter 16 of this book). These three studies on locomotor skills are based on an analysis of the kinematics of the limbs. But many other ways of "dividing up" gait movement are also possible. They stem from another choice of cues such as the acceleration of the center of gravity (a global expression of the movement), the displacement of the center of foot pressure, or the onset of muscular activity of different muscles, among others. To confront data resulting from different ways of considering gait organization would add much complexity to theoretical interpretation. The important point, as suggested by Heuer (1988), concerns the "motor delay" which represents the time interval between a central command and its peripheral registration. The motor delay in turn depends on which peripheral effect is taken into account, i.e. forces, kinematics of limb segments, muscular activity, etc. In this chapter we will question and discuss the possible significance of some temporal characteristics of gait as they are observed at a peripheral level (issued from the displacement of the foot pressure and the acceleration of the center of gravity) during the first two years of independent walking. The focus will be on the absolute and relative invariances of gait movement in relation to changes of other postural or locomotor parameters during early walking. EXPERIMENTAL SETTING

The data presented here are issued from a longitudinal study of five children (4 boys and one girl). The gait sequences of each child were recorded once a month during the first six months after onset of independent walking, then every six months during the following 18 months. Data were recorded by means of a large force plate and synchronized with a video system described in detail in Brenibre, Bril & Fontaine (1989). In each session the child walked about 20 sequences of steps on the force plate and several steps on the walkway ahead of it. Each sequence began with the child standing still and unsupported, barefoot, at the upper edge of the force plate (see figure 2.a). The child was then asked to walk towards its mother to the other side of

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the walkway. Only sequences leading to a regular and steady-state gait were taken into account for analysis.

DEFINITION OF TEMPORAL PARAMETERS. The different phases of gait movement have been defined as follows: - The initiation of gait movement from the initial upright posture starts with the onset of dynamic phenomena (to) and ends at the end of the first step (tvl); - One step is the succession of a double support stance phase (hence referred to as DS) and a single support stance phase (or swing phase of the controlateral leg, hence referred to as SW).The double support phase starts at foot contact (FC) and ends with "toe off' (TO). Time of FC corresponds to the abrupt variation in the curve of Xp, which indicates that the swinging foot has just touched the ground and that the center of foot pressure starts to move toward this foot. The end of DS is not as easy to determine. For Yp, the "levelling off' phases correspond to the time when the center of foot pressure is situated under the supporting foot. The alternation of plateaus corresponds to the alternation of the feet on the ground while walking. The y!evelling off" phases of the Xp and Yp curves start at the precise time that YG shifts sign (the curve of YG crosses the baseline). Consequently, we consider that the change in sign of YG determines the time at which the swing phase begins, which is the time of "toe off". Dynamically speaking, it is the shift of sign of YG that indicates the alternate phases of acceleration toward one foot or the other. Taking into account these definitions, the following temporal parameters were used in the analysis ( see figure 2): - T : duration of a single step. It is the time elapsed between two FCs; - DS : duration of a double-support phase. It is the time elapsed between FC and TO of the controlateral foot. The relative duration of DS is the ratio of DS to total duration of the step; - v : velocity. It is the mean velocity of a sequence of steps computed as the total length walked on the total duration of the sequence of steps; - f : frequency. It is the number of steps walked per second. THE TEMPORAL STRUCTURE OF TODDLERS' GAIT AND ITS RELATION TO SPEED After the end of the first month of independent walking (hence referred to as I.W.) the duration of steps decreases significantly as speed increases. This result confirms those of a previous sample of children under six months of I.W. (Bril & Brenibre, 1989), and concords with data found in the literature on gait for children (Beck et al., 1981) and adults (Grieve and Gear,

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Figure 2. A/Drawing of the force plate and measure of the experimental parameters. B1 Sequence of steps for a child showing 1) the transient phase between upright posture and steady state gait (in grey), 2) several steps at steady state velocity. XG gives the instantaneous velocity of the center of gravity along the antero-posterior axis; Xp and Yp respectively give the displacement of the center of foot pressure along the antero-postenor axis and the lateral axis; k,VG and XG give the accelerationof the center of gravity along the three axes. is the onset of dynamic phenomena and tv 1 the end of the first step. FC is the instant of foot contact and TO the time of "toe off'.

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1966; Kirtley et al., 1985; Murray et al., 1966; etc.). Figure 3 summarizes the data at different times: one month, 2 months, 3 months, 5 months, 12 months, 18 months after onset of I.W.The graphs clearly show the increasing range of speed displayed by children as walking experience increases (Bril & BreniBre, 1990; submitted). The duration of the double-support phase and swing phase 1 month

2 months

T

’

sw

O

O

7

DS

(msl

OC/’

0.b

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0.io

0.b

1.io

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o b

oio

ob

1.io

1 L

v (mls) 3 months

5 months

7w803..

Figure 3. Development of the covariation between the temporal parameters and speed, during the first two years of I.W.:( m ) duration of step, ( H ) swing and ( A ) double support phases.

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Toddlers'Gait

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showed the same trend but the correlation became significant only during the second month of I.W. for DS and during the third month for the swing phase. Concerning the frequency of steps, data showed a value of 2.5 steps per second during the first two sessions of observation, then an increase at two months of I.W. to 3 steps per second. The average frequency remained stable up to five months of I.W., and then showed a slight but constant decrease (Bril & BreniCre , 1990). Now the main question remains: since the duration of step and of its two phases varies according to speed, do absolute or relative temporal invariances exist, and what are their significance?

ABSOLUTE TEMPORAL INVARIANCE: THE DURATION OF THE FIRST STEP The duration of the movement starting with the first dynamic phenomena on the antero-posterior axis (Q) and ending with the end of the first step (tvl) has been analyzed from the data of 8 children having between 100 and 200 days of I.W. (Brenibre et al., 1989). The sequences of steps chosen for the analysis were those in which the child was absolutely still before starting to walk. The mean value of this first step varies between 470 ms and 730 ms, depending on the child. These two values respectively correspond to a mean progression velocity of the sequence of steps of .70m/s and .87 m/s. There was no correlation between the duration of the first step and the progression velocity of the forthcoming sequence of steps. Nor did a correlation exist with the frequency of steps (fig. 4). The duration of the first step thus appears to be a temporal invariant of the initiation of gait when the child starts independent waking. This absolute invariance can be discussed in relation to what has been shown for the adult. The movement, which occurs during the transient phase between upright posture and gait, can be compared to an oscillating system which begins its oscillating movement at its natural frequency. As is the case for the adult (Brenibre & Do, 1986), and contrary to steady state gait, duration of this first step and progression velocity are independent. In addition, this value of natural frequency corresponds to the semi period of the oscillation of either an inverted single pendulum which depends only on the position of the center of gravity with respect to the ground ( T / 2 = x ( l / g ) 1/29 where "1" is the position of the center of gravity with respect to the ground), or an inverted compound that would have the same mass, the same moment of inertia and the same position of the center of gravity a s the child (T / 2 = x ( ( IG + m 1 2 ) / m g 1 ) 1'2, where "I(y is the moment of inertia of the body, and "m" the subject's mass; Breniere et ai., 1989).

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0

.25

.50

.75

1.

1.25

1.50

v(mn)

1.75

Figure 4. Duration of the first step in children, compared with adult data. For the children each dot ( 0 ) corresponds to the value of tvl for one sequence of steps. For the five adults who constitute a reference group, each dot (+)corresponds to a mean value calculated over 7 sequences of steps executed at the same speed (from Brenibe, Bril & Fontaine, Journal of Motor Behavior, 21, pp 20-37, 1989). In the first case corresponding to the smaller values of the duration of the first step, the child seems to behave as if he has integrated the vertical position only of hisher center of gravity, but not the body inertia. In the other case, it would appear that, as for the mature gait, the child has integrated not only the position of hisher center of gravity, but the body‘s mass and moment of inertia as well. In either situation, it appears that anatomical parameters have a dynamic implication in the transient phase of gait from the initial standing posture. The duration of the first step is a good example of an absolute timing invariant. We may infer from this result that in order to be able to initiate a sequence of steps, the child must have integrated anatomical parameters of his body.

RELATIVE TEMPORAL INVARIANCE: DURATION OF THE DOUBLE-SUPPORT PHASE DURING STEADY STATE GAIT Certain characteristics of children gait may stem, at least in part, from the difficulty for the child to master unipodal stance in a non static situation (BreniCre & Bril, 1988; Bril & Breniere, 1990). It is important therefore to consider a gait cycle as the succession of two single steps, meaning two occurences of a double stance phase and a single stance phase, whereas a cycle is commonly described as a stance phase followed by a swing phase. To describe gait movement only in terms of stance and swing observed from the kinema-

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Timing Invariances in Toddlers’ Gait

tics of one lower limb masks the fact that gait is the result of the two lower limbs, and that one of the main constraints is the demand for equilibrium. Some authors have interpreted the shorter duration of swing in children (compared to adults) as an indication of instability (Sutherland, Olshen, Cooper & Woo, 1980). The same idea was developed by Bril & BreniCre (1988, 1989), who interpreted the greater relative duration of the doublesupport phase as a necessary time period for balance recovery. The longitudinal data confirm this interpretation. Figure 5 illustrates the development of the duration of DS during the first two years after onset of I.W.As for the development of postural and locomotor parameters (Bril & BreniCre, submitted), there was at first a large decrease in relative terms (from 38% at onset of I.W. to 28% in average after 5 months if I.W.), followed by a slighter decrease. After two years of I.W.the value of DS is still greater than for adults (figure 5 & 6). Individual data showed an important variability factor between children. One of the children had a very important decrease in the duration of DS, from 38 % at one month to 28 % at 5 months, and 20% at 18 months, while another one had a decrease of only 4% during the first 5 months of I.W. (from 31% to 27%).

0

5

10

15

20

25

months after onset of I.W. Figure 5. Development of the relative duration of the double-support phase in relation to walking experience. The main characteristic of the relative duration of DS is that it remains invariant whatever the walking velocity (figure 6). These data confirm Shapiro et al. (1981) results, as well as Clark & Phillips (1987), even though definition of the phases was based on different criteria. The proportional duration model (Gentner, 1987) applied to the DS data shows that there was a great variability at one month (the relative duration of DS varies from 20 to 45%). After that period the values were more gathered around the mean value (figure 7). The correlation between the relative duration of DS and the total

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duration of the step was not significant, except at five months of I.W. (x=-.5, ~ 4 0 1 ) This . value confirms the data obtained in a previous study (Bril & Brenibre, 1989) where this correlation was significantly negative for 5 children out of 11 observed between 140 and 172 days of I.W.

t/T4' ..

r I

0' 0

r .

.25

.50

.75

a

In0

125

Is0

l.75

a00

v

(m/s)

Figure 6. Relative values of the double-support phase in relation to average progression velocity, for 10 children with 150 to 200 days of I.W. For the children, each dot ( 0 ) corresponds to the mean value of the parameters representing one sequence of steps. For the three adults, each dot (+)corresponds to a mean value calculated on 10 sequences of steps executed at the same speed (from Bril & Brenibre, 1988, Posture and Gait: Development Adaptation and Modulation. Amblard B., Berthoz A. and Clarac F. (eds.), Elsevier Science Publishers B.V., p 27). The interpretation of this data is not easy. If, after onset of I.W., the duration of the DS phase depends on the time needed to balance recovery, we can hypothesize that the duration of DS will decrease as walking experience increases. The great variation in DS duration observed before two months of I.W. can be interpreted in a similar way: increasing stability reduces variability (figure 7). The development of the child propelling strategy may explain, at least in part, the important changes in DS duration observed during the first 5 months of LW. as compared with the following months (see figure 5). In another study we have showed that at the time of foot contact, contrary to the adult, the young toddler is dynamically in the situation of a fall; the value of the vertical acceleration is negative (see figure 2B; Breniere & Bril, 1988, submitted). For the adult, the vertical acceleration is always positive at heel strike. This means that the adult is able to initiate a propulsing phase during the swing phase - that is during unipodal stance - which is not the case in children. Furthermore, the vertical acceleration is correlated with speed from the second month of I.W. to the 6-8 month period. The value of this correlation decreases from the fifth month on, and it is no longer significant

24 1

Timing Invariances in Toddler' Gait

during the second year of I.W. (Brenikre & Bril, submitted). These characteristics of the propelling strategy of the child are interpreted as a lack of unipodal stance control that could be, in part, responsible for the two-phase development of the relative duration of double-support phase. 1 month

050

0 50

2 months

t/T 0 40-

0 30-

OM

0 20-

T (ms)

12 months 0 40

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Figure 7. The proportional duration model: development of relative values of doublesupport phase in relation to the total duration of steps at different periods after onset of independent walking.

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The results of the relative duration of DS for all values of the total duration of the step and at different periods after onset of I.W., is puzzling. The previous discussion established not only that toddlers and adults use different strategies to propel themselves, but that there is a change in the propelling strategy of children after approximately 5 months of I.W. The existence of temporal relative invariances in young walkers as well as in adults regardless of the propulsing strategy used suggests that the invariances in relative timing of children and adults could well result from the segmental organization which characterizes adult or child gait. For adults, the segmental kinematics show that joint angle patterns are invariant, and do not change with walking speed (Winter, 1983). As invariances in the relative duration of DS and SW have been found in children as well as in adults (figure 6 & 7) we can hypothezise that a given propulsing strategy leads to joint angle patterns which remain the same over a wide range of speed. In other words, different strategies could lead to similar relative temporal invariances in movement, as seems to be the case with handwriting (Wann & Jones, 1986). At this stage of the study we can only suggest that a detailed analysis of the segmental kinematics during the development of gait, compared with mature gait, could help to point out the analogies and differences of the segmental organization of movement. Since different propulsing strategies could lead to analogous relative timing invariances, we can hypothesize that the temporal characteristics of gait comes from the segmental kinematic organization, as would suggest the results of both Shapiro et al. (1981) and Clark and Phillips (1987).

CONCLUSION Our results on early walking show that absolute and relative timing can be found in gait movement as soon as a few weeks after onset of independent walking. We have suggested that absolute invariants in the initiation of gait are primarily set up by anatomical and body segment parameters. The developmental analysis of such invariances suggests that children have to learn to optimize the use of the biomecanical properties of their bodies. Relative invariants are more difficult to interpret. We have seen that for each age and regardless of the speed of walking, the relative duration of the double-support phase is constant. However, the relative duration of the double-support phase decreases with walking experience. A very important decrease appears during the first 5 months of independent walking, followed by a slighter decrease during the 18 following months. If the relative timing is, at least in part, set up by the kinematic of the limb segments, as suggested by Roberton and Halverson (1988), then its relative timing invariance would signify that for a given age the kinematic of the limbs is stable accross speed. Here further investigation is needed to test this hypothesis.

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However it is important to note that the similarity between the temporal structure of gait in toddlers and adults insofar as its relation to speed is concerned may mask the remarkable differences in propulsing strategies.

REFERENCES Beck R., Andriacchi T.P., Kuo K.N., Fermier R.W. & Galante J.O. (1981) Changes in the gait pattern of the growing children. The Journal of Bone and Joint Surgery, 63A(9), 1452-1456. Brenibre Y. & Do M.C. (1986) When and how does steady state gait movement induced from upright posture begin ? Journal of Biomechanics, 19, 1035-1040. Brenibre Y . & Bril B. (1988) Pourquoi les enfants marchent en tombant alors que les adultes tombent en marchant ? C.R. Acad. Sci. Paris, 307111, 617-622. Brenibre Y. & Bril B. (1991) Why do the children walk in falling during the first four years of independent walking? (submitted) Brenihe Y., Bril B. & Fontaine R. (1989) Analysis of the transition from upright stance to steady state locomotion for children under 200 days of autonomous walking. Journal of Motor Behavior, 21, 20-37. Bril B. & Brenibre Y. (1989) Steady state velocity and temporal structure of gait during the first six months of autonomous walking. Human Movement Science, 8, 99-122. Bril B. & Brenibre Y. (1990) How does the child modulate his progression velocity during the first 18 months of independent walking ? In T. Brandt, W Bles & M. Dietrich (eds.), Disorder of Posture and Gait, Stuttgart: Georg Thieme Verlag. Bril B. & Brenibre Y. (1991) Why does postural requirement restrain progression velocity in young walkers ? (submitted). Clark J.E. (1982) The role of response mechanisms in motor skill development. In The Development of Movement Control and Co-ordination, Kelso J.A.S. & Clark J.E., New York: J.Wiley & Sons. Clark J.E. & Phillips S.J. (1987) The step cycle organization of infant walkers. Journal of Motor Behavior, 19, 421-433. Gentner D.R. (1987) Timing of skilled motor performance: tests of the propotional duration model. Psychological Rewiev, 94, 255,276.

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Grieve D.W. & Gear R.J. (1966) The relationship between length of stride, step frequency, time of swing and speed of walking for children and adults. Ergonomics, 5, 379-399. Heuer H. (1988) Testing the invariance of the relative timing: Comment on Gentner (1 987). Psychological Review, 95, 552-557. Jansen E.C., Vittas D., Hellberg S & Hansen J. (1981) Normal gait of old and young men and women. Acta Orthop. Scand., 53, 193-196. Kirtley C., Whittle M.W. & Jefferson R.J. (1985) Influence of walking speed on gait parameters. Biomedical Engineering, 7, 282-288. Kugler P.N., Kelso J.A.S. & Turvey M.T. (1982) On the control and coordination of naturally developing systems. In Development of Movement Control and Co-ordination, Kelso J.A.S & Clark J. (eds.),New York: J. Wiley & Sons. Larsson L.E., Odenrick P., Sandlund B., Weitz P & Oberg P.A. (1980) The phases of the stride and their interaction in the human gait. Scand. J. Rehab. Med, 12, 107-112. Murray M.P., Kory R.C., Clarkson B.H. & Sepic S.B. (1966) Comparison of free and fast speed walking patterns of normal men American Journal of Physical Medecine, 45, 8-24. Roberton M.A. & Halverson L.E. (1988) The development of locomotor coordination: longitudinal change and invariance. Journal of Motor Behavior, 20, 197-241. Schmidt R.A. (1985) The search for invariance in skilled movement behavior. Research Quarterly for Exercice and Sport, 56, 188-200. Shapiro D.C., Zernicke R.F., Gregor R.J. & Diestel J.D. (1981) Evidence for the generalized motor programs using gait pattern analysis. Journal of Motor Behavior, 13, 33-47. Sutherland D.H., Olshen R., Cooper L. & Woo S.L. (1980) The development of mature gait. The Journal of Bone and Joint Surgery, 62A, 336-353. Wann J.P. & Jones J.G. (1986) Space-time invariances in handwriting: Constrasts between primary school children displaying advanced or retarded handwriting acquisition. Human Movement Science, 5, 275-296. Winter D.A. (1983) Biomechanical motor patterns in normal walking. Journal of Motor Behavior, IS,302-330.

The Development of Thin Control and Temporal Or anization in 8mrdinated Action J. Fagad anjP.H. Wolff (Editors) 0 Elsevier Science Publishers B.V., 1991

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T h e d e v e l o p m e n t of i n t r a l i m b c o o r d i n a t i o n in t h e f i r s t six m o n t h s of walking

Jane E. Clark and Sally J. Phillips Biomechanics Laboratory, Department of Kinesiology, University of Maryland, College Park, M D 20742 USA

Abstract Our previous work on the development of temporal organization in walking revealed that interlimb (i.e., between limb) coordination was adult-like with the infant’s first walking 5te s. In the present paper, we describe our efforts to study intralimb (i.e., witiin limb) coordination. Using a dynamical systems approach, we argue that the leg motion seen in walkin can be modeled as a low dimensional limit cycle attractor. Coordination wit in and between the le s, then, is viewed as the couplin of these limit cycle systems. H e r e we descri e how intralimb coupling can \e expressed in terms of the phasing relationship between the thigh and shank’s motion. W e then present data on this phasing relationship in one infant over her first six months of walking and compare it to that of a n adult. Finally, we argue that the principles of dynamical systems offer a predictive and generative framework within which t o understand the development of coordination.

a

t

1. I n t r o d u c t i o n

To walk, humans must coordinate their limbs in such a way as to produce a ait that will move them in the desired direction and prevent them from falling. the task is complicated further in that a variety of speeds - some quite fast may be required and the environment in which walking occurs is often changing. The achievement of walking seems all the more remarkable when we consider the vast number of component elements that contribute to this simple human act. With a nervous system comprised of billions of neurons and a musculoskeletal system with over a thousand muscles containing thousands of fibers, the complexity of assemblin the constituents into a well ordered but flexible organization appears formi able. And yet that is precisely the problem facing us when we cross a busy street o r make our way throu h a crowded room. The problem becomes more daunting when we consider t e development of walking. Humans are not capable of walking a t birth, indeed they take about one year before they a r e capable of achievin this feat. And as many have argued, it is many more years before they evi ence a mature walking pattern. Indeed some have suggested that it is not until 3 years and possibly as late as

cf

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7 years of age before walkin is mature (Bernstein, 1967; Okamoto & Kumamoto, 1972; Sutherland, O k h e n , Cooper, & Woo, 1980). But in what ways is the infant’s walking pattern immature? When the infant attempts her first walking ste s is the temporal organization of her leg action different from that of a n adult. In previous work, we have shown that the organization between the two le s (i.e., the interlimb coordination) exhibited b newly walking infants is adult-ike, although more variable (Clark, Whitall & $hillips, 1988). However, after only three months of walking, these infants gained a consistency in their interlimb coordination that did not differ from adults. In the present cha ter, we explore another aspect of temporal organization, namely intrayimb coordination or the relationships within a leg. Is it possible that this form of coordination, also is adult-like very early in the development of walking? We begin the chapter with a brief examination of past approaches to understanding the development of locomotion before detailing the approach we have ado ted. We next resent data from our laboratory on an infant’s first six mont s of walking. Finally we conclude with an argument f o r the advantages of using the dynamical systems approach for the study of coordination.

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2. A framework for t h e study of locomotion In the past, the study of locomotion, and walking in particular, has been approached from two quite diverse experimental traditions, one biomechanical and the other neurophysiological. Interestingly, both have their roots in seminal work done around the turn of the century that resulted in establishin firm foundations for both traditions, but little precedent for interacting wit! each other. The biomechanical approach to locomotion has been focused primarily on describing movement, estimating forces and develo ing mathematical models. Many of the advances made have been tied to the fevelopment of technolo Pioneering work by Muybridge (1887/1955) and Marey (1886) resulted in t g advancement of photographic techniques for recording movements. Later scientists such as Fischer (1899) and Elftman (1934) calculated t h e instantaneous values for the position, velocity and acceleration of various body segments during movement as well as calculating the ground reaction forces and pressure distribution in the stance phase of gait. Newtonian motion equations were applied to link-segment models of the human body by Elftman (1939) and Bresler and Frankel (1950) to estimate kinetic parameters in terms of resultant muscle moments of force and joint reaction forces during walking. Electromyo raphy added information about which muscles were active during the gait cyc e. By the mid-l970s, researchers were using sophisticated muscle models and optimization techniques to redict the load-sharing and individual muscle-tendon forces in locomotion ( t h a o & Rim, 1973; Seireg & Arvikar, 1975). Although biomechanical models of gait have become more elaborate, explicit explanations about the activation of muscle forces are lacking. Neurophysiological models address the issue of neural activation of muscles, but they ignore the mechanical context within which the movement occurs. Sherrington (1910) and Brown’s (1911) observations that locomotor movements in the cat’s hindlimb could be generated b the isolated lower segments of the spinal cord, set in lace a model o?motor control and coordination in which the animal’s beRavior was considered to result solely from the central nervous system (CNS). Locomotion, in this view, arises from CNS structures, referred to as central pattern generators (CPG) which set the sequencing and timing of muscle activation. Subsequent work would demonstrate the importance of sensory feedback to modulate the CPG output

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(cf. Grillner, 1981). While it is true that neural structures and the mechanical context within which the movement is performed a r e im ortant in movement coordination and control, the role each plays is far less ogvious. For example, the CPG is clearly not a hard-wired circuit that contains the code for a specific act. These a r e multifunctional structures that can produce backward and forward locomotion, a feat requiring a change in the temporal relationship between joints of the leg (Grillner, 1985). These are also not circuits that have fixed relationshi s with the periphery. Bernstein (1940/1984) as long ago as 1940 recognizec! the nonlinearities inherent in the neuromusculoskeletal system that precludes a one-to-one correspondence between a neural signal and the resulting movement. Indeed it was the rediscovery of Bernstein and his insights into these issues of motor control and coordination that lead to the emergence of an alternative to the neurophysiological and biomechanical models. This alternative model finds order and regulation in self-organizing properties of open, nonequilibrium systems comprised of many constituent elements (Kugler, Kelso, & Turvey, 1980; Schoner, Jiang, & Kelso, 1990; Schoner & Kelso, 1988). In this perspective, locomotor patterns a r e seen a s emerging from the collective dynamics of all contributing subsystems, includin the nervous system and the musculoskeletal s stem. In addition, the behaviora pattern emerges from the constraints offeredYby the environment within which the behavior occurs and the task itself (e.g., walking fast or walkin around objects). Referred to as coordinative structure theory (Kugler, et af., 1980), attern theory (Schoner & Kelso, 1988), or as we prefer, dynamical dynamic t eory, this erspective on motor coordination finds its origins in the systems physical theories of giolo (Pattee, 1977; Yates, 1982), mathematical biology (Rosen, 1970), n o n e q u i l i f h m thermodynamics (Morowitz, 1968; Nicolis & Prigogine, 1977), and synergetics (Haken, 1983). A central characteristic of these theories is their view that complex s stems consist of collectives of energy flows that interact in such a way that be avioral patterns a r e exhibited. T h e s atiotemporal order that is found in these patterns is an emergent property of t e system. Movement patterns such as walking, therefore, a r e viewed as emer ing from the constraints of the organism, environment, and task. bynamical systems theory offers powerful concepts and analytical techniques for understanding patterned movement. First, it provides a means by which to capture a low dimensional description of a high dimensional system. capture systems containing many degrees Put another way, it provides a wa? of freedom (e.g., the CNS with 10 neurons, musculoskeletal system with over a 1000 muscles, etc) into a virtual system of f a r fewer degrees of freedom. Thus for walking that arises from a high dimensional system, the form of the motion may be described by a collective variable or order arameter that yields a low dimensional description (Schoner & Kelso, 1988f These low dimensional descriptions enjoy special dynamical solutions referred to as attractors. An attractor lives in state space and is defined as a low-dimensional subset of that space to which all nearby trajectories converge (Abraham & Shaw, 1982). Walking, or any coordinative structure, may be seen as the behavioral unit that the attractor captures. The attractor is more than a representation of the motion, it also provides predictions about the behavior of the system it represents. Thus if we can map locomotion onto an attractor then the attractor's dynamic properties may provide important insights into our understanding of how this action is coordinated.

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3. P a t t e r n s of c o o r d i n a t i o n i n walking

Before examining how we have used dynamical systems theory to understand the development of locomotion, let us begin by considering the locomotor pattern that we are trying to understand. Figure 1 shows a tracing of an infant who has been walking 3 months. In this figure, the walking cycle begins as the right leg’s foot leaves the ground (toe-off) and ends with the same event. A step cycle is defined here as the time between successive toe-offs of the same foot. Each limb’s ste cycle also may b e decomposed into the time when the leg is in contact with t e ground (stance) and the time when the leg is off the ground (swin ). The swing hase, therefore, occurs between toe-off and heelstrike, stance foflows from hee strike to the next toe- off.

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Figure 1 A schematic of an infant walking Walking is cyclic movement in which the limbs continue to repeat the same actions -- one step cycle after another. Ins ection of the movement of the two major leg segments (the thigh and shan ) reveals a to-and-fro movement reminiscent of the oscillations of a pendulum. But unlike a freely swinging pendulum, the leg segments encounter the ground f o r a n extended period of time. In terms of the temporal organization of walking, two types of coordination have been most frequently examined: interlimb and intralimb. I n t e r l i m b c o o r d i n a t i o n refers to the relationship of one le ’s step cycle to the other leg’s step cycle. In mature walking, half way throu& the right leg’s step cycle, the left foot is placed on the groung. The interlimb coordination between the two limbs is expressed as being 180 out-of-phase with each other at footfall. In terms of proportional timing, the relationship can be described as one in which one leg is 50% out-of-phase with the other leg. I n t r a l i m b c o o r d i n a t i o n describes how the components within a leg (e. ., segments, joints, muscles) relate to each other. In our work, we have studiel f how the two major leg segments, the thigh and shank, relate t o each other during the step cycle.

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4. Using t h e dynamical systems p e r s p e c t i v e in t h e study of l o c o m o t i o n

In looking over the years at the volumes of research on locomotion, one is struck by the number and variety of measures that have been used t o characterize walking. For exam le, Sutherland (Sutherland, Olshen, Biden, & Wyatt, 1988) in his research on tge development of walking reports 12 measures of body position, 6 force measures, 7 muscle activation patterns and 9 time/distance parameters for any one walking cycle. Across the ages 1 to 7 years, children exhibited changes in all of the variables. So how does walkin develop? What is changing when step cadence decreases o r stride ]en& increases? How are we to see the " attern of coordination" develop f o r walking in such a collection of variables? {he answer to this question was offered over a hundred years ago by PoincarC who suggested that the solution could be found in qualitative dynamics (Garfinkel, 1983). For PoincarC it was the pattern o r form that held the key to understanding how systems changed. Thus for those using a dynamical systems approach, the first challenge is to find a low dimensional descri tion of the system that captures the behavioral pattern. Once we have this &scription, we can ex lore the pro particular attention to the system's stabi ity and loss o T o describe a dynamical system, we need instantaneous description of the system's state, and (2) a dynamic o r rule by which the system evolves from one state t o another (Crutchfield, Farmer, Packard, & Shaw, 1987; Rosen, 1970). The state and its trajecto is mapped system into state space. The low dimensional, qualitative description o the emerges in this state space as an attractor. T o find a n attractor that captures our system, we must find the dimensions that give us a n instantaneous description of the system's state. In previous work (Clark, Truly, & Phillips, 1990), we have shown how position and velocity of segmental motjon provides the lowest dimensional description of segmental motion. In Flgure 2, the motion of the shank is plotted f o r one step cycle. The instantaneous description of the system's motion may be seen as any one single point.(A) re fesented by two dimensions (x,k). T h e picture we have in Figure 2 of this shan s motion is referred to as its phase portrait.

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The ortrait that emerges of this segment’s motion, we have su gested is that of a ! k i t cycle attractor (Clark et al., 1990; Clark, Truly, & P illips, in press). A limit cycle attractor is one in which nearby trajectories form a closed orbit (Crutchfield, et al., 1987). Limit cycle attractors a r e unique in that if the encounter small perturbations or changes in their initial conditions, they w i i return to the same stable orbit. We have found that the motion of the other major leg se ment (i.e., the thigh) also may be portrayed as a limit cycle (Fig. 3). Althoug! its orbit is different in shape, it seeks a periodic closed orbit -cycle after walking cycle. It too prefers this region of state space and resists small erturbations or changes in initial conditions (Clark e t al., in press). ?he thigh and shank motions of newly walking and more experienced walking infants provide additional support for the robustness of the limit cycle attractor as the proper low dimensional dynamical model of se mental motion during walking. In the first attempts at walking in which 3 in ependent steps can be achieved, the segmental actions of the infant demonstrate limit cycle behavior (Clark, et al., in press). In Figure 4 and 5 , we can see the shank phase ortraits for the same infant during her first walking attempts and six months rater. Sur risingly the infant’s first attempts at walkin result in a phase portrait o f t h e shank’s motion that bears a striking resemElance to that of the adult’s (Fig. 2). Although there a r e differences in the trajector’s path during stance (i.e., following clockwise from heelstrike), the orbit itse f is closed and periodic. After six months of walking (FigS), the infant’s shank phase portrait is almost identical to the adult’s including the stance portion.

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How is coordination to be understood using attractor dynamics? We have pro osed earlier (Clark et al., 1990; Clark et al., in press; Clark & Whitall, 1988) that locomotion can be modeled as a system of coupled limit cycle oscillators. Thus if segmental motion can be described as limit cycle attractors, then the coordination within the legs may be viewed in terms of the “couplin$‘ between these two systems. To represent how the motion of one attractor is related to another, we must first transform the C rtesian coordinates (x,i) into polar coordinates, with a phase an le 9 = tan -?[k/x] and a radius. Fi ure 6 shows the convention we have used or measuring phase angles (0 is at t e left

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horizontal, the trajectory moves clockwise). In thjs figure, a phase portrait f o r the shank is depicted with a phase angle of 135 . Using the phase angle to represent where the system is at any one time on its trajectory, now permits us to ask, where in the tra’ectory of one attractor is the other attractor a t the time of a particular event. d e refer to this relationship as oint coordination (Clark et al., 1990). Figure 7 is a graphical r e resentation o this relationship. In this figure, we see the points on both the shpank and the thigh phase plots when the thigh reverses. We mi ht also wish to see how the segments a r e coordinated throughout the step cyc e (referred to as continuous coordination). In Figure 8, we plot the phase angle as it changes across the step cycle for the thigh on the y-axis and t h e shank on the x-axis. Clearly, the coupling relationshi between the two se ments is not a linear or phase-locked relationshi . T f i s t pe of cou ling re ationship is referred to as p h a s e - e n t r a i n m e n t (f;and, C o en, & Ho mes, 1988). Thus while both segments complete their periods of oscillation in t h e same time, the phase difference or lag between the two phase angles is not constant throughout the cycle. Particular points within the cycle, however, may be phase locked but the relationship across the entire cycle clearly cannot b e characterized as such.

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5 . T h e development of i n t r a l i m b c o o r d i n a t i o n

The infant’s first upright independent walking steps signal the emergence of a new coordinative organization. Prior to those first independent steps, the infant’s principle modes of locomotion were crawlin and supported walking. But with independent walkinp, new constraints sca fold the infant’s action. How do these new constraints influence the coordination between the segments? While we have argued that the infant’s se mental motion is of the limit cycle type, clearly as Fi . 4 reveals, the shape of the attractor is not the same throughout the step cyc e (i.e., stance) as that seen in the adult o r in that same infant six months later (Fi . 5 ) . But d o these differences in attractor sha es result in differences in t i e way the two segments are coupled? To ad ress this question, we focus here on point coordination using segmental reversals as the events of interest. As the thigh and shank move through a step cycle, they both rotate forward and back about the joint center axes. Segmental movement reversals offer us a special window on coordination for this is the time when the segment changes its direction. What relationships d o the two segments have as each segment changes direction? To calculate this coordination, we determine the phase angle of segment A when segment B reverses its direction, and converse1 we find the hase angle of segment B when segment A reverses direction. g a c h segment as two reversals, forward rotation to backward rotation and back-toforward. These a r e desi nated in Fi ure 9 b the following notation convention: S for shank, .$for thi h, &B or B r F indicatinj the reversal direction from forward to back (F/I!) o r back to forward (B/ ). The phase angle reported in Fieure 9 is that of the angle on the opposite phase portrait a t the time of the indicated segment’s reversal. For example, the phase angle

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f o r (S F/B) is the thigh's phase an le when the shank reverses from forward t o back. It should be noted that we cfo not need to report the phase angle of the reversing segment since the phase angle associated with segment reversal (i.e., zero velocity) is either 0 or 180 degrees and therefore a constant across subjects. In Figure 9, the hase an$le of the third step cycle at the four different reversals are depictecffor one infant when she is newly walking (i.e., within a few days of her first 3 walking steps), one month later, and subsequently a t three and six months of walking experience. An adult's phase angles also a r e included f o r reference. Clearly for three of the four reversals, the infant at 3 months of walking demonstrates the same point coordination as the adult. Only in the shank reversal from b p k to front is there some deviation from the 6month and adult values (-50 difference). However inspegtion of the 3-month walker's very next ste cycle reveals a phase angle within 8 of the 6-month and adult values. After [months of walking, the intralimb coordination of these four selected points in the step cycle a r e almost identical to those of a n adult walker. It should be noted that a study of 8 adults of which the adult in Fig. 9 is one, found quite consistent phasing relationships at segmental reversals by t h e third ste cycle (Clarke, 1990). Interestin ly, the new walker also has adult-like intralimg coordination at thigh forward- l a c k reversal. This is a reversal that occurs near footstrike at the end of swing and may reflect the attractor stability of the segments' motion during swing. What has a dynarnical systems approach provided us in our search for a n understanding of intralimb coordination? At first glance it may seem that it has yielded only another description of the system, but one needs to look farther into the a p roach to see that it has the potential to give us much more. For example, t1e development of intralimb coordination modeled as coupled nonlinear limit cycle systems would predict that as stable attractors coupling between the two segments would reveal an entrained, stable relationship that is phase-locked. Indeed we see that in the more experienced walkers, their phase relationship as measured at selected points is quite stable. However such is not the case for the newly walking infant. Schoner and Kelso (1988) propose that when old behavioral patterns give way to new behavioral patterns, there is increased variability in the dynamics of the system. Indeed in developmental time, the variabilit we see in behavioral patterns of coordination (in both intralimb and interfimb) result from this transition between stable behavioral states. Once the behavior is stable (in walking this would be about 3 months after walking onset) changes in initial conditions or perturbations would not b e expected to disrupt the coordination. Some evidence of this stability is found in Fi ure 10 where the same coordination events used in Figure 9 a r e d e icted or the same infant a t 1, 6 months of walking. Figure 10 differs !om the previous figure in that it represents t h e intralimb coordination for a leg that has a wei ht affixed to t h e ankle that e uals 5% of the infant's body weight. T h e other feg has n o weight attached. Also included on the raph is the same adult used earlier who is walking here with a weight e q u a k t o 7.5% of her body weight affixed to o n e ankle. For comparison, the no-weight condition in the adult is included. Note that the newly walking infant is not represented. This is owing to t h e infant's unwillingness to walk with a weight on one ankle at this early stage in her new skill develop men t . Two aspects of Figure 10 require our attention. The first is t h e com arison of intralimb coordination with the weights to the adult no-weight c o n i t i o n . Almost without exception, the infant at all walkin4 ages and the adult's weighted trials appear to have the same phasing relationship as t h e

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unweighted adult walk. If we examine the data in Figure 9 along side that of Figure 10, we see an even more interesting trend. The infant a t 1-month seems t o have become more adult-like when walking with the weight! This is particularly striking in T B/F. It is as if the weight damped the system making it more stable.

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From a dynamical systems perspective, a coordinative structure emerges from the organism, environment and task constraints that surround the action. As the infant attempts her first walking steps, these constraints converge in such a manner that the first locomotor patterns of coordination bear striking similarities to the adult’s. However as predicted, these newly emer ing patterns a r e less stable dynamically. It is not until the infant has been wal ing about three months that adult-like consisten is maintained. In our work, we have used the dynamica systems approach to identify the low dimensional dynamical model that captures limb motion during walking. Given the multitude of biomechanical variables available t o describe

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locomotion, we find much appeal in attractor dynamics for their ability t o capture the qualitative form of action whilst providing a predictive and generative framework within which to study the development of coordination.

7. R e f e r e n c e s Abraham, R.H., & Shaw, C.D. (1982). D y n a m i c s - T h e g e o m e t r y of b e h a v i o r . P a r t I : P e r i o d i c b e h a v i o r . Santa Cruz, CA: Aerial Press. Bernstein, N. (1984). Biodynamics of locomotion. I n H.T.A. Whiting (Ed.), H u m a n m o t o r a c t i o n s . B e r n s t e i n r e a s s e s s e d . Amsterdam, T h e Netherlands: Elsevier Science Publishers. (Original work published in 1940.) Bernstein, N. (1967). T h e c o o r d i n a t i o n a n d r e g u l a t i o n of m o v e m e n t s . Oxford: Pergamon Press.

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Bresler, B., & Frankel, J.P. (1950). T h e forces and moments in the l e during level walking. T r a n s a c t i o n s of A m e r i c a n S o c i e t y of M e c a n i c a l Engineers, 7 2 , 27-36. Brown, T.G. (1911). The intrinsic factors in the act of progression in t h e mammal. P r o c e e d i n g s of t h e R o y a l S o c i e t y , B, 84,308-319. Chao, E.Y., Rim, K. (1973). Application of optimization principles in determining the applied moments in human leg joints during gait. J o u r n a l of B i o m e c h a n i c s , 6,497-510. Clark, J.E., Truly, T.L., & Phillips, S.J. (1990). A dynamical systems approach to understandin the develo ment of lower limb coordination in locomotion. In Bloch & B.1. Bertenthal (Eds.), Sensory-moror o r g a n i z a t i o n s and development in infancy and early c h i l d h o o d ( p p . 363-378). T h e Netherlands: Kluwer Academic Publishers.

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Clark, J.E., Truly, T.L., & Phillips, S.J. (in ress). On the develo ment of walking as a limit cycle system. In Thelen & L. Smitg (Eds.), D y n a m i c a l systems in d e v e l o p m e n t : A p p l i c a t i o n s . Cambridge, MA: MIT Press.

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Clark, J.E., & Whitall, J. (1989). Chan ing patterns of locomotion: From walking to skipping. In M. Woolfacott & A. Shumway-Cook (Eds.), D e v e l o p m e n t of p o s t u r e a n d l o c o m o t i o n a c r o s s t h e lif e s p a n ( p p . 128-151). Columbia, SC: University of South Carolina Press. Clark, J.E., Whitall, J., & Phillips, S.J. (1988). Human interlimb coordination: The first 6 months of independent walking. Developmental P s y c h o b i o l o g y , 21,445-456. Clarke, L.C. (1990). I n t r a l i m b c o o r d i n a t i o n in m a t u r e w a l k i n :D o e s t h e l o w e r e x t r e m i t y a c t as c o u p l e d n o n - l i n e a r imit-cycle o s c i l l a t o r s ? Unpublished masters thesis, University of Maryland, College Park.

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Crutchfield, J.P., Farmer, J.D., Packard, N.H., & Shaw, R.S. (1987). Chaos. S c i e n t i f i c American, 254(12), 46-57. Elftman, H. (1934). A cinematic study of the distribution of pressure i n the human foot. A n a t o m i c a l Record, 59,481-491. Elftman, H. (1939). Forces and energy changes in the legs during walking. A m e r i c a n J o u r n a l of Physiology, 125,339-356. Haken, H. (1983). Synergetics - A n Introduction.(3rd ed.). New York: Springer.

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Grillner, S. (1981). Control of locomotion in bi eds, tetrapods, and fish. In V.B. Brooks (Ed.), H a n d b o o k of physiorogy - T h e nervous system 11. M o t o r control(pp. 1179- 1236). Baltimore, MD: Williams & Wilkins. Grillner, S. (1985). Neurobiological bases of rhythmic motor acts in vertebrates. Science, 228,143-149. Fischer, 0. (1899). Der Gang des Menschen I I . Leipzig: Teubner. Kugler, P.N., Kelso, J.A.S., & Turvey, M.T. (1980). On the concept of coordinative structures as dissipative structures: I. Theoretical lines of convergence. In G.E. Stelmach & J. Re uin (Eds.), T u t o r i a l s i n m o t o r behavior(pp. 3-47). New York: North J o l l a n d . Marey, E.J. (1886). L a m a c h i n e a n i m a l . Paris: Felix Alcan. Morowitz, H.J.(1968). Energy f l o w i n biology: Biological o r g a n i z a t i o n as a p r o b l e m i n thermal physics. New York: Academic Press. Muybridge, E. (1955). T h e h u m a n f i g u r e i n m o t i o n . New York: Dover. (Original work published in 1887.) Nicolis, G., & Pri ogine, I. (1977). Self -organization i n n o n e q u i l i b r i u m systems: P r o m dissipative structures t o order through f l u c t u a t i o n s . New York: Wiley. Okamoto, T., & Kumamoto, M. (1972). Electromyographic study of the learning process of walking i n infants. Electromyography, 12, 149-158. Pattee, H.H. (1977). Dynamic and linguistic modes of complex systems. I n t e r n a t i o n a l J o u r n a l of General Systems, 3,259-266. Rand, R.H., Cohen, A.H., & Holmes, P.J. (1988). Systems of coupled oscillators as models of central attern generators. In A.V. Cohen, S. Rossignol, & S. Grillner ( E J . ) , N e u r a l control of rhythmic m o v e m e n t s i n vertebrates(pp. 333-367). New York: Wiley.

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Rosen, R. (1970). D y n a m i c a l s y s t e m t h e o r y i n b i o l o g y . V o l u m e I : S t a b i l i t y t h e o r y and i t s a p p l i c a t i o n . New York: Wiley. Schoner, G., Jiang, W.Y., & Kelso, J.A.S. (1990). A syner etic theory of quadrupedal gaits and gait transitions. J o u r n a l of T h e o r e t i c a l Biology, 1 4 2 , 359-391. Schoner, G., & Kelso, J.A.S. (1988). Dynamic pattern generation in behavioral and neural systems. S c i e n c e , 239, 1513-1520. Seireg, A., & Arvikar, R.J. (1975). The prediction of muscular load sharing and joint forces in the lower extremities during walking. J o u r n a l of B i o m e c h a n i c s , 8,89- 102. Sherrington, C.S. (1910). Flexion-reflex of the limb, crossed extension reflex and reflex stepping and standing. J o u r n a l of P h y s i o l o g y ( L o n d o n ) , 40, 28-121. Sutherland, D.H., Olshen, R.A., Biden, E.N., & Wyatt, M.P. (1988). T h e d e v e l o p m e n t of m a t u r e w a l k i n g . Oxford, UK: Blackwell Scientific Publications, Mac Keith Press. Sutherland, D.H., Olshen, R., Coo er, L., & Woo, S. (1980). The development of mature gait. J o u r n a l of o n e a n d J o i n t Surgery, 62-A, 336-353.

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Yates, F.E. (1982). Outline of a physical theory of physiological systems. C a n a d i a n J o u r n a l of P h y s i o l o g y a n d P h a r m a c o l o g y , 60,217-248.

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SECTION 111: Current research on development of timing during childhood Chapter 13

HOW TO STUDY MOVEMENT IN CHILDREN M.G. Wade and W. Berg

Chapter 14

COORDINATIVE STRUCTURES AND T H E DEVELOPMENT OF RELATIVE TIMING IN A POINTING TASK D.L. Southard

Chapter 15

SYNCHRONIZATION AND DESYNCHRONIZATION I N BIMANUAL COORDINATION: A DEVELOPMENTAL PERSPECTIVE J. Fagard

Chapter 16

THE DEVELOPMENT OF TIMING ACROSS FOUR LIMBS: CAN SIMPLICITY PRODUCE COMPLEXITY? M.A. Roberton

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The Development of Tmin Control and Temporal Or anization in &ordinated Action J. Fagard aniP.H. Wolff (Editors) Q Elsevier Science Publishers B.V., 1991

How to S t u d y Movement in Childmn Michael G. Wade and William Berg Division of Kinesiology 1 University of Minnesota 1. INTRODUCTION

It might be argued from the outset that there is no need for a specific chapter on how to study movement in children; the chapters that make up this volume reflect a great deal of information on how to study movements in children. Having developed a possible rationale for the exclusion of this chapter, what might be said by way of justification for it? What we present here is first a n overview of how movement has been studied i n children in terms of both the techniques and dependent variables used; and second, how this has formulated models and theoretical explanations about the origins and development of coordination and control in children. The chapter is divided into six sections: First, a brief review of the past 25 years of motor development research, focusing primarily on the style of inquiry and the nature of the dependent variables used. Second, a discussion of the dependent variables t h a t traditionally measure the product rather than the process of movement, and how their contribution to the description and analysis of movement patterns in children has both helped and constrained progress. Third, movement studies of children incorporating the ecological perspective. Fourth, research on fetal motor activity is reviewed. Fifth, a discussion of periodicity in motor behavior; how it is measured and its promise in understanding movement behavior. A sixth and final section summarizes the chapter and comments on future directions and initiatives, one of which is the use of allometry as a technique for studying movement patterns in children. It is worth spending a moment analyzing the definition of the word pattern. A dictionary definition (Webster, 1986) uses terms such as "reliable," "traits," and "acts" in characterizing a n individual. Thus, in addressing the issue of how to study movement in children, it is perhaps reasonable to suggest that the class of movement that we would want to study should be reliable and have a n observable class of features that characterize the developing organism. Moreover) to study movement in children (developmental kinesiology), a central focus of this activity should describe) analyze and seek to explain the activity which reflects both the phylogenetic and ontogenetic elements of the species. It is not possible to review in detail all of the interests of the authors assembled in this volume, but hopefully we capture the important elements of studying movement.

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In a chapter published 14 years ago Wade (1976)proposed two lines of developmental research that could build on the then extant theoretical developments in the field of motor learning. With reference to Adams (1971)closed-loop theory of motor learning and Schmidt's (1975)schema theory of motor learning, Wade (1976)asked why scientists interested in the motor behavior of children had chosen to ignore these theoretical ideas and had failed to apply them to developmental questions. Both theories offered opportunities for systematic research, not only how children acquired motor skills, but more generally how motor skills developed and degraded across the life span. Wade's view was that the subdomain calling itself "motor development" had an atheoretical history and most of its empirical activity had provided only product oriented, descriptive contributions with few attempts to develop theoretical explanation. The chapter (Wade, 1976) was titled Developmental Motor Learning in an attempt to make just that point. Some of the issues raised by Wade (1976)had been raised earlier by the British psychologist Kevin Connolly (1970),who provided several examples of how to study motor skill behavior in children employing the traditional information processing paradigm. Connolly's criticism of the field was also directed at what he saw as an excess of description and a dearth of explanation and theorizing. The literature from 1965 onward reveals few theoretical models, that have been applied in any extensive way, to study motor skill development in children. Perhaps this last remark should be qualified by operationally defining theory as something that both seeks explanation and possesses predictable validity; description alone does not possess this kind of explanatory power. While several investigators developed descriptive accounts, Todor (1974)was one of few to apply a theoretical paradigm (Pascale-Leone's 1970 neo-piagetian theory) to study skill development in children during the decade between 1965 and 1975. Seefeldt and his coworkers at Michigan State (Seefeldt & Haubenstricker, 1974)and Roberton (1978) and her co-workers at Wisconsin used descriptive analysis t o evaluate qualitative change in skill development in children, but there was never any closure brought to these studies. The data reported described changes in skill level across several age groups reflecting essentially an increased probability for the development of more mature skill patterns. During this period there were no attempts to build a theoretical framework around these data that would account for changes in the activity or that would predict future developments. The points raised by Wade (1976)were echoed by Keogh (1977)in a monograph contribution entitled "The Study of Movement Skill Development." The comments of Connolly, Keogh and Wade all called for a reassessment of the methodologies that were being used in studying motor skill development and motor patterns in children. In an earlier paper, Wade (1974)reviewed methodological differences between quantitative and qualitative research techniques used to study motor skill development in children. Wade argued that quantitative analysis failed to provide the insights needed to understand the emergence of skilled behavior and that the use of quantitative methods (error scores; and a variety of spatial and temporal performance measures) reflected

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primarily the effects of age and gender. Wade (1974)called for a greater use of topological description (qualitative change) that would require both different methodologies and techniques. We advocate in this chapter to move beyond the dependent variables that measure the product of movement and use process based measures that focus more on kinematics and external constraints. 2.

THE PROBLEM OF MEASUREMENT

It is probably true to say that the quality of a science is reflected in part by its capacity to measure particular phenomena. It is also probably true to say that generating metrics for a particular set of phenomena is considered more sophisticated than mere description. Unfortunately in the study of movement patterns in children the measures used, particularly by those imbued with either of Cronbachs (1957)two psychologies, have relied more on product measures, and this has constrained the development of explanations for the observable changes in the movement patterns of children. Early quantitative investigations of skill development have emanated primarily from long-term growth studies. The usual procedure was to measure a range of basic motor activities or patterns across a selected range of ages. Changes in performance of these skills usually exhibited monotonic change with respect to age. Investigators followed their subjects over long periods of time, and while this has produced some useful data, the problem has been that in the absence of a model to account for changes in performance, these data have remained impenetrable to the information they may hold regarding how the developing organism acquires coordination and control of action. While qualitative investigations of motor skill activity are by no means new (Bayley, 1935; Goodenough & Brian, 1929), they have been infrequent in the past 20 years, prior to 1980. Qualitative changes in motor skill development produce different relationships between variables of interest. For example, Hutt (1973) suggested that patterns of qualitative skill changes are most likely not gradual and approximate more a step function than a monotonic relationship and should correlate low with the age of the subject. A paper by Connolly (1973)presented a topological analysis of children's skill development in solving a series of manual grip problems. Connolly argued that the changing topology of grip patterns used by the babies represented the acquisition of what he referred to as a "dictionary of grips." Connolly employed the computer metaphor to propose that the development of different grip patterns were analogous to the sub-routines of a computer program. The validity of such a metaphor is debatable, but more important for this discussion was that Connolly presented a modular account that reflects the kind of science necessary to attack problems of motor development (McCain & Segal, 1973). Keogh (1975)proposed that the use of the twin concepts of "consistency" and "constancy" to characterize the development of skill acquisition for a variety of motor tasks. Keogh saw these two concepts as interrelated, with "consistency" (repetitive and successful action skill reproduction) as a precursor to "constancy" (the

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ability to use a specific activity and generalize it to other instances of a class of skills). Repetition develops "consistency" and experimentation (free play?) develops "constancy". Thus, research activity that analyzes both the kinematics and dynamics of skilled activity should provide data for analysis that seeks to explain and account for change in both the skill level and the pattern of movement behavior in children. Not unlike the descriptive analyses common in many studies of motor skill development, the use of product measures such as error scores, by and large, have been impediments in developing and identifying the essential organizing principles that provide the basis for the changes observed in motor skill development. The use of error scores has focused more on trying to understand learning, with an emphasis on the cognitive aspects of motor behavior rather than the organizing principles that sit behind action per se. Error scores are constraining in that they record only the degree to which movement outcome is achieved. This kind of measurement may not produce insight into the process that underlies motor skill development. In fact, an error score may sometimes misrepresent the process by which it was achieved. While it is recognized that the product (outcome) is usually what is important in the real-world, an understanding of the process is required for explanations of the regularity observed in the development of control and coordination in children. The traditional product (task) approach to the study of motor development is founded on some rather tenuous assumptions. First, there is the assumption that the investigator has selected a task that will represent a wide range of other skills, and second, that experimental results of performance on this task (often measured by error scores) can be generalized to other skills. This approach tends to use tasks in which the measurement of movement through kinematic methods is not practical, so that little information can be gleaned about how the performer produced the movement (Schmidt, 1988). This approach is not concerned with the process that generated the performance, and thus the relationship between product and process is not readily apparent nor is it necessarily stable, making inference of product to process difficult. On the other hand, the process-oriented approach is interested in the underlying structure of motor performance, not just the outcome. Because it focuses on internal processes that are not directly observable, it often requires, for example, the recording of kinematic variables that describe the movement of the limbs or the entire body, and/or electromyographic recordings of the electrical activity of muscle during a skilled response. An example of the danger of characterizing the process of movement solely from the movement outcome, and of the utility of using kinematic measures to make usefid inferences about process, can be found in the theorizing about the lawful relationship between movement speed and accuracy described by Fitts (1954). The typical measures recorded in Fittstype experiments include reaction time, movement time and a variety of accuracy measures (holding error rates constant). Developmental studies using the paradigm have been reported by Wallace, Newel1 and Wade

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(1978);Sugden (1980);and Burton (1987). Crossman and Goodeve (1963) sought to explain the relationship observed between movement time and the index of difficulty described by Fitts (1954). This original interpretation of Fitts' law employed an information-processing model whereby increasing the index of difficulty of the movement increased the amount of information to be processed. Crossman and Goodeve (1963)sought to explain the inverse relationship between speed and accuracy by suggesting how the mover was actually getting to the target. The theory suggested that simple aiming movements were comprised of short bursts of open-loop movements (no feedback) followed by rapid integration of feedback to monitor the precision of the action with corrections made if necessary. This process was thought to continue until the limb arrived at the target. The theory stated that the amplitude of the movement, in combination with the width of the target would determine how many adjustments in trajectory would have to be made. And since it is well established that little substantive modification of movement can occur in less than about 190 ma, the number of corrections needed during a movement was thought to control the time needed to complete the movement. Traditional product measures could not assist in the testing of this theory. This problem called for a different kind of measurement, one that focused on the subject's movement to the target, not where the subject ended up. Langolf, Chaffin, and Foulke (1976)recorded the movement kinematics which permitted a closer examination of the processes t ha t underly motor performance in Fitts' task. High-speed motion pictures of these movements clearly demonstrated that subjects did not make the number of corrections predicted by the Crossman-Goodeve theory. Measuring the kinematics allowed for empirical inference about process and permitted researchers to discount the Crossman-Goodeve theory (1963)as a tenable explanation of the l a d relationships described by Etts (1954). 3. MEASUREMENT AND THE ECOLOGICAL APPROACH TO MOTOR DEVELOPMENT Traditional theories of motor development, be they from the cognitive (e.g., Piaget, 1952)or neural-maturational (e.g. Gesell, 1946;McGraw, 1945) traditions are based on a class of concepts one could generally describe a s prescriptive. These theories of the development of skill have been anchored to the idea that representations (i.e. symbolic knowledge structures) existing within the central nervous system are fundamental to the control of action. Both views also assume that development of skill is due to the development of prescriptions for action at some level of representation. Skill is thought to emerge a s a result of the maturation of the neuromuscular system. In other words, maturation leads to the unfolding of a predetermined pattern - that plans exist before the behavior emerges. For example, traditional theories would explain the onset of walking i n children as the point a t which the neuromuscular system had developed to a level where i t could support such activity. Again, implicit in this view is that the potential for walking exist i n the neural substrates in immature form until differentiation permits this prescriptive action to emerge.

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These traditional ideas about the emergence of motor skill are now facing a challenge from new and innovative perspectives of the development of control and coordination. A conceptual basis for these contemporary approaches can be found in Gibson's (1977,1979) ecological psychology, Kugler and Turvey's dynamical systems approach (Kugler & Turvey, 1987; Kugler, Kelso & Turvey, 1980 & 1982) and Reeds (1982)theory of action. At the heart of these approaches is the idea that coordination and control emerges not from prescriptions for action, but as a consequence of the constraints imposed on action. Constraints reduce certain configurations of response dynamics with the resulting pattern of movement a reflection of the "self-organizing optimality of the biological system," rather th a n specifications from prescriptive knowledge structures (Newell, 1986). There is a fundamental dispute about whether the order and regularity in motor development can be attributed to in te r n a l prescriptive representations of action, or to self-organizational characteristics of the biological system and its interaction with the environment. However, the differences between traditional and contemporary views of motor development lie not only in the interpretation of data, but also a t the level of analysis (Schmidt, 1988). Measurement techniques nontraditional to the study of motor development are now being employed by those of the ecological persuasion in their examination of the processes of skill development. Investigators are beginning to realize the value in recording topological descriptions of behavior, and are taking steps to incorporate new methodologies and techniques which permit such description. Kinematic measures employing movement analysis via film and video techniques (e.g. PEAK, WATSMART, SELSPOT, and others) in addition to electromyography are helping investigators to expand the frontier of the ecological perspective of motor skill development. For example, Thelen and Cooke (1987)used kinematic techniques to their full potential in their study of the relationship between the stereotyped movement pattern of infant stepping and the development of adult locomotion. With detailed video and EMG data, they compared infant stepping with an adult gait pattern. They concluded that mature walking may evolve from infant stepping, and th a t the gradual changes in the organization of the step during infancy may be evoked "by the dynamic functional demands of up-right locomotion" (p. 3921, in addition to the development of, balance, postural control and strength. They also claimed that the changes in the organization of gait during infancy must be explained as an emergent property of the dynamics of the system, with no need for recourse to centrally represented gait patterns to account for changes in locomotor behavior. This approach to the study of motor development is the "new kind of science" referred to by Turvey and Carello (1981)and it requires a new way to observe and record behavior. With the advancement of this type of inquiry we will see more sophisticated kinematic techniques and a n even greater reliance on a topological description of movement in the development of theoretical explanations for the processes that contribute to the emergence of skilled motor behavior.

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An important focus of the ecological perspective is the child's capacity or sensitivity for detecting information in the environment relative to his or her actions, what constitutes information, and how the information used to control movement. To describe the relationship between the animal and the environment in extrinsic units (e.g. such as recording diameter and height in meters or feet), and to suggest that the child uses these extrinsic units to control behavior, undermines the notion of ecological realism and is unacceptable (Turvey & Carello, 1981). Because, in this view, the actor and the environment are functionally inseparable, units that are intrinsic to an organism environment system and share common bases in both "such that certain parts and processes of the system define the units in which other parts and processes are measured (Turvey & Carello, 1981,p. 317), are favored. Extrinsic measures can be transformed into performer-scaled units by selecting the dimension of interest and transforming it into a bodyscaled metric by dividing the dimension value by the performer value. This yields a body-scaled ratio in which the extrinsic values cancel, expressing an invariant person-environment relationship across persons of different body sizes (Davis & Burton, in press). For example, Warren (1984) concluded that the stair riser height requiring minimum energy expenditure should not be stated in terms of absolute (extrinsic) units, rather the optimal height is just about one quarter of the leg length for both tall and short climbers. By using this intrinsic measure, Warren was able to conclude that the optimal riser height was constant over scale changes in the system. In a study of road crossing behaviors in children and adults (Lee, Young, & McLaughlin, 1984). the temporal gap between vehicles in a simulated (yet realistic) road crossing task was scaled to the subjects by computing the ratio of this time gap and the actual time the subject needed to cross the street. This resulted in a performer-scaled metric in which a value of 1.0 afforded crossing the street. In the future, it will be the goal of researchers in this field to identify relevant environment dimensions scaled relative to the performer, like those discussed above, so that we may better understand the interaction between actor and environment, and that this understanding is founded upon the realism of intrinsic measures.

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4. FETAL MOTOR ACTMTY~ Interest in prenatal motor development is an important element in the chain that seeks to better understand the emergence of recognizable motor behavior in the developing infant. What was once considered essentially random activity of the developing fetus has, through the efforts of several researchers, become characterized as recognizable, specific, patternrelated activity quite early in gestation. The important elements that are investigated by research on fetal motor activity are theoretical considerations that relate the prenatal motor development to cranio-caudal developmental theory; the reasons for a change from what appear to be jerky movement activities to smooth in the fluid environment of the womb; the purpose of fetal movement, both in terms of development and the more immediate status of the fetus in the womb; and finally and perhaps more

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importantly, the link between pre- and post-natal fetal development. This section briefly reviews some of these issues. We begin with a discussion of the methodologies of recording fetal motor activity. The strain gauge or tocodynamometer has been interfaced with various devices to record fetal movement. Tocodynamometry records changes in pressure a t the abdominal wall of the mother as a function of fetal movement. Duration is the variable recorded, and the technique is benign in that it requires no energy to be introduced into the mother or the fetus. The other common non-invasive technique is ultrasound, which generates a sound wave profile of the moving and developing fetus. The type of ultrasound used most often creates a two-dimensional still picture called a sonogram. This picture depicts the growing fetus, the number of fetuses in the uterus, and the positions of the fetus and placenta. Another form of ultrasound, called real-time, combines still pictures in rapid succession to show movement, similar in style to a motion picture. This can depict the fetal heart beat, movements of the arms and legs, other body movements, size of body segments, all of which may be measured in real time and may be used to predict biological age. Research comparing the non-invasive techniques of tocodynamometry, ultrasound and reported movements by mothers were reported by Sorokin, F’illary, Dkjerkar, Hark and Roson (1981) and later by Prechtl(1985). Of the three techniques, the ultrasound demonstrated the best overall sensitivity to fetal movement, especially for movements of less than one second in duration. By comparison, the tocodynamometer detected 70 percent of the movement detected by the ultrasound while mothers reported movement only approximately 50 percent of the time compared to ultrasound. For fetal movement longer than three seconds, the patients and the tocodynamometer detected movement closer to that of the ultrasound. Tocodynamometry is less expensive than ultrasound and other than maternal perception, it is considered to be a less expensive method which could be used safely and effectively over a long periods of time. In addition, both Sorokin et al. (1981) and Prechtl(1985) noted that complex movement patterns observed in the first half of pregnancy are more difficult to record during the last half of the pregnancy because of the increasing size of the fetus. Having established the reliability of the three best-known methods of studying fetal movement, several studies have used tocodynamometry and ultrasound together as investigative tools. Timor-Tritsch, Zadoc, Hertz and &sen (1976)identified four distinct movements in fetuses between 26 weeks and birth. A second study by Bimholz, Stephens and Faria (1987) used phased-array ultrasound in 40 individual examinations and identified 11 distinct spontaneous movement patterns in the fetuses of women experiencing normal pregnancy. Further, Van Dongen and Goudie (1980) recorded increasingly complex movements via ultrasound as gestational age increased. Movement patterns were found to be related to the age of the fetus. The definitive work using ultrasound was embodied in three investigations by deVries, Visser and Prechtl (1982, 1985 & 1988). The qualitative aspects of fetal motor activity were examined in the first study;

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the rates of fetal movement in the second; individual differences and inconsistencies in fetal movement in the third. Collectively these three studies concluded that movements during the second half of gestation were more difficult to assess accurately with one transducer because of the increasing fetal size. The use of fetal activity as a predictor of postnatal performance has received only modest empirical attention. An early study by Richards, Newberry and Fallgatter (1938)reported fetal activity in seventeen mothers during the last twenty weeks of pregnancy. They used a polygraph technique to record both maternal and fetal activity. Maternal activity, time of day, fetal heart rate, fetal age a t the time of the study, and rise i n maternal basal metabolism were not reliably correlated with fetal activity. Further, there was no appreciable increase in fetal activity aRer the seventh month of pregnancy. A second study (Richards & Newberry, 1938) compared the activity indices of the last two months of pregnancy, as reported by mothers, to the results of a Gesell schedule, given to each corresponding baby at six months of age. Although the sample was small, the relationship was positive and rank difference coefficients of fetal activity and test performance predicted 30 to 70 percent of the variance a t six months on the Gesell schedule, but the small sample size precluded generalizability. Twenty six years later Bernard (1964)sought to predict postnatal data from prenatal heart rate and fetal movement. The results did not support making any postnatal predictions from prenatal data. Walters (1964) recorded fetal movement identified by maternal perception. The number of specific fetal movements described a s kicks, squirms, ripples, and hiccups were reported weekly in a sample of 35 women. Walters concluded that fetal activity decreased during the last month of pregnancy and that there were real differences between the specifically described movements. A second study (Walters 1965) followed babies from the first study. Kendall rank-order correlations were significant at 12 weeks for the motor, adaptive and total scores; at 24 weeks for the motor, language, and total scores; and a t 36 weeks for all five areas of the schedule (motor, adaptive, language, personal-social and total score) with fetal activity. The ninth month of fetal activity was the best predictor of postnatal development, and correlations were highest between fetal activity and the Gesell Development Schedule at 36 weeks. The only other recent study was by Shadmi, Homburg, and Insler (1986). Perceived fetal movement counts were recorded by 51 pregnant women, whose babies formed two groups, over several weeks. No significant correlations were found between the mean number of fetal movements and the partial Brazelton test scores for either group. Predictions of postnatal performance based on the prenatal activity of normal fetuses would thus seem to be inconclusive. The methodologies used to date to study fetal motor activity suggest the following: First, movement of the fetus that was at one time considered essentially random has been characterized as recognizable i n many specific patterns, very early in gestation. The appearance of specific movement patterns seems to follow a definitexhronological order. Further,

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fetal movement has a certain intra-individual consistency and very real inter-individual differences, but these appear not to be sex dependent. In addition, the spontaneous movements have demonstrated periodicity or a cyclic patterning (see section below). The key elements appear to be the link between pre- and post-natal development, the purpose of fetal movement and the notion that it might somehow reflect the maturational timetable. There are others, however, who view it as an interaction with the environment, and Wolff (1986)sees this as reflecting a dynamic interaction of motor patterns within the environment. At this point no single theory or model can be regarded as conclusive. Needless to say, studying fetal movement is on-going, and as technology advances, it will permit further systematic investigation into what was earlier viewed as a relatively chaotic approach to the study of fetal utero development. 5. PERIODICITY IN MOVEMENT

As noted above, the use of error scores has limitations. The magnitude, direction and variability of errors provide some insight about motor skill performance, but does not generate information or permit inferences about how skill behavior emerges from the developing organism. This has generated a large body of empirical evidence that has provided theoretical support as to rates of acquisition and the nature and scope of strategies of learning, but i t requires a different style of inquiry to understand more clearly the basis of skill behavior in terms of its underlying properties. Rhythmicity, or periodicity is a property o r characteristic of most living systems and can be found a t different levels of analysis: mechanical, physiological, and biochemical, to name but three. There is a large body of evidence in the life sciences, in the study of human movement and in psychophysiology to demonstrate that such systems exhibit periodicity that responds to or reflects the essential interaction between the organism and its immediate environment. The study of biological clocks has a long history, as does the study of biochemical systems with their periodic characteristics of secretion. Within the contemporary field of kinesiology and the study of human movement, the dynamic systems appr ach has, as one of its key elements, the study of periodic activity. his can be demonstrated in several movement domains and while space does not permit a n exhaustive review, a few instances will illustrate the point. Earlier research from our own laboratory (Wade & Ellis, 1971;Wade, 1973;Wade, Ellis & Bohrer, 1973)examined the play and motor behavior of groups of normal and mentally handicapped children in free play settings t h a t manipulated both social group size and the complexity of the play environment. The research sought to test the hypothesized periodic relationship that was predicted to exist between a system that required chemical support for energy expenditure and renewal, and behavioral support to maintain a hypothesized optimal level of arousal. Our research suggested that it was possible to reliably detect periodicities in the play behavior of young children measured by continuously monitored heart rate, as well a s corroborating observational data that reflected patterns that could be assigned to both cycles of energy expenditure (worklplay) and

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habituation to a play environment that was modulated by levels of arousal. It is interesting to note that in a second study this characteristic periodicity in the play of normal children was absent in a sample of mentally handicapped children (Wade, 1973). These studies demonstrated that the interplay between the biochemical constraints of the system and the arousing properties of the environment couple in such a way as to emit measurable or detectable periodicities. Periodicity has also been detected in fetal motor activity. Robertson (1985)investigated cyclic motor activity in the human fetus during the second half of pregnancy. Using two strain gauges applied to the mother's abdomen, 29 human fetuses were studied longitudinally for periods of two to three hours. Each fetus was studied.at least twice and possibly up to seven times between weeks 20 and 40 of pregnancy. The data were analyzed to investigate whether the fluctuations in the duration of movement were random or periodic. Spectral analysis detected significant peaks (using a five second sampling interval) at a frequency of 6.0 cycles per second. The evidence suggested that cyclic motility or strong periodicity in spontaneous movement is present in the fetus during the second half of gestation. Fluctuations in fetal movement were not random, but characterized by definite consistency. As a methodology, investigating periodicity requires the collection of time series data and the use of fourier transform and associated spectral analysis to reliably detect the existence of such periodic activity. While this is not a new technique, it is receiving increased empirical attention as equipment for recording continuous movement and the analytical capabilities of microcomputers improve. Periodicity is a particular characteristic of the temporal basis of activity that is relevant for studying developmental issues as well as general problems of control and coordination of motor skills. At one level, the absence of periodic behavior in the organism over a range of movement behaviors may be a n initial signature of dysfunction, to appear later as both cognitive and motor disabilities (Burton, 1990;Wade, 1973;&Wade, 1990). Central to Gibson's ecological approach to perception and action (Gibson, 1979)is the assumption that perceptual systems are coupled with action systems. David Lee and others (Butterworth & Hicks, 1974;Lee, 1980; Lee & Aronson, 1974;Stoffregen, 1985; Bertenthal & Bai, 1989) have all investigated the coupling between changes in perceptual information and the motor activity of the organism as reflected in the maintenance of upright posture and whole body sway. The results of these studies suggests that this coupling is a critical element of skilled activity. Thus, when recording levels of motor development in children, which are reflected in either poor, average or enhanced levels of skillful behavior (coordination and control), the periodicity exhibited may well reflect the sensitivity of the organism to this perception action coupling. The development of competent skilled behavior is often described by such terms as "smooth," "unhurried," "rhythmic" and "well-timed." These are descriptors that we can readily appreciate in a wide variety of motor skill activities. The use of these adjectives conjures the notion of

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rhythmicity or periodicity, and of living systems that exhibit preferred rates of activity which regulate and thus permit optimal performance. The idea of preferred rates of activity may well reflect an important characteristic of a living system (Kugler & T w e y , 1987). What is interesting is that this inherent periodicity in motor systems is also present in a wide range of social-psychological behaviors. The whole panorama of social behavior and person to person interactions has its o w n temporal basis, which is now beginning to be investigated (Van Acker & Valenti, 1989). Periodicity appears to be a characteristic of a range of bio-behavioral activities. This perhaps should not come as a surprise, since the biology of a living system and the organism's behavior must both be viewed within its environmental context. 6.

SUMMARY This chapter has reviewed not so much the specific methodologies used

to study how children develop movement, but rather, discussed some of the issues that need to be confronted in deriving a better understanding of the role that movement behavior plays in the developing organism. We have presented information that focuses on the nature of dependent variables used and the implications that they have for studying movement behavior, as well as a discussion of the two contrasting theoretical views of movement behavior. One adopts an ecological stance and studies movement development more from an emergent properties perspective, and the other seeks to better understand the acquisition of motor skills in a more traditional learning perspective, and employs traditional descriptive based and error based measures. Both sets of empirical activity have made important contributions to our understanding of how movement develops in children. The rapid advance in technology made available in the past decade suggests that this progress will only accelerate in the future. What is certainly true is that the style of inquiry between the learning of motor skills in the developing organism, as opposed to the dynamic systems perspective, is fhdamentally different. It is different not only in terms of the techniques and methodology, but it it characterized by a fundamental philosophical difference. Orthodox cognition from which traditional theories of motor behavior has their philosophical foundation adheres strictly to the Lockean view that the development of motor skills is achieved and explained by a special class of "things" that are intermediary between the world and the organism. Locke referred to these "between things" as "ideas," and they are seen as interphasing the organism and the environment. Cognitive theorists addressing motor behavior have referred to these as "representations" (e.g., Mounoud & Vinter, 1981)or "programs" (Bruner, 1970). Irrespective of the terminology, they refer essentially to a device which acts as an intermediary between the organism and the environment. Theorists from the ecological perspective rely on a crucial philosophical point of departure; namely, a commitment to realism. This view eliminates the Lockean notion of ideas and promotes a direct relation between the organism and the environment. Thus, for the realists, the model construct for the

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development of coordination and control is that it is autonomous, selforganizing and possesses no "between things." The differences between the two views are reflected not only in their philosophical underpinnings but also in the nature of the empirical activity which has evolved from the two approaches. Traditional motor behavior research borrowed heavily from traditional information processing models, This typically involves the recording and evaluation of error scores from subject's performance on a laboratory motor task. Further, the data are analyzed using a traditional experimental design format with a control group, and experimental groups that receive different levels or different degrees of some treatment. The empirical activity for the ecological approach to the study of coordination and control produces what Turvey and Carello (1981)have referred to as "an eccentric way of doing science" (p. 319). The investigations are nontraditional, often omitting control groups and the need for traditional parametric statistics. The study of action systems requires valid and systematic demonstration of styles of control, with reliance on careful observation and a level of analysis that focuses more on the descriptive topology of the activity to explain elements of control and coordination, rather than the measurement and analysis of error scores and measures of time. What, then, does the future hold for the "how" of studying movement in children? In our efforts to research the background for this chapter, one interesting area of potential research activity that has not received much attention, is the systematic study of what is called in evolutionary biology and ethology, "life history." This is the study of both the inter- and intraspecies differences that focus on issues such as body size, age at first reproduction, and the effort invested into growth and reproduction by a particular species. The methodology that investigates the impact of body size on such factors is called allometry. Allometry investigates the effects of size on variables that tend to mediate energy assimilation and metabolism. Its application is potentially very important for a clearer understanding of the growth and development of children, and how this may influence their potential for movement and ultimately their motor skill behavior. It is only recently that implications for the study of motor development via allometry have begun to appear in the literature. The standard equations for allometry rest on the power function:

where X and Y are size related measures and alpha and beta are constants. This is generally known as the allometric equation after Huxley (1924and 1932). Standard allometry provides exponents that compare size and performance. As a technique for studying movement in children, it holds considerable promise, since the scale values of the developing child tend not to follow the notion of geometrical similarity. An early study by Asmussen and Heeboll-Nielsen (1955)investigated physical performance in young boys by employing allometric techniques.

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The focus of this study was primarily physiological and sought to determine relationahips between the capacity of work and body size. For an excellent review, readers should consult Astrand and Rodahl (1986). ARer this initial foray by exercise physiologists in the 1950'4 it is only recently that studies on motor development from this perspective have again appeared. A recent study by Ross, Grand, Marshall and Martin (1984) suggests boys from 10 to 16 years of age do not grow as geometrical entities. Differential growth rates in the development of muscle tissue produced compensatory development to explain increases in muscle strength. The general conclusion of the Ross et al. (1984)study is that growing boys do not follow geometrical similarity, and between 6 and 16 years appear to grow faster in stature than might be expected from geometrical increases in body mass. This finding is significant and one that highlights the importance of this element of developmental research. It would seem from the Ross et al. (1984) study that standard allometry is inappropriate to account for the physical growth of the developing child. Standard equations of allometry are criticized because they emphasize scaling of one variable at a time rather than taking into account rates of change of several variables. This criticism has been elaborated first by McMahon (1975) and by Yates and Kugler (1986). McMahon (1975) developed several models to better understand the relationship between animals of varying size relative to predicting dynamic variables such as the stride length and frequency in running; and metabolic power in a variety of quadrupeds. His most reliable model used elastic similarity relationships between variables rather than the traditional geometric similarities. Yates and Kugler (1986) also argued the inappropriateness of standard allometry as it relates to procedures that seek to determine drug dosage based on allometric coefficients derived in the traditional way, one variable at a time. They point out that, depending on the variable employed (body volume, metabolic rate, surface area, or heart rate), dosage levels for humans compared with mice may differ as much as 3500 times when based on body volume, down to 8 times when based on heart rate. Yates and Kugler (1986) reject the idea of geometric similarity or mechanical similitude (from the original work of Galileo in the 17th century) as failing to account for such wide ranges of dasages between humans and other species. They argue that allometry should embrace thermodynamic variables which reflect those computed from transformations of coordinate space rather than one dimensional variables. Finally, a recent paper by Turvey, Schmidt, Rosenblum, and Kugler (19891, investigated periodic time in locomotion and flight as it relates to the allometric variables of mass and length. Space does not permit further discussion of allometry as a method to study movement behavior, but it would seem to provide an important step forward beyond the cataloging of data that abounds in our field from the anthropological literature, and certainly holds promise in supporting the dynamical systems approach advanced by Thelen (1986). As we head into the last decade of the second millennium, the prospects for future research appear bright.

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1We thank Allen Burton for helpful comments on earlier drafts of this chapter. 2The authors wish to recognize the major contribution to the background, research and narrative of this section by Elizabeth Spletzer.

€tEmmas Adams, J. A. (1971). A closed loop theory of motor learning. Journal of Motor Behavior, 3, 111-150. Asmussen, E., & Heeboll-Nielsen, K. (1955). A dimensional analysis of physical performance in boys. Journul of Applied Physiology, 7 , 593. Astrand, P-0.. & Rodahl, K. (1986). Body dimensions and muscular exercise. I n Astrand, P-0 and Rodahl, K. (Eds.) Teztbook of Work Physiology, 3rd Edition, (pp. 391-411). New York McGraw-Hill. Bayley, N. (1935). The development of motor abilities during the first three years. Monographs of the Society for Research in Child Development, 1 , 1-26. Beek, P.J. (1989). Timing and phase locking in cascade juggling. Journal of Ecological Psychology, 1 (11, 55-96. Bernard, J. (1964). Prediction from human fetal measures. C h i l d Development, 35, 1243-1248. Bertenthal, B.I., & Bai, D.L. (1989). Infants' sensitivity to optical flow for controlling posture. Developmental Psychology, Vol. 25(6), 936-945. Birnholz, J.C., Stephens, J.C., & Faria, M. (1978). Fetal movement patterns: A possible means of defining neurologic developmental milestones in utero. American Journal of Roentgenology, 130, 537-540. Burton, A. W. (1987). The effect of number of movement components on walk time in children. Journal of Human Movement Studies, 13, 231247. Butterworth, G.E., & Hicks, L. (1977). Visual proprioception and postural stability in infancy: A developmental study. Perception, 6, 255-262. Bruner, J.S. (1970). The growth and structure of skill. In K. J. Connolly (Ed.), Mechanisms of motor skill development (pp. 63-94). New York: Academic Press. Connolly, K.J. (1970). Skill development: Problems and plans. In K.J. Connolly (Ed.), Mechanisms of motor skill development, New York: Academic Press. Connolly, K. J. (1972). Learning and the concept of critical periods in infancy. Developmental Medicine and Child Neurology, 14(6) 705-714. Connolly, K. J. (1973). Factors influencing the learning of manual skills by young children. In R. A. Hind, & J. Stevenson-Hind (Eds.) Constraints on learning. New York: Academic Press. Cronbach, L.J. (1957). The two disciplines of scientific psychology. American Psychologist, 12, 671-684. Crossman, E.R.F.W., & Goodeve, P.J. (1983). Feedback control of hand movements and Fitts' law. Quarterly Journal of the Experimental Psychology, 35A, 251-278. (Original work published 1963).

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Davis, W.E., & Burton, A.W. (in press). Ecological task analysis: Translating movement behavior theory into practice. Adapted Physical Activity Quarterly. deVries, J.I.P., Visser, G.H.A., & Prechtl, H.R.F. (1982). The emergence of fetal behavior. Z. Qualitative aspects. Early Human Development, 7, 301-322. deVries, J.I.P., Visser, G.H.A., & Prechtl, H.R.F. (1985). The emergence of fetal behavior. II. Quantitative aspects. Early Human Development, 12, 99120. deVries, J.I.P., Visser, G.H.A., & Prechtl, H.R.F (1988). The emergence of fetal behavior. ZZZ. Quantitative aspects. Individual differences and consistencies. Early Human Development, 16, 85-103. Fitts, P.M. (1954). The information capacity of the human motor system in controlling the amplitude of movement. Journal of Experimental PSyChOlOgy, 47, 381-391. Gesell, A. (1946). The ontogenesis of infant behavior. In L. Carmichael (Ed.), Manual of Child Psychology. New York Wiley. Gesell, A., & Amatruda, C.S.(1965). Developmental diagnosis (2nd Ed.). New York Harper and Row. Gibson, J.J. (1977). The theory of affordances. I n R.E. Shaw and J. Bransford (Eds.), Perceiving, acting and knowing: Toward an ecological psychology (pp. 67-82).Hillsdale, N J Erlbaum. Gibson, J. J. (1979). The ecological approach to visual perception. Boston: Houghton Mifflin Company. Goodenough, F. L., & Brian, C. R. (1929). Certain factors underlying the acquisition of motor skill by pre-school children. Journal of Experimental Psychology, 12, 127-155. Grant, A., Valentin, L., Elbourne, D., & Alexander, S. (1989). Routine formal fetal movement counting and risk of antepartum late death in normally formed singletons. The h n c e t , 1989 ZZ, 345-349. Hopkins, B., & Prechtl, H.F.R. (1984). A qualitative approach to the development of movements during early infancy. I n H.R.F. Prechtl (Ed.), Clinics in developmental medicine, 94, 179-197. Haywood, K.M. (1986). Life span motor development . Champaign: Human Kinetics. Hutt, S. J. (1973). Constraints on learning: Some developmental considerations. In R. A. Hind, & J. Stevenson-Hinde (Eds.), Constraints on learning-. New York: Academic Press. Keogh, J.F. (1975). Consistency and constancy i n preschool motor development. In H.J. Miller, R. Decker, & F. Schilling (Eds.), Motor behavior of preschool children. Schorndorff, W. Ger.: Hofman.. Keogh, J.F. (1977). The study of movement skill development. Quest, Monograph 28.76-88. Kugler, P.N., Kelso, J.A.S., & Turvey, M.T (1980). On the concept of coordinative structures as dissipative structures: I. Theoretical lines of convergence. In G.E. Stelmach, & J. Requin (Eds.), Tutorials in motor behavior (pp. 3-7). Amsterdam: North-Holland.

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Kugler, P.N.,Kelso, J.A.S. & Turvey, M.T. (1982). On the control and coordination of naturally developing systems. In J.A.S. Kelso, & J.E. Clark (Eds.), The development of movement control and coordination (pp. 5-78).New York: Wiley. Kugler, P.N., & Turvey, M.T. (1987). Information, natural law, and the self-assembly of rhythmic movement. Hillsdale, N J Erlbaum. Langolf, G.D., Chaffin, D.B., & Foulke, J.A. (1976). An investigation of Fitts' law using a wide range of movement amplitudes. Journal of Motor Behavior, 8, 113-128. Lee, D.N., Aronson, E. (1974). Visual proprioceptive control of standing in human infants. Perception & Psychphysics, 15, 527-532. Lee, D.N. (1980). The optic flow-field The foundation of vision. Phil. Trans. Royal Society, London B, 290, 169-179. Lee, D.N., Young, D.S., & McLaughlin, C.M. (1984). A roadside simulation of road crossing for children. Ergonomics, 27, 1271-1281. McCain, G., & Segal, E.M. (1973). The game of science, Monterrey, CA: BrookdCole. McGraw, M. G. (1945).Neuromuscular maturation of the human infant. New York; Columbia University Press. McMahon, T. A. (1975).Using body size to understand the structural design of animals: quadrupedal motion. Journal of Applied Physiology, 39(4), 619627. Mounoud, P., & Vinter, A. (1981). Representation and sensimotor development. In G. Butterworth (Ed.), Infancy and epistemology: An evaluation of Piaget's theory (pp. 200-235). Brighton, Sussex: Harvester. Newell, K.M. (1986). Constraints on the development of coordination. In M.G. Wade, &H.T.A. Whiting (Eds.), Motor development in children: Aspects of coordination and control (pp. 341-360). Dordrecht: Martinus Nijhoff. Pascale-Leone, J. (1970). A mathematical model for the transition role in Piaget's developmental stages. Acta Psychologica, 32,301-365. Piaget, J. (1952). The origins of intelligence in children. New York: International University Press. Prechtl, H.F.R. (1984). Continuity and change in early neural development. In H.F.R. Prechtl, (Ed.), Clinics in Developmental Medicine, 94, 1-15. Prechtl, H.F.R. (1985). Ultrasound studies on human fetal behavior. Early Human Development, 12, 91-98. Prechtl, H.F.R. (1986a). New perspectives i n early human development. European Journal of Obstetrics and Gynecology, 21, 347-355. Prechtl, H.F.R. (1986b). Prenatal motor development. In M.G. Wade, & H.T. A. Whitney (Eds.), Motor development i n children: Aspects of coordination and control (pp. 53-64). Dordrecht: Martinus Nijhoff. Richards, T.W., Newberry, H. & Fallgatter, A. (1938). Studies in fetal behavior: 11. Activity of the human fetus in utero and its relation to other prenatal condition, particularly the mother's basal metabolic rate. Child Development, 9, 69-78.

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Richards, T.W., Newberry, H. (1938). Studies in fetal behavior: 111. Can performance on test items at six months postnatally be predicted on the basis of fetal activity? Child Development,l8, 79-86. Roberton, M.A. (1978). Stages in motor development. In M.V. Ridenour (Ed.), Motor development: Issues and applications. Princeton: New Jersey. Robertson, S.S. (1985). Cyclic motor activity in the human fetus after midgestation. Developmental Psychobiology, 18, 411-419. Ross, W. D., Grand T. I., Marshal, G. R., & Martin, A.D. (1984). On human and Animal geometry, procedings of the VII commonwealth and international conference on sport, physical education, recreation and dance. Kinesiological Sciences, Volume VII, M. L. Howell and V. D. Wilson, (Eds), Department of Human Movement Studies, University of Queensland, Brisbane, Australia, 1984. Schmidt, R.A. (1988). Motor and action perspectives on motor behavior. In O.G. Meijer and K. Roth (Eds.), Complex movement behavior: The motor-action controversy (pp. 3-44).Amsterdam: Elsevier. Schmidt, R.A. (1988). Motor control and learning: A behavioral emphasis. Champaign, IL: Human Kinetics. Schmidt, R.A. (1975). A schema theory of discrete motor skill learning. Psychological Review, 82, 225-260. Seefeldt, V., & and Haubenstricker, J. (1974). Developmental sequences of fundamental motor skills. Unpublished manuscript, Michigan State University, Department of Health and Physical Education, East Lansing. Shadmi, A., Homburg, R., & Insler, V. (1986). An examination of the relationship between fetal movements and infant motor activity. Acta Obstetricia et Gynecologica Scandanavia, 65, 335-339. Smoll, F.L. (1982). Developmental kinesiology: Toward a sub-discipline focusing on motor development. In J. Kelso & J. Clark (Ede.), T h e development of movement control and coordination (pp. 319-354).New York: Wiley & Sons. Sorokin, Y., Pillary, S., Dierker, L.J., Hertz, R.H., & Rosen, M.G. (1981). A comparison between maternal, tocodynamometric, and real-time ultrasonographic assessments of fetal movement. American Journal of Obstetrics and Gynecology, 140,456-460. Stoffregen, T.A. (1985). Flow structure versus retinal location in optical control of stance. Journal of Experimental Psychology: Human Perception and Performance, 11, 554-565. Sugden, D. A., (1980). Movement speed in children. Journal of Motor Behavior, 12,125-132. Thelen, E., & Fisher, D.M. (1982). Newborn stepping: An explanation for a "disappearing reflex". Developmental Psychology, 18, 760-775. Thelen, E., & Cooke, D.W. (1987). Relationship between newborn stepping and later walking: A new interpretation. Developmental Medicine and Child Neurology, 29,380-393. Thelen, E. (1986).Development of coordinated movement: Implications for early human development. In M.G. Wade & H. T. A. Whiting (Eds.),

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Warren, W.H. (1984). Perceiving affordances: Visual guidance of stair climbing. Journal of Experimental Psychology: Human Perception and PeTformnce, 10, 683-703. WolfFt P.H.(1986). The maturation and development of fetal motor patterns. In M. G.Wade & H.T.A. Whiting (Eds.), Motor development in children: Aspects of coordination and control (pp. 65-74). Dordrecht: Martinus Nijhoff. Yates, E. F., & Kugler, P.N. (1986). Similarity principles and intrinsic geometries: contrasting approaches to interpecies scaling. Journal of Pharnaceutical Sciences, 75(11), 1019 - 1027.

The Development of Timing Control and Temporal Or anization in Coordinated Action J. Fagard an~!€’.H. Wolff (Editors) Ca Elsevier Science Publishers B.V., 1991

Coordinative structures and the development of relative timing in a pointing task D.L. Southard Department of Physical Education, Texas Christian University, Box 32901, Fort Worth, Texas, 76129, USA Abstract The development of interlimb coordination has received a good deal of attention in recent years. Much of that attention is owed to the dynamical systems perspective. This approach to understanding coordination is a breakaway from most other theories which view developmental change as an a priori formulation of instructions from some controller, or executive system. Rather, limbs are organized into functional units by a process termed a coordinative structure. This coordinative function acts, in a post hoc fashion, according to specific tasks and within given environmental constraints. An accepted recognition of coordinative structures is the by-product of invariant relative timing in the face of changes in absolute velocity of limb components. Here, the development of multilimb pointing tasks involving the same limbs, combinations of hands and feet, and singlelimb components are examined from a dynamical systems perspective. It is suggested that: 1) a coordinative structure is the functional unit of control regardless of age; and 2) relative time to peak velocity is not the best indicator of mutual influence between limbs for all interlimb tasks.

1. Introduction The relative influence of one limb on the other has captured the curiosity of movement scientists for many years. Perhaps Woodworth (1903) was the first (in this century at least) to note that “movements of the left and right hands are easy to execute simultaneously“. When each hand simultaneously performs the same task there appears to be a facilitating effect between limbs. Moreover, when each hand performs a different task the mutual effects of one limb on the other are equally observable. Earlier twentieth century researchers examined these co-mutual effects by investigating the syncopated rhythms of fingers when subjects attempted to tap each hand at the same and different tempos (Davis, 1904; Farnsworth, and Poynter, 1931; and Langfield, 1915). Generally, the results of such studies verified what Woodworth had already observed. That is, there is considerable

28 1

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difficulty in retaining individual tempos by hand when both hands tap at the same time. More recent tapping studies by Klapp (1979, 1981) and Klapp, Hill, Tyler, Marten, Jagacinski, and Jones (1985) have confirmed the work of earlier polyrhythmic paradigms by demonstrating that it is the disruption of relative time, or the non-harmonic nature of tapping rhythms (e.g. 3:2, and 5:4) that lead to mutual interference. Early explanations for "limb coupling" were instinctual alibis. Langfield (1915) noted that there must be some "innate coordination" responsible for interference between limbs. Davis (1904) was more descriptive, but no more informative when he stated that there must be a "close connection between different parts of the muscular system through neural means". Recent researchers have expounded upon earlier explanations. Peters (1981, 1985) utilized a tapping paradigm to provide evidence for a supraordinate control mechanism responsible for the coupling effects between limbs. Perhaps the least allegorical approach has been taken by Yamanishi, Kawato, and Suzuki (1980). They attribute the linkage between limbs to the oscillatory properties of the nervous system. The dynamic approach of Yamanishi et al. has been supported by recent oscillatory tapping studies concerning the formation of interlimb patterns (Scholz, and Kelso, 1989), and changes in such patterns relative to loss of pattern stability (Scholz, and Kelso, 1990). The efficacy of tapping studies for the investigation of interlimb coupling stems from the ease with which features of movement patterns (such as relative time between limbs) may be manipulated. It is the strength of such paradigms that also serve as a weakness. First, the task demands do not reflect the complexity of the motor system, and second, subjects are "instructed" to move their fingers at differing rates which produces the very effects that researchers oftentimes investigate. An alternative approach, which has not enjoyed the historical popularity of tapping paradigms, is the examination of bimanual pointing tasks. In 1979 Kelso, Southard, and Goodman introduced a paradigm which required subjects to move one index finger to an easy target (wider target with relatively short amplitude) and the other index finger to a difficult target (narrower target with greater amplitude). The only instructions given to subjects were to move as fast and accurately as possible. When the movements were combined in a two-hand condition, subjects initiated and terminated the movements together. It is important to note that simultaneity, in and of itself, is not the issue of importance. Rather, simultaneity of hands serves to reinforce the coupling effect between limbs. That is, the hand moving to the difficult target moved more rapidly than its singlehand control, while the hand moving to the easy target moved more slowly than its single-hand control. Kelso, et al. (1979) attributed their findings to a functional linkage of muscle groups which constrain the limbs

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to act as a single unit. The process by which homologous and non-homologous muscle groups are "coupled" to act synergistically is called a coordinative structure (Bernstein, 1967). Coordinative structures preserve a common temporal metric over changes in the magnitude of activity in individual components. The Kelso et al. (1979) data indicated that the velocity of each finger to respective targets was different, but the relative time to peak velocity and acceleration was the same for each limb. Later studies using a similar paradigm have indicated the robustness of the relative invariance between limbs from a spatial as well as temporal perspective (Southard, and Goodman, 1982), with a mass added to one hand (Marteniuk, and Mckenzie, 1980), and with a boundary placed between one hand and the target (Kelso, Putnam, and Goodman, 1983). Other studies have reported the breakdown of simultaneity of movement initiation and completion, but support the overall coupling effect during movement (Corcos, 1984; and Marteniuk, Mckenzie, and Baba, 1984). Does the mutual relationship between limbs demonstrated by coadunate timing, common to adult bimanual movements, change with age? The answer to this question remains unresolved. Albeit, the dynamic perspective of motor coordination (Kelso, and Tuller, 1984) and its application to motor development provides a rationale for examining the question. The dynamic approach to developing systems views coordinative structures as dissipative structures which constitute a set of organizational constraints operating within a particular environment. A n important characteristic of this approach is that emerging patterns (and resulting temporal consequences) are the result of the mover interacting with the environment rather than a planned prescription for pattern change. The interaction of organizational constraints, movement goal, and environment may be most evident in the study of quadruped gait patterns. The work of McGhee and Frank (1968) has shown that there are six patterns that might theoretically be used for quadruped (including human) crawling. The pattern which occurs at slow speeds for all species is in the order of Left Hind, Left Front, Right Hind, and Right Front. The (LH, LF, Rh, RF) pattern is an excellent €it between the mechanical demand of static stability placed on the slow moving terrestrial form and the goals of its intrinsic organizational constraints. As quadrupeds scale up on velocity there is a change from low speed static stability to higher speed dynamic stability. The more rapid gaits are characterized by periods of static instability in which support is relinquished in the interest of obtaining greater speed (Frank, and McGhee, 1969). New mechanical demands require a change in phase relationships between limbs to accommodate the goal of increased velocity. Kugler, Kelso, and Turvey (1982) refer to such changes as "bifurcations" in the structural stability of the biomechanical system. The structural stability for interlimb pointing tasks should not be jeopardized by performance criteria (such as increasing

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velocity of limbs to targets, or more accurate limb positioning), providing the relative motion of limbs represents an optimal parameterization of the coordinative function. That is, if a coordinative structure represents the most efficient means of accomplishing interlimb tasks, and the goal of the movement does not change, then structural stability should be preserved. The by-products of such stability (e.g., relative time) should, and do (see Kelso, Putnam, and Goodman, 1983) remain constant. However, optimization criteria are determined not only through interaction of the environment and task, but the organism as well (Newell, 1985). From a developmental perspective, increasing bodily dimensions which accompany increases in age constitute a change in interaction of variables that determine an optimal coordinative function. There are constraints, both structural and functional, that relate to such scaling problems encountered by developing organisms. Scaling is defined as the structural and functional consequences of a change in size or scale among similarly shaped animals (Schmidt-Nielsen, 1977). When humans develop and consequently increase in size, limits in the efficiency of motor patterns may be reached which can be overcome by changes in design, materials, and or coordinative function. Given that, for the human body, design and materials are scale-independent factors, our only recourse may be to change the coordinative function to accommodate an increase in size. Of course, such changes are necessary only if the increase in size is accompanied by a decrease in efficiency. When efficiency of the system is not challenged, the coordinative function for bodies of similar design and construction may persist over a change in scale. The experiment reported here investigated whether the fundamental unit for the dynamical systems theory (coordinative structure) is utilized to constrain limbs to act as a unit during a four-limb pointing task. Furthermore, if the limbs are coordinated by an interlimb coordinative structure, does this coordinative function change developmentally? The experimental design allows for investigation of contralateral coupling within limbs, as well as ipsilateral, and cross lateral coupling between limbs. 2. Methods 2.1 Subjects

Twenty male subjects were placed in four equal groups according to age. Group 1 was the 5 year old group (mean age 5 . 4 ) , Group 2 were 7 year olds (mean age 7.3), Group 3 were 9 year olds (mean age 9.6), and Group 4 were 11 year olds (mean age 11.5). All subjects were right handed for writing and throwing.

CoordiMtive Structures and Relative Timing in a Pointing Task

285

2.2 Apparatus The apparatus consisted of an Apple IIe computer interfaced with normally closed and normally open switches for the collection of reaction and movement times. The computer controlled all aspects of the experiment including a 1-5 second variable foreperiod, auditory stimulus to move, and 3 second intertrial interval. TWO normally closed switches (reaction time keys for the hands) were centrally positioned on the edge of a glass table top (1 meter X 1 meter). Similarly, two normally closed switches (reaction time keys for the feet) were positioned on the floor directly under the keys on the glass table. "wo normally open switches (movement time keys for the hands and feet) were located laterally from RT keys located on the table top and floor. The glass top allowed subjects to view each limb during conditions requiring the movement of both hands and feet. A WATSMART (Northern Digital) motion analysis system was used to obtain data from all four limbs. Infrared emitting diodes (IREDS) were placed on the index fingers of each hand and the first toenail of each foot. The system was calibrated with a metal frame of known dimensions. Accuracy was achieved to within 1.5 mm. Data were collected at a sampling frequency of 100 HZ and filtered with a cutoff frequency of 5 HZ using a doublepass Butterworth filtering process. 2.3 Procedure Subjects were seated in a chair and centered behind the glass table. The chair and table top were adjustable S O that subjects of different heights could be adjusted to the same relative position to the apparatus. Subjects were instructed to depress the RT keys with their index fingers and or first toes. Then, following an auditory stimulus, subjects moved the designated limb(s) to respective targets as fast and accurately as possible. There were no directions offered to subjects concerning synchronous behavior of limbs. Speed and accuracy were equally stressed. If a subject missed any one of the targets, they were required to repeat the trial. A miss was defined as not closing the target switch(es) with the index fingers and or first toes. Error rates varied by condition and group, however, the overall error rate was 14%. See Figure 1 for a representation of subject preparation and apparatus. 2.4 Design A within subjects design was utilized with all subjects completing 15 trials for each of 40 randomly presented conditions. All combinations of easy (6 cm diameter and 10 Cm amplitude) and difficult (2.5 cm diameter and 25 cm amplitude) targets were balanced by limb and side for each block of conditions. All extraneous RT and MT switches were removed from the apparatus for movements requiring less than four limbs. See figure 2 for a representation of conditions by block.

D.L. Southard

286

I

WATSMART SYSTEM

Figure 1. Subject preparation and apparatus.

3 . Results

3.1 Temporal Reaction Times

X 2 Limbs X 2 Sides) analysis of variance indicated differential initiation times for Groups F(3,20) = 72.73, P <.001. post hoc analysis revealed significant decreases in reaction time with increases in age. A significant main effect by Blocks F(4,20) = 57.33, p <.001 indicated that when arms and legs are paired (Blocks 2, 3, and 5) reaction times are significantly increased over single-limb (Block 1) and contralateral (Block 4 ) conditions. Furthermore, Block 3 was significantly slower than other arm/leg combinations. Significant main effects by Limbs F(1,23) = 35.55, p <.001 indicated that it was the legs which accounted for increased reaction times in those blocks where arms and legs were paired. The differing initiation times between arms

A four-way ( 4 Groups X 5 Blocks

CoordinativeStructures and Relative Timing in a Pointing Task

287

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Figure 2. Representation of Conditions by Block. The first row for each condition represents arms; the second row represents legs.

and legs may not be an indication of a breakdown in synchronous behavior. Rather, the disparate reaction times may be a function of the larger moments of inertia possessed by the lower limbs (Anson, 1989). Mean scores for reaction times may be found in Table 1. Movement Times A four-way ( 4 Groups X 5 Blocks X 2 Limbs X 2 Sides) analysis of variance indicated a significant main effect for Groups (F(3,20) = 162.96, P <.001.) Examination of mean scores indicates that moveme?ittimes decreased as age increased. Post

D.L. Southard

288

Table 1 Mean scores for reaction times by Block, Group, Limb, and Side. Mean scores are in milliseconds. 1 M (SD)

2 M (SD)

3

M (SD)

4

M (SD)

Block

252.76 (53.38)

278.00 (41.47)

316.73 (71.85)

243.02 (46.25)

Group

316.76 (61.44)

291.12 (53.44)

266.09 (53.60)

240.21 (50.47)

Limb

266.79 (53.32)

285.82 (67.15)

Side

276.23 (61.69)

281.21 (61.09)

5 M (SD) 262.71 (35.66)

hoc analyses for Blocks (F(4,20) = 4.91, p <.01) indicated that single-limb movements were significantly faster than other conditions. A significant main effects for Limbs (F(1,23) = 98.00, P <.001) showed that the arms were significantly faster Than the legs. Additionally, there were significant two-way (Groups X Blocks F(12,24) = 3.47 p <.01; Groups X Limbs F(3,24) = 11.76, 2 c.001; Groups X Sides F(3,24) = 5.26, p <.01) interactions, and a three-way (Groups X Blocks X Limbs F(12,24) = 4.19, p <.01) interaction. The interactions are an indication of mutual adjustment within and between limbs. For Blocks 2, 3, and 5, the legs were slower to initiate movement, but had faster movement times. The adjustment allows for each set of limbs to reach their targets synchronously. For Block 4, the hand or foot moving to the easy target slows to the level of its more difficult counterpart. Such adjustments are in agreement with earlier studies using a similar design for only the upper limbs (Kelso et al. 1979, 1983). Mean scores for movement times may be found in Table 2. 3.2 Kinematics The kinematic variables chosen to represent movements of the limbs were peak velocities in three planes of motion, negative peak velocities in the Y and Z planes, time to peak velocities, and relative time to peak velocities. F o r the purposes of analyses, positive direction for t h e X plane was considered to be away from body midline regardless of the relative direction of left and right limbs. The reference point for computing time to peak velocity was the first initiation of movement by any limb. For Blocks 2, 3, 4, and 5, the time to peak velocity for each limb began

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289

Table 2. Mean scores for movement times by Block, Group, Limb, and Side. Mean scores are in milliseconds. 1 M (SD)

2 M (SD)

3 M (SD)

4

5

M

M

(SD)

Block

223.56 (53.23)

236.15 (42.32)

237.84 (41.16)

238.52 (46.67)

Group

256.12 (45.52)

263.57 (52.35)

219.31 (28.43)

202.25 (28.90)

Limb

222.93 (43.11)

245.59 (47.99)

Side

232.41 (47.60)

235.89 (46.23)

(SD) 231.39 (53.76)

from the initially established reference point. Relative time to peak velocity was computed by dividing the time to peak velocity by the total movement time for each individual limb. The initiation of movement for each limb served as its own reference point for computing relative time to peak velocity. Peak Velocity A five-way (4 Groups X 5 Blocks X 2 Limbs X 2 Sides X 3 Planes) analysis of variance of peak velocity in the positive direction indicated significant main effects for Groups (F(3,20) = 4.50, p <.01); Blocks (F(4,20) = 2.89, p C.05); and Planes (F(2,22) = 238.69, p <.001). Post hoc analysis revealed that peak velocity increased with age. Block 1 was significantly greater than remaining blocks. Block 4 was greater than Blocks 2, 3, and 5, and Block 5 was greater than Block 3. Peak velocity in the x plane was significantly greater than remaining planes, with Y plane velocity being significantly greater then Z plane velocity. There were also significant Groups X Limbs F(3,24) = 5.76, p <.01; and Limbs X Sides F(1,24) = 4.28, p <.05 interactions. A five-way analysis of variance of peak velocity in the negative direction (only applies to the Y and Z planes of motion) indicated significant main effects by Limbs (F(1,23) = 5.49, p <.05); and Planes (F(1,23) = 24.31, p <.001). The arms were significantly greater than the legs, and the Y plane was significantly greater than the 2 plane of motion. Means for peak velocities may be found in Table 3. Time to Peak Velocity A five-way (4 Groups X 5 Blocks X 2 Limbs X 2 Sides X 3 Planes) analysis of variance in the positive direction indicated significant main effects for Groups, Blocks, Limbs,

D.L. Southard

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Table 3 Mean scores for peak velocities by Block, Group, Limb, Side, and Plane. Velocities are in millimeters per second. 1

M (SD)

Block

Pos Neg

Group

POS

Neg Limb

Pos Neg

Side

Pos Neg

Plane Pos Re 3

2 M (SD)

3 M (SD)

4

5

M

M

(SD)

1058.76 (88.92) 522.46 (56.11)

903.64 (58.24) 342.31 (28.51)

882.07 (52.63) 358.90 (30.56)

989.99 (90.44) 567.48 (52.98)

845.02 (50.91) 458.17 (36.28)

878.87 (52.37) 357.92 (29.42)

974.65 (80.17) 453.04 (93.23)

1055.38 (85.89) 450.21 (83.46)

995.98 (69.20) 508.14 (67.48)

886.44 (71.09) 350.98 (71.09)

930.25 (68.56) 446.79 (67.89)

954.03 (72.16) 418.07 (71.49)

1261.07 (51.46)

755.59 (63.47) 582.39 (69.67)

(SD) 923.91 (64.63) 426.86 (29.75)

261.55 (67.94) 263.25 (65.68)

and Planes (Groups F(3,20) = 12.67, p <.001; Blocks F(4,20) = 6.56, p <.01; Limbs F(1,23) = 25.98, p c.001; Planes F(2,22) = 48.43, p c.01); with significant Groups X Blocks (F(12,24) = 2.87, g <.01), Groups X Limbs (F(3,24) = 4.68, p <.01), and Blocks X Limbs (F(4,24) = 3.74, <.05) interactions. Post hoc analyses revealed that Groups 1 and 2 were significantly greater than Groups 3 and 4. Block 3 was significantly greater than Blocks 1, 4, and 5. The legs were significantly later to reach peak velocity than the arms, and time to peak velocity in the X plane was significantly greater then the Y and 2 planes of motion. A five-way analysis of variance for time to peak velocity in the negative direction indicated significant main effects for Groups, Blocks, Limbs, and Planes (Groups F(3,20) = 74.93, P <.001; Blocks F(4,20) = 11.34, p <.001; Limbs F(1,23) = 61.14, P c.001; Planes F(1,23) = 18.36, P <.001) with significant Groups X Blocks (F(12,24) = 4.16, P c.01, and Groups X Limbs (F(3,24) = 6.01, p c.001) interactions. Post

Coordinative Structures and Relative Timing in a Pointing Task

29 1

hoc analysis revealed that Groups 1 and 2 were significantly greater than Groups 3, and 4. The legs were significantly later to reach peak velocity than the arms, and the Y plane was greater than the Z plane of motion. Mean scores for time to peak velocities may be found in Table 4. Relative Time to Peak Velocities A five-way (4 Groups X 5 Blocks x 2 Limbs X 2 Sides X 3 Planes) analysis of variance for relative time to peak velocity in the positive direction indicated significant main effects for Limbs and Planes (Limbs F(1,23) = 4.27, <.05; Planes F(2,22) = 5.86, P <.01); with significant Blocks X Limbs (F(4,24) = 5.14, p-<.Ol) and Limbs X Planes (F(2,24) = 4.87, p <.05) interactions. Post hoc analysis revealed that relative time to peak velocity in the X plane was significantly greater than the Y and Z planes of motion. The arms were relatively slower in reaching peak velocity than the legs. A five-way analysis of variance for relative time to peak velocity in the negative direction indicated a significant main effect for Groups (F(3,20) = 8.36, p <.001); with a significant Limbs X Planes (F(2,24) = 5.58, P <.05) interaction. Post hoc analysis revealed that Groups-1 and 2 were significantly greater than Group 4. Mean scores for relative time to peak velocities may be found in Table 5. 3.3 Trajectory Data Displacement, velocity, and acceleration a € I imbs wt:Yt: plotted over time for each condition in thxee 3t motion. However, only Condition 21 (mixed diffichty Lc;ur limb) and the contralateral (Conditions 25 and 28) and singlelimb (Conditions 1, 4, 6, and 7) counterparts are represented for each group. The mixed difficulty four limb conditions best indicate mutuality between and within limbs when compared with contralateral and single- limb counterparts. Movement Patterns representing kinematic data may be found in Figures 3A through D and 4A through D.

4 . Discussion

Behavioral and trajectory pattern data indicate mutual influence within and between limbs for all groups of subjects. When arms or legs were required to move to targets of disparate difficulty (Block 4), there is mutual adjustment of reaction time, movement time, velocities, and movement pattern in order to accomplish more synchronous behavior. Older subjects (7, 9, and 11 year olds) were able to initiate and complete four-limb movements in tighter synchrony than 5 year olds. However, movement pattern data indicates that younger subjects (ages 5 and 7 years) are more tightly coupled between limbs following movement initiation (note the change in

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292

Table 4 Mean scores for time to peak velocities by Block, Group, Limb, Side, and Plane. Time to peak velocities are in milliseconds. 1 M (SD)

2 M (SD)

3 M (SD)

4 M (SD)

103.71 (36.42) 187.02

116.89 (38.83) 217.32

128.92 (26.47) 228.86

108.39 (37.38) 197.03

133.57 (26.20) 250.88 (28.63)

122.69 (21.13) 245.83 (31.32)

106.75 (41.26) 106-75 (24.22)

103.33 (32.82) 103.33 (19.15)

105.87 (32.69) 194.99 (24.84)

125.79 (30.72) 230.39 (33.00)

Neg

112.52 (28.60) 208.43 (31.82)

119.01 (35.88) 215.68 (28.36)

Plane Pos

131.95 (26.52)

98.78 (33.63) 223.35 (27.84)

Block

Pos Neg

Group Pos Neg Limb

Pos Neg

Side

Pos

Neg

5 M (SD)

108.78 (17.19) 219.21

89.80 (36.86) 199.19 (31.53)

patterns when comparing four-limb movements to contralateral and single-limb counterparts for 5 and 7 year olds in comparison to 9 and 11 year olds). Both trajectory and temporal data support tighter coupling within limbs and weaker coupling between limbs as groups increase in age. Constrainments between the arms and legs are asymmetrical, with the influence of the arms on the legs being more profound. With four-limb conditions, both the timing and pattern of the arms is altered less than that of the legs in comparison to contralateral and single-limb counterparts (see Figures 3A through 4D). Significant differences in initiation times and movement times by limb, but not by side, support the contention that contralateral movements (Block 4) are most tightly coupled across groups. The data agree with Thelen (1986) that at earlier ages there are more global constraints imposed by coordinative structures. These generalized constraints may account for tighter coupling between arms and legs for younger subjects.

293

Coordnative Structures and Relative Timing in a Pointing Task

Table 5 Mean scores for relative time to peak velocities by Block, Group, Limb, Side, and Plane. Relative time is expressed as a percentage of movement time. 1

Group

2

3

4

5

Pos

Neg Limb

Pos Neg

Side

Pos

Neg Plane

Pos -9

The constancy of timing relationships across scaler changes in rate is an accepted signature of coordinative structures (Kelso, et al., 1983; Kelso, and Tuller, 1984; Kugler, Kelso, and Turvey, 1980; Thelen, Bradshaw, and Ward, 1981; Wetzel and Stuart, 1977). Such timing is commonly expressed as relative time. That is, time to muscular activity and or peak kinematic variables divided by total movement time. Data from this study indicates that the breaking action of the limbs (peak velocity) in the positive direction occurs at the same relative time for each age group, but at earlier relative times in the negative direction for the oldest group. This likely reflects differences of confidence in accuracy rather than any breakdown in coupling effect by age. It appears that a coordinative structure is the coordinative function for interlimb pointing tasks across changes in age. Relative time is a by-product of limb coupling, but may not always reflect the mutual influence of one limb on the other.

Figure 3A. Patterns of kinematic data for a four-limb condition and contralateral components: Group 1. Subject LC.

E

m

i

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al c m

ii

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Figure 3B. Patterns of kinematic data for a four-limb condition and contralateral components: Group 2. Subject OA.

m

Q)

c

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Figure 3C. Patterns of kinematic data for a four-limb condition and contralateral components: Group 3. Subject JS.

E

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Figure 3D. Patterns of kinematic data for a four-limb condition and contralateral components: Group 4. Subject HS.

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Figure 4A. Patterns of kinematic data for single-limb components of Condition 21: Group 1. Subject LC.

Figure 4B. Patterns of kinematic data for single-limb components of Condition 21: Group 2. Subject OA.

Figure 4C. Patterns of kinematic data for single-limb components of Condition 21: Group 3. Subject JS.

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Figure 4D. Patterns of kinematic data for single-limb components of Condition 21: Group 4. Subject HS.

302

D.L. Southard

Significantly greater relative time to peak velocity (positive direction) for the arms, in comparison with greater absolute time to peak velocity for the legs reinforces a differential movement pattern by limb when arms and legs are paired (Blocks 2, 3, and 5). As age increases, differences in relative time to peak velocity between limbs decreases. On the other hand, as age increases, there is increased stability in movement pattern when comparing arm and leg combinations with their single-limb counterparts. The stability that occurs with increasing age is interpreted as a weakening of the mutual influence between arms and legs. Invariant relative time between limbs is more likely a by-product of movement simultaneity rather than a valid indication of mutual influence between limbs. Adjustment in limb kinematics and movement pattern indicates the integration of relative task demands with a functional coordinative unit (coordinative structure). 5 . References

Anson, J.G. (1989). Effects of moment of inertia on simple reaction time. Journal of Motor Behavior, 21, 60-71. Bernstein, N.A. (1967). The Coordination and Regulation of Movements. Oxford: Pergamon Press. Corcos, D.M. (1984). Two-handed movement control. Research Quarterly for Exercise and Sport, 55, 117-122. Davis, W.W. (1904). L' action motrice bilaterale de chaque hemisphere cerebral. L'anoree Psychol., 11, 434-445. Farnsworth, P.R., and Poynter, W.F. (1931). A case of unusual ability in simultaneous tapping in two different times. American Journal of Psychology, 43, 633. Frank, A.A., and McGhee, R.B. (1969). Some considerations related to the design of autopilots for legged vehicles. Journal of Terramechanics, 6, 23-35. Kelso, J.A.S., Putnam, C., and Goodman, D. (1983). On the space-time structure of human interlimb coordination. Quarterly Journal of Experimental Psychology, 35A, 347375. Kelso, J.A.S., Southard, D.L., and Goodman, D. (1979). On the nature of human interlimb coordination. Science, 203, 1029-1031. Kelso, J.A.S., and Tuller, B. (1984). A dynamical basis for action systems. In M.S. Gazzinga (Ed.), Handbook of Cognitive Neuroscience (pp. 321-56). New York: Plenum. Klapp, S.T. (1979). Doing two things at once: The role of temporalcompatibility. Memoryand Cognition, 7, 375-381. Klapp, S.T. (1981). Temporal compatibility in dual motor tasks: 11. Simultaneous articulation and hand movements. Memory and Cognition, 9, 398-401. Klapp, S.T., Hill, M.D., Tyler, J.G., Martin, Z.E., Jagacinski, R.J., and Jones, M.R. (1985). On marching to two different drummers: Perceptual aspects of the

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difficulty Journal of Experimental Psychology: Human Perception and Performance, 11, 814-827. Kugler, P.N. Kelso, J.A.S., and Turvey, M.T. (1982). On the control and coordination of naturally developing systems. In J.A.S. Kelso, and J. Clark (Eds.), The Developnent of Movement Control and Coordination (pp. 5-78). New York: Wiley and Sons Ltd. Langfield, H.S. (1915). A study in simultaneous and alternating finger movements. Psychological Review, 22, 453-470. Marteniuk, R., and MacKenzie, C.L. (1980). A preliminary theory of two hand coordinated control. In G.E. Stelmach, and J. Requin (Eds.), Tutorials in Motor Behavior (pp.122-144). North-Holland: Elsevier Publishers. Marteniuk, R., MacKenzie, C.L., and Baba, D.M. (1984). Binanual movement control: Information processing and interaction effects. Quarterly Journal of Experimental Psychology, 94, 633-643. McGhee, R.B., and Frank, A.A. (1968). On the stability properties of quadreped creeping gaits. Mathematical Bioscience, 3, 331351. Newell, K.M. (1985). Coordination, control and skill. In D. Goodman, R.B. Wilberg, and I .M. Franks (Eds.) , Differing Perspectives in Motor Learning, Memory, and Control (pp. 295-317). North-Holland: Elsevier Publishers. Peters, M. (1981). Handedness: Coordination of within and between hand alternating movements. American Journal of Psychology, 9 4 , 633-643. Peters, M. (1985). Constraints in the performance of bimanual tasks and their expression in unskilled and skilled subjects. Quarterly Journal of Experimental Psychology, 37Ap 171-196. Schmidt-Nielsen, K. (1977). Problems of scaling: Locomotion and physiological correlates. In T.J. Pedley (Ed.), Scale Effects in Animal Locomotion (pp. 1-21). New York: Academic Press. Scholz, J.P. , and Kelso, J.A.S. (1989). A qualitative approach to understanding the formation and change of coordinated movement patterns. Journal of Motor Behavior, 21, 122144. Scholz, J.P., and Kelso, J.A.S. (1990). Intentional switching between patterns of bimanual coordination depends on the intrinsic dynamics of patterns. Journal of Motor Behavior, 22, 98-124. Southard, D.L., and Goodman, D. (1982). Bimanual coordination and memory: A further examination of the simultaneity effect. In L. Wankel, and R.B. Wilberg (Eds.), Psychology of Sport and Motor Behavior: Proceedings CSPLSP (pp.401410). Edmonton: University of Alberta. Thelen, E. (1986). Development of coordinated movement: Implications for early human development. In M.G. Wade, and H.T.A. Whiting (Eds.) , Motor Developnent in Children: Aspects of Coordination and Control (pp. 107-124).

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Boston: Martinus Nijhoff Publishers. Thelen, E., Bradshaw, G., and Ward, J.A. (1981). Spontaneous kicking in month-old infants: manifestations of a human central locomotor pattern. Behavioral and Neural Biology, 32, 45-53. Wetzel, M.C., and Stuart, D.G. (1977). Activation and coordination of vertebrate locomotion. In R. Alexander, and G. Goldspink (Eds.) , Mechanics and Energetics of Animal Locomotion (pp. 115-52). New York: John Wiley and Sons. Woodworth, R.S. (1903). Le Mouvement. Paris: Doin. Yamanishi, J. Kawato, M., and Suzuki, R. (1980). Two coupled oscillators as a model for coordinated finger tapping of both hands. Biological Cybernetics, 37, 219-225.

The Development of Tmin Control and Temporal Or anization in 8oordinated Action J. Fagard an(fPH. Wolff (Editors) 0 Elsevier Science Publishers B.V., 1991

305

Synchronization and desynchronization in bimanual coordination: a developmental perspective 1 Jacqueline Fagard Laboratoire de Psychobiologie de 1’Enfant 41 rue Gay Lussac 75005 Paris France Abstract Temporal constraints are apparent in all kinds of bimanual activities in adults. They do not seem to influence the spontaneous movements of neonates but can be observed in the goal-directed activity of somewhat older infants. Infants use several strategies (mirror, unimanual, se uential) before being able to coordinate asymmetrical output from the two ands. Whether temporal coordination within these preferred patterns becomes tighter or looser with development remains to be determined.

a

1. INTRODUCTION 1.1. The ubiquity of t h e temporal constraints issue The development of temporal constraints on bimanual coordination is part of the broader issue of motor control and its development. A motor pattern seems well coordinated when the tuning among the participating segments and between the successive sections of the action is smooth. Actions are made up of subactions which are carried out sequentially as well as simultaneously, and each subaction involves several movements and postures. Each movement, and its accompanyin postures, re uires the complex coordination of many body segments. There ore sequentiaq timing and temporal atterning are important at many levels of action, even for simple activities. i5 hatever the theoretical approach adopted to investigate motor control and coordination, whether it be traditional neurobehavioral theories based on concept of central/peripheral control, or more recent approaches based on conce ts of erception-action and dynamical systems, one central issue confronts afl stucfies of motor control and/or coordination: How is an activity unitized?; how does an aggregate of muscle-joint complexes become a single functional unit; and how are various streams of activity inte rated into unified acts? in other words, where does coordination come from. Answers to this question differ according to the theoretical frame adopted but in all cases the analysis of temporal parameters in motor behavior provides essential information for addressing such questions. The observation of invariances in the temporal structure of a series of events --or in the timing relationships between effectors particiuatinn in the action- when other

‘i

Is

1 I would like to thank P.B. Wolff and A. Diamond for their helpful conents and critical reading of the manuscript.

306

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temporal variables such as total duration are varied, have motivated the hypothesis that coordination does not result from individual control over each single segment. The hypothesis derives from Bernstein's pioneer contribution in pointing out that control acts on collectives of muscles or synergies, and that the resulting coordination into a low dimensional ensemble reduces the number of independent degrees of freedom in the motor system that must be regulated (Bernstein, 1967). Over the last ten years, extensive research in the motor domain has been devoted to the question of temporal invariances and their significance in terms of motor control. The idea that such invariances are prescribed at a central level has been challenged by a more economical approach postulating that temporal invariances d o not have to be programmed at the cortical level (cf. chap. 2) or generated at the brain stem level (cf. chap. 4), but instead reflect organizational constraints of the motor apparatus as a consequence of the system dynamics (cf. chap. 3).

1.2. The specificity of the bimanual system Bimanual coordination provides an interesting example of multimovement coordination because (1) it requires the cooperation of several groups of effectors, some of which are symmetrically organized with reference to the body's sagittal axis; (2) it provides an opportunity to observe natural constraints (just try to rotate simultaneously two arms at different speeds!); (3) it occurs in most daily activities, and can be easily studied in many different situations. The term bimanual coordination covers several different kinds of bilateral actions involving the arms and hands (MacKenzie & Marteniuk, 1985). Bimanual movements may vary along the same Feneral dimensions as all movements: they can be open (performed in a moving environment) or closed (performed in a stable frame of reference); discrete (such as using one hand to cap a bottle held in the other hand), serial ( laying the piano), o r continuous (winding a thread). They can be part of a roader action (openin a jar to remove an object), or for no other purpose than the movement itself b u c h as in many experimental situations). They can sustain a common goal (most daily activities, such as holding an object with one hand while the other hand manipulates it) or they ma involve a simple juxtaposition of two activities (two-hand pointing task). &hat makes bimanual movements unique is the relationship of the movements between the two hands. Different temporal and spatial relationships between the movements can be distin uished: movements can be simultaneous, alternating, o r sequential. They can %esymmetrical with reference to the body's axis (block banging a t the midline), symmetrical with reference to each other (two hands reaching to a side-presented object), or asymmetrical (opening a jar). Guiard ( 1987) has suggested categorizing bimanual movements according to the way the two hands are assembled in the coordinated action. H e identified three broad classes of bimanual movements. When the hands act on the same object (e.g. moving a single target on a screen by manipulating two cranks that independently control a different component of the motion or using a tracing table), the assembl of discrete movements is said to be "orthogonal". When two similar and non-di%erentiated actions b the two hands contribute to the same activity, for instance while lifting a weigat, the assembly is said to be "parallel". Finally, when the two hands cooperate asymmetrically in the same action, such as peeling an apple, opening a jar, etc., the assembly is said to be "serial".

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These distinctions are helpful f o r describing different types of relationships between simultaneous movements of the two hands, but they d o not classify bimanual activities comprehensively. Many bimanual activities may start as parallel assemblies (for instance when graspin an object to be manipulated with the two hands) and then shift to seria organization (the asymmetric manipulation of the object). Furthermore, the bimanual assembling of discrete movements is constrained not only by the task itself. Different subjects can perform the same task using different strategies depending on a variety of factors such as age, skill, etc. For example, an asymmetrical activity such as cuttin a sheet of aper with scissors tends t o be performed symmetrically y young childPren, and asymmetrically by older children (Corbetta, 1989). To review some of the extant findings on temporal constraints of bimanual coordination in adults, I have classified the three major kinds of bimanual tasks on which temporal constraints have been studied as follows: (1) d u a l t a s k s , where subjects must simultaneously perform a different task with each hand, (2) b i m a n u a l single t a s k s , where the two hands contribute to a single goal with a s i m i l a r output (symmetrical complementary tasks), (3) b i m a n u a l s i n g l e t a s k s , where the two hands contribute to a single goal with an a s y m m e t r i c a l output (asymmetrical complementary tasks). Within each category, I will emphasize the most important aspects of the bimanual activity for each task, in order to examine whether the temporal constraints depend on particular attributes of the bimanual movements.

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2.1. Dual tasks

Many studies have focused on temporal relationships in d u a l t a s k s , i.e. tasks where t w o s i m u l t a n e o u s but supposedly i n d e p e n d e n t 2 bilateral manual activities a r e required from the subjects (one with each hand). ets, simultaneous these studies: by the two hands are d i s c r e t e p o i n t i n g m o v e m e n t s with d i f f e r e n t s p a t i a l c o n s t r a i n t s (different movement amplitude, different target width), the initiation and termination of the two movements are, on average, roughly simultaneous. In addition, many kinematic parameters remain relatively invariant between limbs (Kelso, Southard & Goodman, 1979; Kelso, Putnam ((r Goodman, 1983). The movement time to a target is a function of both the amplitude of the movement and the level of precision required (Fitts, 1954,!, therefore unimanual pointing to a close and wide target is faster than unimanual pointing t o a distant and small target. Such differences in movement time almost completely disappear when the two hands point s i m u l t a n e o u s l y 2 They are independent because they are not directed to a single goal. However the fact that they must be performed at the same time (or in alternation) induces temporal dependency.

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to targets of disparate amplitude and width. Comparison of the temporal characteristics of movements when performed by one hand alone and the same characteristics when performed simultaneously with the two hands gives a n indication of the interference between the two movements (Marteniuk, MacKenzie & Baba, 1984). One explanation for this synchronization effect is that motor control does not bear on individual muscles and that the two hands behave as a single coordinative structure; coordinative structures a r e "modulable and functional units of action directed towards accomplishing particular goals" (Kelso e t al., 1983, p.370). When perfect synchrony is explicitly required in the instructions and subjects a r e asked to perform d i s c r e t e o r r e p e t i t i v e movements with the two arms as s i m u l t a n e o u s l y a s p o s s i b l e , either in reaction to a signal o r at their own pace, the initiation of the two movements is almost perfectly simultaneous (within less than a 10 msec delay; Bartlett & White, 1965; Paillard, 1949). The slight delay between the two hands is comparable to the difference between the reaction times of the two hands when studied se arately in a unimanual condition (Seashore & Seashore, 1941). Therefore t1e delay in the bimanual condition is compatible with the hypothesis of perfect simultaneity in the central initiation of the two movements. When a d i s c r e t e unidirectional flexion must be performed with one arm concurrently with a s e q u e n t i a l movement (flexion/extension/flexion) with the other arm, kinematic analysis shows interference between the two limb movements (Walter & Swinnen, 1990). The interlimb interference is greater when the more difficult, sequential movement is generated by the non referred left arm and the unidirectional movement by the preferred right arm tKan in the converse. b) - When subjects are asked to make r e p e t i t i v e flexion/extension of the arms, the correlation between the spatio-temporal parameters of the two limbs is very high, and the reversal time for both limbs is synchronized within a 30 msec dela (Cohen, 1971). The degree of correlation and synchronization are higher w i e n the movements a r e the s a m e (both arms flex o r both arms extend: homologous condition) as com ared to r e v e r s e d (one a r m flex, one arm extend: non-homologous conditionf Cohen su gests that unitary coupling mechanism facilitates simultaneous action of homo ogous muscles of the upper limbs (sometimes referred to as a "symmetry constraint"). However alternation also seems to be a stable mode, as has been shown by several studies of finger tapping. When subjects are requested to move homologous fingers a t a c o m m o n f r e q u e n c y , two {atterns are clearly more stable than any other patterns: synchronous (in p ase) and alternating (anti-phase, at 180 phase ag). When subjects a r e required t o sustain a hase relationship different from these two stable modes, they tend t o simplify tge task by returning t o the easiest mode (Yamanishi, Kawato, & Suzuki, 1980). When the frequency increases, subjects required to tap with a n anti-phase mode switch to a n in-phase mode (Kelso, 1981; 1984; Schoner & Kelso, 1988). In the dynamical systems approach to attern formation, such stable modes pla the role of a t t r a c t o r s of the colpective variable dynamics (See below for a grief account of different models of bimanual coordination). c) - In some conditions, the bimanual finger tapping task requires the right and left hands to carry out i d e n t i c a l f u n c t i o n s b u t n o t m i r r o r i m a g e m o v e m e n t s . Two main conditions can be distinguished: (1) When the two fingers are required to tap different patterns, one finger for exam le tapping as fast as possible while the other produces a stable rhythm at a ,rower rate, the condition is usually classified as a dual task. The temporal constraints in this case are generally assumed to result

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from a n "interference" between the hands due to left-right asymmetries of neuromotor control. Thus, interference is relatively less when the preferred rather than the nonpreferred hand performs the more difficult task; the ma nitude of interference also depends on the hand with which subject starts, performance generally being more stable when subjects begin by tapping the more demanding task (Peters, 1985;Ibbotson & Morton, 1981). (2) When the two fingers a r e required to perform different rhythms, for example in order to produce a n intermanual 2:l or 3:l ratio (polyrhythmic tapping), the condition is sometimes classified as a single task, a t other times a s a dual task. Subjects may, f o r example, construct a larger temporal pattern that integrates the temporal structures of each finger in a supra-ordinate rhythm. The stability of bimanual performance decreases as the complexity of the combined rhythms increases (Deutsch, 1983); in general subjects tend to simplify the temporal relationship between the two rhythms (Povel, 1981). Highly skilled performers (e.g, pianists) may develop the capacity to perform polyrhythms where t h e relationshi between the two rh thms is very complicated (Shaffer, 1981). This ability [as sometimes been a duced as evidence that trained individuals a r e able to execute two independent timing programs concurrently. However, the fact that the accuracy of erformance decreases with a n increase in the complexity of the associated pogrhythm at any skill level, argues against the hypothesis of two independent timing programs. An alternative hypothesis holds that skilled erformers construct a mental representation of the pattern as a whole that su sumes the two rhythms as components of a larger unit (Deutsh, 1983; Jagacinski, Marshburn, Klapp & Jones, 1988). Finally, a dynamical system approach t o attern formation implies a still different and less "cognitive" explanation (See gelow for a brief account of different models of bimanual coordination). d ) - When the two coupled tasks a r e f u n c t i o n a l l y d i f f e r e n t , similar synchronization effects can be observed. For instance, when a continuous tracking task is coupled with a two- choice tone identification task, dependency in the times at which two manual responses a r e given has been found, even though timing should not be synchronized if tasks a r e performed maximally (McLeod, 1977). When subjects were asked to track with o n e hand and to respond to a second stimulus with the other hand, responses from both hands were interdependent. Therefore in this case a s well, the two manual responses are apparently produced by a single process. Results were different when the response t o the second stimulus was verbal: vocal response and manual tracking responses were produced as two separate, temporally independent streams.

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2.2. Symmetrical c o m p l e m e n t a r y t a s k s

The second type of bimanual tasks on which temporal constraints have been studied covers single tasks requiring explicit hand c o l l a b o r a t i o n a n d a n o n - d i f f e r e n t i a t e d r o l e f o r each hand, such as drawing a pattern with a n X/Y tracing table (Etch-a-Sketch): to perform the task, each hand must control a different device on t h e apparatus, each of which corresponds to one of the two dimensions of the two-dimensional pattern. In such conditions, movements could theoretically be performed independent1 , since the two devices a r e not physically associated, but the single goal ma es it a single task where the actions of the two hands must be coordinated if the desired result is to be obtained. Therefore coordination between the two hands is constrained by t h e goal of the action and helped by visual feedback of the results. The "Etch-aSketch", which was first used experimentally by Preilowski (1975)with acallosal

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patients, belongs to this category. The movements involved a r e c l o s e d , c o n t i n u o u s , s i m u l t a n e o u s and s i m i l a r . In this task, the temporal constraints a r e reflected in the tendency of subjects to synchronize the velocity of the two hands during the early stages of learning. Subjects need no practice to draw the pattern in the same-velocity condition. By contrast, when they must rotate o n e crank twice a s fast as the other to track the presented path, the direction of error indicates that the two arms show a preference for operating at a same velocity ratio. With practice, subjects can coordinate the two hands into a smooth pattern of action even under differential velocity condition (Fagard, Morioka & Wolff, 1985; Preilowski, 1975). 2.3. Asymmetrical complementary tasks Somewhat different temporal constraints a r e observed in a n a s y m m e t r i c a l c o o p e r a t i v e b i m a n u a l task such as reaching f o r a bottle and removing a plug on its top. While cooperative tasks require asymmetrical simultaneous outputs from the two hands, the action starts in a fairly parallel manner as the two hands reach out for the object. In his preliminary observations (in a no-visual-feedback condition), Jeannerod (1984) found that temporal constraints can be observed even when the spatial characteristics of the two movements a r e asymmetrical. The velocity peaks in the course of reaching were synchronized, and the time of maximum grip aperture was synchronous for the two hands (within 80 ms) although grip amplitude (thumbto-finger distance) was different for each hand. 2.4. Some models for bimanual coordination A number of conclusions can be drawn from studies of temporal constraints on adult bimanual coordination tasks. Simultaneous goal-directed movements of the two hands tend to be synchronized. Even when two independent tasks must be carried concurrently, and when an optimum performance would require different timing for each hand, the two movements tend to exhibit several similar temporal parameters including initiation, termination, and critical moments of the action such as reversal (in the case of alternating movements), or maximum peak of acceleration. When the task requires functionally identical repeated o r continuous movements from the two hands, interlimb coordination is more o r less stable, d e ending on the temporal characteristics of the task (rhythm, velocity, angular vefocity). A ratio different from isochrony is easy to perform if the two velocities a r e related in a simple ratio. When asked to perform in other modes, subjects tend to go back to the simple modes. More difficult ratios require a reat deal of practice to perform. Invariant kinematic parameters a r e noticeabye even when the bimanual task requires differentiated complementary roles for t h e two hands. Different models can account for the observed temporal dependencies between the two hands. Temporal constraints are viewed either as interference reflecting constraints at the central level of movement programming; o r as a n outcome of the low-level organization of muscles into functional groups. One class of models assumes that interference occurs because the timing initiation and other temporal parameters for the two hands functioning together a r e controlled centrally by common mechanisms. They assume a "central timekee ing process" (Wing, 1982), a "superordinate controlling mechanism" (Mcfeod, 1977; Peters, 1985), or "general movement program" (Schmidt, Zelaznik, Hawkins, Frank, & Quinn, 1979) that determine certain

Synchronization and Desynchronization in Bimnnuul Coordination

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common properties of the two-hand movements whereas other properties can be thought of as parameters applied to each hand separately. For example, movement topographies o r degree of muscle activity a r e specific for each hand but the two hands are related to each other regarding w h e n they a r e activated (therefore initiation, termination and other critical moments are related). Some have hypothesized that inhibition mechanisms help to reduce such structural interference, for instance by delayin the initiation of one activity, and thus easing the uncoupling of the two limbs [Swinnen & Walter, 1988) The structural interference model approach adopted by Heuer and'Wing (1984) to explain interference between any two simultaneous tasks stresses that interference may occur at multiple levels. Limitations on dual task performance (such as in the double tapping task) arise when the two tasks involve common processes o r structures at different levels of t h e nervous system. A second class of models (see chapter 3 in this volume for a detailed presentation of this approach) assumes that coordination is not owing to a n a priori prescription but is a n a posteriori consequence of the system's dynamic (Kelso, Holt, Rubin & Kugler, 1981). Kelso, Turvey, Kugler and others have adopted Bernstein's notion that coordinated motor patterns involving muscle groups are controlled as a single synergy rather than as independent muscles (Bernstein, 1967). They emphasize the similarities between behavioral coordination and physical processes in which multiple components become collectively co-organized. Synchronies and easy modes of temporal coordination reflect the organization of the motor system at the low-level of functional groupings, and can be explained by laws governing dynamical patterns. 2.5 Coordination: c o n s t r a i n t o r construct?

How d o the temporal constraints in bimanual movements contribute to our understanding of motor coordination? Coordination is sometimes describes as a limitation, an unavoidable occurrence as soon as several effectors a r e associated in the same action. Examples of this limitation a r e the involuntary co-timing between the different effectors involved in the same action, or the role of state attractor played in some conditions by particular patterns (inphase tapping for example), making difficult a shift to other patterns. In this perspective, coordination is a constraint. However, this term not only refers t o a spontaneous unintentional state, but also to the intentional action of bringing "parts into proper relations" (Kugler & Turvey, 1987, p. 252). Thus, it refers t o both the involuntary co-timing between the different effectors involved in a n action; and to the proper temporal relationships between the same effectors intentionally developed to make an action smooth and "well coordinated" once it has been mastered. Learning a skill consists of eliminatin the inappropriate, though inevitable relationships between effectors, and bui ding new temporal relationships between these effectors, ones suitable f o r a smooth realization of the action. "Coordination" implies there are several effectors "working together" as well as "working together in a way appropriate to a goal" (the desired action). Because of this dual aspect, some questions arise: What resemblance between spontaneous (the constraint) and acquired coordination (the construct)? Is there coordination without a goal or is it necessarily linked to a goal-oriented motor act? A developmental perspective should in principle provide some answers to this question. Investigating the temporal constraints in spontaneous bilateral movements of the newborn and their changes a s infants attempt to achieve intended motor goals, should help to clarify whether

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dependency between different effectors moving simultaneously depends on the goal-orientation of an action. 3. THE D E V E L O P M E N T A L C O U R S E OF T E M P O R A L C O N S T R A I N T S IN BIMANUAL COORDINATION 3.1. T e m p o r a l relationships in neonate's movements The movements of neonates are often described in terms of mass activity, with the implication that the co-activation of limb motions is undifferentiated. Such descriptions raise the fundamental question of what mechanisms of motor control a r e prefunctionally given, and what control processes emerge with maturation and training. Are the temporal constraints observed in adults resent at birth? Are the more constraining at birth and become more Flexible? O r d o the temporarconstraints develop with voluntary motor control?

patterns such as mouthing o r crying, for example, a r e temporally well patterned and even stereotypic (Wolff, 1968; see also this volume, chap. 7). Modern techniques of movement analysis tend to disconfirm the idea that the segments a r e more tightly coupled at birth than later in development. For instance the temporal phase relation between the two le s during kicking does not become tightly coupled until about 5 months of age (&helen, Skala, & Kelso, 1987). The synergy is present at birth but the temporal patterning within the synergy improves with ractice. The deve opment of manual coordination results from the interaction of many subsystems. The use of one o r two hands f o r instance may depend on many factors such as postural constraints (Rochat & Stacy, 1989). object size, perception of Object properties, (Newell, Scully, McDonald & Baillargeon, 1989; Rochat, Clifton, Litovsky, & Perris, 1989), anticipation of mani ulation. The study of the spatio-temporal relationships between the upper limgs when t h e y a r e u s e d i n s y n c h r o n y is one way to understand which kinds of bimanual coordination exist at birth, and which ones develop as reaching, grasping, and manipulation emerge.' The spontaneous movements of newborns reveal n o systematic synchrony in the onset of activation of the two hands, and during motion their trajectories are not symmetrical (Cobb, Goodwin, & Saelens, 1966). Although movements of both arms frequently co- occur, fine temporal analyses have found n o evidence for either synchronous o r lead-lag temporal dependencies between spontaneous movements of the right and left arms (Dowd & Tronick, 1986).

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3.2. T h e o n s e t of reaching a n d grasping When newborn infants a r e presented with a graspable object a t a reachable distance, their prereachinga is primarily one handed (Bower, 1974) 3 The problem of coordination between the several ipsilateral segments involved in reaching (for instance grip configuration, o r hand opening during reaching) will not be treated in this chapter which focuses on the constraints in bimanual coordination.

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and more with the right than with the left hand (von Hofsten, 1982). During t h e newborn period, however, presenting an out of reach object will initiate coactivation between arms and legs that can be described as interlimb synchronization, when synchronization is operationally defined as a cooccurrence of movements in two or more limbs within 100 ms. Such synchronization is not observed when no graspable object is presented, but it becomes evident as soon as the object is presented. Synchronization between a n arm and the contralateral leg in response to a n object increases with age from 1-5 months, but no such tendency is observed f o r interarm synchronization (Mc Donnell, Corkum, & Wilson, 1989). Apparently, the motor s stems controlling the two arms a r e not strongly coordinated during the neonata period, either for s ontaneous or goal-directed activity. However, the limited motor repertory w i n g the newborn period makes it difficult to draw any firm conclusions about the extent of temporal constraints on voluntary bilateral coordination a t birth. As the asymmetrical tonic neck reflex (ATNR) diminishes, movements become more bilateral. At about 3 months, infants start to reac and grasp simultaneously with the two hands, and the mouth apparently plays an important mediating role during early bimanual coordination. For example, when the experimenter introduces an object into the subject's hand, infants a s young as 2 t o 3 months frequently bring the object to the mouth with both hands, using a "bimanual action organized in a mirror synergy" (Rochat, 1989, p. 882). However, young infants a r e not limited to bilateral synchronous movements to achieve a target goal. After a n initial bilateral start, they fre uently make unilateral reaches (Flament, 1975). More generally, the evilence converges on the conclusion that the frequency of bilateral reaching increases from two-three months to five-six months, and then gives way t o unimanual reachin (Bresson, Maury, Pieraut-Le-Bonniec, and d e Schonen, 1977; Flament, 1975; Gesell & Ames, 1947; Ramsay & Willis, 1984; Rochat & Stacy, 1989; White, Castle & Held, 1964). Despite the many empirical studies carried out to date it remains unclear, however, whether early bilateral reaching is tightly or loosely coupled, and whether the stabilit of such synergies increases or decreases over time. Goldfield and Michel 6 9 8 6 ) , for exam le, found less temporal linkage in bimanual reaching at 11 than at 7 montfs of age, in t r i a l s w h e r e t h e t w o h a n d s c o n t a c t e d t h e o b j e c t w i t h i n I s e c of e a c h o t h e r , the pro ortion of these trials differin not si nificantly between the two age groups. &wever, Humphrey and Hump rey (1 87) found that when objects are presented to 5- to 12 month-old infants at the end of a rod, the mean proportion of reaches that end in simultaneous contact of the object by the two hands was higher in 9-12 month-olds than in 5-8 month-olds 5 . It is therefore important to separately consider (1) the strategies predominantly used by the subjects (one- vs two-handed) and (2) the spatiotemporal intermanual relationships w h e n t h e b i m a n u a l s f r a t e y is c h o s e n . In addition, difficulties arise when t ing to compare the different results because of the different criteria usedP6y researchers in identif ing bimanual strategies. Reaches were respectively categorized as two-hande when the two

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4 Prereaching refers to the swiping reactions of oung infants when exposed t o attractive stimuli (see also this volume, chapter 7J.

5 Humphrey and Humphrey used three objects, among them a large dowel (30 cm) presented once horizontally. Goldfield and Michel's presented only small objects to the infants, in a 14.6 cm transparent box. This difference in procedure might partly explain the different findings in bimanual vs unimanual strategies as a function of age.

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hands simultaneously contacted the object (Humphrey & Hum hrey, 1987; Rochat, 1989), when they contacted the object within 1 sec o f each other (Goldfield & Michel, 1985), when the "second" hand moved at least halfway toward the target by the time the leading hand had reached the object (Lockman, Ashmead 8z Bushnell, 1984), or, without further precision, when both hands were used (Newell et al, 1898). More extensive descriptive analysis or/and more precise criteria are necessary to describe the chan e in bilateral reaching with age. Whether the temporal constraints of bimanua synergies are an end result of skill ac uisition, or whether early motor development involves a progressive "release"%om the initial tightly coupled synergies, remains an issue re uiring more detailed investigation. A l i o u g h symmetrical bimanual activities, such as banging objects together at the midline, remain a n important component of the infant's bimanual repertory during the second half of the first year (Ramsay, 1985), qualitatively new patterns of bimanual coordination, such as fingering a n object with one hand that is held by the other, or transferrin a n object from one hand to the other, emerge at around 4 months or shortly t ereafter (Rochat, 1989). Fin ering involves hand role differentiation and therefore can be considered as ear y evidence of bimanual asymmetrical cooperation. However, it must be noted that in fingering, the two hands are not asymmetrically active a t the same time: one hand is rather passive (holding the object) while the other hand acts on the object. In summary, with the exception of tonic postural reflexes, the earliest stages of bilateral coordination a parently require the presence of a graspable object, the hands themselves p e r i a p s bein the first such object (White et al., 1964). Bilateral synergies emerge with t e onset of goal-directed activity, although not necessarily with the onset of visual control over directed movements. The bilaterality of reaching is not the only possible pattern and infant's early reaching is frequently unilateral. When they a r e bilateral, reaching patterns begin as approximate mirror synergies, gradually followed by complementary asymmetrical movements patterns.

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As the preceding discussion suggests, s mmetrical and asymmetrical bimanual coordination must be distinguished t roughout the course of motor development, but particularly during the first year of life. Reciprocal or asymmetrical bimanual coordination is thought to depend on the functional integrity of brain structures that mature during the second half of the first year For example, lesions of the supplementary motor area (SMA) that presumably mature between 5 and 8 months of age (Diamond, 1991a), result in deficits of bimanual coordination. Brinkman (1981) trained monkeys to retrieve currants loosely wedged into a hole drilled in a plate. To retrieve the bait, the animal had to push it with the fin e r of one hand and catch it with the other hand as it fell. Trained normal mon eys had no difficult in performing the asymmetric bimanual skill, but after a unilateral lesion o?the SMA, they performed in a symmetrical pattern (using both hands in a mirror- like fashion), so that they were unsuccessful in retrieving the bait. Similarly, human patients with a SMA lesion have difficulty concurrently flexing and extending the two hands in a n alternating pattern, instead either moving the hands in succession or in a symmetric pattern as mirror movements (Luria, 1966; L a lane, Talairach, Meininger, Bancaud, & Orgogozo, 1977; see Goldberg, 1985 or a review). It is generally assumed that a n intact corpus callosum is necessary f o r the acquisition of novel bimanual coordination tasks, interhemispheric processes

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presumably shaping asymmetrical motor output via the corpus callosum (Preilowski, 1975). Anatomical (Yakolev & Lecours, 1967), physiological (Salamy, 1978) and behavioral evidence (Quinn & Geffen, 1986) suggests that the corpus callosum is not functionally mature until the age of 10 years. Such maturation in turn, may account for the decrease of the unintended mirror synkineses after the age of 5 (Wolff, Gunnoe, & Cohen, 1983). The cooperation of asymmetrical movements between the two hands t o achieve a common goal may therefore depend on the functional or structural maturation of interhemispheric communication, the callosal connections between the SMAs possibly being the most critical. 3.4. T h e e m e r g e n c e of asymmetrical c o o p e r a t i o n

Diamond (1991a) hypothesizes that the complementary use of the two hands is dependent upon maturation of both SMA and the corpus callosum because it requires not only coordinating the actions of the two hands but inhibitin the tendency of the two hands to d o the same thin . Asymmetric bimanuafcoordination has been found to develop by the end of t f e first year of life (Ramsay & Weber, 1986), or even earlier (Diamond, 1991b; Fagard & Jacquet, 1989). When retrieving an object while holding a container, a behavior which becomes common after 10 months of age (Flament, 1975; Fagard & Jacquet, 1989), infants show a capacity for sequencing complementary actions with the two hands. It has often been observed that infants tend to erform a complementary bimanual activity with either a bilateral mirror-fike or a unilateral strategy, before using a complementary one. For instance when 8 month-old infants raise a transparent box to get the toy laced under it, they either tend to raise the box with the two hands and to yower the two hands simultaneously to try to get the toy (Diamond, 1981, 1991), or they raise the box with one hand and try to get the toy with the same hand (Diamond, submitted; Fagard & Diamond, in preparation). Using a n opaque box with a hinged lid in which a toy is inserted while the infant watches, we found that many 8- to 11 month-olds spontaneously use a unimanual strategy (see also Bruner, 1970). When the experimenter blocked the opening of the lid, obliging t h e child t o hold it with one hand while getting the object with the other hand, most of the babies were able to retrieve the toy with this differentiated bimanual strategy even a t 8 1/2 months of age. However, for youn e r infants, the timin of the successive com lementary actions is f a r from perfect and the hand holiing the lid lets it go be!rei the other hand gets out of the box with the toy. By 11 months of age, most of the infants could perform the task, not only with asymmetrical cooperation, but with the correct timing for coordinatin the two hands. Similarly when infants raise the front of the Object Retrievaf box and then try to lower one hand to reach in, they have trouble keeping the other hand on the box (Diamond, 1988). Diamond concluded that younger infants lack the necessary inhibition to avoid mirror actions, but it IS also possible that young infants forget about their other hand once they attend to the grasping hand. For example, in our study 7- to 11-month-old infants often neglected one hand even though two-handed manipulation would have made the task much easier. When an object was placed deep inside a transparent box situated f a r enough out of the infants’ reach so that they had to draw the box closer before retrieving the object, the younger infants performed the whole sequence with one hand (see also Diamond, 1981). Most infants 10-month-old or older, by contrast, used both hands in a complementary strategy. Neglect of one hand was also striking during unimanual tasks. For example, when the transparent box with an object inside was placed to the right or the left of the subject, babies usually used the

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hand contralateral to the opening to retrieve the object. As a net result their reach was "awkward" (Diamond, 1988; 1991). In a subsequent study, we found that 7- to 10-month-old babies both initiate and then rasp the object with the hand contralateral to the opening (but ipsilateral to t e side of presentation), while 11-month-olds will initiate the action with the contralateral hand but then shift to the other hand f o r grasping. In conclusion, studies on the development of bimanual coordination during the first two years of life indicate that the temporal constraints on interlimb coordination during spontaneous movements emerge in the context of goal-directed activity. The first evidence of simultaneous activation f o r voluntary action is seen in the proximal limb segments (the two arms alone o r in conjunction with the mouth), and they generally produce a m i r r o r - l i k e m o v e m e n t p a t t e r n . When the task precludes a symmetrical pattern of movement, infants under 10-11 months prefer a u n i m a n u a l strategy to grasp the object, even when the use of both hands would be more efficient. The onset of goal-directed bimanual motor action is usually associated with constraints imposed by the tendency to make mirror movements and homotopic coupling, and the development of skilled actions is characterized by a departure from this spontaneous mode of bimanual activation. The earliest evidences of asymmetrical coordination a r e hand r o l e d i f f e r e n t i a t i o n with one hand active and one hand passive (fingering) o r a t e m p o r a l s e q u e n c e of a c t i v a t i o n (one hand moving after the other). Once the two hands begin to work together, the timing of simultaneous asymmetrical coactivations is generally poor. One hand either stops its supportive action prematurely, .or there is a long delay between the initiation of movements by the two hands. However, more detailed investigations using currently available quantitative techniques of movement analysis a r e required to clarif the residual question whether the intrinsic constraints of syner formation &ring bimanual activity have a greater limiting influence on t e development of complex patterns of bimanual coordination in young as compared to older infants, o r whether formation of stable motor synchronies increases during development. We may, in fact, hypothesize that, as the child develops skills, a lessening influence of the intrinsic constraints allows for the development of complex patterns of bimanual coordination as reflected by increasingly stable temporal relationships. In other words coordination- constraint might give way to coordination-construct, and the meaning of the temporal synchronies probably changes with development. With older children, dual tasks paradigms were used to examine the developmental course of bimanual temporal constraints.

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3.5. T e m p o r a l c o n s t r a i n t in bimanual c o o r d i n a t i o n i n c h i l d r e n a) Kelso and his collaborators studied bimanual coordination in adults, using a d u a l t a s k paradigm that requires the subject to point to two separate targets with the two hands that have either the same o r different spatial requirements (Kelso et al., 1979). Southard (1985) used the same paradigm t o study children (5 to 14 year olds). H e found that in children as well as adults the movement time of one hand in the easy condition (hitting a large close target) is longer when the movement is coupled with that of the other hand performin the difficult condition (hitting a small distant target) than during unimanua! performance of the same task. Unlike in adults, however, the movement time of the hand Performing the difficult task showed no decrease in time when coupled with the hand performing the eas task. In addition simultaneity of MTs were found in the two-hand same con&tions but not in the easy- difficult

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condition until age 10. H e concluded that although coordinative structures represent a n invariant mode of interlimb control across changes in a e, maturational factors influence the constraint of two-hand movements (see a so Southard, in this volume, chapter 13). b) A few studies have analyzed the develo ment of b i m a n u a l c o m p l m e n t a r y tasks that require the coordination o similar outputs from each hand, as in the "Etch-a-Sketch'' task mentioned earlier. The subject must draw a pattern by mani ulating two cranks, each hand or crank controlling a different dimension o f t e two-dimensional drawin t o be made on a screen o r on a sheet of paper. The two movements a r e p ysically separate, but t h e specified target output requires close coordination between t h e hands. Comparing children and adults on this "Etch-a-Sketch'' task, we found that regardless of the specific task requirements, younger subjects exhibit a greater tenden to synchronize the velocities of the two hands than older children. T h e f o r m e r y a d much greater difficulty than the latter when the task required that one hand had to rotate faster than the other, but age groups performed with a proximately equal skill when the two hands had to rotate at the same velocity. &e errors made by young children in the more difficult different- velocity condition could be attributed to a consistent tendency to draw a line that would correspond to the same-velocity ratio (Fagard, Morioka, & Wolff, 1985). In a separate study we found that the bimanual performance of 5- and 7year-old children under the same-velocity condition was better in the mirror than parallel mode of hand rotations, but the modal effect was no longer apparent in 9-year-old children (Fagard, 1987), suggesting that the symmetry constraints that lead the two hands to form a single synergy during mirror ima e rotations diminish with age. Despite the strong disposition t o synchronize t e velocity of the two hands, perfect synchrony is not easily achieved. T h e out ut by the right hand of right- preferring children tends to exceed output by the eft hand, so that even when the experimental setting is perfectly symmetrical in order to avoid any bias towards asymmetry (vertical line to trace instead of slanted, equal li ht from the left and right side in the room) the errors tend t o be significantly [iased toward the axis that is controlled by the riGht hand. To determine whether such asymmetries of motor output a r e associated with a tendency of the preferred hand to begin rotating before the nonpreferred hand, we calculated an intermanual synchronization index. The peak acceleration of the preferred right hand anticipated that of the left hand by 50 msec, and the effect was significantly greater during mirror than parallel rotations suggesting that the effect of coupling on bimanual coordination is ex ressed more strongly during mirror than parallel rotations (Fagard & Barbin, 1987). The relative ease with which young children can coordinate movements of the two hands that must be rotated a t the same velocity, in contrast to their difficulty in rotating the arms at different velocities has also been reported by Jeeves and collaborators (1988) who compared 6- and 8-year-old children as well a s adults on the "Etch-a-Sketch'' device. Six and 10-year- old children made more errors in the asynchronous than the same- velocity condition, whereas such differences were not observed in adults after prolon ed training. When 6year-old children were asked to close their eyes at the mi$-point of a trial, they made significantly more errors than the other age groups in the differentvelocity condition, and they needed continuous monitoring by visual feedback to rotate the two hands at different velocities. In sum, synchronization of the two hands a t the same velocity does not require visual feedback a t any age, whereas the desynchronization of a r m movements appears to require visual feedback, particularly in young children o r during the early stages of skill acquisition.

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4. CONCLUSIONS

The central theme of the chapter has been the development of temporal constraints and their implications for motor development. Temporal constraints are clearly observed in the performance of interlimb bimanual coordination tasks in adults. Whether necessary for, or in oppositioq to, the goal of the action, the tendency toward synchronization of limb movements appears to be an inherent property of the motor system. This may be expressed in a number of temporal parameters. When movements a r e repetitive, simple alternation represents a stable mode of temporal relationship, but when the two movements are functionally similar, subjects tend to shift from an alternating to a synchronous mode as the response frequency increases. When the two hands must critically respond a t different rates, the stability of performance depends on the ratio between the two rhythms, but when the response frequency increases, subjects tend to revert to the simplest modes. Similar temporal constraints have been found in children. Mirror coupling decreases with age, but whether movements a r e mirror or parallel, young children have difficulty desynchronizing coupled movements and must therefore rely on visual feedback. However, temporal coupling increases in some conditions between 5 and 10 years of age. The synchrony of movements first shown by infants w h e n t h e y u s e b o t h h a n d s (bilaterality is not a constraint per se), although never perfect, is the first mode of relation between the two hands that can be observed in a goaldirected situation. Asymmetrical cooperation develops later and a t first requires a sequential temporal organization.

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The Development of Timing across Four Limbs: Can Simplicity Produce Complexity? M. A Roberton Motor Development and Child Study Laboratory, Department of Physical Education and Dance, University of Wisconsin-Madison USA 53706 Abstract In this paper I describe fifteen years of longitudinal data on the natural development of internal timing between the arms and legs during the acquisition of a childhood locomotor task (Roberton & Halverson, 1988). These data on hopping show 1) dramatic changes in the spatial relationships across the limbs, 2) gradual, but frequently disrupted, evolution of temporal relationships across the same limbs, and 3) evidence of mutual influence between the co-developing timings. I present a model of the data which views the body as a trunk from which four oscillators are suspended. Indeed, the data are consistent with the idea that the hopping leg acted as a forcing oscillator to which the other three limbs entrained, while mutually entraining with each other. The process of mutual entrainment could also cause the disruptions in timing observtci :ib alevcli.p~:c::~i proceeded. The hopping leg itself developed from non-linearity to linearity in t a r n 5 of the stiffness (force-displacement ratio) with which it landed (Getchell &k Roberton. 1989). Thus, for several years it acted analogously to a non-linear, inverted pendulum or "hard spring-mass system. Through a qualitative change, which occurred between 7 and 10 years of age, the hopping leg transformed into an adult, linear landing system, which obeys Hooke's law. I argue that this simple model, based in the dynamical systems perspective, is more parsimonious than information-processing models, yet can account for the complexity seen in the data. 1. THE ONTOGENY OF INTERNAL TIMING

The ontogeny of the internal timing associated with coordinated human movements is relatively unstudied. Most of the work on timing in the motor system has come from laboratory studies of adults (Keele & Ivry, 1987) or children (Smoll, 1974a, 1974b; Thomas & Moon, 1976; Thomas & Stratton, 1977; Williams, 1985), or from musical analyses of rhythmic behavior (Clynes & Walker, 1982). In most of these studies movements were timed to an external stimulus. Internal timing, such as the timing within or between limb segments, has always been recognized as an integral part of the development of motor skills (Eckert, 1987; Schmidt, 1988). Yet, only recently has it been studied longitudinally (see Clark, this text; Roberton & Halverson, 1988). In this chapter I will review data on the natural development of internal timing as it occurred during the acquisition of a childhood, locomotor task. The data were taken

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from a longitudinal study of hopping over distance (as opposed to "in place" hopping), filmed as it developed in 7 children followed for 15 years (Roberton & Halverson, 1988). These data revealed the extreme complexity involved in the evolution of timing across multiple body parts. For instance, limb movements are timed both spatially and temporally; that is, the limbs arrive at certain points in space at certain times. Two or more limbs, swinging forward and back, may be considered to be working in "opposition" or "anti-phase''when one or more are moving forward while another is moving backward. Or, they may move forward and back together "bilaterally" or "in-phase.'' These descriptions simply address the spatial relationship of the segments. Occurring concurrently is their relative timing. 'hvo or more segments may be moving in-phase, for example, but stopping and/or starting at different times. As we will see, at the minimum, an ontogenetic model for the spatial-temporal timing revealed in these hopping data must be able to account for 1) dramatic changes in spatial relationships across body parts, 2) a gradual, but frequently disrupted, evolution of temporal relationships across these same body parts, and 3) an apparent mutual influence between the co-developing, limb timings. 2. SPATIAL-TEMPORAL TIMING IN THE ADVANCED HOP

To appreciate the complexity of the spatial-temporal timing involved in this "simple," childhood task, I have displayed in Figure 1 the timing of the advanced hop. These data are from the 7 children when they were 15 to 18 years of age. Each child was individually filmed performing a variety of motor skills 4 times a year from ages 3-4, every six months from ages 5-7, and yearly, thereafter, until their 16th to 18th year. During each filming, the children were always asked to hop at their own rate to another location about 5 m away. As they did so, they were filmed with 16 mm cameras running at 64 fps. To obtain timing information from the films, the frames for onset/cessation of key actions of the four limbs were identified by projecting the slow-motion film, frame by frame. From the key frames the duration of any event of interest was calculated using the known frame time. These actual times were then normalized to "relative time" percentages of the total time used for a particular hop cycle (landing to landing) and averaged across the 2-3 cycles available for each trial. Measurement error was calculated to be within 1 frame (-15 msec) of the selected frame. Across occasionally-differing camera speeds, this error could cause, at most, a 4.5% miscalculation in the relative timing data. The relative timing data in Figure 1 represent the average of 13 trials in which the children were evaluated as being advanced in both their hopping arm and leg action. As the tracings at the top of the Figure show, during one cycle the non-support leg swings forward to accompany support leg extension, then backward during the flight phase of the hop. The arm contralateral to the non-support leg pumps forward in-phase with that leg, then back, and the remaining arm works in opposition or anti-phase to that same movement. All of this (one hop cycle) occurs, on the average, in one-half second. The four horizontal bars in Figure 1 depict the averages of normalized, timing data for each limb. The bottom bar of Figure 1 represents the relative timing of the hopping

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Figure 1. Normalized timing averaged across 13 trials of the advanced hop (arm action-developmental level 5; leg action-level 4) when the seven children were 15 to 18 years old. Each bar represents the action of one limb for one cycle of the hop. Numbers are percentages of the hop cycle. From 'The Development of Locomotor Coordination: Longitudinal Change and Invariance"by M.A. Roberton and L.E. Halverson, 1988, Journal of Motor Behavior, 20, p. 212. Reprinted with permission of Helen Dwight Reid Educational Foundation. Published by Heldref Publication, 4000 Albemarle St., N.W., Washington, D.C. 20016. Copyright (c) 1988.)

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leg during one hop cycle, which is portrayed from the first detectable foot touch of landing to foot touch of the next landing. Two key portions of the hopping leg action are the support phase and the flight phase. The support phase, in turn, can be divided into two parts: from foot touch to the point of deepest knee flexion, and from deepest knee flexion until take-off. Landing, deepest knee flexion, take-off, and the second landing are all noted on the bottom bar of Figure 1. Superimposed on the cyclic action of the hopping leg is the movement of the non-hopping leg or "swing leg" (Roberton & Halverson, 1984). As the tracings at the top of Figure 1 show, the swing leg moves through a range of approximately 120" both forward and upward and, then, down and back in the course of one hop. Represented as the second bar from the bottom of Figure 1, the swing forward begins about 6% into the hop cycle and ends roughly 10% before take-off. The backward swing starts about 1%into the flight phase and ends simultaneously with the end of the cycle, foot touch. Added to the actions of both legs are the swinging actions of the arms (Figure 1). Working in opposition to each other, the arm contralateral to the swing leg swings forward at the same time as the swing leg and for the same duration. Meanwhile, the arm homolateral to the swing leg begins backward movement, again for approximately the same duration: 36% of the cycle. The reverse swings of the arms and the leg are again tied, having similar durations of about 42%. 3. SPATIAL CONFIGURATION CHANGES IN THE DEVELOPING HOP

In the years preceding the children's ability to perform the hop as described in Figure 1, their hop attempts looked distinctly different from Figure 1. As Table 1describes, the spatial configuration of the children's movement changed dramatically several times in those years. The age at which the changes occurred varied with the child, but the sequence of changes was uniform across the children (Roberton & Halverson, 1988). Of particular interest in Table 1 is the change which took place between developmental levels 2 and 3 of leg action. In developmental level 2, the non-hopping or swing leg was held stationary, usually in front of the child. In developmental level 3, the child moved the swing leg forward and backward in the fashion described for Figure 1, although with less range of movement. This shift from no movement to movement is a dramatic, qualitative change in the use of the non-hopping leg. Several, equally dramatic changes occurred in the arm action of the children over the years. Of particular note, in developmental level 3 they used their arms in a parallel or in-phase, pumping action, both arms swinging upward together and downward together. In level 4, the arms sometimes worked together, sometimes in opposition, all in the course of one hopping trial. In level 5, the children clearly worked their arms in opposition to each other, as depicted in Figure 1. Finally, it should be stressed that the spatial configurations shown by the arms and legs did not develop in parallel. That is, developmental levels in leg action did not directly correspond with specific arm action levels, except in the most primitive and the most advanced hops. Thus, a model for the developing spatial configurations in the hop must account for the apparent variability of movement patterns across body parts (arms and legs), yet the predictability of the next qualitative change within a body part.

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A probabilistic model seems applicable to such data, an argument which I have made in more detail for other large muscle skills as well (Roberton & Langendorfer, 1980; Roberton & Konczak, submitted). 4. INTER-LIMB TIMING CHANGES IN THE DEVELOPING HOP

While the spatial configuration of the limbs was changing with development, their timing was also changing. Figure 2 illustrates the emergence of a leg-leg relationship, the timing of the swing leg to the beginning of knee extension in the hopping leg. The swing leg began swinging in leg action-developmental level 3; prior to that time, it was held in a stationary position; hence, no timing relationship existed for levels 1 and 2. J R s individual graph (insert, Figure 2) shows the emergence of the timing in level 3 and the gradual working out of the leg-leg relationship. For him, this relationship became invariant at age 9, when he entered developmental level 4. The data points represent the relative time difference between when the swing leg began forward movement and when the support leg began knee extension. A negative percentage indicates that the swing leg was starting ahead of the support leg. Zero percent indicates they were simultaneous. Also noted on the individual graph is the leg action-developmental level or spatial configuration that the child was showing as the timing relationship was evolving. As comparison with the bar graph indicates, like the other children, JR began his leg swing closer to the beginning of support leg extension in level 3. As level 4 was entered, he settled into starting the leg swing some 20+ percent ahead of extension in the other leg. In all the children, the timing between the two legs emerged after a qualitative, spatial change from developmental level 2 to 3 and, then, took a developmental level for the tight relationship to evolve. The main part of Figure 2 indicates this statistically significant (p < .05) timing change averaged over all the children. In addition, the average within-subject standard deviation for level 3 was 8%; the average for level 4 was 3%. This drop in within-subject variability was also statistically significant (p < .05). While the legs were working out their relationship, the two arms also worked over a long number of years to coordinate their spatial-temporal timing, which culminated in the spatial anti-phasing known as "opposition." Figure 3 shows the absolute, relative timing values (without regard to which arm moved first) for the differences in starting time of the two arms. It is clear that they were closely timed (6% or 21 ms apart) during arm developmental level 3 when they were pumping up and down together. This relationship was interrupted in developmental level 4, when the arm homolateral to the swing leg was breaking out of the bilateral pattern (11% or 41 ms apart). The relationship came back close to simultaneity (3% or 12 ms apart) in the final developmental level. The insert in Figure 3 shows this developing relationship for one girl, KME. The data nicely show how the timing was interrupted as the arms went through the spatial qualitative changes from levels 2 to 4. To add to all this complexity, while the arms were working on their timing and the legs on their timing, a timing relationship between the arm contralateral to the swing leg and that leg was also developing. Figure 4 shows how 4 individuals gradually achieved the timing relationship between the forward movement of the swing leg and the forward

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MA.Robertan Figure 2. Percentage of the hop cycle that the swing leg started forward before the beginning of knee extension in the support leg. Group standard deviations are indicated at the top of each bar. Insert graph shows the longitudinal record of one child. (See text for full explanation.) From 'The Development of Locomotor Coordination: Longitudinal Change and Invariance" by M.A. Roberton and L.E. Halverson, 1988,J o d ofMotorBehavior, 20, p. 220. Reprinted with permission of Helen Dwight Reid Educational Foundation. Published by Heldref Publications, 4000 Albermarle St., N.W., Washington, D.C. 20016. Copyright (c) 1988.)

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Figure 3. Timing of the forward swing of the contralateral arm with the swing of the homolateral arm across developmental levels of arm action. Main graph shows the relative difference in starting time. A difference of zero would indicate simultaneity of movement. Insert illustrates the longitudinal record of one girl. Each data point represents the relative timing difference between the start of the forward swing of the contralateral arm and the start of the concurrent swing (forward or backward) of the homolateral arm. Negative differences mean that the contralateral arm started ahead of the homolateral arm. From "The Development of Locomotor Coordination: Longitudinal Change and Invariance" by M.A. Roberton and LE. Halverson, 1988, Journal of Motor Behavior, 20, p. 225. Reprinted with permission of Helen Dwight Reid Educational Foundation. Published by Heldref Publications, 4000 Albermarle St., N.W., Washington, D.C. 20016. Copyright (c) 1988.)

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Table 1 Developmental Sequences in Hoppine over Distance Leg Action Step 1. Momentary Flight. The support knee and hip quickly flex, pulling (instead of projecting) the foot from the floor. The flight is momentary. Only one or two hops can be achieved. The swing leg is lifted high and held in an inactive" position to the side or in front of the body. Step 2. Fall and Catch; Swing Leg Inactive. Forward lean allows gravity to combine with minimal knee and ankle extension to help the body "fall" forward of the support foot; through quick knee and hip flexion in the support leg, balance is recovered in the landing or "catch." The swing leg is inactive and is usually held in front of the body. Repeated hops are achieved. Step 3. Projected Takeoff; Swing Leg Assists. Perceptible pre-takeoff extension occurs in the support hip, knee, and ankle. There is little delay in changing from knee and ankle flexion on landing to take-off extension. The swing leg now pumps up and down to assist in projection, but range is insufficient to carry it behind the support leg when viewed from the side. Step 4. Projection Delay; Swing Leg Leads. The weight of the child on landing is smoothly transferred to the ball of the foot before the knee and ankle extend to takeoff. The swing leg now begins forward action well before initiation of knee extension in the support leg. The range of pumping action in the swing leg increases so it passes behind the support leg when viewed from the side. Arm Action Step 1. Bilateral inactive." The arms are held bilaterally, usually high and out to the side, although other positions behind or in front of the body may occur. Any arm action is slight and not consistent. Step 2. Bilateral reactive. Arms swing forward briefly, then move downward and backward through medial rotation at the shoulder in a winging movement prior to take-off. This movement appears to be in reaction to loss of balance. Step 3. Bilateral assist. The arms swing up and down together, usually in front of the trunk. Any downward and backward motion of the arms occurs after take-off. The arms may move parallel to each other or be held at different levels as they move up and down. Step 4. Semi-opposition. The arm on the side opposite the swing leg swings forward and upward in synchrony with the forward and upward movement of that leg. The action of the other arm is variable, often moving through a short forward and backward cycle, or moving up and down out to the side of the body, or held relatively inactive at the side. Step 5. Opposing-assist. The arm opposite the swing leg moves forward and upward in synchrony with the forward and upward movement of that leg. The other arm moves in the direction opposite the action of the swing leg. The range of the arm action may be minimal unless the task requires speed or distance. Note. Modified from Halverson and Williams (1985). "The term "inactive"means there is little or no movement assisting in force production.

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movement of the arm contralateral to that leg. Again, the data points represent the relative time difference between when the contralateral arm began moving forward and when the swing leg began moving forward. Negative values indicate that the arm started ahead of the swing leg; positive values that it started after the swing leg; zero indicates the two limbs started together. Also indicated on each graph is the arm action-developmental level through which the children were passing. The arm action levels (see Table 1) indicate the arm-arm relationship which was simultaneously developing. Increased variability of the contralateral arm-swing leg timing seemed to coincide with the time periods of particular arm action-developmental levels. This finding suggests that the homolateral arm may have been affecting the contralateral arm-swing leg relationship at that time. The arm patterns most affecting the arm-leg timing differed among the children. For instance, in contrast to the other 3 children, CRs arm-leg timing was most affected in the early part of arm action-level 5. The interaction of all the limbs on each other is further shown in Figure 4. Located on each graph is also the point at which the child reached level 4 of leg action. This is the level in which the swinging leg increased its range of movement to about 120O. Without exception, the final, invariant timing between that leg and the contralateral arm was reached after the children started increasing the range of their swinging leg. Thus, these data suggest an interaction of homolateral arm, contralateral arm, and swing leg in achieving the final relationship between swing leg and contralateral arm action.

5. THE SEARCH FOR PARSIMONY My purpose in describing these longitudinal data on internal timing was to highlight 1) the appearance of qualitatively-different spatial relationships across body parts at various points in each child's development, 2) the gradual evolution of timing between body parts, an evolution that was periodically disrupted, and 3) correlations between the times of disruption and spatial-temporal events occurring between other body parts. The challenges of these data lies in conceptualizing an ontogenetic model that can explain such occurrences in as parsimonious a fashion as possible. Current explanations of timing, such as information-processing models (Keele & Ivry, 1987), invoke a "timer" somewhere in the body, one which meters out an internal rhythm with which body parts gradually match, using feedback mechanisms. In these views, disruption of the evolution of timing would be posited to "interference" between the control mechanism(s) for the competing limbs, all of which would be trying to match the internal timer. Such processing interference could be either structural (memory limitations) or functional (nonparallel processing). Presumably, the changes in spatial configuration would be attributed to changes in the "motor programs" or to the adoption of new motor programs for telling the limbs where to be at what time. In point of fact, information-processing models have never really addressed the issue of qualitative, spatial change in movement. They grew from the data of laboratory experiments, which usually constrain the movement degrees of freedom available to the performer (Newell, 1985). In such situations, qualitative changes in movement rarely occur. Thus, the models coming out of these data tend to account only for quantitative rather than qualitative change.

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Figure 4. Longitudinal change in the timing of the start of the contralateral arm swing forward relative to the forward movement of the swing leg. Graphs of four individual children are shown. Each data point represents the relative time difference between when the contralateral arm started forward and when the swing leg started forward. Negative values indicate the arm started ahead of the swing leg. Also indicated are the arm action-developmentallevels through which the child was passing, and the point at which level 4 leg action began. (See text for full explanation.) From 'The Development of Locomotor Coordination: Longitudinal Change and Invariance" by M.A. Roberton and L.E. Halverson, 1988,Journal ofMotor Behavior, 20, p. 224. Reprinted with permission of Helen Dwight Reid Educational Foundation. Published by Heldref Publications, 4000 Albermarle St., N.W., Washington,D.C. 20016. Copyright (c) 1988.)

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Given that one did assume that qualitative changes were due to the information-processing "executive" invoking a new motor pattern at some point in ontogeny, it is difficult to understand why the executive would choose to perform the same skill in qualitatively-different ways at different points in development (Getchell & Roberton, 1989). For instance, since the task of hopping over distance stays the same, why at one point in development would a child use a motor program which did not swing their swing leg and, later, substitute one which did swing it? In like manner, why would they have a motor program for bilateral arm use at one point and opposing arm use at another? Finally, the role of an executive in the brain needs to be re-examined. As many have pointed out (Turvey, Fitch, & Tuller, 1982), models which pose an executive "who does the thinking" are the products of logic that has experienced an infinite regress. While it is difficult for our minds not to posit a "Prime Mover" in charge of controlling our movement, the parsimonious model will be one which minimizes the role of the executive or any other construct (motor programs, timers) lacking physical substantiation. Constructs can always be added later if physical models prove unsatisfactory. The reader may recognize that this reasoning comes from the dynamical systems perspective, proposed as a new paradigm for the study of motor development by Kugler, Kelso, and Turvey in 1982. Drawing from theoretical physics and mathematics, as well as Gibson's (1979) ecological psychology, the paradigm attempts to apply to biological events principles of pattern formation and dissolution that generalize across all natural phenomena. Using this reasoning, then, the first choice for models to account for the internal timing seen in the Roberton and Halverson (1988) longitudinal study comes from physical models stressing the basic mechanics of the musculo-skeletal system. What can such models explain without recourse to hypothetical constructs?

6. OF OSCILLATORS AND SPRINGS An oscillator is any kind of physical system which displays periodic behavior. Clearly, the back and forth or up and down, cyclic rhythm of the four limbs in the hop is periodic. Thus, the simplest model of the developing hop is a physical model in which four, initially-independent oscillators hang from the child's trunk. Roberton and Halverson proposed this model in 1988, suggesting that it might account for their data. The developmental question their model raises is: If these oscillators were set vibrating, would their individual behavior and inter-relationships over time look like the longitudinal data of Roberton and Halverson (1988)? To date, this omnibus question has not been answered. The potentially heuristic nature of this simple model may become evident, however, as I discuss a few subquestions, which have been addressed. For instance, the first question stimulated by the model deals with the nature of the oscillations shown in the children's movements: were they simple harmonic (sinusoidal or linear) or did they show more complex harmonics (non-linearities)? Simple harmonic motion is that motion which obeys Hooke's law, that is, motion in which the restoring force is proportional to the displacement of an object from its resting position, or

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F=kx where F = the restoring force k = a constant, known as "stiffness" or the "force constant" x = displacement of the object from its resting position Blickhan (1989) has used this assumption to model hopping mathematically. He assumed that the hopping leg acted like a specific kind of harmonic oscillator, the mass-spring system. The analogy here was that the hopping leg acts like a spring with a certain elasticity or stiffness (k). The spring is compressed a certain distance ( x ) upon landing because of the force (F)caused by the mass of the body as it accelerates into the ground due to the pull of gravity. Both Roberton and Halverson (1988) and Getchell and Roberton (1989) have measured the downward displacement of children's bodies in relation to their landing force in the hop. The latter showed that children landing with a developmental level 2 leg action (see Table 1) did not follow Hooke's law. Rather, their force/displacement curves were nonlinear, third-order polynomials. Furthermore, both Roberton and Halverson (1988) and Getchell and Roberton (1989) showed that stiffness was not developmentally constant. Rather, it changed dramatically between developmental levels 2 and 3 of the leg action. Thus, modeling the hopping leg motion like an harmonic oscillator revealed that the leg action changes ontogenetically from non-linearity to linearity. Children's legs in the early developing levels may act as "hard springs," in which the stiffness coefficient changes non-linearly at certain points in the compression of the spring. Basically, the children resist displacement in the initial part of their landings and, then, they "give" as the landing continues. Another, familiar oscillating system is the pendulum. It could be that the landing leg in the hop acts as an inverted, compound pendulum. Either form of oscillatory system could account for the decline in hopping rate which Roberton and Halverson (1988) documented in the children followed over the 15 years. If the leg were acting as an inverted, compound pendulum, then its growing length would slow the hopping rate simply because the rate of swing of a pendulum is solely determined by its length and the acceleration of gravity. On the other hand, if the leg were acting as a mass-spring system, then the slowing hopping rate would be due to the increasing mass of the body. Both models are testable empirically; both models illustrate how a developmental phenomenon may be explained using physical models that do not need explanatory constructs (timers, motor programs) beyond the physics of the system. 7. ENTRAINMENT

Another characteristic of oscillatory systems is that two or more can undergo non-linear couplings, which lead to entrainment or mode-locking of the systems. If, for example, the two arms and swing leg were envisioned to act as pendula, the development of the timing behaviors described by Roberton and Halverson (1988) may be due to the evolving entrainment of the 3 pendula, first with the hopping leg and, secondly, with each other. This physical phenomenon could account for the periodic disruptions in the otherwise gradual timing development, disruptions that seemed correlated with other developing, body part relationships.

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Evidence that the hopping leg acted as a "forcing oscillator," that is, that the other oscillators entrained to it but did not affect it, is that Roberton & Halverson (1988) found timing invariances in the landing action of that leg from the earliest hops at age 3. These invariances lasted the length of the study through the children's teen years. Thus, they hypothesized that the hopping leg began the rhythm, a rhythm specified by the leg's length or the child's body mass. It was passed, in turn, to the three, other, independent oscillators. How could such coupling take place? The nature of biological couplings can be quite complex in that they could be informational (visual, neuronal) as well as mechanical (tissue-elastically-transmitted vibrations, momentum transfers across body parts). An example of a simple, mechanical coupling is the classic discovery of Huygens (Abraham & Shaw, 1982) that two independent, pendulum clocks, hung on the same wall, gradually synchronized. The vibrations passing in both directions via the elasticity of the wall formed a nonlinear coupling between the clocks. It may be that the human body acts in a similar fashion. Limbs at first independent of each other begin to couple mechanically and/or neuronally. This tendency toward mutual coupling causes the multi-directional disruptions of timing during development as well as the final, synchronized product achieved in the teen years. An intuitive, physical model for the different arm configurations seen in the hop, for instance, is two rods hanging from a cross-piece, coupled with a rubber band. If one rod is started swinging forward and back, the rubber band transmits the swing to the other rod in a non-linear way. At times, the rods exhibit "bilateral" or in-phase movement (level 3 of arm development), erratic movement or "semi-opposition" (level 4), and anti-phase movement or "opposition" (level 5) (see Table 1). The challenge of the model is to find the conditions or "control parameter(s)" that would cause it to simulate the precise ordering of these phases seen in development. Getchell and Roberton (1989), for instance, have hypothesized that stiffness ( k ) may be the control parameter that causes the predictable phase transitions or developmental level changes in hopping leg action. The need to lessen stiffness (scale downward) to avoid injury causes the child to begin swinging their non-hopping leg which, in turn, marks the advent of a new developmental level (Table 1). 8. CAN SIMPLICITY PRODUCE COMPLEXITY?

As students of chaos theory have demonstrated (Gleick, 1987; Peitgen & Richter, 1986), non-linearity in data can quickly produce complexities. It is well-known that pendular oscillations, for example, are non-linear, particularly if the displacement of the pendulum is greater than its length. Compound pendula, such as the human arm or leg, would also produce non-linearity. Thus, it seems that the simple model of a trunk with 4 oscillators could, indeed, produce the complexities revealed in the internal timing of the developing hop. At the least, the model gives us new ways to think about timing. At the most, it may open our eyes to the physics behind human motor development.

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9. REFERENCES

Abraham, R., & Shaw, C. (1982). Dynamics - The geometry of behavior. Pt. 1. Periodic behavior. Santa Cruz, C A Aerial Press. Blickhan, R. (1989). The spring-mass model for running and hopping. Joumal of Biomechanics, 22, 1217-1227. Clynes, M., & Walker, J. (1982). Neurobiologic functions of rhythm, time, and pulse in music. In M. Clynes (Ed.), Music, mind, and brain (pp. 171-216). New York Plenum. Eckert, H. (1987). Motor development (3rd ed.). Carmel, IN: Benchmark. Getchell, N., & Roberton, M.A. (1989). Whole body stiffness as a function of developmental level in children’s hopping. Developmental Psychology, 25, 920-928. Gibson, J.J. (1979). An ecological approach to visual perception. Boston: Houghton Mifflin. Gleick, J. (1987). Chaos: Making a new science. New York Viking Penguin. Halverson, L.E., & Williams, K. (1985). Developmental sequences for hopping over distance: A prelongitudinal screening. Research Quarter4 for Exercise and Sport, 56. 37-44. Keele, S., & Ivry, R. (1987). Modular analysis of timing in motor skill. In G. Bower (Ed.), The psychology of learning and motivation, (Vol. 21, pp. 183-228). New York Academic Press. Kugler, P., Kelso, J.A.S., & Turvey, M. (1982). On the control and coordination of naturally developing systems. In J.A.S. Kelso & J.E. Clark (Ed.), The development of movement control and coordination (pp. 5-78). New York: Wiley. Newell, K. (1985). Coordination, control, and skill. In D. Goodman, R.B. Wilberg, & I.M. Franks (Eds.), Difiering perspectives in motor learning, memory, and control (pp. 295-317). Amsterdam: Elsevier. Peitgen, H.O., & Richter, P.H. (1986). The beauty offractals. Berlin: Springer-Verlag. Roberton, M.A., & Halverson, L.E. (1984). Developing children - Their changing movement: A guide for teachers. Philadelphia: Lea & Febiger. Roberton, M.A., & Halverson, L.E. (1988). The development of locomotor coordination: Longitudinal change and invariance. Journal of Motor Behavior, 20, 197-241. Roberton, M.A., & Konczak, J. Longitudinal prediction of children’s ball velocities using developmental components of their overarm throws. Manuscript submitted for publication. Roberton, M.A., & Langendorfer, S. (1980). Testing motor development sequences across 9-14 years. In C. Nadeau, W. Halliwell, K. Newell, & G. Roberts (Eds.), Psychology of motor behavior and sport - 1979 (pp. 269-279). Champaign, I L Human Kinetics. Schmidt, R. (1988). Motor control and learning: A behavioral emphasis, (2nd ed.). Champaign: Human Kinetics. Smoll, F. (1974a). Development of rhythmic ability in response to selected tempos. Perceptual and Motor Skills, 39, 767-772. Smoll, F. (1974b). Development of spatial and temporal elements of rhythmic ability in children. Journal of Motor Behavior, 6, 53-58.

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Thomas, J.R., & Moon, D. (1976). Measuring motor rhythmic ability in children. Research Quarterly, 47, 20-32. Thomas, J.F., & Stratton, R. (1977). Effect of divided attention on children’s rhythmic response. Research Quarterb, 48, 428-435. Turvey, M.T., Fitch, J., & Tuller, B. (1982). The Bernstein perspective: 1. The problems of degrees of freedom and context-conditioned variability. In J.A.S. Kelso (Ed.), Human motor behavior: An introduction (pp. 239-252). Hillsdale, N.J.: Erlbaum. Williams, K. (1985). Age differences on a coincidence-anticipation task: Influence of stereotypic or “preferred movement speed. Journal of Motor Behavior, 17, 389-410.

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SECTION IV: Discussion paper Chapter 17

THE ROLE OF TIMING IN MOTOR DEVELOPMENT J.C. Fenfress

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The Development of Tmin Control and Temporal Or Lation in 8oOrdinated Action J. Fagard anK.H.Wolff (Editom) G3 Elsevier Science Publishers B.V., 1991

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I N 3 W d 0 1 3 h 3 a UOlOW N I O N I W I I 4 0 310H 3 H l

THE ROLE OF TIMING I N MOTOR DEVELOPMENT John C. Fentress Departments of Psychology and Biology, Dalhousie University, Halifax, Nova Scotia CANADA B3H All

Timing Is an essential defining characteristic of both behavior and development. Natural events occur within specific temporal windows. These events are sequenced and otherwise combined into broader constellations of expression. My goal i n this chapter i s t o examine certain timing events as they apply t o behavior and t o development, and especlally t o the link between them. In each case I shall stress properties o f dynamic order. A major challenge of current research Is to see how the temporal frames of integrated performance and development operate together. It is the relations among events that I wish t o emphasize. The orchestration o f a performance cannot be understood solely through an analysis of isolated parts. Parts are embedded within broader expressive contexts. One of the problems we need t o address is how these parts operate through principles of "self-organization" as well as mutual dependence. While my emphasis in t h i s chapter is upon comparative (animal) analyses of motor performance and development, Ibelieve that these analyses illustrate broad themes that also apply to human action. It Is the artlculation of these themes, and the problems which they reveal, that is my fundamental purpose. More specific details o f method and fact can be found In the cited references. TIME FRAMES AND THE ORGANISM-ENVIRONMENT INTERFACE For ethologists, and other biologically oriented investigators of behavior, behavioral patterns are important reflections of events that originate within the organism and i n its external world. These relations among self-organizing and interactive processes (Fentress, 1976)do not imply simple additivity of otherwise separate events. Rather, they often reveal an interdependence, where each slde In the relationship not only reflects b u t also molds Its complement. This fact, combined with the multiple pathways of internal-external communication, i s a major reason why many current investigators have expressed dissatisfaction with linear models of adaptive performance ( a s . Fentress, 1984, 1990a; Kelso et al., 1990; Kugier & Turvey, 1987; Thelen et al., 1987; Wolff, 1987; Wolff & Ferber,

1979). Terms such as "adaptive" and "adaptation" must be used with care. They often have ambiguous and even inconsistent implications. Adaptive usually refers to flexibility within the individual, such as i n the adjustments of internal states t o external demands (e.g. t o maintain successful goal directed performance). The term adaptation i n blology i s often restricted t o evolutionary perspectives, and thus need not refer t o flexlbllity i n either performance o r ontogeny at ail. Adaptation is also a population term that is focused upon

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biological diversity and limited opportunity. These are also considerations relevant t o motor performance and its development (cf. Edelman, 1987). I n each case, a fundamental concern is with the match between internal and external states. No biological phenotype can be explained by looking only inside o r only outside. It is inside and outside, together, that sets the boundaries o f both adaptive performance and i t s historical roots (Lewontin, 1983). The boundaries are relational and dynamic. A characteristic of behavior is that the temporal links among inside and outside worlds exhibit fluctuations as well as more protracted trajectories. I n young humans, nursing, cooing, waving and walking movements w a x and wane. Emotional expressions come and go. These fluctuations occur within longerterm changes that mark ontogeny. Fluctuations and trajectories are also constrained. They are bounded by stiii more stable (but not rigidly fixed) limits that mark personalities and even species-characteristic profiles. Depending upon one's temporal microscope, fluctuations become stabilities become trajectories. I n each case, however, the twofold task of the investigator is, first, t o divide properties of living material into "inside" and "outside", and second, to ask how these abstracted "inside" and "outside" properties become synthesized. Components are variably sensitive t o and constrained by their contexts (which also vary). I n stressing inside-outside relations i n time it i s equally critical t o recognize that nature has boundaries. Layers of at least partial insulation are critical t o organized systems. Complete transgression of inside-outslde boundaries, at any level, is as impossible as is complete autonomy f o r either the development o r maintenance of life processes. Celis, as organisms, have internal integrity as well as sensitivity t o their surrounds. Behavioral actions, as well as their constituent properties, are i n some sense both modular and interconnected. Hereln lies one of the great puzzles of biological (and behavioral) order (Fentress, 1981). We do not know what it means t o be separate yet interconnected (Fentress, 199Oa, i n press). As stressed by several authors o f this volume, timing parameters and evai uations of co-ordered events (Fentress, 1986) are complementary concerns. Are there "hard-wired clocks" within the brain; if so, how many and wlth what properties? Or, are timing mechanisms more llke the relative coordination principles outlined by workers such as von Hoist (1939) i n his studies of animal locomotion? Are Invariants relational and relative rather than absolute? Arblb (1985) has summarized one modern view i n these terms: "To understand the nature of the timing of human behaviour, we must downplay the nature of clocktime and instead emphasize the coordination of processes, both within the organism, and between the organism and i t s environment" (p. 63). This i s similar to the posltion Itake i n the present chapter. BEHAVIORAL STATES The concept of behavloral states provides a useful exemplar of muitilayered processes embedded In time that can affect motor performance. A behavioral state refers to an internal dynamic of the organism that can set alternative profiles i n performance (e.g. Wise, 1987). Events that impinge upon the organism also have dlfferent consequences with changes i n state, and may (within iimits) change the state. Changes i n response provide an objective definition of changes i n state (Hinde, 1970). Often it is posslble t o have multiple measures of state change, including direct (physiological) measurements, thus improving the objectivity of one's inferences.

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State changes can at the same time yield different profiles with different measurements. They represent a constellation of processes that rarely, if ever, allow exhaustive definition. This does not imply that states are fictions; they are simply complex realities (as, of course, are organisms). An interesting feature of state changes is that transltions may occur quickly, and then stabilize f o r variable periods (Wolff & Ferber, 1979). That is, fluctuations o f state exhibit (in relative terms) both dynamlc and stable properties. This is a common feature of many complex systems (Abraham & Shaw, 19821, including various neural network operations (Kugler & Turvey, 1987; Liinas, 1988; Seiverston, 1985). Periodicities, including relative plateaus as well as rapid transition phases, thereby provide potentially important insights into underlying organizational constraints. As stated by Wolff & Ferber (1979), “state fluctuations in the neonate are more rapid and fluid, and more significantly related t o the intensity, frequency, and quality of discrete behavior patterns than they are i n the child and adult“ (p. 292). One approach t o the study of behavioral states is t o “perturb” ongoing behavior during different observed phases. Changes i n response can be quantified as a prelude to the search f o r organizational regularities. For example, it is possible t o ask when the ongoing trajectory o f behavior appears to be buffered from applied perturbations and when the form o r direction o f activity changes. Careful evaluations also allow one t o determine the duration as well as direction and magnitude of change, t o search for self-corrective features i n the system, to examine indirect as well as direct consequences of change i n trajectory, and so forth (Fentress, 1976, 1983a,c, 1986). It is t h i s weaving together of qualitative, quantitative and temporal parameters of organization that offers especially r i c h opportunities f o r subsequent analysis. An animal study by Fentress (1968a,b) illustrates one analytic procedure. Two species of vole, Microtus agrestis and Clethrionomys britannicus, were exposed t o a model o f a flying predator (cloth ”hawk”) at set intervals. The initial aim of this study was t o examine species differences, t o relate these differences t o the animals’ genetic background and ecological niches, and t o see whether response tendencies could be modified by rearing conditions. While the data were “significant” for each of these distinctions, they also contained a high degree of intra-group variation. A t the time I became very impressed by ethological research strategies that seek not to rest with statistical significance, but to probe more deeply into the nature of intra-group variations. The obvious question was whether some o f these differences could be accounted f o r by momentary differences in the animals’ ongoing behavioral states. Actions concurrent with and also preceding the model predator presentations were used as my assay. For eachof the groups animals that were, o r had recently been, locomoting were much more likely t o flee i n response t o the “hawk” than were animals doing something else. Several lessons emerge. First, different ongoing behavior leads t o different response. Secondly, such dlfferences may apply t o each o f several different experimental groups, thus indicating how one can search f o r common principles and dlversity together. Thirdly, it i s not j u s t behavior at the moment that is important t o consider, b u t also preceding actions. For example, voles that were sitting stiii, b u t which had been iocomoting within the previous 10 seconds were as likely t o flee as were the animals that were still engaged i n locomotion. This last observation brings us closer to an evaluation of behavioral states as hidden variables, and with Interesting implications. While states can be defined in terms of ongoing behavior, experiments can also be designed t o show that there is a “carry over”, o r momentum, among states that does not map i n a simple one t o one manner with actions observed at the moment. These “hidden“

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Processes can still be revealed, however. The data also indicate that processes underlying one class of actlon may exist during the performance of another class of action. This warns us how simple models that assume isomorphic relatlons between internal states and overt performance are I1kely to mlsleadlng. It also reminds us that there are multiple events that occur simultaneously within the organism, rather as chords in a musical composition (Fentress, 1978). These events may also play agalnst (affect) one another in ways that we do not yet understand (Fentress, 1984). Neither animals nor humans run on the basis of linearly defined state variables that cancel one another out In clear cut sequences. I n an age of increased technology it is refreshing to remember that even simple observations of perturbed natural action patterns can provide critical insights. Sensltlve observation demonstrates a fatal flaw in models that stress unitary serial (single step by step, "tick-tock clock") processing. Reality argues for a much more rlch combination of serial and parallel events. This combination can Include events with variable degrees of spatial and temporal overlap that also operate at several levels of organization (cf. Arblb, 1985; Sejnowskl & Churchland, 1989). A related but somewhat more subtle approach to state variables , I s to present the behaving organism with stimuli that do not necessarily induce an overt response but modify the organism's response to subsequent stimuli. The "priming stimuli", as they are often called (Posner, 19891, can be deflned objectively as producing state changes even though their Immediate consequences are not apparent. The time course of these hldden state variables can be assessed by Introducing probes at different intervals. Increases as well as decreases In response to probe stimuli form the data set. Such research tactics have been used with considerable success in both anlmal (Heiilgenberg, 1976) and human (Posner, 1978) studies, and extension of their appllcatlon Into problems of human development are highly promising (Wolff, 1987). An important theoretical possibllity, that still needs further evaluation, Is that the direction of Influence of a given state variable on a deflned action can be elther positlve (facilltatory) or negatlve (Inhibitory) as a function of both quantitative and temporal conslderatlons (Fentress, 1984, 1990a). For example, rodent actions that range from grooming to perseverant motor stereotypies can be facllltated by a wlde range of perturbations at low Intensltles. These same perturbations at higher lntensltles may produce lnhlbltlon (Fentress, 1983a). The importance of time considerations is clear from the fact that perturbations may lead to short-term response suppression followed by "rebound" excltatlon of the same actions (Fentress, 1984). There is also a possible trade-off between quantitative and temporal factors. This is due to the fact that the effects of a perturbatlon take a flnlte period to reach full effectiveness, and also decline systematically In their effective strength over time once removed. It Is for these and related reasons that a full evaluation of state variables must take into account qualitative, quantitative and temporal properties as only partlally separable aspects of integrative operations. Finally, if multlple state Variables operate simultaneously as well as sequentially, one must ask how these state Variables affect one another. It Is not sufficient to ask how they add or subtract, as mlght be Implied from a linear arlthmetlc problem. I f they mutually mold one another's properties then such simple arithmetic w i l l miss entirely one of their most important features. This mutual molding of concurrent and serially displaced processes in behavior demands analytical procedures that are both subtle and precise. A s I shall argue below, I believe such considerations are as Important to our understandings of Integrated movement and developmental events as they are to more global considerations of state variables in behavior.

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In summary: There are several lessons about research into "behavioral states". First, the concept of a state emphasizes dynamic principles of behavioral organization. Views of the organism as frozen in time are clearly inadequate. The boundaries o f underlying control systems are also dynamically ordered. Secondly, state variables emphasize the relational nature of behavioral processes. The organism's state must be viewed i n reiation t o t h e state of extrinsic events. A t a slightly more abstract level, a// events occur i n the context of other events. Thirdly, motor processes are themselves embedded within state variables. Motor systems can be abstracted f o r analysis, b u t f u l l understanding must also take into account that altered contexts can alter o u r views of control (cf. Wolff, 1987). Fourthly, the multiplexed nature of behavioral states warns against simple linear (additive) models. Nonlinearities are the rule rather than the exception. Finaliy, because o f state varlables, we should not expect responses of a system w i l l simply mirror the details of events that impinge upon the system. There are transformations that can only be understood when current state variables are viewed t o be critical partners with extrinsic factors i n producing observed outcomes. Such considerations are equally critical t o any evaluation of developmental trajectories (e.g. Purves, 1988). I n each case, o u r view is of systems that are necessarily both interactive and self-organized. Later sections of this paper w i l l r e t u r n t o this theme. SEQUENCES OF ACTION One approach t o action sequences i s t o treat "classes" of action as separable events. A rodent may walk, groom, f i g h t and sleep. A wolf may howl, dig a den, and feed. An infant may cry, nurse and smile. It is perfectly legitimate t o abstract action streams into such functionally coherent categories, as long as one remembers that a considerable process o f abstraction is involved (Fentress, 1990b). This means that refined measures may necessitate a reordering of initial behavioral taxonomies. Once actions are separated f o r analysis, a number of questions follow. What are the causal underpinnings of these actions, as isolated entities? How are the actions strung together over time? How diverse (heterogeneous) i s their internal structure? Do they share processes that might offer alternative forms of classification? Do actions that are superficially similar have a different causal structure; do actions that are superficially distinct share a common causal structure? It is critical that we as investigators recognize that there is no single "best" way t o categorize behavior. Different methods can give different insights. Each method, no matter how rigorously pursued, can also blind us t o possible alternatives (Fentress, 1990b, i n press). The danger comes when we fail t o acknowledge that even at the level o f behavioral taxonomy o u r methods reflect our expectations as t o what i s important, and what i s not. On the assumption that, f o r certain purposes, it i s f r u i t f u l t o divide the "behavioral stream" (Hinde, 1970) into mutually exclusive actions, one can then ask how these actions are organized i n time. One approach i s t o apply information theory techniques, i n which the degree of "uncertainty" of action occurrence is used as a basic starting point. "Uncertainty", i n t h e formal information theory sense, refers t o the relative difficulty an investigator would have i n guessing what action should occur next. For example, if an animal's behavioral repertoire were divided into 8 equally probable and randomly sequenced actions, then one could guess the next action one out of eight times, or z3 (cf. Attneave, 1959 f o r a delightful rendition of information theory methods).

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The logic of information theory involves the employment of a log scale t o the base two i n making these calculations. The basic unit is called a "bit". On this scale two alternatives yield one b i t of information, four alternatives yield two bits of Information, eight alternatives yield three bits of information, and so on. The intuitive value of this "log logic" is one similar t o the familiar Twenty Questions game of early North American radio and television. I f there are two alternatives, one "yes" o r "no" question can Indicate which is correct (i.e. one "bit" of information Is gained). I f there are four alternatives, then two properly asked questions w i l l yield the answer (1.e. two "bits" of information galned). I f there are eight alternatives, then three such questions w l l l reveal the answer. The trick here i s t o divide the population of possibilities i n half by each question. Thus i n the Twenty Questions game, a (perfectly!) clever participant can cover more than one million (i.e. 220) alternatives. A given square on a checker board (which contains 64 squares) can be guessed by a series of 6 questions (2 x 2 x 2 x 2 x 2 x 2 = 64 = 2'). These numbers yield the maximum amount of uncertainty that an animal o r human subject can exhibit, given the number of alternatives that we allow it t o express. There are two obvious ways t o Improve one's ability t o guess correctly. The f i r s t is t o capitalize on the fact that animal and human actions are not equally probable In any given context. There are times that we expect an animal t o fight or a child t o cry, even though each could do a variety of other things. This is akin t o the weighted coin o r loaded die problem of casino operations. Bias either and predictions become easier. I n such cases it is still reasonable t o assume that Individual events have no sequential dependencies; i.e. i n an honest casino a given event does not influence a subsequent event. Clearly t h i s is not a rule that reflects animal or human behavior. Events predict, and Influence, others. Information theory allows one t o evaluate such predictive connections. To do t h i s one can look at the immediately preceding event, combinations o f preceding events, o r f o r that matter anything else In the organism's history. The numbers, expressed i n relative uncertaintiesof prediction (bits), tell us how f a r removed from a random sequence of events a given action stream may be. Such numbers can be useful f o r a variety of reasons. For example, Berridge et ai. (1987) capitalized on an earlier study by Fentress & Stilwell (1973; cf. Fentress, 1972) t o document different degrees of sequential coherence (stereotypy) i n rodent grooming actions. One of the interests i n doing such work i s that actions that differ i n their stereotypical constraints are likely t o be controlled by different processes. This is t r u e even though the individual actions that make up a sequence of events are unchanged. To cite the example of rodent grooming, stereotyped sequence phases appear t o be more under the s t r i c t and autonomous control by central pattern generating mechanisms than are those phases that exhibit greater flexibility. Whatever the usefulness of these information approaches, their limitations should also be noted (cf. Wolff & Ferber, 1979). First, the employment of information theory approaches Involves a choice on the part of the investigator i n terms of how behavioral events are coded. I f one assumes that the important measure i s transitions between action classes, f o r example, then it follows by definition that no action can follow itself. If, on the other hand, one scores behavior on a time sampling basis then (depending upon the time scale used) actions may often repeat themselves i n successive time bins, or (when larger bins are used) the actual sequencing of events can be distorted (Fentress, 1972). Secondly, information measures assume that the sequential linkage among events follow constant probabilistic rules. This is called the assumption o f ergodicity or stationarity (Attneave, 1959). I n behavior the assumption i s often

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broken. Indeed, this breakage of a simplistic statistical assumption is frequently what provides the most valuable opportunities f o r subsequent behavioral analysis. Animals o r children i n different circumstances should be expected t o do not only different things b u t also the same things i n different combinations. Fentress & Stilwell (1973) capitalized on t h i s fact of nonstationarity t o demonstrate that rodent movement patterns have hierarchically ordered rules o f organization. That Is, there are rules, and also rules that change the rules (cf. Bateson, 1976). One might create a slogan from such phenomena: Break a statistical rule t o find something useful! Thirdly, information measures, as traditionally used, confound temporal and sequential data. Unfortunately, there is no simple solution t o this problem. While most workers would agree that temporal (e.g. duration) and sequential events are logically distinct, they remain faced with t h e dilemma of how t o deal with these two properties i n a unified manner. Fentress (1972) offered an illustration of the problem. The duration of licking movements i n mice serves a predictor of which type of grooming stroke Is most likely t o follow. The perfection of formalized methods that combine sequential and temporal variables is obviously Important, but they have proven t o be analytically difficult. The cross-tal k among temporal and sequential events in behavior clearly deserves further investigation. For example, Berrldge et al. (19871, [cf. Fentress ( i n press) for elaboration], noted that i n grooming sequences of rats, stereotyped phases of the behavior are indicated by the animals switching into stereotyped rhythms of licking which are then transferred t o identical rhythms o f paw t o face stroke sequences. This last example reveals a critical fourth point. There are action properties (dimensions) that are often shared among action classes. Timing properties may be shared among classes of behavior that are formally distinct by other criteria (cf. Vivian1 & Terzuolo, 1980; other chapters i n t h i s volume). Force properties may also be shared across sequentially ordered actions that are distinct i n their form. What t h i s means is that action categories that are distinct by certain criteria may not be distinct by other criteria. This is an important point i n that I t indicates the multiplexed nature of even relatively simple action categories i n animals. I n the study o f human development one can expect even more subtle relations among categorized behavioral events (e.g. Meltzoff, 1988). I n terms of developmental precursors t o integrated action such considerations have yet t o receive the attention they deserve (Fentress, 1990a, i n press). For example, would changes i n the timing properties of one action also be reflected i n the timing properties of another action? There are a number of still more subtle issues that Ishall r e t u r n t o later i n t h i s chapter. Fundamental among these issues is how we can conceive of behavioral events that appear to be both separable and interconnected. I remain convinced that we have t o date paid only superficial l i p service t o t h i s Issue of combined separablllty and interconnection. Those of us Interested in the developmental course of behavior get h i t with the same question yet again. How can developmental events be self-organized and also interconnected? Isubmit there i s no satisfactory answer to t h i s problem, i n large part because we do not even know how t o think about it. POLARITIES I N THOUGHT: A SHORT SUMMARY THUS FAR By way of summary, the above illustrations can be viewed as representing two basic polarities i n our thinking about integrated action sequences, and their development (cf. Fentress, 1984). The f i r s t o f these polarities is how separate as opposed t o interconnected events are. I f Istand or sit, then Iam i n each

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case doing something different. But how different? Perhaps those events that contribute t o my style of standing also contribute t o my style of sitting? Certainly the two actions can interfere with one another. The second polarity concerns our attempts t o deal with more o r less stable features of behavior while also paying appropriate attention t o the rules that change these stable features. Stability and change, as separation and interconnection, provide a fundamental conceptual challenge. To what extent do organisms exhibit one or the other? To what extent do they reflect some mix of the two? Clearly, if one shifts time frames or levels of inquiry the answers may also alter. For readers of this chapter there is also the concern with limitations of constructing models that attempt t o cross species barriers. There are two related issues. The f i r s t is how we examine the basic polarities of separation and connection across levels and time frames of organization. The second i s how we evaluate the very principles of stability and change from alternative frameworks. These are not trivial issues; but, they are too easliy and too often ignored (Fentress, 1984). TEMPORAL DIMENSIONS OF ACTION LAYERS I N ONTOQENY The time parameter of action has still not been addressed very explicitly. How indeed do we deal with events whose characteristics vary i n a time dependent manner? There are a number of time frames from which we can ask this question, ranging from moment t o moment episodes of expression through developmental and even evolutionary trajectories. For those of us who employ animal models there i s the additional issue of how we can relate events as expressed i n different species t o the search f o r common underlying (temporal) perspectives. As a conceptual introduction, it can be useful t o move t o "higher" levels of human experience. Music provides a test case. A r e there certain rhythms that we expect, and others that we do not expect? I f so, why? Music has additional advantages as a model f o r questions in animal as well as human movements (Fentress, 1978). We are reminded, f o r example, that individual actions are comblned Into kinetic "melodies", that transpositions of key do not remove the invariant relations among notes, that variations and themes can coexist, that there are constraints i n allowed variation, and that chords (parallel events) are often as important as are melody iines (serially ordered events). [Indeed, one might ask why music plays such an important role in human experience. It is reasonable to assume that music reflects brain processes that also contribute to various adaptive functions.] The importance of time can be seen i n the sequencing of events. As mentioned, we have found that licking bouts of dlfferent durations were followed by changes in the probability of subsequent motor events (Fentress, 1972; Fentress 8 Stilwell, 1973). More recently, we have found that transitions into stereotyped phases of rat grooming are marked by highly rhythmic bouts of licking whose temporal characteristics are then carried over into bouts of short paw strokes across rostra1 regions of the face (Berridge et al., 1987). This last example offers two additional lessons. First, the fact that the same timing mechanism can be shared across physically distinct actions may not only help account f o r the transition among actions i n a sequence, b u t also demonstrates that these actions are not fully independent i n their control. The phenomena of co-articulation among adjacent actions i n a sequence, common i n both animal and human movements, make a similar point (Fentress, 1983a, c). Our views of what Is a "unit" i n behavior must take into account the broader contexts within which such abstracted "units" are articulated. Secondly, not

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only are individually abstracted actions composed of multiple properties (such as timing, force, direction), but the fact that common properties may be shared among "units" cautions us to think carefully about the meaning of hierarchical models of motor control (Fentress, i n press). That is, if timing, force and direction are subproperties of a given movement then we can legitimately establish a taxonomy i n which these subproperties are viewed as components o f the act as defined at a higher level; but, if several acts i n a sequence also share common properties then i n some sense these acts can also be viewed as subservient t o these higher properties the hierarchy becomes re-ordered; top becomes non-top and vice versa. Young animals (and children) often show two characteristic properties i n the timing of their sequentially ordered actions. The first, seen f o r example i n both human speech and rodent grooming, is that early actions often lack the smooth integration seen later. Instead, the actions are articulated on a "one at a time" basis, with pauses inserted between them (Fentress, 1983c; Kent, 19811. Secondly, early performances are often accompanied by a greater variation i n timing than are later performances. An excellent example i n t h e animal literature is the articulation of early "plastic" song In birds. Thus, Margollash et al. ( i n press) found that plastic song phrases i n the indigo bunting are characterized i n p a r t by variable durations of individual notes. What this means i s that statistically defined variations i n themselves offer important data; it is not sufficient t o view such variations merely as "noise" that detracts from the usual business of group comparisons. A question of considerable interest, for which as far as Iknow there are few data, Is how flexible or rigid are the timing characteristics o f action. Certainly in human speech people i n different geographical regions often have speech with different temporal properties. I n animals the literature has given t h e impression that timing mechanisms are t o a large extent "hardwired". However, critical experiments remain t o be performed. I n this context it Is of considerable interest that even in invertebrate systems neural "modulators" (e.g. Marder, 1988) can affect the absolute and relative timing of certain patterns. Animals are often very sensitive t o the timing of events i n their environments, and the study of timing in motor development might therefore offer useful Insights that extend beyond self-referenci ng performance properties (Fentress, i n press). On a broader scale, timing and gradients i n development are clearly critical. For example, current biological models o f development stress t h e importance of appropriate temporal activation and de-activation of genes (Davidson, 1986). The phenomenon of sensitive periods is well known to all students of either behavior o r neuroscience. Experiential events have limited windows of opportunity to exert their maximum influence. These temporal windows, while constrained, are not absolutely immutable, however. They may shorten or lengthen depending upon the organism's p r i o r developmental history as well as specific configurations (contexts) within which particular stimulus events are offered (Bateson, 1981). Their boundaries (e.g. limits t o flexibility) need much f u r t h e r investigation. To reiterate a point I made earlier, Ithink that it is not only differences between time windows, but also variations within time windows, that deserve our attention.

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Note on Movement Dimensions Versus Actions It is convenient to think of motor performance i n terms of discrete actions. One can then arrange these actions into observed sequences, and so on. However, there are at least two limitations t o such endeavors which 1 can now summarize. First, actions are harbors of heterogeneous events (dimensions).

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Secondly, analyses of these events (or dimensions) can reveal organizational properties that are not apparent from the study of actions as unitary classes of expression. Take the case of rat exploration and its ontogeny (Eiiam & Golani, 1988). A n important contribution made by these investigators is that a number o f "discrete" actions share common organlzational properties. As iIIustration, movement patterns i n ontogeny can be separated Into rostral t o caudal components, as well as into trajectories that are horizontal, forward, o r vertical. I n rat exploration there i s a general trend from rostral to caudal that is accompanied by trends to move i n a horizontal, then forward, then vertical direction. These trends cross over alternative categorizations of acts A, B, and so forth. I n an earlier study o f rodent (mouse) grooming actions, Golani and Fentress (1985) found that quite different developmental profiles could be discerned f o r limb segment kinematics, forepaw trajectories in space, and contact pathways between the forepaws and the face. One of the interesting profiles which occurred i n this study was that the overall sequential structure of grooming movements exhibited transitions that were at f i r s t rich b u t loosely organized, then simple in their sequential form, and then elaborated into more complex patterns that captured both the initial richness and later patterns o f movement invariance. These are, Isuspect, common properties of mammalian movement ontogeny. I f so, they deserve much more explicit empirical investigation than they have enjoyed i n the past. Ishall return t o a more detailed evaluation of these properties i n the subsequent section on developmental trajectories. First, it is valuable t o acknowledge the breadth of contexts within which integrated movements occur. Social behavior is a prime example. Note on Socially Coherent Action Patterns Animals live their Ilves i n "social" contexts. Postnatally, animals, as well as people, need t o adjust their individual movements on the basis of momentary as well as long term constraints within these social contexts (e.g. Hinde, 1982). A mother and her child must not only be able t o articulate actions defined at the individual level, but also to connect these actions into a broader social stream. The critical question is how we evaluate individual and social constraints toget her. I t t u r n s out that there are few relevant data, f o r any species (but see Wolff, 1987). This i s a major limitation i n both our studies of individually coordinated movements and their social nexus. The social nexus of coordinated movements both constralns and emanates from properties of coordination defined at the individual organism level. Here our own animal work has concentrated upon the social behavior of timber wolves (Canis lupus). As illustration, McLeod (1987) has shown that during the ontogeny of displays of wolf pups the animals perfect individual styles of articulation prior to the time that they give obvious responses t o display patterns exhibited by other pack members. This supports general theories of motor development that stress the importance of intrinsic events during the ontogeny of performance (Fentress & McLeod, 1986, 1988). It is a moot point whether such developmental progressions w i l l occur i n a similar pattern if extrinsic circumstances are varied. McLeod's (1987) study is of f u r t h e r interest because o f i t s quantitative precision from alternative frameworks. He examined the rules of sequential cohesion among actions both within and between participating wolf pups. Over

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the period of one t o three months postnatally his wolf pups exhibited a progresslve increase In the regularity of their actions, defined for the individuals. I n contrast, their rules of social connection (defined by crosscorrelational analyses between the PUPS) increased then decreased over t h i s same three month period. A t early ages the social behavior o f the wolves was loosely connected. A t two months their behavioral patterns fell into rather simple ("tick-tock") patterns of alternation. A t three months the rules o f connection between the animals became looser, although now definable by higher order rules of connection. The point is that different measures (e.g. individual versus social connections of action patterns) can follow quite different time courses. I n adult wolves there are important invariants that connect the actions o f individual anlmals, even when these animals perform a variety of distinctive actions as individuals (Moran, Fentress & Golani, 1981). This means that individual wolves adjust their actions t o the actions o f their social partners. I n young wolves the rules of peer coordination are different. For example, Havkin (e.g. Havkin & Fentress, 1985) showed, i n a detailed analysis of biomechanical processes, that young wolves go through an early period of Increasing individual coordination, followed by relatively simple rules of inter-animal coordination, followed In t u r n by more elaborate and flexible sequences of social movement. I n this latter case one observes individual variations while at the same time there are increasing invariants (rules) among the social partners. TOWARDS A DETAILED EVALUATION OF MECHANISM I N THE CONTEXT OF SYSTEM Each of the previously discussed examples presents a paradox. How do we separate a complex system into i t s component parts while also giving proper acknowledgement t o the fundamental importance of rules that connect these parts? Indeed, how separable are "parts" and their "relations"? How can we say that either "parts" o r their "relations" are "primary"? These are not trivial questions. A common approach i n science i s t o seek invariances. These invariances need not be all o r none, but relative (more or less). Invariances can s h i f t with levels of inquiry, as well as with criteria of inquiry at a particular level. The term "mechanism" i s i n itself tricky. A mechanism is generally viewed t o be an autonomous mediator of events that we measure. Thus, we can have timing mechanisms o r mechanisms of expressive priority. Nonetheless, it is possible that such abstracted mechanisms are not as autonomous or unitary as we traditionally define them. There are few magic bullets i n the organization of motor actions o r other aspects of behavioral performance. Mechanisms, however we define them, occur within the context of other variables. It is an empirical question how autonomous o r interconnected our "mechanisms", as abstracted, t u r n out t o be. I n the motor behavior literature one can see these two conflicting ideas i n strong relief. For example, there is an impressive literature on "central pattern generators". These "CPG" models Imply autonomous processes that may be triggered but are otherwise uninfluenced by extrinsic variables (for recent critiques, see Pearson, 1985; A t the other extreme there are an increasing number o f Fentress, in press). models that stress more broadly defined "systems" perspectives i n motor control, where each property of action can be understood only i n the broader context of other events that emanate within and external t o the organism (e.g. Kelso, 1981; Thelen, 1986). Current empirical data do not allow for a full resolution of these alternatives (e.g. Fentress, 1990a). This is i n part because they do not represent t r u e opposites, but are complementary.

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I t is certainly possible t o demonstrate the importance of contextual variables i n motor control. Such data l i m i t the u t i l i t y of autonomous ("modular") models, at least as these can be extrapolated across diverse and changing backgrounds (surrounding events). Ican illustrate from research done i n my laboratory. Kent Berridge and I were interested In the influence of trigemlnai afferents upon the production of facial grooming and licking movements i n rats (Berridge & Fentress, 1986). We tested rats, before and after trigeminal deafferentation, with a method that allowed us t o infuse different taste substances directly into the animals' mouths. Some of these substances elicited ingestive responses; other substances led t o aversive responses (e.g. forepaw swipes and gaping). The consequences of trlgeminal deafferentation upon the laterality of tongue movements were maxlmai during ingestive phases, whereas the form of forepaw to face grooming movements was most disrupted during phases of postprandial grooming (a double dissociation). Further, when phases of postprandial grooming were divided into fiexlbly coupled actions versus stereotyped action sequences it was found that trigeminai lesions selectively disrupted strokes in the flexible sequence phase. I n later studies the details of ingestive and grooming actions were subjected t o a variety of quantitative analyses (Berridge et al., 1987; Berridge & Fentress, 1987). For example, the animals show tendencies both f o r response perseveration and alternation among action components (generating the global rule of "alternating perseveration"). During other phases of grooming they adopt a strict linear sequencing rule of the type ABCDE. Although the form of individual grooming movements was altered by tri gemi nai deafferentation outside of the stereotyped ABCDE sequence phase, the same actions were unaffected when they were embedded within this stereotyped sequence phase. Further, overall sequential rules were maintained after trigeminal deafferentation (even i n cases where the form of individual strokes was altered). These data indicate that i n even relatively simple action sequences multiple mechanisms are operative, and that thelr individual contributions may vary with expressive context. The data also support the hypothesis that brain pattern generating mechanisms contribute importantly t o the sequential integrity of movement. This was tested directly by kainic acid lesions of the corpus striatum. I n contrast t o the peripheral lesions, striatal lesions (a) had minimal effect upon movement form, but (b) did disrupt the integrity of the linear sequence phase. An unpublished study in my laboratory also demonstrated that 6-hydroxydopamine lesions of the striatum in infant mice led to the failure of these animals t o complete most linear sequences of grooming (cf. Berridge, 1989). The lesioned animals also appeared t o be hypersensltive t o environmental perturbations, once again indicating the subtle interplay between central and peripheral contributions to integrated movement. Striatal lesions i n rats also increase the likelihood that the animals w i l l inject unusual movements ("flails") into otherwise intact sequences, and may also result in hyperkinetic paw treading movements when the animals are also given specific taste solutions (Berridge et al., 1988). Once again it is clear that there is an interlocking among multiple sensory and central processes that must be evaluated if we are to understand how such movement sequences are produced. The challenge of thinking about mechanisms and systems together is considerable. This is because organizational processes i n movement are both differentiated into partially isolated properties and integrated into more comprehensive systems. Put i n other terms, processes exhibit a certain degree of intrinsic order as well as contextual sensitivity. This contextual sensitivity can also vary in time. Rodent grooming movements are relatively easy t o disrupt

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in their initial and terminal phases, b u t are much less easily interrupted i n their central phases (Fentress, 1972). It i s as if systems open and close. Even t h i s metaphor can be misleading, f o r the opening and closing may be relative rather than absolute, and must be defined each potential source of extrinsic influence. Of course once extrinsic influences operate upon a system they i n some sense become part of that system. The rules o f combination are often nonlinear; simple additive models rarely work at the level of complex performance (cf. Wolff, 1987). I t is best t o think of systems as being both "interactive" and "selforganizing" (Fentress, 1976). The challenge is t o probe what t h i s duality of operation means. Part of this challenge may be answered only if we add three considerations t o our models. First, rather than thinking of systems (or mechanisms) as being statically organized it appears more realistic t o view thelr properties as evolving and dissolving i n time. Their very boundaries of influence appear t o be dynamically ordered, but I t has proven difficult t o probe beneath the surface of such realizations. Even i n invertebrates modulators of neuronal properties can lead t o circuits that are have multiple foci and functions (Getting & Dekin, 1985; Marder, 1988; Selverston, 1985). Secondly, when systems (or mechanisms) interact they may "mutually mold" one another's properties. To the extent that this is true it becomes unrealistic t o expect that the properties of processes i n behavior that are isolated for analysis reflect properties as they operate i n more complex configurations. As noted, early models of central pattern generating mechanisms In motor control were limited by unrealistic expectations that isolated processes reflect operations at the intact organism level (Fentress, 1990a; Pearson, 1985). Thirdly, recent data in both invertebrate and vertebrate systems suggest that distributed control is the rule rather than the exception. This has led t o experiments on neural populations, such as in the analyses by Georgopoulos (1990) on cortical processes i n primate movement. Individual cells may code only broadly for the direction o f movement; one has t o examine population vectors across neurons t o find invariant relations among neural activity and movement direction. These sources of flexibility and complexity do not imply that motor control systems have no constraints o r stable modes o f operation. Rather, they lead t o renewed demands upon how we examine these constraints and stabilities. Recent dynamic models (e.g. Kelso et al., 1990; Kugler & Turvey, 1987; Thelen, 1986) have sought t o b r i n g i n considerations of central states, sensory influences, limb mass, task demands, and so forth. This has provided an important corrective t o early compartmentalized models. The potential danger of the dynamic systems approach i s that i n stressing interconnections among multiple events one can lose sight of the isolable properties that are also necessary f o r control (cf. Posner, 1978, on chronometric factors i n behavior). We need much more thought as well as experiment if we are t o comprehend how motor and other control systems attain both modular and global properties (Edelman et al., 1990). One of the difficulties appears t o be at the level of behavioral taxonomy. Since behavioral streams can be subdivided i n numerous ways, it follows that alternative taxonomies can generate different perspectives on control modularity. To cite a single illustration, Keele and his colleagues (e.g. Keele et al., 1990) have found that patients with certain forms of lateral cerebellar damage have difficulties i n timing that affect both motor performance and perception. I f "acts" rather than "operations" had been used i n their taxonomies t h i s degree of timing modularity would not have been apparent. Berridge (1990) has reported timing properties i n the grooming movements in different species that appear t o be robust across peripheral changes in development (limb mass).

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DETAILING DEVELOPMENTAL TRAJECTORIES Developmental dissections of movement, including timing parameters, provide a powerful analytical tool. However, this is t r u e only if the behavioral analyses are conducted with precision. One problem i s that the unaided eye, while good at broad forms of pattern recognition, i s often insufficient t o account for subtle parameters. To cite an early example from our own laboratory (Fentress, 1972) young mice appear t o make certain grooming strokes more slowly than do adults. One of these stroke categories, which we labelled "singlestrokes", occurs in a serles of 8 or so repetitions. High speed film analyses revealed that the duration of the stroke cycle was essentially identical i n infant and older mice, but that in the infant mice successive strokes were separated by short pauses. I n addition, although the overall sequential integrity among successive "single strokes" was found i n young animals, they would often fall t o exhibit the strict alternation between major and minor limb movements seen i n adults (i.e. r i g h t and left paws move together, but with asymmetrically alternating shorter and longer trajectories). For another stroke, the longer duration and more flexible "overhand" movements, the young mice did show increased duration as well as greater variability in comparison to adults. The bllateral coupling between the forellmbs durlng these long strokes was less preclse than that seen i n adults. [One simple test for t h i s is that observations restrlcted t o one side of the face are good predictors of stroke amplitudes and timing on the other side o f the face f o r adult animals, but not f o r infants.] I n adult animals the "single-stroke'' series i s followed immediately by the "overhand" series of strokes. I n young mice this overall sequencing rule was also apparent, but was often accompanied by the interspersion of other miscellaneous strokes. Thus In addition t o changes i n the timing, amplitude, and form of individual movements, there are developmental changes that can be traced i n the higher-order patterning of these movements over time. An additional point that can be made from observations on grooming sequences i n adult mice, briefly referred t o above, Is that the same motor "acts" are variously combined into predictable "words" and "phrases". I f one thinks of a grooming "act" as being represented by a letter, then the concept of a "word" can be thought of as particular combinations of letters i n a group, and a "phrase" can be thought of In terms of the sequencing of words. This implies that adult rodent grooming is hierarchically ordered i n the sense that sequential rules of connection among "acts" can be modified, I n a rule governed way, across the sequence as a whole. The existence of these higher-order rules Is less apparent i n young mice than i n adults, but this may In part reflect a taxonomic bias. I n the young animals, f o r example, there are also strokes that are difficult to classify by adult crlteria. Without quantitative assessment of individual movement parameters it is difficult to be confident that different levels of descriptive organization are being treated i n a uniform manner. As previously indicated, while the abstraction of movement "acts" (as i n rodent grooming strokes) Is valuable, more fine-grained dlssections are often necessary t o clarify the emergence of organizational constralnts i n ontogeny. To pursue the illustration, Golani and Fentress (1985) examined the early ontogeny of facial grooming in mice from three complementary perspectives: a) limb segment kinematics, b) forepaw trajectories i n space, and c) contact pathways between the forepaws and the face. It is important to recognize that these are not redundant descriptions; no one can be extrapolated from the knowledge of either other. Further, multiple descriptions can sensitlze us t o the

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fact that animals, as humans, are often involved in multiple simultaneous tasks, as well as tasks that are strung together in a linear array. An animal needs t o maintain i t s balance while rotating a limb segment while combining limb segment movements into a limb trajectory while combining multiple limbs into a coherently orchestrated movement sequence - and so forth. Failure t o combine these layers of action together can provide important clinical as well as ontogenetic indicators (Wolff, 1987). Further, the relative priorities among multiple control processes can provide useful indicators of organizational constraints at any given moment (Fentress, 1984; Fentress & McLeod, 1986, 1988, Golani, 1976; Golani & Fentress, 1985).

The method of movement notation we employed i n our study of mouse grooming ontogeny was adopted from the Eshkol & Wachmann (1958) polar coordinate system of human choreography. The basic idea is t o view each limb segment of interest as having one end fixed within the center of a sphere, with the other end free t o trace trajectories across the surface of the sphere. The three logical trajectorles possible are a) rotations around the axis of movement, b) movements that are perpendicular t o the axis of movement, and c ) conical movements that are between 90 degrees and zero degrees to t h e axis o f movement. These curved pathways f o r individual limb segments can then be combined for analyses of more complex multisegmental movements, such as trajectories of the limbs through space o r forepaw t o face contacts. Frames o f reference can also be shifted systematically, such as by referring movements of one limb segment t o i t s immediate neighbor, or by referring limb segment movements t o an environmental referent. The starting point of analysis i s t o examine postures defined by the relative positions of limb segments, with respect to one another or with respect t o some environmental referent. Movement then becomes a change i n these postural relations. This view of movement clearly stresses the relational as well as dynamic nature of movement (cf. Bernstein, 19671, and allows f o r a method of description that does not rely upon the employment of fixed movement categories, or "acts". By separating and then combining different properties of movement one can then seek foci of relative variation and invariance, along a number o f different dimensions and f o r various combinations of individually defined events. One can also access the various consequences of movements f o r a given limb segment i n terms of other limb segments (called a movement "hierarchy" i n Eshkol-Wachmann terminology). For example, if a person i s clutching a chinning bar with the hands, with body suspended, then movementsof the wrists w i l l lead t o a swinging of the lower torso; wrist movements with the arms i n the same position, but with the person standing upon the ground, would have minimal consequences upon the position of the lower arms, body torso, o r legs i n space (see Fentress, 199Oc; Golani, 1976; Golani & Fentress, 1985 f o r more detailed summaries). To allow f o r the quantitative evaluation of grooming-like strokes from the f i r s t postnatal day, it proved useful t o place the animals in a mirrored "high-chair". The infant mouse was centered between two vertical mirrors with a 90 degree angle between them (45 degrees t o each side of the forward facing mouse). The animal's body was placed through a small hole of a t h i r d mirror, tilted downward from the back of the chamber at 45 degrees. The mirrors allowed high-speed (100 f.p.s.) filming of the animals from on front, t o each side, and from underneath. The forward tilted mirror with the hole provided body support, so that the animal could maintain an upright (adult grooming) positlon. This eliminated confounding between variables such as muscular strength and the animal's ability t o maintain i t s balance with concerns for basic abilities to articulate coordinated forelimb and head movements. The forward directed mirror could be replaced by others with increasing large "body

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holes" to support the animal as it grew older. Additional observatlons were made of the animals i n their nests. Major ontogenetic progressions In grooming could be clustered into three major temporal phases, of approximately 100 hours each. During the f i r s t phase (0 100 hours postnatally) the mice employed both temporally isolated strokes and stroke bouts which were richly constructed but variable i n amplitude, symmetry and timing. Forepaw t o face contacts often appeared fortuitous, and occurred with considerable varlatlons i n amplitude, dlrection and force (e.g. sometimes the paws got stuck on the face through excessive lateral force; sometimes the paws missed the face altogether, or bounced off t h e face after momentary contact). During phase I1 (100 - 200 hours) the asymmetry of forepaw movements was eliminated, their amplitude was greatly restricted, short forepaw to face contacts were predictable (partially through restrictlon of head movements), and the strokes almost always occurred as isolated events (rather than in bouts). The general impression was that rlchness In movement was replaced by stereotypy i n details, with resulting precision (Invariance) In result. Phase I11 (200 - 300) hours ushered In a return of bouts with both short and long, symmetrical and asymmetrical strokes. Head, neck and t r u n k movements became more elaborate, with the result that the same contact pathways could be maintained through a varlety of articulatory details defined for the Individual limb segments (cf. Lashley's "motor equivalence", 1951 1. During phase I11 and beyond one sees the f i r s t clear signs of motor compensation In response t o perturbations of a single limb segment, along with the crystallizatlon o f more discrete (distinctive) grooming "acts" and thelr sequential plus hierarchical arrangement as deflned for adults (Fentress, 1972; Fentress € Stilwell, i 1973; see also Fentress, 1988). Several summary points can be made from these an related observatlons (cf. Fentress, 1984, 1988; Fentress & McLeod, 1986, 1988). 1) Capacitles f o r movement in ontogeny have multiple loci, including, f o r example, neural maturation, limb strength and ability t o maintain supportive postures must each be considered (cf. Bekoff, 1988, on chickens; Thelen, 1986, on human infants; Bradley & Smith, 1988, on klttens; Stehouwer, 1988, on frogs). 2) Movements are multidimensional, and the separation of these dimensions can clarify shifts i n the relative constraints as well as flexibilities that occur during development (cf. Prechtl, 1986, and Woiff, 1987, for discussion of human infants. 3) During ontogeny there can be both progresslve transitions and reversals. For the infant mice the three periods were marked both by improved coordination of individual limb segments and by transitions from i ) rich and loose, i i ) t o restricted t o iii) re-elaborated combinations of movement. Three additional comments deserve mentlon. 1) The animal's overall behavioral state can affect movement production throughout ontogeny. I n our Infant mice we could illustrate this by plnching their tails lightly after piaclng them Into a movement posture; when thus "activated" the young mice would utilize their body postures t o Initiate grooming (Fentress, 1972, 1984, 1988). 2) Phase transitions in ontogeny can appear either gradual or sudden, but t h i s too must be evaluated i n terms of behavioral state as well as motor capacity. Thus, when the young mice appeared fatigued they often reverted t o earlier styles of grooming; conversely, when activated (such as through injections of amphetamine, unpublished; David Ellam, personal communication) the animals may exhibit coordinated profiles of movement that are normally only seen hours o r even days later in ontogeny. This last point brings with it the necessity t o think about factors such as "arousal" as having potentially bimodal consequences on behavioral performance. A t moderate levels, performance can be facilitated, whereas at higher levels performance may be retarded or revert t o an

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ontogenetically earlier profile of expression (Fentress, 1968a, b; Eilam & Golani, 1988). 3) More or less independently of these last consideratlons, we have also found that young animals often go through short-term r u n s o r "habits" i n performance that may switch quite suddenly t o other short-term runs. The impression that one gains is that certain expressive circuits dominate f o r a period, then relinquish the stage t o other circuits, perhaps t o r e t u r n again at another time. The combination of these observations provide a stern warning against any attempts t o construct unitary models of motor o r other forms o f behavioral ontogeny, at least in their expressive aspects at the intact organism level (cf. Wolff, 1987). One wants, of course, t o detaii not only the expressive profiles of motor and other behavior during ontogeny, but t o relate these profiles t o the organism's biological capacities. Here it is important t o remember that evolution operates throughout ontogeny, and has molded the organism's capacities accordingly. Early appreciation of this perspective was captured by the Russian physiologist, Anokhin (1964) in his concept of systemgenesis Anokhin argued that at each phase of behavioral development animals and human infants must perform certain integrated actions with considerable skill. Indeed, processes of differentiation and integration co-exist in complex patterns, and it i s an error to presume that either follows unidirectionally from the other (see Fentress & McLeod, 1986, 1988 for more detailed reviews). The organization of human nursing behavior is an excellent example of behavior that must achieve a high degree of coordination from the moment o f birth, as shown i n the elegant studies by Wolff and his colleagues (Wolff, 1987). Two critical factors i n this research are a) the systematic documentation of behavioral states, and b) the dissection of infant movements as "our only source of information about what infants perceive, do, feel, o r think" (p. 15). Woiff and his colleagues have also stressed the "inherently nonlinear" nature o f organizational systems i n infant behavior, such "that physically identical stimuli may produce very different motor outputs i n different behavioral states, and that spontaneous motor patterns are asymmetrically distrlbuted across the various states" p. 21). Even when discriminating variables are continuous the patterns among them are often characterized by discontinuous (distinctive) behavioral events (cf. Fentress, 1976, Kelso & Schoner, 1988; Kugler & Turvey, 1987; Theien et al., 1987). Spontaneous infant sucking movements are organized into bouts (repeated bursts) and pauses. This i s a pattern that is similar t o the spontaneous mouthing movements seen i n sleep, thus suggesting common mechanisms i n each. I n contrast, nutritive sucking, when the infant i n hungry, involves a continuous stream of sucks at approximately half the mean frequency seen i n nonnutritive sucking (Wolff, 1972). Thus, patterns of nutritive and nonnutritive sucking, although superficially similar (e.g. term "sucking" applied t o each), their details of organization and presumably control differ. This provides a human analogue to superficially similar patterns of grooming found by Berridge, Fentress & Parr (1987), dlscussed earlier, that have different fine-grained structure, contexts of expression, and mechanisms o f control. Mammalian nursing behavior also raises other interesting questions with respect t o developmental continuities and discontinuities. For example, Hail and his colleagues (reviewed i n Hall and Williams, 1983) have shown that suckling and subsequent feeding behavior I n rats are not only different i n form, but also are mediated by separate (neural) mechanisms. As illustration, early suckling i s dominatedd by exteroceptlve stimuli rather than either nutritional state or nutritive consequences. I n addition, their experiments have demonstrated that another ingestive sytem does occur concurrently with infant suckling, and that

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it is this other, normally hidden, system that may be the t r u e precursor of subsequent feeding. Actions that appear developmentally dlscontlnuous on the surface may also represent common control systems, as illustrated by Thelen and her co-workers on human infant kicking and stepping movements (e.g. Thelen, 1986), and by Bekoff (e.9. Bekoff, 1988) on continuities between hatching and locomotor circuits i n chicks. The movements I have emphasized thus f a r are t o a large extent "selfreferring" movements that do not involve complex tracking with reference t o a mobile environment. Clearly both animals and humans must often deal with these more complex tracking situations. Animals In social contexts and predator-prey relations are two obvious cases. Here we see multiple rules of constraint that must include coordination (e.g. relative tlming) between individuals. Tracking of mobile targets i s also a major component of many skilled actions that do not involve another living creature. Here the studies by von Hofsten (1984) on infant catching movements are exemplary. These timing skills involve not only reaction but also antlcipatlon of f u t u r e object positions. I n our studies of wolf social movements that I referred t o only briefly (e.g. Havkin & Fentress, 1985; McLeod, 19871, we have similarly been concerned with the anticipatory as well as reactive timing propertles that exist between animals. An especially important task is t o relate changes of coordination within the individual t o changed patterns of coordination defined across individuals, as their developmental trajectories In time may be quite distinct. For the purposes of the present chapter I have maintained my primary focus on individually coordinated actions, for these offer an important window into the ontogeny of events that are likely t o provide important "building blocks" f o r more complex situations. I n saying t h i s Imust also emphaslze that higher-order constraints In forms of motor timing are unlikely t o be simply "composed" of additions among simpler events, b u t t o have properties that must be studied explicitly i n their own terms. Recent studies by Fagard (1987) and McDonnelI et al. (1989) of bimanual coordination of children during reading tasks are Illustrative of important new perspectives that are afforded when separable and combined movement properties are evaluated together. (See also other chapters In this volume). As Indicated i n brief terms earlier, socially combined movements take these same considerations t o a still broader level. What Is most Important is how careful developmental dissections can be related t o ways we conceptualize and analyze organizational processes that are necessarily nested across levels

DE VE LOPMENT A L MACHINERY Wolff (1987) has argued that, "patterns we recognise as motor types are not ontological entities with prescribed adaptive functions, b u t 'emergent properties' resulting from the interaction of different combinations of neuromotor units, and inducing novel ensembles with greater or lesser Internal cohesion or 'self equilibrating' tendencies" (p. 69). He stresses, correctly, that such patterns must emerge from "spontaneous" events within the organism, even though the organism (and its parts) are also sensitive t o extrinsic factors. Selforganization with Interaction - [as differentiation with integration, or local with global, central with peripheral, higher with lower, progressive with regressive, etc.] - represent essential polarities of behavioral ontogeny that we have identify and seek to understand. As many chapters in the volume attest, simple dichotomies do not work; we need more subtle perspectives. Let us take a look at some elementary facts. First, development can be viewed (and often is viewed) as the product of a delicate timing of gene

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expression (Davidson, 1986). Secondly, this timing involves what Ede (1978) has labeled the "sociology of cells", where neighboring cellular events build and restrict their lines of communication i n complex temporally as well as spatially distributed patterns (cf. Constantine-Paton e t al., 1989; Cowan, 1978). Thirdly, and related, both motor performance and i t s developmental precursors involve "population codes" that transcend single cellular events (e.9. Edelman, 1987; Georgopoulos, 1986). Fourthly, the subtle relations among interactive and selforganizing [: "ISO'1 events i n ontogeny indicate that the consequences o f developmental experiences are not simple "mirrors" of extrinsic factors. The less than clear distinction between selective and instructive mechanisms i n development (e.g. Fentress, 1990a, in press) i s iliustrative. Finally, circuits i n movement as well as i t s development are likely t o be polymodal (Getting & Dekin, 1985) and multifunctional (Bekoff, 1988), with the implication that even questions of continuities versus discontinuities among events w i l l have answers that are taxon dependent (Fentress, 1990b,c). Interactive and self-organizing processes in development are in each of these cases are both relative and dynamically ordered. This view offers pessimism t o those who seek "magic bullets" i n development as unitary explanations for the ontogeny of motor expression. Events may connect that we initially viewed t o be separate, and separate along dimensions that we initially viewed as spread across a seamless continuum. Events may be stable i n certain domains, and then exhibit marked instabilities i n other domains. These two basic polarities, discontinuity-continuity and stability-change, can play against one another as well, and must be viewed together. For example, how discontinuous is the distinction between stability and change, or how stable is the distinction between continuity and discontinuity? Each is both level and time frame dependent, with the added caveat that qualitative (as well as quantitative) distinctions are likely t o crop up at every turn. The growing link between behavioral and embryological thought i s an encouraging development (e.9. Greenough & Juraska, 1986; Oppenheim & Havercamp, 1986; Smotherman & Robinson, 1988). Questions of motor patterns i n development are being pursued f u r t h e r and further back in time. Future students of behavioral development who do not have a f i r m grounding i n embryology WIII seriously compromise their opportunities t o make significant contributions. Equally important, students of molecular and cellular mechanisms i n development who do not appreciate the facts of systems interactions, as exemplified by animal (and human) performance w i l l be compromised i n their ability t o speak meaningfully about organismally constrained events. Most encouraging i s the increased appreciation among researchers with different specializations t o recognize their mutual dependence upon one another. Future biological, and behavioral, research must be t r u l y bi-directional if it is t o succeed. I n t h i s context, the comparatively "simple" models provided by animal and neurobiological research can offer important bridges, as long as these models are not viewed to be substitutes for phenomena of intact organism behavior in our own species. Neither simple-minded reductionism nor simpleminded comparativism w i l l work. TOWARDS A SYNTHESIS AND PROJECTION Both integrative events and their developmental substrates are embedded i n time. Each also represents dynamic patterns that are synthesized among often widely distributed events. Each can be best understood through Dynamic

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Network Analyses ( "DNA"!) that seek explicit rules of interaction and selforganization ( " I S 0 models") among component properties and their various higher-order configurations, i n space and in time (Fentress, 1990a, i n press). The very boundary between integrative and developmental processes is imperfect. This i s because integrative systems, as developmental events, form and devolve. Neither unitary not static models are appropriate. For integrative processes the time frames happen, as a rule, to be rather shorter, and reversals are the expectation. But critical developmental changes can also occupy short as well as protracted time frames, and reversals as well as straight line trajectories are commonly observed. I n neither case have we attained the necessary conceptual tools t o know what it means t o say that systems are both independent and interactive. To think more clearly about t h i s essential paradox of biological organization is perhaps are most critical theoretical challenge. The joining of time frames i s a related challenge. Analogies t o mechanistic models i n physics have provided, and w i l l continue t o provide, a useful f i r s t approximatlon f o r many problems. It is a fact, however, that these models tend t o treat "mechanisms" as isolated entities that can be added together as an exercise in linear summation. Once we consider interdependencies, as weii as interactions, the potential limitations of such models begin to appear. There is, I believe, the counter danger that what we might call "seamless" models w l i l be offered In their place, but these are equally inadequate. There are "seams" (boundaries), i n space and i n time, that also form the very foundations of what we call organization (including organization across layers of complexity). The problem is that the seams can be relative and dynamically ordered; that their processes can be mutually molding as these processes interpenetrate one another t o varying degrees and with varying consequences; that brain, behavioral and developmental events emerge from collectives rather than as preformed packets. The explicit quest for rules of pattern, and the formation of pattern, offers our strongest analytical tool. It is no longer sufflcient t o say that events occur i n greater or lesser amounts; it is critlcal t o state how these changes are embedded amongst others. Timing i n behavior, as i n development, i s one critical expression of such patterns. Too often i n the past the analysis of behavior has been smudged into simple statistical statements that parts of the world are not the same, or that they affect one another. Such analyses simply help define the problems; they do not i n any way resolve them. Questions of relative invariances and foci of variation i n motor performance, posed both by the editors and many authors of this volume, offer tractable foci for f u t u r e empirical inquiry into the dynamics of pattern in performance and development. The very recognition that invariances can be, and often are, relational within each of these domains is a major step. I n the physical sciences issues of time, dynamic patterns, and even chaos (e.g. Gleick, 1987; Hawking, 1988) are challenging previous simple "piecesrelations" models of order in the universe. Some of these models are now being extrapolated t o brain functions, where "Statistical, collective behavior" is the primary focus (e.g. Little, 1990). Development offers a both a tool and a renewed challenge to think about such things. While it is clear that our present models are not very satisfactory it is not, but definition, clear where future solutions w i l l lie. The dissection o f biological and behavioral time, from multiple perspectives, may help add clarity t o present mysteries while opening f u r t h e r mysteries that we have j u s t begun t o contemplate. Perhaps the most valuable metaphor of developing motor systems Is one of circles within circles. For each system there is a coherent core of shared

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operations, surrounded by a protective ring of insulation from potential sources of interferences. Both the core and i t s surround can change i n time. Separations across different cores and different rings are imperfect; there can be variable degrees of overlap and mutual influence. From these partially separate and partially overlapping rings (or, t o be three dlmensional, "spheres of influence") a functionally integrated organism can and does somehow emerge. The geometry is not simple. Forms and patterns grow, melt, divide, and combine. Movement and growth provide the time domains f o r the proceses that reflect and give force t o these dynamics. This i s not an easy picture t o contemplate. Timing, temporal organization, and development provide three perspectives, surveyed through the rich chapters of t h i s volume, that may give more coherent perspectives i n the future. Images o f circles within circles can, through f u t u r e research, be related, conceptually and analytically, i n a more precise way t o integrative and developmental models of organization i n "simpler" systems. Processes of "surround" o r "lateral" inhibition are gaining empirical support not only i n sensory systems, but also i n motor systems (e.g. Fetz, 1984; Fromm, 1987) and as developmental models f o r biological pattern (e.g. Gierer, 1988; Meinhardt, 1982). It is important, of course, t o remember that different levels o f organization w i l l differ i n appropriate details of explanation. Not only are organism level processes likely t o Include global as well as local events (e.g. Edelman et al., 1990; Purves, 19881, but they are also likely t o include widely distributed networks that have emergent operations as a collective. Nonetheless, i n each case the "center-surround" models remind us t o be sensitive t o boundarystates i n motor performance and I t s development. By definition, a boundarystate has borders that are relationally defined and dynamically ordered (Fentress, 1986, 1990a, in press). Additional issues that remain t o be addressed in future research contain several interconnected parts. The f i r s t is what we expect extrinslc factors to da State models make It clear that they do not simply "instruct" an inert system. Through self-organization, systems may both "respond and do their own thing". The next issue is t o specify when external events accentuate (facilitate) ongoing states and when they respecify these states. A tentative hypothesis i s that the switch between accentuatlon and respecification is i n part threshold dependent (respecification belng higher threshold than Is accentuation; Fentress, 1990a, i n press; Fentress & McLeod, 1988). The final Issue concerns rules b y which experiences are generalized within the performing and developing organism: Here o u r current models may reflect limitations imposed by expectations from imperfect taxonomies. Only through further detailed studies of pattern, as exempllfied by other chapters i n this volume, w i l l such rules o f organizational convergence and divergence become clarified. ACKNOWLEDGEMENTS

I thank Jacqueline Fagard and Peter Wolff f o r their invitation t o contribute t o this volume. Research reported here was supported i n p a r t by the Medical Research Council of Canada and by operating and infrastructure grants from the Natural Sciences and Engineering Research Council. Wanda Danilchuk, once again, provided enormous help i n the preparation of this manuscript, from tracking down references, through proofreading drafts, t o the final stages of typing (except f o r t h i s sentence!}.

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Fentress, J.C. (1990~). Animal and human models of coordination development. I n Development of Eye-Hand Coordination Across the Lifespan, C. Bard, M. Fleury, & L. Hay (Eds.), (pp. 3-25). university of South Carolina Press. Fentress, J.C. (in press). Analytical ethology and synthetic neuroscience. I n The Development and Integration of Behaviour, P.P.G. Bateson (Ed.), (pp. 77120). Cambridge: Cam bridge Universit y Press. Fentress, J.C., & McLeod, P.J. (1986). Motor patterns i n development. I n E.M. Blass (Ed.), Handbook of Behavioral Neurobiology: Developmental Processes in Psychobiology and Neurobiology (pp. 35-97). New York: Plenum Press. Fentress, J.C., & McLeod, P.J. (1988). Pattern construction in behavior. I n W.P. Smotherman & S.R. Robinson (Eds.), Behavior of the Fetus (pp. 63-76). Caldwell, N.J.: Teiford Press. Fentress, J.C., & Stilweli, F.P. (1973). Grammar of a movement sequence i n inbred mice. Nature, 244, 52-53. Fetz, E.E. (1984). Functional organization of motor and sensory cortex: Symmetries and parallels. I n G.M. Edelman, W.E. Gall & W.M. Cowan (Eds.), Dynamic Aspects of Neocortical Function (pp. 453-473). New York: John Wiley & Sons. Fromm, C. (1987). Sensorimotor integration: The role of pyramidal t r a c t neurons. I n H. Heuer & A.F. Sanders (Eds.), Perspectives on Perception and Action (pp. 13-168). Hillsdale, NJ: Lawrence Eribaum Associates. Georgopoulos, A.P. (1986). On reaching. Annual Review of Neuroscience, 9, 147-

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254. Havkin, G.Z. & Fentress, J.C. (1985). The form of combative strategy In interactions among wolf pups (Canis lupus). Zeitshrift fur Tierpsychologie, 68, 117-200. Hawking, S.W. (1988). A Brief History of Time. New York: Bantam Books. Heiligenberg, W. (1976). A probabilistic approach t o the motivation of behavior. I n J.C. Fentress (Ed.), Simpler Networks and Behavior (pp. 301-313). Sunderland, MA: Slnauer Associates. Hinde, R.A. (1970). Animal Behavior: A Synthesis of Ethology and Comparative Psychology (2nd ed.). New York: McGraw-Hill. Hinde, R.A. (1982). Ethology: I t s Nature and Relations With Other Sciences Oxford/New York: Oxford University Press.

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AUTHOR INDEX

Abraham, R.H Accardo, P.J. Adams, J.A. Allen, G.D. Als, H. Ames, L. Amiel-Tison, C. Anderson, W.G. A n d e r s o n , 0. Andrews, M.S. Andriacchi, T.P. Anokhin, P.K. Arbib, M.A. Armstrong, T.R. Arnold, V.I. Aronson, E. Arshavsky, Yu.1. Arvikar, R.J. Ashmead, D.H. Asmussen, E. Astrand, P.O. Attneave. F.

77,83,22 1,247,331,343 153.155.168 177;262 135,136 169 227,3 13 167,168 24. 95’ 167 234 120,357 178-180,342,344 38,39,47,53 83 27 1 95-97,105,106,111,112 246 188,314 273 274 345,346

Baba, D.M. Bai, D.L. Baillargeon,R. Baken, R. Bakow, H.S. Balaban, M. Baldissera, F. Baltaxe, C. Bampton, S. Bancaud, J. Barbin, Y. Barnes, D.M. Barnes, H.J. Barraud, E.M. Barrier, G. Bartlett, N.R. Bartlett, S.C. Barto, A.G. Bateson, P.P.G. Bauer, H.R. Bauer, R.

283,308 27 1 187.312 138’ 169 120,128 73 136 42 3 14 317 86 183 143 168 5,308 5 201 347,349 139 85

368

Bauers, K.A. Bayley, N. Beck, R. Beek, P.J. Beggs, W.D.A. Beintema, D. Bekoff, A. Beloozerova, I.N. Benjamin, P.R. Benson, J.B. Berkinblit, M.B. Bernard, J. Bernstein, N. Berrian, R.W. Berridge, K.C. Bertenthal, B.I. Beverle , K.I. Biden, 8.N. Bierman-van-Eendenberg, M.E.C. Biguer, B. Binet, A. Bingham, G.P. Birmin ham, H.P. Bir n h o h , J .C. Bizzi, E. Blass, E. Blickhan, R. Bloom, K. Blurton-Jones, N. Bobath, B. Bobath, K. Bohm, J. Bohrer, R.E. Bosma, J.F. Bourbonnais, D. Bowden, J.M. Bower, T.G.R. Bradley, N.S. Bradshaw, G. Braendle, K. Bramble, D.M. Brazelton, T.B. Breni*re, Y. Bresson, F. Brestler, B. Brian, C.R. Bridger, W.H. Bril, B. Brinkman, C. Brodin, L. Brosch, M. Broughton, J . Brown, J.V. Brown, T.G.

Author Znder

137 169,263 234 82,342 42 166 356,358,359 96,111 103 207 95.112 269 24,177,188,207,2 14,246,283,306,311,355 24 346-348,352,353,357 27 1 49 249 166 183 9,70 2 14,2 15,205 50 181.268 186;187 155 334 136 126 158 158 120,213 144.270 123; 130,138 176 42 153.158.184.312 356' 293,204 120 82 156,168,169 208.233.234.236-24 I 313 246 263 181 208,233,234,236-24 1 3 14 102,103 85 153,184 126 246

Author I&

369

Brown-Sweeney, S. Brucek, W. Bruner, J.S. Bryan, W.L. Buchanan, J.T. Bullin er, A. Bulloc!, D. Bunz, H. Burke, P.M. Burton, A.W. Bushnell, E. Butterworth, B. Butterworth, G.E. Byrd, K.E.

139 168 123,125,184,272,315 16,70 73,102,103 185 51 3 2 72,74,82,83 124 265,267,271 153,155,184,185,188,314 16 181,189,271 144

Campadelli, P. Campos, J.J. Canli, T. Capute, A.J. Carello Carnahan, H. Carrier, D.R. Carter, M.C. Castle, P. Cavallari, P. Cenzato, M. Cervantes-Perez. F. Chao, E.Y. Chaffin, D.B. Chandler. L.S. Changeux, J.P. Cheun M.N. Chomsfy, N. Christenson, J. Churchland, P. Civaschi, P. Clark, J.E. Clarke, L.C. Clarkson, B.H. Clifton, R. Cline, H.T. Clynes, M. Cobb,K. Cochran, W.D. Cohen, A. Cohen, A.H. Cohen, C. Cohen, H.J. Cohen, L. Collard, R.F.A. Condon, W.S. Connolly, K.J. Constantine-Paton, M. Conway. E.

54 189 18 1 153,155,167 266,267 2 73 48,59,48,59 82 18,38,44,58 184,313,314 73 11-13 178 246 265 167 86 144 82 103 217.344 I

77

IJ

208,23 1,232,239,242,245,249,250 253 231.236 154;312 359 323 312 127 353 93,25 1 3 15 161 73,308 5,50

135 175,176,182,187,262,263 359 2

310

Cooke, D.W. Cooper, L. Corbetta, D. Corcos, D.M. Corkum, V. Corner, M.A. Coryell, J.F. Courtier, J. Cowan, W.M. Crain, S.M. Creelman, C.D. Cronbach, L.J. Crooke, C.K. Cross, E.E. Crossman, E.R.F.W Cruse, H. Cr u t chf ie Id, J .P. Dale, N. Darian-Smith, I. Davidson, E.H. Davies, P. Davis, W.E. Davis, W.W. Dean, J. De Boysson-Bardies, B. Debski. E.A. DeGuzman, G.C. Dehaene, S. Dekin, M.S. Del Colle, J.D. Delcomyn, F. Delia ina, T.G. Derr,%.A. Derwort, A. Deutsch, D. De Vries, J.I.P. Diamond, A. Diestel, J.D. DiFranco, D. Dkjerkar, Do, M.C. Dodd, B.J. D’Odorico, L. Dodwell, P. Dowd, M. Draper, D. Drasgow, F. Dreier, T. Drew, T. Dubowitz, L. Dubowitz, V. Dubuc, R. Dugas, C.

Author h u h

266 239,246 208,307 5,283 152.156.313.358 120’ 184,185,189 9.70 353,359,361 120 6 263 123,124,128 127 265 50,s

250 44,45 175,176 349,359 119 267 281,282 50,55

135 359 82,83,85 86 353,359 341,353 37,136 39,4 1,49,50,56 50 53 5,85,309 268 3 14-316 19,38,42,70,231,232,239,242 153 268 237,238 140 137,140 153,184 312 157 144 127 95 167 167 103 42

Author Index

Durand, C. Duysens, J.

135 95

Easton, T.A. Eckert, H. Eckhorn, R. Ede, D.A. Edelrnan, G.M. Eickrneier, B. Eilam, D. Eisenberg, J.F. Ekeberg. 0. Elbers, 1. Elftman, H. Elliot, C.J.H. Elliott. J.M. Ellis, M.J. Engel, A.K. Eschallier, J.F. Eshkol, N. Essens, P.J. Euler, C. von Ewan, W.G.

128,151,152 323 85 359 82,144,203,206,342,359,361 42 350 126 103 139 246 103 175,176,182,187 270 83,85 183 355 6 111 144,146

Fagard, J. Fa ioli, I. Fa Igatter, A. Faria, M. Farmer, J.D. Farnsworth, P.R. Feldrnan, A.G. Fenson, L. Fentress, J.C. Ferber, R. Ferguson, G.P. Ferrnier. R.W. Feroe, .I: Fetz, E.E. Finlev. F.R. F i o r e h n o , M.R. Fisher, C. Fisher, D. Fisher, 0. Fisk, J.D. Fitch, J . Fitts, P.M. Flarnent, F. Flandres, M.J. Flash, T. Fogel, A. Fontaine, R. Forssberg, H. Foulke, J.A. Fowler, C.

70,189,310,315-317,358 126 269 268 250 281 95,112,205,216,226 189 119,137,158,175,341-361 341.343,346 103 234 5 36 1 38 168 20 1 158,204 246 42 333 70,264,265,307 313,315 113 16,55 152,155,202,204 233.237.208

f

265 135

37 1

Author Znder

312

Fox, J.G. Fraisse, P. Francis, P.L. Franco, D. Franco, F. Frank, A.A. Frank, J.S. Frankel, J.P. Freeman, F.N. Fromm, C. Frysinger, R.C.

25 6,85 169 184 137,140 283 39,41,3 10 246 9,70 36 1 176

Galante, J.O. Gall. W.E. Gallenstein, J.S. Gallistel, C.R. Garcia-Colera, A. Garcia-Rill, E. Garfinkel, A. Garthwaite, C.R. Gay, T. Gear, R.J. Gee, J.P. Geffen, G. Gelfand, I.M. 8 Genest, M. Gentner, D.R. Geor opoulos, A.P Gesefi, A Ge tc he 1L.N. Getting, P.A. dS. Gibson, J.J. Gidoni, E. r OE-IPE,Z Gielen, S.C.A.M. Gierer, A. Gilbert, G. Glass, L. Gleick, J. Golani, I. Goldenber D. Goldberg, Goldfield, E:C. Goodale, M.A. Goodenou h, F.L. Goodeve, b.J. Goodman, D. Goodwin, A.W. Goodwin, B.C. Goodwin, G.M. Goodwin, R. Goto, Y. Gottfried, A.W. Gottlieb, G. Goudie, E.B.

234 353,361 167,168 3 4 95 249 144 144.146 23 11234 135 315 95.112 25'

2,18-21,23,37,42,43,45,50,70,239

b

pL

353,359 227,265,313 323,333-335 11.353.359 179,266,27 1,333 157 4,42,45 36 1 128,129 85,119,120,122,127 335,360 350,35 1,354,355 181 314 188,219,222-224,226,227,313,3 14 42 263 ,-284,288,293,307,308, 316

Author Index

Gramsber en, A. Grand, T . f Gray, C.M. Green, D.M. Greeno, J.G. Greenou h W.T. Gregor, Grieve, D.W. Grillner, S.

137 274 83,85 6 5 359 19.38.42.70.23 1.232.239.242 231,234 4,83,93,95,102,103,111-113,120,144, 203.247 135’ 51,52 2 306 315

f.;.

I

Grosjean, F. Grossberg, S. Grudin, J. J. Guiard, Y. Gunnoe, C. Haken, H. Hall, W.G. Halton, A. Halverson, H.M. Halverson, L.E. Hambuch, R. Hamburger, V. Hannan, T.E. Hansen, J. Hardiman, S. Harkins, D.A. Harris, K.S. Harryman, S. Harter, N. Hartz, R.H. Haubenstricker, J. Havercamp, L. Havkin, G.Z. Hawking, S.W. Hawkins, B. Hawkins, S.R. Heath, R.A. Heeboll-Nielsen,K. Heiligenberg, W. Held, R. Hellber S. Henry, f M . Herman, R. Heuer, H. Hertz. R.H. Hicks; L. Hill. M.D. Hinde, R.A. Hinzel, H.G. Hoagland, H. Hodge, M.M. Hoequist, C.E.

313

’

,

.

I

I

7 1,72,74,82,83,247 143,357 153,184 124,187 233,242,323-325,333-335 3,6,46 120,128 152.155 23 1 187 185,188,189 119,121 168 16 268 262 359 35 1,357 360 39,4 1,310 60 7 273 344 184,313,314 23 1 3.14 42,95 18,39,41,43-45,48,50,51,53,55-59,70, 233.3 11 268 27 1 282 342,345,350 111 6

138,139,141,144 135

Author Index

314

Hoffmeyer, L. Hofsten, C. von Ho an,N. Hoffelt, T. Hollerbach, J.M. Holmes, P.J. Holroyd, T. Holst, E. Holst, E. von Holt, K.G. Homburg, R. Hopkins, B. Hopkins, G.W. Horii, Y. Horowitz, F.D. Houk, J.C. Howarth, C.1. Hoyt, D.F. Hubley, P. Hughes, S.C. Huisjes, H.H. Hulsti'n, W. Hump rey, D.E. Humphrey, G.K. Humphre ,T. Hunt, J.dcV. Hutt, S.J. H uxley ,

155 153,155,183-186,188,313,358 15,16,55 103 8,177 25 1 83.85 93' 49,82,85,121,342 82,176,311 269 189 5,6 140 161,168,169 20 1 41 71 185 168 166 2 3 13,314 313.314 152. 175 263 273

Ibbotson, N.R. Inoue, S.A. Insler, V. Ivry, R.

309 349 269 5,323,331,353

Jacquet, A.Y. Jackson, H.J. Jagacinski, R.J. Jansen, E.C. Janssen, B. Jeannerod, M. Jeeves, M.A. Jefferson, R.J. Jeka, J.J. Jenkins, J.J. Jennings, L.S. Jensen, J.L. Jiang, W.Y. Johansson, R.S. Jones, J.G. Jones, M.R. Jones, R.G. Jordan, L.M. Jordan, M.I. Jordan. W.

189,315 128,129 6,46,282,309 23 1 189 24,70,310,183,187,201 3 17 231.236

h

81 55 204,205,208 72,247 180 ~ _ . 242 6,46,282,309 25 95 176,180,191 85

Author Inder

375

Jorgensen, M.J. Jouen, F. Juraska, J.M. Jurgens-van der Zee, A.D.

183 185 359 166

Kahn, J.A. Kalveram, K.Th. Kamm, K. Kandel, E.R. Kaplan, B. Kasicki, S. Kawato, M. Kay, B. Kaye, K. Keele, S.W. Kelso, J.A.S.

102 39 208.225 110 127 103 15,55,73,77,282,308 74,221 169 3,5,18,50,52,53,177,323,331,353 8,9,27,37,5 1,52,70-74,76-78,80-83,85 86,119,120,121,176,178,180,188,202,204 -206,214,215,217,218,221,232,247,253, 266,282,283,288,293,307,308,311,312, 316,333,341,351,353,357 50 19,137-139,141,144,145,349 262,263 144 231,236 6,24,46,282,309 19,141 168 152,169 6,24 152,157-159 183. 327 83.85 189 24 23 1.236 169’ 119,181,213 5,6,45,46 143 85 112 95,113 9,70,82,119,121,176,178,191,205,206, 214.2 16-222.226.232.247.266.272.274. , , 293131 1,333,’341:343[353;357’ 82 246 234 207 183

Kenny, S.B. Kent, R.D. Keogh, J.F. Keren, G. Kirtley, C. Klapp, S.T. Klatt, D.H. Kliewer, D. Knobloch, H. Knoll, R.L. Kolb, S. Komilis, E. Konczak, J. Konig, P. Konishi, Y. Kornblum, S. Kory, R.C. Krafchuk, E.E. Kravitz, H. Kristofferson, A.B. Kruijt, J.P. Kruse, W. Kubota, K. Kudo, N. Kugler, P.N. Kulagin, A S . Kumamoto, M. Kuo, K.N. Kuperstein, M. Kuypers, H.G.J.M.

Author I&

376

Lacquaniti, F. Laissard, G. Lalonde, C. Lamarre, Y. Landsmeer, J.M.F. Lange, L A . Langendorfer, S. Langfield, H.S. Langley, D.J. Langlois, A. Langolf, G.D. Lansner, A. Laplane, D. Larson, C.R. Larsson, L.E. Lashley, K.S. Lecours, A.R. Lee, D.N. Lee, T.D. Leeuwenberg, E.L.J. Leikind, B.J. Lems, W. Leonard, E. Lester, B.M. Lestienne, F. LeveIt, W.J.M. Levinson, G. Lewontin, R.C. Lieberman, P. Lind, J. Lindblom, B. Linn, P. Liske, D. Litovsk R. Little, +.A. Llinas, R. Lock, A.J. Lockman, J.J. Loeb. G.E. Longuet-Higgins, H.C. Luce, R.D. Lund. J.P. Lundber , A . Luria, Luschei, E:S.

360 217,343 189 187,188,314 95 5 6 95,144 113 314 144

MacKenzie, C.L. Mackey, M.C. Mandell, A.J. Mannin , E . Marcha&,F. Marder, E. Marey, E.J.

42,283,306,308 85,119,120,122,127 71 154 183 111,349,353 246

AS

11,12 23 81 144 182 41 327 281,282 48,58-60 138 265 103 314 144 23 1 3,39,49,356 315 55,267,271 48,59 5 39 189 153,160 137,138,169 4

16,135 168 342 122 122,137,138 144 169 42

Author Index

Mar oliash, D. Marfer, P. Marshal, G.R. Marshall, R.N. Marshburn, E. Marteniuk, R.G. Martin, A.D. Martin, Z.E. Martin, R.E. Maury, L. McCabe, P.M. McCain, G. McClelland, McCollum, G. McDonald, P.V. McDonnell, P.M. McGhee, R.B. McGraw, M.G. M cLaughl i n, C. M. McLeod, P.J. McMahon, T.A. Mebert, C.J. Meinhardt, H. Meininger, V. Mellier, D. Meltzoff, A.N. Merz, F. Meserve, A. Metz, A.M. Meyer, D.E. Michel, G.F. Michelsson, K. Michon, J.A. Mikawa, H. Milani-Comparetti, A. Miller, R. Milne, A.B. Minifie, F.D. Mitchell, P.R. Monk, M. Monsell, S. Moon, D. Mooney, K. Moore, D. Moore, M. Moran, G. Morasso, P. Morioka, M. Morowitz, H.J. Morrongiello, B. Morton, J. Moulins, M. Mounoud, P. Muir, D.

377

349 137 274 55 6,46,309 42,283,306,308 274 282 145 313 144 263 191 11-13,70 187,222,312 152,153,155,156,184,186,3 13,358 283 152.227.265 267' 309,3 10,350,355-358,361 205,215,274 189 361 3 14 185 347 39 181 54 39,4 1 181,184,185,188,189,222,313,314 122 '

5

189 157 83 317 19 139,141 85 24,4 1 323 135 154 153,184 35 1 2 310,317 247 188 309 111 54,262 153,154,184

Murray, A. Murray, L. Murray, M.P. Mussa Ivaldi, F.A. Muybrid e E. Mysak, EfD.

137 185 231,236 2.186.187 246 152

Napier, J.R. Navon, D. Nelson, W.L. Newberr H. Newell, k M . Neyhus, A. Nice, M.M. Nickel, R.E. Nicolis, G. Niki, H. Niles, D. Nimmo-Smith, I. Norman, D.

182 59 55 269 187,222,264,266,284,313,327 181 143 167,168 7 1,247 112 82,205 54,70 18,70

Oatley, K. Oberg, P.A. O'Brien, M.J. Odenrick, P. Ohta, Y. Okamoto, T. Olinga, A-.A. Oller. D. Olshen, R.A. Oppenheim, R. W. Or ogozo, J.M Or ovsky, G.N. Ovrut, M.R.

122 23 1 119,121 23 1 103 207,246 166 138-141 239,246,249 128,359 314 95-97,105,106,111,112 189

Packard, N.H. Paillard, J. Palmer, F. Panchin, Yu,V. Papousek, H. Papousek, M. Parker, C.E. Parmelee, Parr, H. Pasamanick. B. Pascale-Leone, J. Pattee, H.H. Paulson, G. Pavlova, G.A. Pearson, K.G. Pearson, P.H. Peiper, A. Peitgen, H.O. Pelisson, D.

250 86,156,183,308 153.155 96,97,105,106,111,112 140 140 175 168 346-348,352,357 152,169 262 247 128 97,111,112 95.35 1.353 167 123,124,152,154,157 335 183,186,187

B

'

Author Index

Pellionisz, A. Pepper, C.E. Perret, C. Perris, E. Person, R.S. Peters, M. Pew, R.W. Phillips, C.G. PhilliDs. S.J. Piagei, j. Pieper, A. Pieraut-Le Bonniec, G. Pillarv. S. Pohl, P . Poincarrk, H. Pokorny, R.A. Popova, L.B. Porges, S.W. Porter, R. Posner, M.I. Poynter, W.F. Poulton, E.C. Povel, D. Prablanc, C Prechtl, H.R.F.

217 82 95,113 312 54 282,309,310 39,177 176

Preilowski, B.F.B. Prescott, R. Pri ogine, I. Pufi ter Gunne, F. Purves, D. Putnam, C.

268,23 1,232,239,242,245,249,250 152.179.184.265 , , 126’ 313 268 213 248 5 96 144 176 344.353 281’ 5335 5,6,50,85,309 183,186,187 119,120,121,128,137,153,157,161,166, 168.268.356 309:310:315 138. 71,119,247 4 345,361 70,188,284,293,307

Quinn, K. Quinn, J.T.

315 39,4 1,3 10

Rader, N. Ramsa D.S. Rand, 8 . H Randol h ‘M. Rapp, Reed, E.S. Regan, D. Reitboeck, H.J. Renken, C.A. Requin, J. Restle, F. Richards, T.W. Richter, P.H. Ricour, C. Ridley-Johnson, R. Riegels, V. Riesz, R.R. Rim, K.

184 189,223,313-315 25 1 154 119,120 127,224,266 49 85 167,168 4.24

F k

C J

269 335 126 158 38 145 246

379

380

Author Index

Roberton, M.A. Roberts, A. Roberts, B.L. Robertson, S.S. Robinson, S.R. Rocca, P. Rochat, P. Rodahl, K. Roennqvist, L. Rogers, D.E. Rose, S.A. Rosen, M.G. Rosen, R. Rosenbaum, D.A. Rosenblith, J.F. Rosenblum, L.D. Ross, A. Ross, W.D. Rossignol, S Roth, K. Rubenstein, J. Rubin, P. Ruff, H. Ruggiero, C. Rummelhart, D.E.

233.242.262.323-326,333-335 93,100-102 ’ 93,102 27 1 359 188 155312-314 274 188 3,50 181 268 247-249 39,50,183 170 9,2 16,274 153 274 93,95 41 168 82,3 11 153,184 2 18,70,191

Saelens, E. Sagart, L. Saint-Anne Dargassies, S. Saint Clair, K.L. Salamy, A. Salomon, F. Saltzman, E. Salzarulo, P. Sameroff, A. Sandlund, B. Sargent, G.I. Scherzer, A. Schmidt, R.A.

312 135 167 161 3 15 126 9,s 1,74,180,2 7,22 126 169 23 1 60 156 2,3,18,37,39,41,42,44,45,48,49,50,5358,70,121,123,177,178,262,264,266,310, 323 9,214,216,274 284 42 204,205,208 10,11,12,14 74.282 185,313 72,74,79,80,119,120,121,202,341,353, 357 121 187.3 12 308 308

Schmidt, R.C. Schmidt-Nielsen, K. Schmidtke, H. Schneider, K. Schneider, R. Scholz, J.P. Schonen, S. de Schoner, G.S. Schulte, F.J. Scully, D.M. Seashore, R.H. Seashore, S.H.

Author Index Seefeldt, V. Segal, E.M. Seireg, A. Sejnowski, T.J. Self, P. Selverston, A. I. Semjen, A. Sepic, S.B. Service, V. Shadmi, A. Shaffer, L.H. Shapiro, D.C. Shapiro, R. Shaw, C.D. Shaw, R.S. Sheppard, J.J. Sherrington, C.S. Sherwood, D.E. Shik, M.L. Shlesinger, M.S. Shnider, S. Shoner, G . Silver, P.H. Simon, H.A. Simmons, J. Simmons. M. Sjmpson,’D.C. Singer, W. Singh, S.P. Skala. K.D. Skinner, R.D. Slotla, J.D. Smith, A.M. Smith, B.L. Smith, J.E.K. Smith, J.L. Smoll, F. Smotherman, W.P. Soechting, J.F. Sollberger, A. Soffe, S.R. Sorokin, V.N. Sorokin, Y. Southard, D.L. Spearman, C. Stacy, M. Staicer, C.A. Stanley, W. Stansfield, R.G. Stanton, P.K. Stark, R. Stefani, S.J. Stehouwer, D.J.

38 1

262 263 246 85,344 161,168,169 93,111,120,343,353 4 23 1,236 189 269 8,16,19,25,85,309 18,19,38,41,42,44,56,58,70,231,232,239, 242 153,155 77,83,221,247,335,343 250 152 152,154,246 39 82,95 71 168 247,253,308,202 3 17 5 136 122 182 83,85 201 206,3 12,341,357 95 183 176 139-141 39,41 356 323 359 2,73,113 119 100,101 144,146 268 70,282,283,288,307,3 16 47 312,3 13 349 123,124 25 85 137,139,140 168 356

Author Z n d a

382

Stein, P.S.G. Sten ers, I. Step ens, J.C. Stern, J.D. Sternber S. Stewart, StilweII, F.P. Stoel-Gammon, C. Stoffregen, T.A. Strange, W. Stratton, P. Stratton, R. Stuart, D.G. Sufit, R.L. Su den,D.A. suhivan, J.W. Summers, J.J. Sutherland, D.H. Suzuki, J. Suzuki, R. Swain, I. Swanson, M.W. Swinnen, S.P. Szekely, G.

95 119 268 184 6,24 247 346-348.356 139 27 1 81 120,121 323 95.293 145 265 169 18,38,39,60 239,246,249 189 15,55,73,77,282,308 154 167 308,311 120

Taeusch, H.W. Taft, L.T. Talairach, J. Taylor, C.R. Taylor, F.V. Tenenbaum, F. Terzuolo, C.A.

122 161 314 71 50 187 2,11,12,19,20,23,25,38,42,43,54,70,73, 347 54,70 122 82,120,121,128,130,138,139,152,155,157 158,159,201,202,204,206,208,213,215 225,266,274,292,293,312,341,351,353, 356-358 137 25 323 54,70 216 215 268 262 166,167 103 5 168 184,185,188 169,312 122

a

h.~.

Theulin s, H.L. Thach, %.T. Thelen, E.

Theorell, K. Thomas, E.A.C. Thomas, J.R. Thomassen, A.J.W.M. Thompson, D. Thompson, J.M.T. Timor-Trisch, I. Todor, J. Touwen, B.C.L. Travkn, H. Treisman, M. Trembath, J. Trevarthen, C. Tronick, E. Truby, H.

Author I n d a Truly, T.L. Tscharnuter, 1. Tuller, B. Tunstall, M.J. Turvey, M.T. Twitchell. T. T ler, J.G. &rich, B.D. Umeda. N. Uno, Y: Uzgiris, I.C.

383

249.250 180’ 8,70,73,77,119,12 1,205,333,283,293 102 9.70.1 19.120.121.176.178.202.205.206. 214,216,221,226,247,266,267,271,273,’ 274,283,293,3 11,333,341,343,353,357 151.155.188 282. 82,201,202,204,205 141 15,55 175

Vorberg, D.

272 272 4 268 222 2,70 56 82 22 1 183 137.140 168 272 268 23 1 2,lO-13,19,20,23,25,38,42,43,54,60,70, 357 3,6,46

Wachmann, A. Wachtel, R. Wade, M.G. Walker, J. Wallace, S.A. Wallen, P. Walter, C.B. Walters, C.E. Wann, J.P. Ward, J.A. Warner, R.M. Warren, W.H. Wasz-Hoeckert, 0. Weber, S.L. Weeks, D.L. Weiss, M. Weiss, P.A. Weitz, P. Westling, G. Werker, J.F. Werner, H.

355 153,155 262-264,270,27 1 323 70,73,264 95,102,103 44,308,311 269 54,70,242 204,293 135 267 122 315 70 153,154,160 120 23 1 180 81 127

Valenti, S.S. Van Acker, R. Van den Oosten, K. Van Dongen, L.G.R. VanEmmerik, R.E. Van Galen, G.P. Van Rossum, J.H.A. Van Wierin en, P.C.W Vat ikiotos-hat eson,E. Vaughan, J. Vidotto, G. Vining, E.P.G. Vinter, A. Visser, G.H.A. Vittas, D. Viviani, P.

384

Author Index

w o o , S.L. Wood, G.A. Woodworth. R.S. Wri ht, C.E: WUII, G Wvatt. E.P. W i a t t ; M.P.

293 245.250 1841313,354 308 143 231,236 217 138 7 357 323,330 313 93 168 152,156,313,358 122 5,45,46,54,70,310,31I 201 242 42 342 119-122,124-129,137,129,137,138,202, 2 13,214,310,312,317,341,343-346,350, 353,355-358 239,246 55 28 1 24,39,41,191 48.57 24' 249

Yakolev, P.1. Yamada, T Yamanishi, J. Yates, F.E. Young, A.W. Young, D.S. Young, D.E.

315 95,113 73,77,282,308 71,119.247.274 189 55,267 2,4 1

Zadoc, I. Zangger, P. Zanone. P.G. Z e e , E. Zelaznik, H.N Zelazo. N. Zelazo; P. Zemke, R. Zernicke, R.F.

268 112,113 70,77,78,80,81,86 136 39.41.42.45.48.58-60.3 10 157-159,282 153,154,157-160,282

Wetzel, M.C. Whitall, J. White, B.L. White, C.T. Whiting, H.T.A. Whittle, M.W. Wicken, J.S. Wilder, C. Willcox, C.H. Williams, C.L. Williams, K. Willis, M.P. Wilson, D.M. Wilson, J. Wilson, L. Winfree, A. Wing, A.M. Winold, H. Winter, D.A. Wirta, R. Wise, S.P. Wolff, P.H.

Zeskind, P. Zlatin-Laufer, M. Zukofsky, P.

1 C?

I J I

19,38,42,70,204,205,208,231,232,239,

242 138 140,141 6

SUBJECT INDEX Action classes of 306,344,345,347,350 theory of 266 see also i n t e g r a t i o n , p e r c e p t i o n Activation theory 23-25,27 Adaptation 69,72,74-76,93,179,186,341 onto enetic 128,129, see a so v a r i a b i l i t y

f

Adjustment see m u t u a l Affordance 179

Arm flexion/extension 37,48,307,308 movements in infants 156,158,159,175,178,180-186,190,192,205 movements in children 286-293,302,317 see also b i l a t e r a l Articulatory movements 19,25,139-144 Assembly dynamic 204 soft 205,213,215,218,219,222,306 system (assembly) of neural and energetic components 204 Assimilation 179,184 Asymmetry lateral 185,222-226,309 of movements 306,307,3 10,3 14-316,318,354,356 of neuronal networks 95,107 postural 155,181,188,219,222,313 of Tonic Neck Reflex 155,181,185 Attractor 74-82,85,86,122,214,2 15,218,219,22 1,247,249,250,252-255,308,311 intrinsic 78,79,81, see also l i m i t c y c l e , s t a b l e Auditory perception 137,143,145 Babble 138,139,141,142

386

Subject Index

Behavioral rhythm 122,213,245 state 119,121,125-127,137,166,169,187,214,253,341-345,356,357 stream 345,353 taxonomy 353 test 16 1,168,169 see also c o n s t r a i n t s , f l u c t u a t i o n , r h y t h m i c , v a r i a b i l i t y Bilateral coordination of legs 204,206,207 coordination of arms 306,307,311,313,314,324,330 pattern 315,318,327,333,335 reaching 188,189,313,314 see also c o u p l i n g Bimanual see c o o r d i n a t i o n Biological model of development 349 see also c o n s t r a i n t s , rhythms Biomechanical characteristics 130 data 207 factor 144,145 variable 180,190,254 see also c o n s t r a i n t s , l o c o m o t i o n Breathing 121,122,126-128 see also p h a s e , r e s p i r a t i o n Central pattern generators 4,5,93-113,120,124,203,246,346,352,353 see also rhythms g e n e r a t o r -peripheral interaction 45,46,49,50,203,352 programming 4,5,7,16,18,20,93,113,120,204,308,310 see also i n v a r i a n c e Chewing 152 Co-activation 312 of leg flexors and extensors 204 Co-articulation 349 Co-contraction 201,207,208 Cognitive abilities 153,157,160,175,191,271 factors 130,140,176,178,182,190,264

Subject Inak

Collective 214 dynamics 82,247 states 71-73,79,86,215 variables 72-74,76,82,83,85,121,123,125,215,247,308,361 see also s t a b i l i t y of spatial or temporal parameters 11~0,44,70,71,82,112,121,122,124,126,137,138,253,29~

Constan

Constant-proportion test 43 Constraints 9,18,19,24,25,53,55,69,72,74,76,78,86,202,205,

207,214,218,224,227,239,247,252,254,263,266,27 1,283,284,292,305,307,30 9-312,314-318,343,346,348,350-359 behavioral 69 biological 16 biomechanical5,24,176,181,190,202 endogenous 53,60 environmental 70,72,76,78,81,176,119,181,119,201,202,227, 247,254,281,283 intrinsic 247,254,283,316 neural 181,191,202 peripheral 54 postural 175,181,185,188,190,3 12 spatial 53,60,307 symmetry 308,316,317 task 176,179,187,190,19 1,201,202,247,254 temporal 7,305,307-3 14,316,318 Contextual effects 1,16,23-28,207,352 Continuity/discontinuity 359 in relative timing 55,56,58 Control parameter see P a r a m e t e r Cooperation 80,85,86,121,124,202,306,314-316,318 see also interhemispheric Coordination bimanual75,83,188,189,305-310,312,318 continuous 251 eye-hand 182-186 hierarchical 24 intralimb 70,73,176,205,245,246,248,250,252-254 interlimb 69,70,72,73,95,102,182,189,204,245,246,248,281-

284,293,310,316,356 intersegmental 102 between cry and respiration 122,137,138 between honatory and articulatory events 142,143 see also i l a t e r a l , d i f f e r e n t i a t i o n , intersegmental, t e m p o r a l

1

388

Subject Index

Coordinative structures 176,180,214,2172 19,232,247,254,281,283,284,292,293,302,308,317 Couple 125,130,206,207,271,309,312-314,316,318,335 Couplin bifateral354 informational 335 interlimb 206,207,2 14,250-253,282-284,291-293,354 mechanical 335 (coupled) oscillators 82,83,85,250,334,335 perceptual-motor 271 phase 83,111,129,129 spatio-tem oral 9,10,53,54 temporal 78,318 decoupling 123,311 see also m u t u a l Crawling 105,207,219,222-224,226,227,283 Creeping 223,224,227 Crying 122,123,125,137,138,141 see also c o o r d i n a t i o n , c y c l e , s p o n t a n e o u s Cycle 2,4,5,7,8,10,11,15,19,74,83,96-102,105110,112,113,122,203,206,208,232,238 breathing 122,123,140 crying 138 ait 232,246 op 324,326,330 step 19,42,113,208,231,232,248,249,25 1-253 stroke 354 sucking 126 cyclic movement 248,27 1,326,333,354 cyclicity 144 see also l i m i t , o s c i l l a t o r s , p h a s e , rhythms, s t a b l e

a

Degrees of freedom 84,121,179,191,214,247,306,331 Differentiation of coordination 123,128,130,187,192 of hand roles 314,316 /integration 357,358 Dimensional descri tions 214,247,249,250,254 high imensional) system 247 low (dimensional) collective variables or ensembles 121,124,215,247,306

(is

Dissipative structure 71,283 Dual-tasks 307-309.31 1,316

Subject Index

389

Dynamic order 341,345,353,359-361 organization 126,205 properties 205,248 Dynamics 7 1,72,74-83,85,86,202-204,206-208,215,218,219,221,249,253,255,366 autonomous 20 1-203,206-208 intrinsic 69,76-81,86,120,122,124,126,208 natural 208 (dynamical) systems theory 1,9,27,69,71,72,74,76,79,82-86, 120,124,130,143,176,178-181,187,191,192,201-208,213,2 15,218220,226,232,246-249,253,254,266,270,272,274,28 1-284, 305,308,309,311,323,333,353

see also a c t i v a t i o n t h e o r y , c o l l e c t i v e Ecological approach 213,214,2 16,225,262,265,266,271-273,333,202 Emergent properties 120,123-125,129,201-204,247,266-272,359 Endogenous 120 see also c o n s t r a i n t s , r h y t h m s Environment 93,95,119,120,123,177-181,191,192,202,214,218,227, 245,247,254,266,267,270,272,283,284,341,342,349,353,355,356,359 see also c o n s t r a i n t s Equilibrium reaction 153-155,159,160 see also s t a t e Escapement 214,215,217,225 Feeding movements 95,104-108,110,111 Fetal motor activity 121,267-272 see also p r e n a t a l Finger movements 72-74,76,82,175,176,180- 183,187,188,191,282,283,314,3 16 see also t a p p i n g Flexibility 7 1,179,3 16,34 1,346,349,352-354,356 Flow of energy 202,214,216,218,226,247 see also n e u r a l Fluctuation of behavior 20,21,71,79,119,271,342 of hand preference 223 of relative hase 74 of state 12f126,343 spontaneous 21,23 Formant transition 141.143

Subject Index

390

Gait 7 1,82,23 1-235,237-239,242,245,246,266,283 see also c y c l e Generative structures 50-52,55, Grasping 15 1,155,175-177,179-183,187-189,20 ,312,3 5,316 Grooming 158,344,346-357 Hand -and-knees Dosture 207 movements82,113,152,180,183-189,192,207,281,285,288,306,311 preference 189,190,222-225,309,317 -to-mouth 155,157,180,181,183,184,186 use 175-178,180,182,183,189,222,224-226 writing 70,242 see also c o o r d i n a t i o n , d i f f e r e n t i a t i o n , f l u c t u a t i o n , m a n i p u l a t i o n Haptic flow field 206 tactile input 180,181,183,190,207 Hierarchical 6,23,24 see also c o o r d i n a t i o n Homothetic principle 23 Impulse-variability model 39,41,50 Information processing 180,181,183,184,186 - rocessing model 262,265,323,331,333 tgeory 345-347 see also c o u p l i n g , l i n k a g e Inhibition 152,158,311,315,341,344,345,353,359,360 cortical 129,153,156,157 mutual 97-103,107-112 "surround" or "lateral" 361 "postinhibitory rebound" 98,102,113 Innate 4,5,144,15 1,155,158,160,201,282 Integrated actions (or movement components) 183,344,347,349,350,352,357,359 see also d i f f e r e n t i a t i o n

Subject Index

Interaction between patterns or systems 123,126,127,152,160,179,202, 206,2 15,226,227,267,270,283,284,3 12,33 1,34 1,345,353,359,360 excitatory 110-112 neurone to neurone 95,102,109-112 see also c e n t r a l Interhemispheric cooperation 3 14,315 Interlimb see c o o r d i n a t i o n , c o u p l i n g , l i n k a g e Internal clock 1,s-9,11,12,27,28 see also p a c e m a k e r , t i m i n g Interneurone 93-113 Intersegmental see c o o r d i n a t i o n , r e f l e x Intralimb see c o o r d i n a t i o n Intrinsic motor syner 123 patterning oymovement 213 oscillation 207 perception-action loop 206 properties 4,9 properties of cell 107 regulation of time sequences 137,138 see also a t t r a c t o r , c o n s t r a i n t s , d y n a m i c Invariance 70-72,74,86,145,177,180,216,23 1-233,237-239,242,308, 310,318,327,335,361 absolute 342 absolute timing 238,33 1,349 central 43-46 1 relative 1,18,23,283,307 relative timing 37,38,39-49,60,69,70,178,232,233,242,281,342,361 see also t e m p o r a l Isochrony principle 12,13,15,16 Kicking 158,343-346 Language 16,17,24,135,136,138,139,142-145,269 Limit cycle 15,122,127,214,215,219,221,250,252,253 attractors 250 see also o s c i l l a t o r s , s t a b l e

391

Subject I&

392

Linkage interlimb 188,282,283 informational 206 neural and mechanical 202,214 segmental-prosodic 136 sequential 347 temporal 313 Locomotion 4,17,19,42,71,82,93-113,160,176,201,203,205,207,216,222,225227,245-255,266,274,352,354

biomechanical approach to 246,247 neural approach to 246,247 Manipulation 175,176,182,183,189-191,201,307,312,315 Mass-spring pendulum system 201,205,206,216-218,225,323,334 Maturation 141,265 (maturational) chan es 138,143,270,315,313 neural-(maturationaf) theory 128,176,265 neuromotor 153,156,158,201,356 Mentally handicapped children 270,271 Mora 135 Motor closed-loop theory 262 -continuity theory 152,153,155,159,160 control theory 2,3,7;11,176,177,181 generalized pro ram 3,37,39-60,232,311 -genre theory 1?1-153,155,158,160 program 1,3,4,9,10,17,15,17,18,23,24,27,28,37,178-180,183, 184,186,190,191,33 1,333,334 -schema theory 262 skill 262,264,265 Mutual adjustment 288,291 connection 96-97,107 coupling 335 de endence 341 iniuence 281-283,291,294,302,323,324,361 molding 344,345,353,361 see also i n h i b i t i o n Natural frequency 82,237 pattern 55,58,59,60 -physical erspective 202 see also Bynarnics

Subject Index

393

Neural or neuronal 85,86,93-96,97,100,109,112,113,120,121,128, 202,204,206,2 14,265,282,343,357 flow (field of otential) 216-219,222,226 "modulators" 949,353 soft-molded ener gating 215 the0 of group s g c t i o n 144,146 see a so a s s e m b l y , c o n s t r a i n t s , l i n k a g e , l o c o m o t i o n , m a t u r a t i o n , symmetry

7

Non-linearity 7,8,215 see also o s c i l l a t o r s Order parameter see P a r a m e t e r Oscillations, oscillators, oscillatory, 7,8,73,82,83,85,99,102, 103,107,110,112,119,122,201,204,207,216,218,219,221,237, 248,25 1,323,333-335 limit-cycle 221,250 non-linear 120-122,126,130 properties 103,110,282 state 104,110 timing 205 see also c o u p l i n g , i n t r i n s i c , rhythms, s t a b l e , t i m i n g Pacemaker 97,98,102 see also i n t e r n a l c l o c k Parameter control 2,13,123,125,215,218,219,222-224 order 121,207.2 15,216,2 18,219,247 see also t e m p o r a l Pattern see b i l a t e r a l , c e n t r a l , i n t e r a c t i o n , i n t r i n s i c , n a t u r a l , p e r i o d i c i t y , p r e f e r r e d , rhythms, s p a t i o - t e m p o r a l , s p o n t a n e o u s , st a b i 1 i t y , st a b 1e , t e m p o r a 1 Perception-action 179,183,192,203,206 see also i n t r i n s i c Perceptual-motor 69,78,85,208 see also c o u p l i n g Perceptual Schema 178,179 Periodicity in motor patterns 2,4,5,17,27,96,100,103,106,107,122124,126,127,129,130,137,138,140,214,216,217,219-221,250,251.270272,274,333,343

394

Subject Index

Phase 76,234,236-242 angle 250-253 breathin cycle 137,140,142,144 diagram $7-81 entrainment 250,251 -locking 8,85,122,127 -plane plots 221,222 portrait 249-252 relationship 54,82,94,248,251,253,284,308,3 11,312,324,326,335 relative 8,72-74,76-83,85 shift 93,113 space 126,127,218,221,222 support stance 112,231,234,236-242 transition 71-76,77,80-83,110,125,155,222-224,226,335,343,348,350,356 see also coupling, f l u c t u a t i o n , temporal Pointing 281-284,293,306,307 Posture 15 1- 160,166,176,182,185,186,204,207,215,225,271,305,355-357 reflexes 15 1,153-158,160 see also asymmetry, constraints, s tabili t y Preferred frequen 144,206 patterns?9,185,305 rate 13-12 rhythm 6,145 see also hand

183,187-190,192 Prehension 175-177,180Prenatal motor activity 154,155,181,182,206,267,269 Prereaching 153,155,184,312 Primitive reflexes 127,128,130,151-157,160,168,187 Proportional model 19-21,23 see also Scaling Rapid aimed movements 41,42,49,50 Reachin 95,113,153,155-158,175,177,179,182,183-190,207,208, 22!,224,225,306,310,312-3 14 see also bi l a ter al, hand Reflexes 151-173 intersegmental 154 segmental 154 suprasegmental 154 see also p r i m i t i v e , walking, pos tur e Repetitive movements 120,121,138,139,142,145,308

Subject Index

395

Respiration 93,95,111-113,138,140,157 see also c o o r d i n a t i o n , b r e a t h i n g Rhythms 3-5,7,8,12,13,15,19,24,25,82,85,95,97,98,101-103,107,135146,213,270,271,281,282,308,309,312,318,335,347-349 biological 122 cyclic 333 endogenous 85,98,106,119-130 generator 95,98,99,104,110 see also b e h a v i o r a l , p e r i o d i c i t y , p r e f e r r e d , s p o n t a n e o u s Rhythmic or rhythmical behavior 95,96,98,102,103,105,106,108,119-123,126,127,309 organization 135 oscillation 102 pattern 95,98,101,102,107,111,112,3 12 process 96,135,136,143,204 Rocking 207,213,219-224,226,227 Scalin law 216,218,220 broportional 18-23,28 Schema 176,178-181.183-186,190,191,202 Theory 179 see also m o t o r , p e r c e p t u a l Scheme 142,179 Segmentation 2,13,16,39,41,45,46,136,140,142 Self-organization71-73,126,129,204,207,213,214,224,226,247, 34 1,345,347,353,358-361 Sequence 1-10,16-28,40,41,50,53,82,94,108,111,123,124,128,136,137142,144,176-178,186,187,191,224,227,233,234,237,240,246,315,316,345349,352,354,356 see also i n t r i n s i c , linkage

Serial 2,6,8,16,23,143,145,191,192,306,307,344,348 seaial/paasallel344 Spatio-ternpasa-al Qrgamizati@m69,247 pimametem 1k4318&312 patterns 71,%6,93,U@,145,3 13,324,32733 1 see also coiupling, t e m p o r a l Speech 19,24,'122,123,135

Subject Index

396

Spontaneous motor rhythms 15,109,120,122,130,201,203-206,268,270,271,358,359 cry pattern 137,138 movements 312,316 pace 10,11,15,19,20 pattern formation 71,73,74,82,83,85,120,122,130 see also f l u c t u a t i o n Stability of collective variables 121 of patterns 7,69,71,72,74,78,81-86,126,139,282,283,302,308-310 postural 15 1,153,156-160,207 of the system 249,254,283,284 Stable attractors (torus attractors) 72,74,78,81,127,250,253 limit cycle 122,127 oscillations 6,10,119,121,122,125,126,129,130,342,343 attern 72-77,80,82,83,85,86,103,125,130,136,143,154,203,20507,254,348 relationships 253 state 71-74,78,85,86,104,119,121,122,126,214,223,226,253 multistable structures 214

1 State

boundary- 361 equilibrium 214,219,221,222 Nonequilibrium or far-from-equilibrium 71,74,80,119,122,247 initial 71,73,202,205 space 214,247,249,250 stead 119,214,215,235,237,238 see a 6 0 b e h a v i o r a l , c o l l e c t i v e , e q u i l i b r i u m , f l u c t u a t i o n , oscillator, stable Stepping reflex 155 Stereotypies 120,130,138,139,158,203,204,213,266,344 Structural interference 311,331 Sucking 123-129,155,358 Swimming 96-102,110-112 Symmetry of movements 356 of neuronal networks 100-104,111 see also c o n s t r a i n t s Synchrony 83,96,97,29 1,308-313,3 16-318,330,335 of behavior 96,97,285,287,291 t a a n external signal 5,6,76

Subject Index

Synergy 4,95,111,121,123,125,127,130,176,180,187,188,283,306, synergetics 71,247 see also i n t r i n s i c

397

31 1-314,317

Synkinesis 315 mirror 3 13-3 18 Tapping 1-8,23,27,53,282,308,309,31 1 Tempo 5,7,9-11,82 Temporal absolute invariance 3,237,281 characteristics 344,348,349 correlation 144,145 dependencies 135,3 10,313 invariance 7 1,208,237,306 organization 72,140,176,177,179,185,188,245,246,248,341,344,361 parameters 130,141,305,308,310,311,318,343 atterns 6,48,49,54-58,70,93,98,110,126,127,136-139,143, 45,203,213,224,305,312 phase 356 relationships 3,201,247,248,293,307,309,312,314,3 18,323,324,327 relative invariance 3,18,120-124,208,237,238,242,349 -spatial coordination 176,179,188 structure 1,4,5,7,9,16,25,26,47,93,98,110,120,126,127,135, 140,185,213,305 see also c o n s t a n c y , c o n s t r a i n t s , c o u p l i n g , s p a t i o - , t i m i n g

P

Theory see a c t i o n , a c t i v a t i o n , d y n a m i c , i n f o r m a t i o n , m a t u r a t i o n , motor, neural, schema Thermodynamics (law of thermodynamics) 202,216,217,226,247 Timin 11 1,120,123,124,136,138,143,201,208,246,305,309-312, 815,316,341,342,354 control 1,3,4,9,11,,12,18,23,27 internal 1,5,6-9,11,12,323,331,333,335 laws 216-219 origins of 201,202,208 oscillatory 205 properties 202,204,347,349,353,354,358 relative 3,4,7,18,19,42-60,69,70,72,81,85,86,141,208,248,281-284,288291,293,302,324,327,349,358 see also c o n t i n u i t y , i n v a r i a n c e , r e l a t i v e , t e m p o r a l Torus 215 attractor 127 Typing 1,2,4,15-17,19-28

398

Subject Index

Units of behavior 2,11,13,14,16,17,24,124,127,130,135-140,142, 176,179,180,247,348,349 functional 267,28 1,283,284,302,305,308,309 structural 127 subunits 6 Variability of behavior 5,7,19,20,24,56,57,71,72,76-79,83,138, 139,204,226,239,240,253,326-331,354 adaptive 120 see also i m p u l s e VITE model 51 Vocal behavior 137,139,140,143,144 Vocalization 122,135-146 Walkin 4,19,82,85,94,95,151,152,155-157,159,160,203,205,207,208,2312f2,245-254,265,266,342 reflexive 155 see also stepping r e f l e x