Studies in Perception and Action VII: Twelfth International Conference on Perception and Action : July 13-18, 2003, Gold Coast, Queensland, Australia

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Studies in Perception and Action VII Twelfth International Conference on Perception and Action

My 13-18, 2003 Gold Coast, Queensland, Australia

Edited by Sheena Rogers Psychology James Madison University Harrisonburg, VA, USA Judith Effken Nursing University of Arizona Tucson, AZ, USA

LAWRENCE ERLBAUM ASSOCIATES, PUBLISHERS 2003 Mahwah, New Jersey London

Copyright © 2003 by Lawrence Erlbaum Associates, Inc. All rights reserved. No part of this book may be reproduced in any form, by photostat, microform, retrieval system, or any other means, without prior written permission of the publisher. Lawrence Erlbaum Associates, Inc., Publishers 10 Industrial Avenue Mahwah, New Jersey 07430 Cover design by Kathryn Houghtaling Lacey Includes bibliographical references and index. ISBN 0-8058-4805-3 Books published by Lawrence Erlbaum Associates are printed on acid-free paper, and their bindings are chosen for strength and durability. Printed in the United States of America 10 9 8 7 6 5 4 3 2 1

Table of Contents Preface Meeting History Contributors

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Visual Perception "Representational Momentum" and the Perception of Complex Biological Motion Mohamed Jarraya & Michel-Ange Amorim 1 Body Shape Contributions to Perception of Point Light Displays Rita Snyder 5 Sensitivity to Emotional Events Pearl Makeig & Dean Owen 9 Property of Human Locomotion in Animations and Biomechanics Toshiharu Saburi 13 Altered Depth Perception in Stereoscopic Visualization Ryan Krumins & Paul Treffner 15 The Mona Lisa Effect: Perception of Gaze Direction in Real and Pictured Faces Sheena Rogers, Melanie Lunsford, Lars Strother, & Michael Kubovy 19 The Logical Structure of Visual Information Nam-Gyoon Kim 25 Effects of Texture and Surface Corrugation on Perceived Direction of Heading Nam-Gyoon Kim 29 Viewing Pictures: Similar Triangles Show How Viewing Distance Increases Size John M. Kennedy and Igor Juricevic 34 Viewing Pictures from Too Far: When are Tiles Perceived Square? Igor Juricevic & John M. Kennedy 37

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Coordination Dynamics Frequency and Amplitude are Inversely Related in Circle Drawing Shannon D. (Robertson) Ringenbach, Polemnia G. Amazeen, & Eric L. Amazeen 41 Learning and Transfer across Different Effector Systems: The Example of Goal-Directed Displacement Tasks C. Camachon, G. Montagne, M.J. Buekers, andM. Laurent...45 Hierarchical Control of the Bimanual Gallop Marline H. G. Verheul and Reint H. Geuze 49 Visual Basis of Directional Constraint in Hand-Foot Coordination Dynamics R. Salesse, J.J. Temprado, and M. Laurent 53 The Role of Visual and Kinesthetic Information in Bimanual Coordination Jeff Summers, Rebecca Wade-Ferrell, & Florian Kagerer 57 The Ecological Meaning of Spatial Symmetry in Bimanual Motor Coordination T.-C. Chan, C.-Y. Tse, H.-Y. Yue, & L.-Y. Fan 61 Musculoskeletal Dynamics of the Wrist During Rhythmic Activity Arne Ridderikhoff, C. (Lieke) E. Peper, Richard G. Carson, Peter J. Beek 65 Recruitment in a Synchronisation Task: A Coalition of Constraints Lorene Milliex, Sarah Calvin, Jean-Jacques Temprado & Thelma Coyle 69 Intention and Attention in Gestural Coordination: Asymmetric HKB Model Paul Treffner & Mira Peter 73 Haptic Perception and Dynamic Touch Bi-Manual Haptic Attention Marie- Vee Santana 79 Heaviness Perception Depends on Movement Claudia Carello, Kevin Shockley, Steven Harrison, Michael Richardson, and M. T. Turvey 83 Contribution of the Inertia Tensor to Manual Multi- Joint Pointing Delphine Bernardin, Brice Isableu, Gilles Dietrich & Jacques Cremieux 87

Contents Transfer of Calibration in Dynamic Touch: Length and Sweet-Spot Perception Rob Withagen and Claire F. Michaels

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Posture, Balance and Locomotion Postural Sway Decreases During Performance of a Digit Rehearsal Task Michael A. Riley, AimeeA. Baker, and Jennifer M, Schmit 95 Modeling Phase Transitions in Human Posture Paul Fourcade, Benoit G. Bardy & Cedrick Bonnet 99 Sports Expertise Influences Learning of Postural Coordination Caroline Ehrlacher, Benoit G. Bardy, Elise Faugloire, & Thomas A. Stoffregen 104 The Dynamics of Learning New Postures Elise Faugloire & Thomas A. Stoffregen 109 Ecological Perception and Cognition An Intentional Dynamics Assessment Procedure for Discrete Tasks Tjeerd Boonstra, Steven Harrison, Michael J, Richardson and Robert Shaw 113 Measuring Exploratory Learning with Minimal Instruction as Drift Endre E. Kadar, Botond Virginas & Judith Effken 116 Experimental Investigations of the Emergence of Communication Procedures Bruno Galantucci, Michael J. Richardson, Carol A. Fowler.. 120 'Mind the Gap': False Memories as a Case of Event Cognition Matthew P. Gerrie and Maryanne Garry 125 Feature Detection: An Adequate Meta-Theory for Fear Responding? Andrew D. M. Dickie& Ottmar V. Lipp 130 Perception for Inhibition": A Dorsal-frontal Pathway for Sensorimotor Regulation? Shun-nan Yang 135 Mobile Phones and Driving: Affordances and Attention Andrew Petersen, Paul Treffner, & Rod Barrett 140 Perception-Action Coupling A Comparison of Real Catching with Catching in a CAVE Joost C. Dessing, C. (Lieke) E. Peper, & Peter J. Beek

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Task-Constraints and Movement Possibilities Influence the Timing of Hitting Simone Caljouw, John van der Kamp, & Geert Savelsbergh 149 Perception-Action Coupling and Expertise in Interceptive Actions Cyrille Le Runigo & Nicolas Benguigui 153 Binocular Depth Vision in the Timing of One-Handed Catching Liesbeth Mazyn, Geert Savelsbergh, Gilles Montagne, & Matthieu Lenoir 157 How Do We Reach and Grasp a Virtual Image? T. Fukui, A, Ishii, & T. Inui 161 Movement Sequences for Cracking an Egg Aya Takahashi, Koji Hayashi, & Masato Sasaki 165 Tau Guidance for Mobile Soccer Robots Joe Leonard, Paul Treffner, & John Thornton 169 Stereoscopic 3D Visualisation Using Gaze-Contingent Volume Rendering: Exploratory Perception in Action Mike Jones & Paul Treffner 173 Does Exploration Promote Convergence on Specifying Variables? Alen Hajnal, Claire F. Michaels, and Frank T. J. M. Zaal....\7S Evidence for Two Visual Pathways: Differences in Walking and Talking Perceived Distance Sheena Rogers, Jeffrey Andre & Rebecca Brown 182 Auditory Perception Linguistic Background and Perception of an Ambiguous Figure: New Findings Kristelle Hudry, Philippe Lacherez, Jack Broerse, & David Mora 187 Behavior of a Harbor Porpoise in an Unfamiliar Environment Yoshiko Honno, Kiyohide Ito, Takashi Matsuishi, Masahiro Okura & Masato Sasaki 191 What is the Sound of One Rod Dropping? Jeffrey B. Wagman 195

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Special Workshop A New Look at Situational Awareness: The Essential Ingredients for Modeling Perceiving and Acting by Animate and Robot Agents Organizers: Robert E. Shaw & William Mace 199 A Precis of a Position to be Elaborated in the Workshop, on the Challenges and Promises of an Ecological Approach to Robotics Robert E. Shaw & William Mace 201 Toward Smart Cars with Computer Vision for Integrated Driver and Road Scene Monitoring Alexander Zelinsky 205 Author Index

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Keyword Index

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Preface This book is the seventh volume in the "Studies in Perception and Action" series, and contains a collection of posters and workshops presented at the Twelfth International Conference on Perception and Action, held in Surfers Paradise, Gold Coast, Australia July 13-18, 2003. The conference, the first to be held "down-under," was graciously and enthusiastically hosted by Griffith University's Complex Active Visualisation Laboratory. The 49 papers included in this volume provide a window onto the cutting edge work currently being done in ecological psychology around the world. Together with the other volumes in this series, they describe the evolution of the discipline and suggest potential opportunities for future investigations. The poster sessions are always a highlight of every conference and the poster book continues to be a valued resource for all of us because it provides a written record of the science presented during the presentations. The papers this year reveal the continuing development in specific areas within the discipline (e.g., haptic perception and dynamic touch, and visual perception-action coupling). In addition, there is evidence that the science is expanding in adventurous and ingenious ways as researchers begin to explore new methodologies and extend the theory. We have organized the papers into seven sections: (a) visual perception, which includes papers on biological motion, stereo and depth effects, and picture perception; (b) coordination dynamics, (c) haptic perception and dynamic touch, (d) posture and locomotion, (e) perceptual and cognitive processes, which includes papers on intentional dynamics, exploratory learning, the emergence of communication procedures and others; (f) perception/action coupling, and (g) auditory perception. An exciting addition to this year's conference was a workshop on ecological robotics organized by Bob Shaw and Bill Mace, which was titled "A New Look at Situational Awareness: The Essential Ingredients for Modeling Perceiving and Acting by Animate and Robot Agents". Two papers from this workshop are included as part of this volume. The first paper, by Shaw and Mace, explores the possibility of developing a theory of ecological robotics. The second, by Zelinsky, reports work on the development of "smart cars."

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It seems only appropriate that, in this volume, we acknowledge the passing of Eleanor J. Gibson, who died December 30th, 2002 at the age of 92. Her influence on our field has been profound. With her husband, James, J. Gibson, Eleanor helped define the field of ecological psychology, taking as her particular focus children's perceptual development and learning. Today, Eleanor Gibson is recognized as the founder of the ecological approach to perceptual learning and development. Her writings, as well as those of her students, are myriad and comprise one of the most accepted theoretical accounts of learning and development today. In 1992, Eleanor received the National Medal of Science for her work on perceptual development and learning, one of only ten psychologists to have received this award. Many people have contributed to the preparation of this volume. The quality of this series depends, in large part, on the quality of the manuscripts that are submitted initially. This year, the level of quality in the submissions was particularly high. All of us are indebted to Paul Trefmer for organizing the conference this year with the help of others at the Complex Active Visualisation Laboratory and of the program committee. We also acknowledge the ongoing leadership and guidance of Bill Mace throughout the publication process. Finally, we are grateful to Art Lizza, Bill Webber and their colleagues at Lawrence Erlbaum Associates for their interest in publishing this volume and their patient and helpful editorial advice. Sheena Rogers Judith A. Effken May, 2003

Meeting History 1. 1981-Storrs,CT,USA 2. 1983 - Nashville,TO,USA 3. 1985 - Uppsala, SWEDEN 4. 1987-Trieste, ITALY 5. 1989-Miami, OH,USA 6. 1991 - Amsterdam, NETHERLANDS 7. 1993 - Vancouver, CANADA 8. 1995 - Marseilles, FRANCE 9. 1997 - Toronto, CANADA 10. 1999 - Edinburgh, SCOTLAND 11. 2001-Storrs,CT,USA 12. 2003 - Gold Coast, QLD, AUSTRALIA

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Contributors Andre, Jeffrey T. School of Psychology, James Madison University, MSC 7401, Harrisonburg, VA 22807, USA [email protected] Amazeen, Eric L. Dept. of Psychology, Arizona State University, Tempe, AZ 85287, USA Amazeen, Polemnia G. Dept. of Psychology, Arizona State University, Tempe, AZ 85287, USA Amorim, Michel-Ange Center for Research in Sport Sciences, University of Paris XI, Batiment 335, 91405 Orsay Cedex, France Baker, Aimee Dept. of Psychology, ML 0376,429 Dyer Hall, University of Cincinatti, OH 45221-0376, USA Bardy, Benoft G. Center for Research in Sport Sciences, University of Paris XI, Batiment 335, 91405 Orsay Cedex, France [email protected] Barrett, Rod Biomechanics Lab, School of Physiotherapy and Exercise Science, Griffith University, PMB 50, Gold Coast Mail Centre, QLD 9726, Australia Beek, Peter J. Institute for Fundamental and Clinical Movement Sciences (IFKB), Faculty of Human Movement Sciences, Vrije Universiteit, Van der Boechorststraat 7-9, 1081 BT, Amsterdam, The Netherlands Benguigui, Nicolas Center for Research in Sport Sciences, University of Paris XI, Batiment 335, 91405 Orsay Cedex, France nicolas.benguigui@staps. u-psud. fr Bernadin, Delphine Center for Research in Sport Sciences, University of Paris XI, Batiment 335,91405 Orsay Cedex, France [email protected]

Contributors

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Bonnet, Cedrick Center for Research in Sport Sciences, University of Paris XI, Batiment 335, 91405 Orsay Cedex, France bonnetcedrick(g).hotmail.com Boonstra, Tjeerd Center for the Ecological Study of Perception and Action, U-20,406 Babbidge Road, University of Connecticut, Storrs,CT 06269, USA Broerse, Jack The University of Queensland, St. Lucia, QLD, Australia 4066 Brown, Rebecca School of Psychology, James Madison University, MSC 7401, Harrisonburg, VA 22807, USA Buekers, M.J. Laboratoire Mouvement et Perception, UMR 6152, Faculte des Sciences du Sport (UFR STAPS), Universite de la Mediterranee et CNRS, 163, avenue de Luminy - Case postale 910, 13 288 Marseille Cedex 09, France Calvin, Sarah Laboratoire Mouvement et Perception, UMR 6152, Faculte des Sciences du Sport (UFR STAPS), Universite de la Mediterranee, 163, Avenue de Luminy - Case postale 910, 13 288 Marseille Cedex 09, France [email protected] Camachon, C. Laboratoire Mouvement et Perception, UMR 6152, Faculte des Sciences du Sport (UFR STAPS), Universite de la Mediterranee et CNRS, 163, Avenue de Luminy - Case postale 910, 13 288 Marseille Cedex 09, France [email protected] Carello, Claudia Center for the Ecological Study of Perception and Action, U-20,406 Babbidge Road, University of Connecticut, Storrs, CT 06269, USA [email protected] Caljouw, Simone Faculty of Human Movement Sciences, Vrije Universiteit, Van der Boechorststraat 9, 1081 BT Amsterdam, The Netherlands [email protected]

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Carson, Richard G. Perception and Motor Systems Laboratory School of Human Movement Studies, The University of Queensland, Brisbane, Australia Chan, T.-C. The Chinese University of Hong Kong Coyle, Thelma Laboratoire Mouvement et Perception, UMR 6152, Faculte des Sciences du Sport (UFR STAPS), Universite de la Mediterranee, 163, Avenue de Luminy - Case postale 910, 13 288 Marseille Cedex 09, France Cremieux, Jacques Faculty of Sport Sciences, University of ToulonVar, BP 132, 83957 La Garde Cedex, France [email protected] Dessing, Joost C. Faculty of Human Movement Sciences, Vrije Universiteit, Van der Boechorststraat 7-9, 1081 BT, Amsterdam, The [email protected] Dietrich, Gilles Faculte des Sciences du Sport (UFR STAPS), Universite de la Mediterranee, 163, Avenue de Luminy - Case postale 910, 13 288 Marseille Cedex 09, France [email protected] Dickie, Andrew School of Human Movement Studies, Connell Building, University of Queensland, St. Lucia, QLD 4072, Australia [email protected] Effken, Judith College of Nursing, University of Arizona, PO Box 210203, Tucson, AZ 85721, [email protected] Ehrlacher, Caroline Center for Research in Sport Sciences, University of Paris XI, Batiment 335, 91405 Orsay Cedex, France Fan, L.-Y. The Chinese University of Hong Kong Faugloire, Elise Center for Research in Sport Sciences, University of Paris XI, Batiment 335, 91405 Orsay Cedex, France [email protected]

Contributors

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Fourcade, Paul Center for Research in Sport Sciences, University of Paris XI, Batiment 335, 91405 Orsay cedex, France [email protected] Fukui, Takao Dept. of Intelligence Science and Technology, Graduate School of Informatics, Kyoto Univerity, Yoshida-Honmachi, Sakyo-ku, Kyoto, 606-8501, Japan [email protected] Fowler, Carol A. Haskins Laboratories, 270 Crown Street, New Haven, CT 06511, USA Galantucci, Bruno Haskins Laboratories, 270 Crown Street, New Haven, CT 06511, USA [email protected] Garry, Maryanne School of Psychology, Victoria University of Wellington, PO Box 600, Wellington, New Zealand Gerrie, Matthew School of Psychology, Victoria University of Wellington, PO Box 600, Wellington, New Zealand [email protected] Geuze, Reint H. Dept. of Psychology, University of Groningen, Grote Kruisstraat 2/1, 9712 TS Groningen, The Netherlands Hajnal, Alen Center for the Ecological Study of Perception and Action, University of Connecticut, Storrs, CT, USA Harrison, Steven Center for the Ecological Study of Perception and Action, U-20,406 Babbidge Road, University of Connecticut, Storrs, CT 06269, USA [email protected] Hayashi, Koji The University of Tokyo, 1-12-1-411, Yaguchi, Ota-ku, Tokyo, Japan Honno, YoshikoN507, Graduate School of Fisheries Science, Hokkaido University, 3-1-1, Minato-cho, Hakodate City, Hokkaido, 0418611, Japan [email protected] Hudry, Kristelle The University of Queensland, St. Lucia, QLD, Australia 4066

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Inui, Toshio Dept. of Intelligence Science and Technology, Graduate School of Informatics, Kyoto Univerity, Yoshida-Honmachi, Sakyo-ku, Kyoto, 606-8501, Japan Isableu, Brice Center for Research in Sport Sciences, University of Paris XI, Batiment 335, 91405 Orsay Cedex, France [email protected] Ishii, Akinori Dept. of Intelligence Science and Technology, Graduate School of Informatics, Kyoto Univerity, Yoshida-Honmachi, Sakyo-ku, Kyoto, 606-8501, Japan Ito, Kiyohide Future University of Hakodate, Japan Jarraya, Mohamed Center for Research in Sport Sciences, University of Paris XI, Batiment 335, 91405 Orsay Cedex, France mohamed .jarrava@staps. upsud.fr Juricevic, Igor University of Toronto - Psychology, 1265 Military Trail, Toronto, Ontario, MIC 1A4, Canada [email protected] Kadar, Endre E. Dept. of Psychology, University of Portsmouth, King Henry I St., Portsmouth PO1 2DY, UK [email protected] Kagerer, Florian School of Psychology, University of Tasmania, Private Bag 30, Hobart, Tasmania, Australia Kennedy, John M. University of Toronto - Psychology, 1265 Military Trail, Toronto, Ontario, M1C 1A4, Canada [email protected] Kim, Nam-Gyoon Department of Psychology, William Patterson University, Wayne, NJ 07470, USA Kubovy, Michael Department of Psychology, Gilmer Hall, PO Box 400400, Charlottesville, VA 22904 Krumins, Ryan Complex Active Visualisation (CAV) Lab, School of Information Technology, Griffith University, Gold Coast

Contributors

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Campus, Parklands Drive, Gold Coast, QLD, 4215, Australia [email protected] Lacherez, Philippe The University of Queensland, St. Lucia, QLD, Australia 4066 [email protected] Laurent, M. UMR 6152, Faculte des Sciences du Sport (UFR STAPS), Universite de la Mediterranee et CNRS, 163, Avenue de Luminy, Case postale 910, 13 288 Marseille, Cedex 09, France Lenoir, Mattiheu Dept. of Movement and Sport Science, University of Ghent, Belgium Le Runigo, Cyrille Center for Research in Sport Sciences, University of Paris XI, Batiment 335, 91405 Orsay Cedex, France Leonard, Joe Complex Active Visualisation (CAV) Lab, School of Information Technology, Griffith University, Gold Coast Campus, Parklands Drive, Gold Coast, QLD, 4215, Australia [email protected] Lipp, Ottmar V. School of Psychology, McElwain Building, The University of Queensland, St. Lucia, QLD, 4072, Australia [email protected] Lunsford, Melanie School of Psychology, James Madison University, MSC 7401, Harrisonburg, VA 22807, USA [email protected] Mace, William Dept. of Psychology, Trinity College, Hartford, CT Makeig, Pearl Dept. of Psychology, University of Canterbury, Private Bag 4800, Christchurch, New Zealand [email protected] Matsuishi, Takashi Hokkaido University, Japan Mazyn, Liesbeth Dept. of Movement and Sport Science, University of Ghent, Belgium [email protected]

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Michaels, Claire F. Center for the Ecological Study of Perception and Action, University of Connecticut, Storrs, CT, USA [email protected] Milliex, Lorene Laboratoire Mouvement et Perception, UMR 6152, Faculte des Sciences du Sport (UFR STAPS), Universite de la Mediterranee, 163, Avenue de Luminy, Case postale 910, 13 288 Marseille Cedex 09, France Montagne, G. Laboratoire Mouvement et Perception, UMR 6152, Faculte des Sciences du Sport (UFR STAPS), Universite de la Mediterranee et CNRS, 163, avenue de Luminy - Case postale 910, 13 288 Marseille Cedex 09, France montagne@iaps. univ-mrs. fr Mora, David The University of Queensland, St. Lucia, QLD, Australia 4066 Okura, Masahiro University of Tokyo, Japan Owen, Dean Dept. of Psychology, University of Canterbury, Private Bag 4800, Christchurch, New Zealand Peper, C. Lieke Institute for Fundamental and Clinical Movement Sciences (IFKB), Faculty of Human Movement Sciences, Vrije Universiteit, Van der Boechorststraat 7-9, 1081 BT, Amsterdam, The Netherlands Peter, Mira Complex Active Visualisation (CAV) lab, School of Information Technology, Griffith University, PMB 50, Gold Coast Mail Centre, QLD 9726, Australia Petersen, Andrew Complex Active Visualisation (CAV) lab, School of Information Technology and Biomechanics Lab, School of Physiotherapy and Exercise Science, Griffith University, PMB 50, Gold Coast Mail Centre, QLD 9726, Australia [email protected]

Contributors

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Richardson, Michael J. Center for the Ecological Study of Perception and Action, U-20, 406 Babbidge Road, University of Connecticut, Storrs, CT 06269, USA Ridderikhoff, Arne Institute for Fundamental and Clinical Movement Sciences (IFKB), Faculty of Human Movement Sciences, Vrije Universiteit, Van der Boechorststraat 7-9, 1081 BT, Amsterdam, The Netherlands [email protected] Ringenbach, Shannon D. (Robertson) Dept. of Kinesiology, Arizona State University, Tempe, AZ 85287, USA [email protected] Riley, Michael Dept. of Psychology, ML 0376, 429 Dyer Hall, University of Cincinatti, OH 45221-0376, USA [email protected] Rogers, Sheena School of Psychology, James Madison University, MSC 7401, Harrisonburg, VA 22807, USA [email protected] Saburi, Toshiharu The University of Tokyo, Graduate School of Education, 5-6-9 Kinuta, Setagaya-ku, Tokyo, 157-0073, Japan [email protected] Salesse, R UMR 6152, Faculte des Sciences du Sport (UFR STAPS), 163, Avenue de Luminy - Case postale 910, 13 288 Marseille, Cedex 09, France [email protected] Santana, Marie-Vee The Proctor & Gamble Company, 11520 Reed Hartman Highway, Cincinatti, OH 45241, USA [email protected] Sasaki, Masato The University of Tokyo, 1-12-1-411, Yaguchi, Otaku, Tokyo, Japan Savelsbergh, Geert J. P. Centre for Biophysical and Clinical Research into Human Movement, Dept. of Exercise and Sport Science, Manchester Metropolitan University, Alsager Campus, Hassall Road, Alsager, Cheshire, ST7 2HL, UK

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Schmit, Jennifer M. Dept. of Psychology, ML 0376,429 Dyer Hall, University of Cincinatti, OH 45221-0376, USA Shaw, Robert Center for the Ecological Study of Perception and Action, U-20,406 Babbidge Road, University of Connecticut, Storrs, CT 06269, USA roberteshaw@aol .com [email protected] ShockJey, Kevin Center for the Ecological Study of Perception and Action, U-20, 406 Babbidge Road, University of Connecticut, Storrs, CT 06269, USA Snyder, Rita Dept. of Psychology, Denison College, Granville, Ohio 43023, USA snyder@den ison.edu Stoffregen, Thomas A. Human Factors Research Laboratory, University of Minnesota, MN, USA [email protected] Strother, Lars The Department of Psychology, Gilmer Hall, PO BOX 400400, Charlottesville, VA 22904 [email protected] Summers, Jeff School of Psychology, University of Tasmania, Private Bag 30, Hobart, Tasmania, [email protected] Takahashi, Aya The University of Tokyo, 1-12-1-411, Yaguchi, Otaku, Tokyo, Japan [email protected] Temprado, Jean-Jacques Laboratoire Mouvement et Perception, UMR 6152, Faculte des Sciences du Sport (UFR STAPS), Universite de la Mediterranee, 163, Avenue de Luminy - Case postale 910, 13 288 Marseille Cedex 09, France [email protected] Thornton, John Complex Active Visualisation (CAV) Lab, School of Information Technology, Griffith University, Gold Coast Campus, Parklands Drive, Gold Coast, QLD, 4215, Australia Treffner, Paul Complex Active Visualisation (CAV) lab, School of Information Technology, Griffith University, PMB 50, Gold Coast Mail Centre, QLD 9726, Australia [email protected]

Contributors

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Tse, C.-Y. The Chinese University of Hong Kong Turvey, M. T. Center for the Ecological Study of Perception and Action, U-20, 406 Babbidge Road, University of Connecticut, Storrs, CT 06269, USA van der Kamp, John Faculty of Human Movement Sciences, Vrije Universiteit, Van der Boechorststraat 9, 1081 BT Amsterdam, The Netherlands Verheul, Martine H.G. Centre for Biophysical and Clinical Research into Human Movement (CRM), Dept. of Exercise and Sport Science, Manchester Metropolitan University, Alsager Campus, Hassall Road, Alsager, Cheshire, ST7 2HL, UK [email protected] Virginas, Botond British Telecom, UK Wade-Ferrell, Rebecca School of Psychology, University of Tasmania, Private Bag 30, Hobart, Tasmania, Australia Rob Withagen Institute for Fundamental and Clinical Movement Sciences, Vrije Universiteit, Faculteit der Bewegingswetenschappen, van der Boechorststraat 9, 1081 BT Amsterdam, The Netherlands [email protected] Wagman, Jeffrey B. CESPA, U-20, Department of Psychology, University of Connecticut, Storrs, CT 06269-1020 [email protected] Yang, Shun-nan Brain Science Institute, RIKEN, Hirosawa, Wakoshi, Saitama 351-0198, JAPAN svangSffibrain.riken.go.ip Yue, H.-Y. The Chinese University of Hong Kong Zaal, Frank T.J.M. Human Movement Sciences, University of Groningen, Groningen, The Netherlands Zelinsky, Alexander Seeing Machines Pty Ltd, Innovations Building, Canberra, ACT 0200 Australia [email protected]

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Studies in Perception and Action VII S. Rogers & J. Effken (Eds.) © 2003 Lawrence Erlbaum Associates, Inc.

"Representational Momentum" and the Perception of Complex Biological Motion Mohamed Jarraya & Michel-Ange Amorim Center for Research in Sport Sciences University of Paris XI, France

Since the pioneering work of Johansson (1973) using luminous points placed on the various joints of the body, it is well established that the kinematics of a biological motion specify the dynamics of the ongoing action. For instance, information about the weight of an object can be detected in the transformational invariants produced by a pointlight character (PLC) lifting and carrying it (Runeson & Frykholm, 1981). What happens if the biological motion is suddenly stopped before its end? Are the dynamics of the action still visually detected? Is the memory of the final posture of the PLC accurate? Does the movement of the observer around the PLC affect its perception? These are the questions addressed in the present study. Method Twenty-four participants memorized the final posture of an interrupted motion of a 3D PLC (round-off / backward somersault) in order to decide if a subsequent « test posture » was located « after » or « before » the actual final posture. Depending on the viewing condition, the observer could be either static or in motion ( "panoramic ": rotation of the viewpoint about the vertical axis; "travelling": translation of the observer with the moving character) relative to the moving PLC. Moreover, a floor could be displayed in addition to the PLC, thus generating a global optic flow when the observer was moving. Finally, a change in the viewpoint was introduced between the final posture and the test posture, from 0° to 90° (Figure 1). The point of subjective equality (PSE) was computed from the responses to various test postures, in order to infer the final posture memorized by the observer.

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Figure 1. Example of the stimulations. The somersault sequence (A) was followed by an empty view (1500 ms, B) and by a brief presentation (500 ms) of a test posture (C-D). The observer's viewpoint changed between B and C.

Results Larger positive memory biases occurred (1) when the global optical flow accompanied the movement of the PLC, and (2) in the static viewing condition with no floor. In addition, the average bias in the responses decreased linearly with increasing angular difference between the final and test posture (from 19 ms to 2 ms for 0° to 90° change in viewpoint). Finally, the travelling condition led to negative biases as compared to the panoramic condition, when no floor was displayed (Figure 2). Discussion It is well known that an observer's memory of photographs with implied motion can be distorted in the direction of the suggested motion (Freyd, 1983). In the same vein, the remembered position of a moving target is usually displaced from its actual final position (Hubbard, 1995). Freyd and Finke (1984) called this forward memory displacement

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Figure 2. A) Observer x Floor interaction on average memory bias. B) PLC trajectory in the panoramic and travelling conditions during execution of the backward somersault.

"representational momentum" (RM). To what extent does this phenomenon apply to the memorization of complex biological motion? In the present study, we have shown that when a visual stimulation such as a complex biological motion is abruptly stopped, its dynamics survive. As a consequence, a RM effect affects the final perceived posture. In addition, we have shown that the displacement of the observer can modulate this phenomenon: When a global optic flow is generated by the displacement of the observer, RM effects are amplified. This result extends the conclusions of Probst et al. (1987) indicating that global optic flow can affect the perception of local optical flow. When this global optic flow is absent, the kinematics of the PLC affects RM: The greater the regularity of its trajectory, the larger the RM effect (Figure 2). The reason could be that an irregular movement is less predictible than a regular movement. The results also indicate that the observer's point of view plays a significant role in matching the memorized and the test posture: RM decreases with increasing angular difference separating them. The more the viewpoint increases the more the "bias" decreases. As a conclusion, complex biological events are not

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immune to memory biases, and this may be due to RM and viewing conditions. This line of reasoning may help us to understand judging errors during the perception of actions and postures in sport. References Freyd, J. J. (1983). The mental representation of movement when static stimuli are viewed. Perception & Psychophysics, 33, 575-581. Freyd, J. J., & Finke, R. A (1984). Representational momentum. Journal of Experimental Psychology: Learning, Memory, & Cognition, 10, 126-132. Hubbard, T. L. (1995). Environmental invariants in the representation of motion: Implied dynamics and representational momentum, gravity, friction, and centripetal force. Psychonomic Bulletin & Review, 2, 322-338. Johansson, G. (1973). Visual perception of biological motion and a model of its analysis. Perception & Psychophysics, 14, 202211. Probst, T., Krafczyk, S., & Brandt, T. (1987). Object-motion detection affected by concurrent self-motion perception: Applied aspects for vehicle guidance. Ophthalmic & Physiological Optics, 7(3), 309-314. Runeson, S. & Frykholm G., (1981). Visual perception of lifted weight. Journal of Experimental Psychology: Human Perception & Performance, 7, 733-740.

Studies in Perception and Action VII S. Rogers & J. Ejjken (Eds.) © 2003 Lawrence Erlbaum Associates, Inc.

Body Shape Contributions to Perception of Point Light Displays Rita Snyder Denison University, USA Point-light displays provide a useful technique for studying perception of human actions and intentions. Studies using this technique generally examine the informative properties of motion and pay little attention to more global aspects of form, such as body shape. Indeed, most studies using point-light displays provided impoverished body shape information. Specifically, actors had similar proportions, adjustments to video frames eliminated size variations, only parts of bodies were displayed, or actions that obscured potentially relevant shape variations were employed. Recent studies suggest that form and motion interact in complex ways (Shiffrar, Lichtey, & Heptulla Chatterjee, 1997); thus, systematically varying form rather than holding it constant may prove useful in elaborating that interaction. Research utilizing static representations of male figures (e.g., line drawings) suggests that two torso attributes, shoulder-to-hip ratio (SHR) and waist-to-hip ratio (WHR), reliably contribute to perception of socially relevant person variables. For example, Dijkstra and Buunk (2001) reported that men with trimmer WHR and higher SHR are rated as more attractive and dominant. The present study explored the possibility that shape variations of a male point-light actor would affect perception of his personal attributes. By manipulating apparent SHR and WHR for a single actor, effects of body shape on social judgment independent of movement variations could be assessed. In addition, two different actions, walking/waving and weightlifting, were examined to test the possibility that body shape influences on social judgments are context-dependent. Method To create point-light displays, green glow jewellery encircled wrists, elbows, knees, and ankles. In addition, glow jewellery strips, 24

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cm long, were placed across the forehead, waist at its smallest extent, hips at their largest extent, and shoulder boundaries at the points of maximum width. One adult male was videotaped in a darkened, L-shaped hallway performing two actions. In one action, he emerged around a corner, walked toward the camera for 2.4 m, stopped, waved, turned around, and walked back around the corner. In another action, he stretched his legs while leaning against a wall, turned to face the camera, lifted a barbell from the floor to above his head, and returned it to the floor. The actor was 1.7 m tall and weighed 56 kg. Circumferences of his shoulders, waist, and hips were 98, 79, and 85 cm, respectively. Foam blocks, approximately 9 x 12 x 5 cm, expanded shoulder and waist circumferences to 116 cm and 95 cm, respectively. Thus, actual and expanded SHRs were 1.15 and 1.36 and actual and expanded WHRs were .93 and 1.12, respectively. These ratios are within normal ranges for adult males and similar to those examined by Dijkstra and Buunk (2002). Participants (27 women, 21 men) viewed four videos of the actor, one for each factorial combination of SHR and WHR, either walking or weightlifting. Four orders of each set, based on a Latin square, were counterbalanced across participants. After watching each video, participants estimated the actor's height and weight and used 8point rating scales to indicate impressions of the actor for ten bipolar adjective pairs presented in random order: healthy /unhealthy, attractive /unattractive, overweight /underweight, weak /strong, shy /outgoing, dates a lot /rarely, gets along with others /does not get al.ong, good /bad leader, successful /unsuccessful, competitive /non-competitive. Results Ratings of social attributes were compared with 2 (WHR) x 2 (SHR) x 2 (Action) mixed ANOVAs. Higher ratings indicate greater endorsement of each descriptor. Significant WHR main effects demonstrated that with the lower WHR, the actor was perceived to be healthier, (M = 5.60 vs. 5.21, F(l,46) = 11.27, p < .01), more attractive, (M= 4.98 vs. 4.55, F(l,46) = 8.50, p< .01), competitive (M = 4.83 vs. 4.31, F(l,46) = 6.89, p = .05), and underweight (M = 3.83 vs. 4.41, F(l,46)=11.15, p<.01). No SHR main effects were found but SHR x Action interactions were significant for ratings of attractiveness, F(l,46) = 9.53, p < .01,

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successfulness, F(l,46) = 6.18, p < .05, and outgoingness, F(l,46) = 4.32, p < .05. Post hoc t-tests showed that when weightlifting, the higher SHR produced ratings of the actor as more attractive (M = 5.15 vs. 4.75), successful (M = 5.29 vs. 5.17), and outgoing (M = 5.21 vs. 4.88), although these differences were not significant (p's > .05). However, when walking, the effect of SHR was significant and in the opposite direction: lower SWR resulted in ratings of the actor as more attractive (M = 4.83 vs. 4.33), successful (M = 5.48 vs. 4.81), and outgoing (M- 5.46 vs. 5.02). Several significant Action main effects emerged. Compared to when he walked, when the actor lifted the weight he was rated as dating more (M= 5.99 vs. 5.39, F(1,46) = 16.08, p< .001), a good leader (M = 4.87 vs. 4.27, F(l,46) = 8.07, p < .01), stronger (M = 5.99 vs. 5.39, F(l,46) = 6.41, p < .05), and more competitive (M = 4.94 vs. 4.21, F(l,46) = 6.83,p<.05). Discussion Body shape appears to influence social perceptions of a pointlight actor. Consistent with results based on static figures, a normative WHR produced more positive attributions of attractiveness, health, and competitiveness than a higher one. Moreover, lifting a barbell resulted in more positive attributions in terms of dating, leadership, competitiveness, and strength than walking/waving. These results are consistent with evolutionary explanations positing that WHR and displays of strength signal mate value. However, the effects of SHR variations were not consistent with this explanation: the smaller SHR prompted more positive reactions when the actor walked/waved and made no difference when the actor lifted the barbell. At least two interpretations appear plausible. First, WHR may be a more useful signal for mate value than SHR. The pattern of results in this study suggests that SHR effects may be contextdependent: larger shoulders may have value primarily in situations where developed musculature is advantageous, such as for lifting weights. An alternative explanation arises from noting that more positive attributions generally were made when participants viewed the actor's true WHR and SHR. Observers readily detect deceptive intent in actions performed by point-light actors (Runeson & Frykholm, 1983); perhaps efforts to deceive observers about body shape are detectable as well. The

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negative impact of false/large shoulders was only evident for the walking/waving action, where center of moment information was available as a possible cue that body proportions were misrepresented. This exploratory study suggests that research examining both body shape and movement variations could prove useful. Do social perceptions vary for actors who actually have different body proportions? The results of this study also suggest that not only motion, per se, but the type of actions engaged in by actors may contribute to social meaning and warrants further study. References Dijkstra, P, & Buunk, B. P. (2001). Sex differences in the jealousyevoking nature of a rival's body build. Evolution and Human Behavior, 22, 335-341. Runeson, S., & Frykholm, G. (1983). Kinematic specification of dynamics as an informational basis for person-and-action: Expectation, gender recognition, and deceptive intention. Journal of Experimental Psychology: General, 112, 585-615. Shiffrar, M, Lichtey, L., & Heptulla Chatterjee, S. (1997). The perception of biological motion across apertures. Perception & Psychophysics, 59, 51-59.

Studies in Perception and Action VII S. Rogers & J. Effken (Eds.) © 2003 Lawrence Erlbaum Associates, Inc.

Sensitivity to Emotional Events Pearl Makeig & Dean Owen University of Canterbury, Christchurch, New Zealand Point-light techniques (Johansson, 1973) were used to test for sensitivity to information about the expression of emotion and emotionrelated states through observation of the kinematics of body movement alone (Makeig, 2000). Spontaneous expressions of emotion collected on videotape were converted to point-light displays. Events reliably categorised as revealing a particular emotion were tested further. Participants observed either the original full-view or the point-light displays and then indicated which emotion states they perceived as well as their rating of confidence in each judgement. In most cases, most emotional states are perceivable and reliably preserved from the fullview to the point-light displays. Clusters of emotional states were found which fit well with the "primary" emotions of joyfulness, anger, fear, sadness, and surprise. Full-view displays were more often required for the detection of the "secondary" emotions such as embarrassment and affection. Patterns of relationship between perceptions of the full-view and point-light displays Each of the 15 emotion categories offered to all observers yielded significant correlations between the two display conditions for all events indicating the extent to which the task-relevant information was preserved (see Table 1). Correlation is higher for events involving more body movement. Since participants had impoverished information to attend to in the point-light displays, lower confidence ratings were expected in the point-light condition. However, these trends do not hold for despair and dejection. Perhaps, through being restricted to information from body movement alone, participants acquired information relevant to these two categories that was overlooked by participants viewing the full-view displays.

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Point-light mean rating

Emotion categories

r(f-v,p-l)

Full-view mean rating

Jubilation Exultation Rage Excitement Frustration

.91 .85 .83 .80 .77

1.40 1.16 .69 1.03 .59

.75 .66 .43 .62 .57

Happiness Anger Surprise Fear Agitation Shock Embarrassment Affection Despair Dejection

.72 .69 .66 .64 .63 .55 .47 .29 .28 .27

1.93 1.04 .86

.73 .64 .28 .41 .40 .26 .27 .23 .49 .44

.74 .50 .64 .39 .58 .23 .12

Table 1. Significant correlations between the average confidence ratings for the full-view and point light conditions (col. 2). Mean confidence ratings for the fullview (col. 3) and point-light (col. 4) conditions for each emotion category.

Patterns within the data Correlations between the average confidence ratings, among all emotion categories across all events for both conditions, show patterns of clustering of emotion categories (see Table 2 for two examples). Emotion categories

1

1 Excitement 2 Jubilation

2

3

4

.91

.85

.65

.91

.69

.84

3 Exultation

.77

.87

4 Happiness

.42

.54

5

6

7

8

.84

.63

.63

.52 .39

5 Agitation 6 Anger

.76

7 Rage

—

.54

8 Frustration

.64

.79

.72

.72 .39

.59

Table 2. Clusters of significant correlations between emotion and emotion-related states. Full-view above the diagonal, point-light below.

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Furthermore, these clusters correlate negatively with each other. Shock and surprise, as well as despair and dejection, positively correlate as two additional clusters, whereas fear seems to stand alone. These groupings of categories seem to fit well with the emotions most often considered primary. Affection correlates positively with happiness across both conditions; embarrassment with fear, shock, despair and dejection for the point-light displays alone. Full-view displays were more often required for the detection of secondary emotions such as these. Inconsistencies within the data Inconsistencies in participants' perceptions of displays for the two conditions were accounted for by (1) the extent to which the expresser's body is fully and uprightly shown within the display, (2) lack of evidence of the "other" with whom the expresser is interacting, (3) body movement "flow" of expression being interrupted, and (4) less body movement. No evidence was found indicating that different emotions can give rise to one and the same expression. However, the same emotions do find expression in quite different situations. This is most interesting in relation to the notion that encounters in the world can sometimes trigger seemingly inappropriate emotional states and behaviours. A degree of affective impact may guide attention to particular environmental or situational affordances. Individual differences Even though indications of emotion and emotion-related states are reliably perceived within the displays for both conditions, distinct individual differences in these do occur, even between individuals viewing displays in the full-view condition. This suggests that individuals may vary in their attention to sources of information available within the displays. An additional experiment gathering written responses to the same displays for the point-light condition further supports this. For every event at least one individual out of 12 was able to accurately describe either the emotions expressed or the activity of the expresser. This indicates that sufficient information is available even within very impoverished displays. Its detection seems to depend on the individual's level of attunement to that information.

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Implications and subsequent research These results have implications for the difficulties experienced by post-traumatically stressed individuals when detecting invariant information across current everyday and past traumatic situations. Considering post-traumatic stress disorder from the ecological perspective suggests that a major effect of severe trauma may involve a significant interruption and resultant breakdown in the natural development of perceptual skills essential for guiding actions in the world. In future research, we hope to identify specific sources of information that, when attended to, lead to positive shifts in emotional reactivity. It is anticipated that such findings could be usefully applied as part of therapy. References Johansson, G. (1973). Visual perception of biological motion and a model for its analysis. Perception & Psychophysics, 14, 201211. Makeig, P. G. (2000). Sensitivity to kinematic specification of emotion and emotion-related events. Unpublished master's thesis, University of Canterbury, Christchurch, New Zealand.

Studies in Perception and Action VII S. Rogers & J. Effken (Eds.) © 2003 Lawrence Erlbaum Associates, Inc.

Property of Human Locomotion in Animations and Biomechanics Toshiharu Saburi The University of Tokyo, Japan Humans perceive objects and events in the environment by which they are surrounded. These natural objects and events are described by natural science. They are also re-created and represented in cell-animations. Many of the facts and properties of the events can be identified in the two approaches. For example, some characteristics of human walking and running actions found in the two approaches are the following: Both walking and running actions have periodicity, and a body goes up and down, forward and back, left and right in this cycle. But, walking actions have a double-support phase and do not have an air phase, while running actions do not have a double-support phase and do have an air phase (see Thorstensson, Nilsson, Carlson & Zomlefer, 1984). There is another difference between human running and walking actions. In the approach of biomechanics, one kind of natural science, it has been found that running actions are more rhythmical and regular than walking actions. Compare this to methods to make running and walking actions in animations. One method to create running actions is as follows: Two key-frame-pictures are created as Figure la and Id, inbetween-pictures are drawn and inserted between Figure la and 1d, and the sequence of running action is complete. Postures in Figures 1d, le and 1f are the anti-phase partners of Figure la, 1b, le. In contrast, the key-frame-pictures method to create walking actions does not have antiphase partners to the key frames in Figure 2a, 2c, 2e. If in-betweenpictures are inserted between each key-frame at regular time-intervals, there is no picture that has a symmetrical posture. These facts suggest that there is a coincidence in the two approaches, natural sciences and methods of creating animations. These similar properties could be considered as invariants of human running and walking, which are informative to specify these actions.

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Figure 1. A sample of pictures drawn using the key-frame method of creating running action in animation (T. Saburi, 2001).

Figure 2. A sample of pictures drawn using the key-frame method of creating walking action in animation.

References Saburi, T. (2001). The animation that Chihiro's love emerged from. The World of Hayao Miyazaki 'Spirited Away'. Eureka, Seidosha. Originally published in Japan. Thorstensson, A., Nilsson, J., Carlson, H. & Zomlefer, M.R. (1984). Trunk movements in human locomotion. Acta Physiol Scand, 121, 9-22.

Studies in Perception and Action VII S. Rogers & J. Effken (Eds.) © 2003 Lawrence Erlbaum Associates, Inc.

Altered Depth Perception in Stereoscopic Visualization Ryan Krumins & Paul Treffner Griffith University, QLD, Australia Stereoscopic (3D) displays are well known for improving a viewer's understanding of the layout of a complex visual scene (Ware, 2000). Plant visualizations can contain complex branching structures making monoscopic visualization difficult for the viewer to understand when determining the depth and relative position of parts of the plant. Altering the manner in which the stereo is created can provide amplified depth information, or a "hyperstereo" effect. The depth of the scene can be exaggerated and the focus of the scene can be positioned in "stereo space", for example, floating in front of the screen and practically "graspable", or alternatively retreating away from the viewer and "into" the viewing screen. This project investigated the effectiveness of altering the way in which stereo is achieved in order to improve the advantages of using stereo in biological plant visualizations. Method Asymmetric stereo frustums (i.e., solid angles from the computer graphic) were chosen based upon the absence of distortions typically found in other methods such as toe-in stereo, and the ease with which such frustums can be modified to alter perceived depth. Asymmetric stereo is achieved by shearing the frustum used for each eye inward to produce a plane of zero parallax, also known as the plane of convergence. Using this stereo configuration the position of the plane of convergence can be modified while leaving the field of view unchanged. Altering the location of the plane of convergence has the effect of positioning the scene being viewed in stereo space (Fig. 1). For example, pushing the plane away from the viewer has the effect of bringing the scene toward the viewer in stereo space with the scene appearing to float in front of the viewing surface. Given the ability to alter the stereo configuration, testing was conducted to determine any effect this would have on a simple selection task performed in stereo.

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Figure 1. Schematic of location of the image relative to the plane of convergence indicating mixed (at the screen; left panel) and negative (in front of screen; right panel) configurations.

Test participants were asked to manually select 5 to 15 random points on 3 different plant models (generated as fractal L-systems; Fig. 2). The selection was carried out using a simple 3D cursor controlled by a conventional mouse with a button used to switch between which axis the cursor moved in. The three plant models selected occupied varying levels of depth space (Bop01: mainly flat; tree 10: basically spherical; fern: more depth than height). Selection using these models was conducted over 5 viewing conditions. The first condition was simply monoscopic to confirm that monoscopic selection would be less accurate than stereoscopic. Stereo plant models were used in 4 plane-ofconvergence configuration conditions: positive (resulting in most of the plant behind the plane of convergence); negative (resulting in most of the plant in front of the plane of convergence); mixed (middle of the plant on the plane of convergence); and self-defined (participant modified the plane of convergence toward a comfortable viewing position). The plant models themselves were intentionally devoid of depth cues in an attempt to isolate the effectiveness of stereo alone. The plants were relatively plain in color, unlit, and perspective-projected.

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Figure 2. The three plant models.

During selection, rotation of the plant model was disallowed, however rotation was allowed before selection began. The time taken and accuracy of each selection were recorded. Results Monoscopic selections were confirmed to be generally less accurate than those using stereo (Fig. 3). Although mixed stereo was better than monoscopic, it was the least effective stereo configuration. Positive and negative configurations were generally better than mixed stereo.

Figure 3. Selection error for the five planes of convergence.

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On average, the pre-defined positive (i.e., behind screen) configuration trials yielded higher selection accuracy compared to the pre-defined negative (i.e., in front of screen). However, the self-selected configurations gave the best overall accuracy and were mostly negative (i.e., in front of screen). The results confirm that self-selected action leads to increased accuracy in perceptual tasks, and that individuals tend to prefer to visualize 3D stereo objects at or slightly "floating" in front of the viewing plane (Fig. 4). Implications follow for how to optimally present viewer-centered affordances using stereographic displays in order to create virtual environments (Stanney, 2001).

Figure 4. Schematic of the results from five participants in the self-selected viewing condition showing the resulting positions in stereo space of the three plants.

References Ware, C. (2000). Information visualization: Perception for design. San Francisco: Morgan Kaufman. Stanney, K. M. (Ed.). (2002). Handbook of virtual environments: Design, implementation, and applications. Mahwah, NJ: Lawrence Erlbaum Associates.

Studies in Perception and Action VII S. Rogers & J. Efiken (Eds.) © 2003 Lawrence Erlbaum Associates, Inc.

The Mona Lisa Effect: Perception of Gaze Direction in Real and Pictured Faces Sheena Rogers1, Melanie Lunsford1, Lars Strother2, & Michael Kubovy2 l

James Madison University, USA 2 University of Virginia, USA

The eyes in a portrait often seem to follow observers as they pass (the Mona Lisa effect). All 3-D objects in a picture, not only gaze, will rotate in virtual space as the observer moves past the picture (Rosinski & Farber, 1980). This phenomenon is predicted by the geometry of pictorial space (See Rogers, 1995, for a review) but it may also be due to limits in our ability to perceive the direction of another's gaze even in the real world, or to general inaccuracies in picture perception. Sedgwick's (1991) analysis shows that the virtual orientation of objects is affected both by the objective orientation of the gaze (towards the station point or away to one side) and by the degree to which the picture is slanted relative to the observer. According to the geometry, objective gaze direction should be increasingly mis-perceived (distorted) as the angle of gaze increases away from the station point (or center) (a differential rotation effect). We conducted two experiments to investigate the Mona Lisa effect as it relates to our ability to judge the direction of another's gaze. In the first experiment, we compared judged gaze direction for a real and pictured face, without slanting the picture plane. In the second experiment we measured the effects of slanting the picture plane on judgements of gaze direction. Experiment 1 Method Observers judged the direction of gaze of a live model and of life-size photographs of the same model. Only the eyes moved, the head

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was frontal. The observer was located at the station point for the picture so the optical geometry of the two conditions was matched.

Figure 1 The apparatus and viewing arrangements for Experiment 1.

The model (both live and photo) directed her gaze at 21 targets, placed horizontally on a panel positioned between the observer and the model/display, at 10 cm increments from the center (0 cm) to 100 cm, both to the left and right. Twenty-three observers participated in 2 blocks of the 21 randomized trials for both live and picture conditions. They indicated perceived gaze direction by shining a laser pointer along the panel to mark the location at which the model appeared to be gazing. Measurements were taken to the nearest .5 cm from the center of the panel to the point of light. Results Performance was similar for both the live and photo conditions. For targets located between 50 cm left and 50 cm right, no significant difference was found between live and photo conditions (see Figure 2). Judgments of gaze direction tended to be more accurate when the target was close to the center of the response panel, and less accurate at the extremes, especially in the photo condition. Figure 3 shows the 95% confidence intervals for the center target only (model looking straight ahead). Notice the greater variability in the photo condition. In figure 4 we show results for the targets between 10 cm and 40 cm to the left, which demonstrate that, in this range, gaze direction tends to be overestimated and that there is a small additive error for pictures.

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Actual location of target (in cm) Figure 2. Perceived gaze direction (indicated location of target along panel, in cm from the center) varied as a function of actual gaze direction (actual distance of target from the center) in both live and picture conditions.

Figure 3. 95% confidence intervals for responses to the center target, showing greater variability for pictures.

Figure 4. Perceived location of each target as a function of actual location (in cm). Observers tend to overestimate gaze direction, especially in the photo (top line).

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We performed a second experiment to explore the effect of a slanted picture plane. In natural picture-viewing settings observers are rarely at the picture's station point. Slanted picture planes are the norm. We asked whether the Mona Lisa effect is limited to the situation when the model is looking directly at the observer (toward the perspective station point or camera), or if it is more general. For example, if the gaze of a picture is directed at your shoulder when you are at the station point, does her gaze follow your shoulder as you pass the picture? The geometry predicts that it will not. If the differential rotation effect is observed, gazes at the center target should appear to be towards the observer at all levels of screen rotation (the Mona Lisa effect). Gazes towards more extreme targets should appear to be increasingly rotated away from the target Method Observers judged gaze direction using a subset of the photographs from Experiment 1. We reduced the range of targets to 0 cm to 50 cm to the right and left in an effort to decrease the amount of off-board responses for extreme gaze locations. The computer monitor was rotated by 0°, 15°, 30°, and 45° to the left and right. Four observers participated in multiple sessions of two blocks of 42 randomized trials (seven rotations by six targets). Responses were measured using the same apparatus and procedure as in Experiment 1.

Figure 5. The apparatus and viewing arrangements for Experiment 2.

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Results Experiment 2 demonstrated the classic Mona Lisa effect. A model looking toward the station point appeared to be looking at the observer (a distortion) when the picture was slanted. The box plots in Figure 6 show responses for one observer for the center target at each level of picture rotation. Median responses are close to zero (the model appeared to be looking toward the observer), although variability increased as the display rotates further away. Perhaps because of an asymmetry in the model's face, the gaze appeared to drift away from the observer with display rotations to the left, although not with rotations to the right.

Figure 6. Box plots of responses to the center target, at each level of display rotation, for one observer.

When the model was not looking toward the station point (targets at 10 - 50 cm from the center) the model's gaze appeared to rotate so that she seemed to be gazing at increasingly extreme locations on the panel as the picture was increasingly slanted away from the observer. There is a hint of differential rotation effects over this range of targets and display rotations, but it seems likely that such effects will become obvious only at extreme values of each variable.

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Discussion Experiment 1 showed that, for the perception of gaze direction, a photo can act as a reasonable substitute for a real scene when the observer is at the station point (center of projection for the picture). Even in this privileged viewing position, however, there was more variability in perception of the pictures and there was a consistent error in picture perception in the form of overestimates of the distance of the target and thus the gaze direction. When the observer is not near the station point for the picture (as is typically the case in picture viewing) systematic distortions in the perception of the objective pictured scene will occur. Rotation of three-dimensional objects, including gaze direction, in the virtual space of slanted pictures is predicted by the geometry of pictorial space. The results of Experiment 2 indicate that perception is governed by this geometry, and not by the geometry of the objective 3-D scene. The Mona Lisa effect is a unique feature of picture perception. It is an example of the predictable, systematic distortion in the perception of pictorial space that occurs under normal picture-viewing conditions. The implication for experimental psychologists and anyone else who uses pictures is that pictures should not be assumed to be adequate standins for real scenes. More research is needed to map the distortions in pictorial space, and to identify situations when veridicality of perception can be expected. References Rogers, S. (1995). Perceiving pictorial space. In W. Epstein and S. Rogers (Eds.) Handbook of perception and cognition: Vol. 5. Perception of space and motion (2nd ed., pp. 119-163). San Diego: Academic Press. Rosinski, R. R., & Farber, J. (1980). Compensation for viewing point in the perception of pictured space. In M. A. Hagen (Ed.), The perception of pictures: Vol. 1. Alberti 's window: The projective model of pictorial information (pp. 137-176). New York: Academic Press. Sedgwick, H. A. (1991). The effects of viewpoint on the virtual space of pictures. In S. R. Ellis (Ed.), Pictorial communication in virtual and real environments (pp. 460-479). New York: Taylor & France.

Studies in Perception and Action VII S. Rogers & J. Effken (Eds.) © 2003 Lawrence Erlbaum Associates, Inc.

The Logical Structure of Visual Information Nam-Gyoon Kim William Paterson University, USA & CESPA, University of Connecticut, Storrs, CT Koffka states, "what we see has color. Therefore, where there is no color, we do not see" (1935, p. 178). Upon observing a red book lying on a black table, however, Koffka notes, "I see the red book on the table, and yet where I see the book I see no black colour, although at the same time I do not see the table as broken." Michotte, Thines, and Crabbe (1991) concur: "It is astonishing how rare it is to find examples of objects where the side facing the observer is completely uncovered. Nearly all of them have parts hidden by other objects (screens), and despite this the shapes we see are neither interrupted nor breeched. Indeed it is clear that the world as it appears to us is not made up of fragments of objects but of things with a complete shape presented to us in this way despite the partial and temporary concealment that happens to them" (p. 165). This problem arises because the environment we live in is typically cluttered with opaque objects and because the light reflected from the surfaces of the objects travels in a straight line. That is, in a cluttered environment, not all surface elements are projected to the point of observation. Only in an open environment, an environment in which a level ground recedes to the horizon with cloudless sky, are all the surface elements projected. When environmental properties are projected, a projective correspondence can be established between the environmental features and the corresponding optical elements. No such correspondence is possible, however, for unprojected hidden surfaces. "The true problem," then, as Gibson (1977) notes, "is how surfaces are perceived when they are temporally occluded, or hidden, or covered, that is, when they are not projected in the array at a fixed point of observation" (p. 162). How can observers perceive the entire layout of the environment as unbroken and complete despite hidden surfaces?

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Indeed, the unprojection of hidden surfaces, or occlusion, as Gibson points out, "poses the greatest difficulty for all theories of visual perception based on sensation" (1979, p. 79). How, then, can the information-based theory of perception, a theory Gibson promoted, address the same problem? For Gibson (1979), the natural stimulus for the visual system is the optic array, a nested set of visual solid angles with a common apex at the point of observation. As a manifold of solid angles, an optic array has structure or pattern. That is, the large solid angles originate from the faces of the environmental layout, whereas the small solid angles originate from the facets of the layout, i.e., the texture of the surfaces. More importantly, the basis of such an arrangement of structure is an adjacent order with the order determined by the arrangement of surface texture elements. A question still remains: Is having such structure sufficient to explain the perceiving of hidden surfaces? A clue can be found by further unpacking the notion of "order." In mathematical logic, order is defined as "a relation among the members of the class, in respect of which some appear as earlier and some as later" (Russell, 1919, pp. 30-31). Intuitively stated, for two elements in a class which is to be ordered, an ordering relation specifies which member "precedes" and which member "follows." To order the members of a class appropriately, the ordering relation must have three properties—asymmetry, transitivity, and connexity (Russell, 1919). Asymmetry. If x precedes y, y must not also precede x. If the preceding holds for a pair of members of a class, the relation is said to be asymmetric. Consider, for example, two relations, husband and spouse. If a is husband of b, b cannot be husband of a. Hence, the relation husband is asymmetrical. In contrast, if a is the spouse of b, b is necessarily the spouse of a. Hence, the relation spouse is symmetrical. Transitivity. For three pairs of a class, (x, y), (y, z), and (x, z), if x precedes y and y precedes z, x must precede z. If the preceding holds, the relation is said to be transitive. For example, 1 is less than 2 and 2 is less than 3. Therefore, 1 is less than 3. So transitivity holds among the three numbers, 1,2, and 3. Connexity. Given any two distinct elements of a class, there must be one which precedes and the other which follows. For example, of any two integers, one is necessarily greater than the other.

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When the preceding three properties are observed among the members of a class, the class is said to be ordered. Consider again Koffka's puzzle, a book lying on a table. Suppose that the optical structure corresponding to the surface texture of the background table is depicted by the following string of symbols: ABCDEFGHIJ and the foreground texture of the book by the following string of symbols:

1234 with each string simply denoting adjacent elements of optical structure without a specification of its "elements." Suppose further that the book occludes the middle portion of the table as ABC1234HIJ Due to occlusion, the optical structure corresponding to the middle portion of the table (DEFG) is unprojected. At the level of projection, the surface texture corresponding to the book is made of two subparts, ABC and HIJ. Nevertheless, the table is still perceived as a single entity, not as two fragments with a gap in the middle. Note that, as an ordered structure, the relation underwriting the optical structure must be also asymmetric, transitive, and connex. Hence, not only are the solid angles corresponding to the surface elements of the table connex, but they also are transitive. In particular, the transitive relation defined over the background surface elements preserves the connectivity between "C" and "H" despite the absence of the intervening texture which, in turn, gives rise to the perception of an intact, complete surface without a gap. Gibson (1979) contended that the optic array specifies the permanent properties in the environment. However, what is specified in the ambient optical structure is neither surfaces nor objects, but the underlying adjacent order of the structure. More importantly, the order characterizing the optical structure reflects the corresponding order of the layout of the environment. Or, as Gibson puts it, "the reality underlying the dimensions of space is the adjacent order of objects or surface parts" (1979, p.101). Hence, perception is specific to ordinal

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stimulation (Gibson, 1950) which, in turn, is specific to the adjacent order of the environmental layout. Therefore, for Gibson, perception is specific to the environment. References Gibson, J. J. (1950). The perception of the visual world. Boston, MA: Houghton Mifflin. Gibson, J. J. (1977). On the analysis of change in the optic array. Scandinavian Journal of Psychology, 18, 161-163. Gibson, J. J. (1979). The ecological approach to visual perception, Boston, MA: Houghton Mifflin. Koffka, K. (1935). Principles of gestalt psychology. New York: Harcourt, Brace, & World. Michotte, A., Thines, G., & Crabbe, G. (1991). Amodal completion of perceptual structures. In G. Thines, A. Costall, & G. Butterworth (Eds.), Michotte's experimental phenomenology of perception (pp. 140-167). Hillsdale, NJ: Erlbaum. Russell, B. (1919). Introduction to mathematical philosophy. London: George Allen & Unwin.

Studies in Perception and Action VII S. Rogers & J. Effken (Eds.) © 2003 Lawrence Erlbaum Associates, Inc.

Effects of Texture and Surface Corrugation on Perceived Direction of Heading Nam-Gyoon Kim William Paterson University & CESPA, University of Connecticut, USA In the kind of cluttered environments through which we normally drive or walk, not all surface elements are projected to the point of observation. Only in an open environment, an environment in which a level ground recedes to the horizon with cloudless sky, are all the surface elements projected (Fig. la). Yet, we safely navigate through such environments with ease and regularity. A central question, then, is what is the form of the information contained in optical distributions that supports the control of locomotion through the cluttered environment?

Figure 1 (a) Optical flow with the focus of expansion corresponding to the observer's path, (b-d) Optical flow induced by translation along corrugated surfaces that are made of (b) random dots, (c) random patches, and (d) a random check pattern.

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To date, research on optical flow has been largely restricted to translation over random dot surfaces or towards frontal parallel planes. The resultant patterns are well defined with a singularity, the focus of expansion, corresponding to direction of heading. In contrast, the pattern arising from translation over uneven surfaces may differ qualitatively from that resulting from translation over level surfaces due to the occluded and disoccluded parts of the environment. In fact, there are no known mathematical descriptions of the resultant optical flow field, nor are there computational algorithms available that can extract the requisite information from the flow field. Because of this limitation, the present study primarily focuses on the collection of data that will define human perceptual capacity for heading under these circumstances, in particular, judging direction of heading during locomotion along corrugated surfaces. Also examined is the perceptual consequence of optical flow rendered from varying types of surface texture. Method Eight observers watched computer-simulated displays depicting observer translation over corrugated surfaces at a translational speed of 4 m/s. Displays were generated on an SGI Indigo Maximum Impact and presented on a 19-inch screen refreshed at 60 frames/s. The display screen subtended 53° horizontal x 40° vertical when viewed from 40 cm from a chin rest. Participants were allowed to move their eyes freely during the experiment. Each display lasted 3 seconds. The task of participants was to indicate their direction of heading by adjusting the pointer on the screen to the location that would intersect a horizontal red line that appeared on the ground plane following the completion of the display. The offset angle subtended by the point on the horizontal bar at which the actual path crosses and the point participants selected was used to evaluate heading accuracy, measured in terms of absolute error. Five variables were controlled: Gaze angle, gaze direction, surface corrugation, starting location, and surface type. Gaze angle in conjunction with gaze direction varied randomly from ±6° to 9° of visual angle from heading direction (positive and negative values correspond to gaze direction deflected to the left and right, respectively). Surface corrugation was controlled by the equation:

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y = a sin bz - eyeheight

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(1)

where y, a, b, z, and eyeheight represent surface height, amplitude, period of the curve, distance along the depth axis, and simulated eye height, respectively. Of these, the amplitude of the surface and eyeheight were fixed at 2.0 and 1.6 m, respectively, whereas period varied randomly among 60, 100, and 150 m. With the horizon set at 300 m, these values yielded corrugated surfaces with 5, 3, and 2 cycles of "hills" and "valleys," respectively. Whereas Equation (1) determined the height (y) and depth (z) of the simulated surface, the horizontal (x) dimension was a simple extension of the same y and z values to 150 m laterally in both directions. Hence, the simulated surface consisted of a 300 x 300 m square region wherein its z axis is corrugated according to Equation (1). A level surface was also included as a control. Also manipulated was the starting location at which the observation point initiated movement. This location varied among 30, 60, 120, and 210° where each value refers to a position on the first cycle of the curve. Finally, surface texture was rendered either as random dots (Fig. 1b), polygonal patches (see Fig. 1c) or a random check pattern (Fig. 1d). This yielded a 2 (gaze direction) x 2 (gaze angle) x 3 (texture type) x 4 (surface corrugation) x 4 (starting location) repeated measures design. Results Overall, participants judged heading direction accurately, with a mean absolute error of 1.8° of visual angle, well within the range of 1° to 3° needed for the effective control of locomotion in cluttered environments (Kim, Fajen, & Turvey, 2000). The results were collapsed over gaze direction and entered into an analysis of variance (ANOVA) with gaze angle, texture type, surface corrugation, and starting location. The ANOVA revealed main effects of texture type, F(2, 14) = 8.12, p = .005, surface corrugation, F(3, 21) = 3.23,p = .04, and starting location, F(3, 21) = 3.03, p = .05, as well as a gaze angle x starting location interaction, F(3, 21) = 3.69,p = .03. Heading accuracy degraded with the degree of surface corrugation. In particular, performance was significantly poorer in the 60 m condition than in other surface conditions (Fig. 2, top panel). Note that the surface corrugation was most extensive in the 60 m condition

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60 m condition than in other surface conditions (Fig. 2, top panel). Note that the surface corrugation was most extensive in the 60 m condition

Figure 2. Mean absolute error in degrees as a function of surface texture for each condition of surface corrugation (above) and as a function of starting location for each condition of gaze angle (below).

with 5 cycles of corrugation. Participants' judgements were also influenced as a function of starting location with significant degradation of performance in the 210° condition (Fig. 2, lower panel). In this condition, the observation position started near the valley and moved downward, arriving near or at the valley when the display stopped. Note that the visible portion of the surface under this condition was severely reduced with only a small amount of the ground projected to the observation point. In other starting location conditions, however, the observation position started near the hill and then either moved upward eventually reaching the top or moved downward facing the next valley. Under these conditions, there was still a vast amount of surface

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respect to the main effect of texture, the patch condition resulted in poorer performance than the random dot or random check pattern condition. However, the rationale behind this result is not clear. So we leave this effect for future consideration. Discussion The deformation of optical pattern due to corrugated surfaces is different from the pattern arising in an open environment. Nonetheless, human observers were quite accurate in perceiving their direction of heading. Under certain conditions performance deteriorated, but not enough to compromise locomotion. Also notable was the fact that human observers were as accurate in the random dot surface condition as in the random check pattern condition. Whereas the continuity of the surface was specified in the latter condition, it was lacking in the former condition. Based on the results of the present study a description other than a two-dimensional velocity vector field may be needed for the general case of locomotion in a cluttered environment. Note that optical perturbation corresponding to translation along corrugated surfaces produces continuous accretion and deletion of optical structure, i.e., dynamic occlusion, along the occluding edges of the surfaces. The resultant optical effect is not a transformation, but a breaking of adjacent order. If the visual system is sensitive to optical structure specific to ordinal stimulation (Kim et al., 2000), it may be equally sensitive to a systematic disruption of such properties. Indeed, for Gibson (1979), dynamic occlusion becomes an important source of information for the perception of observer movement. The results of the present study corroborate this contention. Human observers are quite reliable in exploiting the effect of dynamic occlusion to detect the requisite information such as that which specifies direction of heading from optical flow. References Gibson, J. J. (1979). The ecological approach to visual perception. Boston, MA: Houghton Mifflin. Kim, N.-G., Fajen, B. R., & Turvey, M. T. (2000). Perceiving circular heading in noncanonical flow fields. Journal of Experimental Psychology: Human Perception and Performance, 26, 31-56.

Studies in Perception and Action VII S. Rogers & J. Effken (Eds.) ©2003 Lawrence Erlbaum Associates, Inc.

Viewing Pictures: Similar Triangles Show How Viewing Distance Increases Size John M. Kennedy and Igor Juricevic University of Toronto, Canada Squares and rectangles are often depicted foreshortened. Indeed, a quadrilateral in Figure 1 could depict either of these, depending on the observer's vantage point. Here, we show similar triangles govern the depicted form. Figure 1 (after Kennedy and Juricevic, 2002) is in linear perspective, showing square tiles receding to the horizon. The tile edges orthogonal to the picture plane are depicted by lines converging to point H on the horizon, and the diagonals by lines converging to point 1D. The vantage point from which to view the picture, to ensure all its projections are veridical for squares, is on the normal to the picture through H, at a distance from the picture surface equal to the distance d between H and 1D.

Figure 1. A picture of square tiles receding to the horizon H. Or, a cross-section through a picture surface HG, with tiles on the ground to the left of the picture surface projecting to vantage points 1D and 4D.

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If we view the picture from further than its proper viewing distance d its projections are not correct for horizontal square tiles, and in particular viewing from a distance greater than d can stretch the squares into rectangles that are long in the z-dimension. But how long? Sedgwick (1991) provides a trigonometric answer but, as it happens, similar triangles can also tell us. Helpfully, Figure 1 can also be taken to be a cross-section through a picture surface stretching vertically from a point H to the ground G. Read in this fashion the cross-section includes a set of tiles on the ground receding to the left of the picture surface. As before, the observer's vantage point 1D is set on a line perpendicular to the picture surface at H, at a convenient distance d. The projections of the tile edges on the picture surface are found by connecting the edges of the tiles 1, 2, 3, 4 and so on to the observer's vantage point 1D. The projections are intersections with the picture surface: for example point P is the projection of tile edge 1. To examine what results when an observer is placed further away from the picture surface than 1D, let us consider 4D, 4 times further from H than 1D. On the picture surface, projections from tile edges to 1D depict tiles on the ground for observers at 4D. But which lines correspond to which tile edges for 4D? Consider the projection P of tile edge 1. Interestingly, P is a projection of tile edge 4 for 4D. Evidently receding from 1D to 4D moves projection P from corresponding to tile edge 1 to corresponding to tile edge 4. This fourfold change of tile edges is not just a coincidence. To understand why, let us note the role of similar triangles. Triangle 1, G and P is similar to 1D, H and P. Also, 4, G and P is similar to 4D, H and P. Any move of a vantage point from 1D towards 4D produces a corresponding change along the ground line from G through 1, 2, 3 and so on. That is, the fourfold increase in viewing distance from the picture surface of 4D compared to 1D is equalled by the fourfold increase in distance along the ground. Three extra notes show the generality of this conclusion about proportional increases: a) The fact that the increases were fourfold was arbitrary — just a matter of convenience. The triangles would be similar at any increase ratio: 5D, 6D, ZD. b) The fact that just one tile, G to 1, was chosen in our analysis is also arbitrary. Consider the double tile G to 2. Its projection on the picture surface for Dl would project fourfold to tile edge 8 for D4, the similar-triangles rule tells us. c) The fact that the tile touching G was chosen is also just an apodictic matter of

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convenience. Consider the tile stretching from 1 to 2. It does not touch G. We know the line connecting G to P on the picture surface depicts 4 tiles on the ground for 4D. And we know the projection for 1D of the double tile G to 2 represents 8 tiles on the ground for 4D. Hence, by subtraction, tile 1 to 2 projects a line on the picture surface that depicts 1 tile for 1D and 4 tiles for 4D. Though tile 1 to 2 does not touch G it projects a line that depicts 4 tiles for 4D. By extension, all the other tiles not touching G also project lines on the picture surface for 1D that depict 4 times as many tiles on the ground for 4D. In sum, increase the viewing distance Z-fold and the tiles are depicted as increasing Z-fold in the z-dimension. We must stress that this is a geometrical analysis, a preliminary to studies on perspective's effects in perception. The reader is invited to examine Figure 1 from near and far, from say 4D to 10D. Does the tile with side G to P seem to stretch and contract? It clearly does not stretch much. Vision is quite "robust" (Kubovy, 1986) under some changes in perspective projection (Rosinski and Farber, 1980). Vision's wide tolerance ranges allow correct projection and sizable departures from it to be equivalent, for reasons still unclear. Our straightforward similar-triangles analysis may make the problem plain and intriguing to many in perception research. References Kennedy, J. M. and Juricevic, I. (2002). Foreshortening gives way to forelengthening. Perception, 31, 893-894. Kubovy, M. (1986). The psychology of perspective and Renaissance art. Cambridge: Cambridge University Press. Rosinski, R. R. and Farber, J. (1980). Compensation for viewing point in the perception of pictured space. In M.A. Hagen (Ed.) The perception of pictures. Vol 1. New York: Academic Press (pp. 137-176). Sedgwick, H. A. (1991). The effects of viewpoint on the virtual space of pictures. In S. R. Ellis (Ed.) Pictorial communication in virtual and real environments. London: Taylor & Francis (pp. 460479).

Studies in Perception and Action VII S. Rogers & J. Effken (Eds.) ©2003 Lawrence Erlbaum Associates, Inc.

Viewing Pictures from Too Far: When are Tiles Perceived Square? Igor Juricevic & John M. Kennedy University of Toronto, Canada How does vision use information for 3-D in a 2-D picture? Consider a perspective picture of a series of square tiles viewed at X times the correct vantage point (see Figure 1, from Kennedy and Juricevic, 2002). Five possible solutions are considered. The first is the perspective solution. If the visual system used this solution, the tiles would appear to be rectangular, rather than square, with a length X times longer than the width (Kennedy and Juricevic, this volume).

Figure 1. Panoramic picture depicting a series of square tiles. Notice that the angle between the lines depicting the right and bottom edges of a tile is the same for all tiles in a column.

Compensation theory holds that the visual system determines the correct vantage point and perception coincides with what would have been perceived at the correct vantage point. If so, the tiles would appear to be square, even at X times the correct distance. Invariant theory of picture perception proposes that invariant geometrical relations specify the depicted 3-D world. These do not

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change when vantage point changes. If so, the tiles would always appear to be square, even at X times the correct distance. The "Size-on-Page" solution predicts that the tiles would appear square wherever foreshortening occurs, that is, where receding edges are depicted by an oblique line that is not larger than the horizontal line used to depict the edge that is parallel to the picture plane, referred to as the "bottom edge". Where the opposite of foreshortening "forelengthening" - occurs, the tiles would not appear square (Kennedy and Juricevic, 2002). An "On-Page & Visual Angle" solution employs visual angle ratios (of the lines used to depict the receding and bottom edges of a tile), and the angle on-the-page of the lines used to depict the receding and bottom edges of a tile. For any column of tiles, this on-the-page angle will be equal for each tile in the column (see Figure 1). The onthe-page angle for a single column determines a range of visual angle ratios that will be perceived as square tiles. Any visual angle ratios outside of this range will not be perceived as square tiles. The range of accepted visual angles for each on-page angle is not arbitrary. Rather it is the range of visual angle ratios that would have been produced from that column of tiles if the picture were viewed at the correct vantage point. To test between these five proposed solutions to the problem of perspective picture perception, subjects viewed a picture of square tiles from 6.4 times the correct vantage point and judged then as looking like square tiles, or not. Method There were 8 participants (6 female) (X = 18.6 years, SD = 0.5). A perspective panorama showed square tiles receding in depth (Figure 1). A different tile was highlighted in each. Each tile in the nine leftmost columns was highlighted once. A chin-rest fixed the vantage point of the subjects at 54.1 cm from the pictures, 6.4 times the distance of the correct vantage point (8.5 cm). Participants judged whether or not the depicted tile appeared to be a square tile. Results and Discussion Figure 2 shows the percentage of participants judging each tile as square. The percent accuracy with which each proposed solution

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Figure 2. Percentage of participants judging each tile to be square. Black dots represent tiles that the "On-Page & Visual Angle" theory predicted would be judged as square. The massive changes in judgments of "squareness" are best predicted by the "On-Page & Visual Angle" theory (see Table 1).

predicted the pattern of the subjects' responses is provided in Table 1, with "over 50%" on Figure 2 the criterion for "judged to be square". The "On-Page & Visual Angle" theory explains a higher percentage of the results than any of the other solutions. Most impressive is the theory's ability to predict large changes in the appearance of "squareness" for very small changes in size-on-page (see Figure 2). The performance of the theory for forelengthened tiles may, perhaps, be improved by considering optic array angles. It may be that the angle between the visual angles of the lines depicting the tile edges, rather than the on-page angle, is the key underlying factor. The on-page angle approximates this optic array angle. The discrepancy between onpage angles and optic array angles is greatest for forelengthened tiles, and may be the reason why the accuracy of the predictions of the theory begins to fall for forelengthened tiles.

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All Tiles

Foreshortened Tiles

Perspective Compensation

42 58

29 71

Invariant

58

71

Size-on-Page

76

71

On-Page & Visual Angle

82

83

Table 1. Percentage of subjects' responses predicted correctly by each proposed solution, if over 50% on Figure 2 is taken as criterion for "judged to be square".

References Kennedy, J. M. & Juricevic, I. (2002, November). Foreshortening and "forelengthening": Overestimated and underestimated? Poster presented at the Annual Meeting of the Psychonomic Society, Kansas City, KS. Kennedy, J. M. & Juricevic, I. (2002). Foreshortening gives way to forelengthening. Perception, 31, 893-894.

Studies in Perception and Action VII S. Rogers & J. Effken (Eds.) ©2003 Lawrence Erlbaum Associates, Inc.

Frequency and Amplitude are Inversely Related in Circle Drawing Shannon D. (Robertson) Ringenbach1, Polemnia G. Amazeen2,

& Eric L. Amazeen2 1 2

Department of Kinesiology, Arizona State University, USA Department of Psychology, Arizona State University, USA

While performing many continuous rhythmic tasks, adults demonstrate an inverse relationship between the amplitude and frequency of their movements (e.g., wrist-pendulum movement - Beek, Schmidt, Morris, Sim, & Turvey, 1995; wristflexion-extension- Kay, Kelso, Saltzman, & Schoner, 1987). That is, amplitude decreases as rate increases. One explanation of the inverse relation is that the drop in amplitude may serve to mediate an upcoming phase transition (Beek et al., 1995; Kay et al, 1987). There is some question, though, as to whether this relation appears in all tasks (e.g., finger tapping, circle drawing). In particular, Ringenbach and Amazeen (2003) found that when amplitude and frequency were manipulated in bimanual circle drawing, adults maintained a fairly constant frequency-amplitude relation, whereas children showed a positive frequency-amplitude relation. These results did not support the inverse frequency-amplitude relation found with other tasks. Kadar, Schmidt, and Turvey (1993) have suggested that the frequency-amplitude relation may differ between people or tasks. Most demonstrations of the frequency-amplitude relation use unimanual movements constrained to one dimension (e.g., wrist flexion; elbow flexion). This relation has not been examined in a two dimensional multi-joint movement, such as circle drawing, nor has it been examined in many bimanual tasks. Thus, the aim of the present study is to determine if the inverse frequency-amplitude relation exists in both unimanual and bimanual circle drawing. Participants varied movement amplitude freely as they paced their circle drawing movements to an auditory metronome whose frequency either increased or decreased. Evidence that the relation holds in either metronome

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direction will indicate an independence of the relation from phase transitions. Method Eleven right-handed adults (MAge = 24.2 years) drew both unimanual and bimanual circles to the pace of an auditory metronome. Unimanual circles were performed with both the left and right hands. The auditory metronome either increased or decreased in frequency over four 30-s plateaus (0.77 Hz, 1.0 Hz, 1.43 Hz, 2.5 Hz) for a total trial duration of two minutes. There were two trials per condition. Kinematic data from each index finger were collected using a 3-dimensional electromagnetic tracking device (Polhemustm) interfaced with data acquisition software (Skill Technologiestm). Frequency and amplitude of the movements were analyzed in both the x and y dimensions. Results As expected, the manipulation of metronome frequency produced changes in movement frequency, F(3,30) = 1114.79, p<.0005 (M2.5 = 1.93 Hz, M1.43 = 1.47 Hz, M1.0 = 0.97 Hz,_M0.77 = 0.8 Hz). Figure 1 depicts the expected main effect of frequency on amplitude, F(3,30) = 13.80, p<.0005.

Figure 1. Mean amplitude in the x dimension for circle drawing as a function of frequency and hand.

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As predicted from research on other tasks, amplitude decreased as frequency increased (M0.77 = 9.5 cm, M1.0 = 9.0 cm, M1.43 - 8.1 cm, M2.5 = 6.9 cm). This effect was apparent for both hands, although there was an interaction of hand and frequency, F(3,30) = 3.58,p < .03. As can be seen in Figure 1, there were differences between the left and right hands at the slowest frequency (0.77 Hz) (t = 2.18, p = .05), with the left hand producing larger movements than the right hand. There was also an interaction of task and hand on amplitude, F(l,10) = 9.85, p < .02. As can be seen in Figure 2, the left hand was larger in amplitude than the right hand for unimanual tasks (t = 2.4, p<.05) but the reverse was true for bimanual tasks (t = 2.5,p<.05). There was no interaction of metronome frequency and direction (increasing or decreasing), F(3,30) = 1.05, p = .39, suggesting that the frequency-amplitude relation holds regardless of whether the metronome increases or decreases.

Figure 2. Mean diameter in the x dimension of circle drawing as a function of hand and task.

Conclusions These results demonstrate that the inverse frequency-amplitude relation holds for increasing and decreasing metronomes and for unimanual and bimanual circle drawing. The finding that the frequencyamplitude relation holds for either metronome direction indicates that the relation's role is not only as a mechanism for transitions. In addition, the change from a single-joint one-dimensional movement to a multi-joint multidimensional movement does not necessarily invalidate

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this relationship. There were differences between the left and right hands in the amplitude of movement across task and frequency. In each case, these results may be related to the fact that the preferred (right) hand has more precise fine motor control than the nonpreferred (left) hand. Despite these differences in mean amplitude, though, the inverse frequency-amplitude relation was evident for both hands. Thus, twodimensional multi-joint movements appear to have similar dynamics as one-dimensional single-joint movements. References Beek, P. J., Schmidt, R. C, Morris, A. W., Sim, M.-Y., & Turvey, M. T. (1995). Linear and nonlinear stiffness and friction in biological rhythmic movements. Biological Cybernetics, 73, 499-507. Kadar, E. E., Schmidt, R. C., & Turvey, M. T. (1993). Constants underlying frequency changes in biological rhythmic movements. Biological Cybernetics, 68,421-430. Kay, B. A., Kelso, J. A. S., Saltzman, E. L., & Schoner, G. (1987). Space-time behavior of single and bimanual rhythmical movements: Data and limit cycle model. Journal of Experimental Psychology: Human Perception and Performance, 13, 178-192. Peper, C. E., & Beek P. J. (1998). Are frequency-induced transitions in rhythmic coordination mediated by a drop in amplitude? Biological Cybernetics, 79, 291-300. Ringenbach, S. D. R. & Amazeen, P. G. (2003). Rate and amplitude of bimanual circle drawing are positively related in children. Manuscript submitted.

Studies in Perception and Action VII S. Rogers & J. Effken (Eds.) ©2003 Lawrence Erlbaum Associates, Inc.

Learning and Transfer across Different Effector Systems: The Example of Goal-Directed Displacement Tasks C. Camachon, G. Montagne, M.J. Buekers, and M. Laurent Universite de la Mediterranee, Marseille, France Different series of experiments, conducted from different theoretical approaches, provide evidence for effector-independent learning (e.g., Grafton, Hazeltine & Ivry 1998; Kelso & Zanone, 2002; Tresilian & Stelmach, 1997). Effector-independent learning refers to the idea of a common base when learning visuo-motor actions whatever the effector system used. Most traditional studies were based on simple visuo-motor coordinations performed in an impoverished environment. The purpose of the present study is to extend the former findings to goaloriented displacement tasks in a rich environmental context. Previous results (Montagne et al., in press; Camachon, et al., submitted) show that the effector system involved in the execution of a goal-directed action does not modify the nature of the visuo-motor transformations induced through learning. We thus argued that the operation of the informationmovement cycle underlying the control mechanism of action, could be situated at a non effector-specific level. Because of this, we hypothesized that visuo-motor transformation following learning could be transferred from a trained effector system towards an untrained one. The present study examines whether a transfer of learning occurs between two very different kinds of displacement mode, i.e., walking or handling of a joystick. Method Sixteen participants (M age = 25.62, SD = 3.85) were separated into two experimental groups of equal size. A virtual reality set-up was used in which participants could move forward through a hallway by either walking on a treadmill or handling a joystick, and had to pass through a pair of swinging doors (frequency rate of 1 Hz). The required time-window allowing correct crossings was 188 ms. After every door

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passing, performance feedback was given to the participants. Prior to training, a pre-test was performed on both effector systems (Walking and Joystick). After a ten-day training period, corresponding to 1200 trials, participants submitted to a post-test with the trained effector system. Finally, they were tested on transfer of learning with the untrained effector system. Subjects in the first group were trained to walk on the treadmill (Tr. Walk.) and tested with the joystick (T. Joy.). This order was reversed for the subjects in the second group (Tr. Joy. T. Walk.). Data were digitized at 200 Hz. In the analyses, all trials (i.e., successes and failures) were used. Results Percentage of successes: A two-way repeated measures ANOVA with Tests (Post-tests, Transfer tests) as a within-subject factor and Group (Tr. Walk - T. Joy vs. Tr. Joy - T. Walk) as between-subject factors, revealed a significant main effect for Test (F(l,14) = 20.64, p<.05). Moreover, the Groups x Tests interaction was also significant (F(l,14) = 32.71, p<.05). Newman-Keuls a posteriori tests revealed a decrease in performance on the Joystick transfer test (T. Joy = 37.9%) compared to the treadmill post-test (Tr. Walk = 81.23%), while the performance was similar in the joystick post-test (Tr. Joy = 58.31%) and the treadmill test transfer (T. Walk = 63.28%). Velocity variability: A three-way repeated measures ANOVA with Tests (Post-tests, Transfer tests) and TTC (Time-to-contact) as within-subject and Group (Tr. Walk - T. Joy vs. Tr. Joy - T. Walk) as between-subject factors revealed a significant main effect for Groups (F(l,14) = 4.94, p<.05), Test (F(l,14) = 27.85, p<.05) and TTC factors (F(9,126) = 56.98, p<.05). In these analyses, data were ordered from TTC-10, representing the variability of the velocity at 5 s before crossing, to TTC-1, representing the variability of the velocity at 0.5 s before crossing. An increase of this variable traduces some visually driven displacement regulations at the approach of the doors crossing. The Groups x Tests x TTC interaction was also significant (F(9,126) = 2.01, p<.05). Newman-Keuls a posteriori tests showed, for the Tr. Walk - T. Joy group, an increase of the displacement velocity variability during the last 1.5 s of the approach in the post-test. In contrast, no variations were observed in the transfer test. On the other hand, the results for the Tr. Joy - T. Walk group showed also an increase of the velocity variability

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whatever the test, in the last 1.5 s of the approach (Figure 1). Consequently, the kind of transfer is different depending on the effector system used.

Figure 1. Time course of the velocity variability for the last 5 seconds of the approach in each test for each group. The results reveal an increase of the displacement velocity variability in the last 1.5s, in the post-test treadmill, posttest joystick and transfer treadmill. In contrast, no variations were observed for the transfer joystick.

Discussion This study was designed to investigate whether the learning of goal-directed displacements was effector-independent. More precisely, we wanted to find out whether the task could be performed in a comparable way by an untrained effector system as by a trained effector system. When we observe the behavior at the end of the learning period, it appears that both groups are comparable whatever the effector system used. These findings support the hypothesis that participants have access to informational support to perform the task whatever the effector system used. However, while a good transfer of learning occurs for the Tr. Joy - T. Walk group, suggesting that the informational support is used with the untrained effector system, there is no transfer of learning for the Tr. Walk - T. Joy group. We thus suggest that the problem could be located on the motor side. We can wonder whether the lack of the transfer from the treadmill to the joystick is not due to the time scale necessary to learn the handling of a joystick. Obviously, we are much more comfortable when we use our whole body than when we are obliged to handle a device, when we are engaged in a goal-directed

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displacements tasks. Additional work is required to identify precisely the reasons for asymmetrical transfer of learning. References Camachon, C., Montagne, G., Buekers, M.J., & Laurent, M. (Submitted). How far can one go to define the general nature of control mechanisms underlying the learning of goal-directed displacements? Grafton S.T., Hazeltine E., & Ivry R.B. (1998). Abstract and effectorspecific representations of motor sequences identified with PET. Journal of Neuroscience, 18, 9420-9428. Kelso J.A., & Zanone P.G. (2002). Coordination dynamics of learning and transfer across different effector systems. Journal of Experimental Psychology: Human Perception and Performance, 28, 776-97. Montagne, G., Buekers, M.J., Camachon, C., De Rugy, A., & Laurent, M. (in press). The learning of goal-directed locomotion: A perception-action perspective. Quarterly Journal of Experimental Psychology A. Tresilian, J. R. and Stelmach, G. E. (1997). Common organization for unimanual and bimanual reach-to-grasp tasks. Experimental Brain Research, 115(2), 283-99.

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Hierarchical Control of the Bimanual Gallop Martine H.G. Verheul1 and Reint H. Geuze2 'Centre for Biophysical and Clinical Research into Human Movement (CRM), Manchester Metropolitan University, UK 2 University of Groningen, The Netherlands In asymmetric bimanual tasks, such as opening a bottle, the two hands have different roles. One, usually the non-preferred hand, takes on a supporting role (holding the bottle), whereas the other, usually the preferred hand, performs the action that is the actual goal of the movement (opening the bottle). For asymmetric tasks like this, it has been hypothesized that a hierarchical control underlies the action (Guiard, 1987). There is evidence that a similar hierarchical control mechanism underlies multi-frequency coordination tasks (Byblow & Goodman, 1994; Peper et al., 1995; Summers et al., 1993). In such a task, the two hands perform the same movement, but at different frequencies. The faster hand has been shown to have more influence on the slower hand than vice versa. Thus, the faster hand is the leading hand, and the movements of the slower hand are subordinate. This effect is independent of hand arrangement (i.e., whether the preferred or nonpreferred hand moves faster). However, if the non-preferred hand is leading, i.e. moving faster, task performance deteriorates profoundly (shown for right-handers by Byblow & Goodman, 1994; Peters, 1981). It is unclear whether this deterioration in performance is a result of the difference in frequency between the hands or of the associated hierarchical control mechanism. What if the frequency is not different, but the pattern is asymmetric nevertheless? Is asymmetry in the phase relation alone enough to induce a hierarchical control mechanism? If so, does coordination deteriorate when the non-preferred hand takes on the leading hand-role? To answer these questions, we studied bimanual tapping in a gallop pattern. As yet, studies on the bimanual gallop (e.g., Peck & Turvey, 1997) have not systematically compared both hand-role

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distributions. The anti-phase was included in the study as a control condition. Method Twenty-four participants performed a bimanual tapping task. On the basis of a handedness questionnaire, participants were classified as either consistently left-handed (n = 11) or consistently right-handed (n = 13). They tapped 8 trials in each of the following three configurations: anti-phase (180° phase difference), left-gallop (left hand a quarter of a cycle ahead), and right-gallop (right hand a quarter of a cycle ahead). Trials were randomized. During the first 6 cycles of each trial, both hands were paced with a frequency of 1.25 Hz. Participants were instructed to continue tapping as consistently as possible after pacing stopped until the signal to stop was given by the experimenter after 21 non-paced cycles. Only these non-paced cycles were used in the analysis. To investigate whether a hierarchical control mechanism could be identified in the gallop, correlations between adjacent between-hand inter-tap intervals were analyzed. Thus, the interval between a righthand tap and a left-hand tap (interval RL) was correlated with the subsequent interval between a left-hand tap and a right-hand tap (interval LR), giving the correlation between the interval pair RL-LR for each trial. Similarly, the correlation was calculated between the interval pair LR-RL for each trial. If one hand is leading and the taps of the other hand are interlaced, this would be revealed by a difference between the two correlations within a pattern. The quality of task performance was calculated as the variability (i.e. standard deviation) of the inter-tap intervals and the variability of the relative phase between the hands. A repeated measures ANOVA was performed on the data (with a Greenhouse-Geisser correction when the assumption of sphericity was violated). The significance level was set at a = .05. Results The results of the correlation analysis are depicted in Figure 1. In the anti-phase, the correlation between intervals LR and RL was not significantly different from the correlation between intervals RL and LR (F(l,22) = .003, p>.1). For the gallop patterns, however, a significant interaction was found between interval-pair and gallop pattern (F(l,22) =

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12.54, p<.01). In the left-gallop, the correlation between intervals LR and RL was more negative than the correlations between intervals RL and LR, whereas in the right-gallop, the reverse was found. No significant interaction was found between phase pattern and hand-preference for relative phase variability or inter-tap interval variability that would indicate a decrement in performance related to hand arrangement in the gallop (F(l, 22)= .37, n.s; F(l,22) = .46, n.s.).

Figure 1. Correlations between adjacent intervals: R = right-hand tap, L= lefthand tap.

Discussion The gallop pattern is hierarchically controlled. In the left-gallop, the timing of the right hand was more dependent on the timing of the left hand than vice versa. In the right-gallop, the timing of the left hand was more dependent on the timing of the right hand than vice versa. Thus, in the left-gallop, the left hand was leading and taps of the right hand were interlaced, and in the right-gallop the reverse was the case. No such hierarchical control was found in the anti-phase pattern. It has to be noted that the results do not support a completely unidirectional control model for the gallop. We found only moderate correlations (around -.30) for LR-RL in the left-gallop and RL-LR in the right-gallop. Moreover, the other correlations for the gallop were not zero, but distinctly negative. These results suggest that the leading hand is also timed relative to the non-leading hand to some extent. In contrast to findings from multi-frequency studies, no deterioration in performance was found when the non-preferred hand took on the leading

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hand-role. This suggests that the deterioration reported in multifrequency studies (at least in the tapping studies, i.e. Peper et al., 1995 and Summers et al., 1993) may be due to the difference in frequency between the hands rather than the hierarchical control mechanism. References Byblow, W.D., & Goodman D. (1994). Performance asymmetries in multifrequency coordination. Human Movement Science, 13, 147-174. Guiard, Y. (1987). Asymmetric division of labor in human skilled bimanual action: the kinematic chain as a model. Journal of Motor Behavior, 19, 486-517. Peck, A. J.,& Turvey, M. T. (1997). Coordination dynamics of the bipedal galloping pattern. Journal of Motor Behavior, 29, 311325. Peper, C. E., Beek P. J.,& van Wieringen, P. C. W. (1995). Multifrequency coordination in bimanual tapping: asymmetrical coupling and signs of supercriticality. Journal of Experimental Psychology: Human Perception and Performance, 21, 11171138. Peters, M. (1981). Attentional asymmetries during concurrent bimanual performance. Quarterly Journal of Experimental Psychology, 37A, 171-196. Summers, J. J., Rosenbaum, D. A., Burns, B. D., Ford, S. K. (1993). Production of polyrhythms. Journal of Experimental Psychology: Human Perception and Performance, 19, 416-428.

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Visual Basis of Directional Constraint in Hand-Foot Coordination Dynamics R. Salesse, J.J. Temprado, and M. Laurent Universite de la Mediterranee et CNRS, Marseille, France It is widely accepted that the coordination of movement is founded upon a system of constraints of musculoskeletal, neural, perceptual and cognitive origins (Kelso, 1995). Most research on interlimb coordination has focused on muscular constraints, i.e. the relative timing of homologous muscle activation and mechanical context of the task. However, other studies have also shown that coordination between upper and lower limb movements is subject to considerable directional constraints (Baldissera et al., 1982, 1991; Kelso & Jeka, 1992). In this situation, direction of limb movements in the external space determines both pattern stability and phase transitions, independently of the muscle activation pattern. However, the question remains whether the stability of hand-foot coordination patterns can be accounted for, at least partially, by differences in the visual perception of the relative direction of moving limbs in the external space. The present study addresses this issue. Method Participants were seated on a multi-articular chair (see Temprado et al., submitted, for details). They performed both hand extension/flexion associated with foot dorsi-flexion/plantar-flexion and hand extension/flexion associated with foot plantar-flexion/dorsi-flexion, with the forearm either in prone or supine position. Four patterns were performed depending on the forearm position. The two types of muscular coupling corresponded either to isodirectional (in-phase) or non-isodirectional (antiphase) movements. In the prone position, isodirectional pattern corresponded to simultaneous activation of hand extensors/flexors and foot dorsi-flexors/plantar-flexors (homologous) and non-isodirectional pattern to simultaneous activation of hand

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extensors/flexors associated with foot plantar-flexors/dorsi-flexors (nonhomologous). In the supine position, the simultaneous activation of the same group of muscles corresponded respectively to non-isodirectional (homologous) and isodirectional (non-homologous) patterns. Participants manipulated a joystick (150°) with the forearm strapped to a shaft preventing intrusive movements. The position of each limb compelled subjects to see their foot and hand simultaneously. In each trial, oscillation frequency increased progressively (1.0, 1.5, 2.0, 2.5, 3.0 Hz). The four coordination patterns were performed in full-vision and blindfolded conditions. Subjects were instructed to maintain the pattern until they felt that phase transition would be more comfortable to perform the task. Wrist and ankle positions were digitized at 200 Hz. Results Two dependent variables were analyzed: (1) number of phase transitions and (2) variability of the relative phase. 2 (muscular coupling) x 2 (direction) x 2 (vision) x 5 (frequency) ANOVAs were carried out.

Figure 1: Percentage of phase transitions.

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The analysis of the percentage of phase transitions revealed that: (1) no transition occurred for isodirectional pattern whatever the type of muscular coupling (in-phase/anti-phase) (2) in full vision and nonisodirectional condition, the number of phase transitions was higher for anti-phase than for in-phase patterns; (3) such a difference was attenuated in blindfolded condition since the number of phase transitions increased significantly for the in-phase pattern (figure 1). The analysis of relative phase variability revealed the same trend: (1) in full vision, non-isodirectionality destabilized the anti-phase pattern more than the in-phase pattern; however, in blindfolded condition, such a destabilizing effect was attenuated, (2) removing vision induced an increase of relative phase variability for the in-phase in the non-isodirectional condition and for the anti-phase in the isodirectional condition, (3) variability decreased for the anti-phase in the non-isodirectional condition (figure 2).

Figure 2. Standard deviations of relative phase. Discussion

These results confirmed that, in hand-foot coordination, isodirectional patterns are more stable than non-isodirectional. It appeared that though hand-foot coordination dynamics are strongly

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influenced by directional constraint, muscular coupling also impacts on the number of phase transitions. Moreover, the direction-dependent dynamics seems to be mediated by visual perception of the relative direction of limb movements. In the supine position, removing the vision of hand and foot movements resulted in a decrease of relative phase variability of non-isodirectional coordination pattern. But in both prone and supine positions, removing the vision resulted in an increase of relative phase variability of isodirectional pattern. These results suggest that vision of moving limbs contributes either to destabilize or to stabilize coordination patterns. It has been hypothesized for a long time that hand-foot coordination mainly depended on kinaesthetic afferences (Baldissera et al., 1982). Our results suggest that direction dependent dynamics are also mediated by visual afferences. Such a mediated effect may complement the role of central influences in transitions from nonisodirectional to isodirectional pattern (Baldissera et al., 2002). References Baldissera, F., Cavallari, P., Civaschi, P. (1982). Preferential coupling between voluntary movements of ipsilateral limbs. Neuroscience Letter, 34, 95-100. Baldissera, F., Cavallari, P., Marini, G., Tassone, G. (1991). Differential control of in-phase and anti-phase coupling of rhythmic movements of ipsilateral hand and foot. Experimental Brain Research, 83, 375-380. Baldissera, F., Cavallari, P. (2002). Impairment in the control of coupled cyclic movements of ipsilateral hand and foot after total callosotomy. Acta Psychologica, 110, 289-304. Kelso, J.A.S., Jeka, J.J. (1992). Symmetry breaking dynamics of human multilimb coordination. Journal of Experimental Psychology: Human Perception & Performance, 18(3), 645-68. Kelso, J.A.S. (1995). Dynamic Pattern: The Self-Organization of Brain and Behavior. Cambridge, Mass: MIT Press. Temprado, J.J., Swinnen, S., Tourment, A., Laurent, M. (Submitted.) Bimanual coordination is not purely perceptual in nature: Interacting effects of visuospatial, neuromuscular and egocentric constraints on the stability of preferred coordination patterns.

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The Role of Visual and Kinesthetic Information in Bimanual Coordination Jeff Summers, Rebecca Wade-Ferrell, & Florian Kagerer School of Psychology, University of Tasmania, Australia Recently the mechanisms underlying bimanual coordination phenomena (i.e., symmetry, transitions) have been the subject of much debate. In particular, the view that such phenomena reflect coordinative processes in the motor system (Kelso, 1995) has been challenged by the hypothesis that the symmetry tendency is purely perceptual in nature (Mechsner et al., 2001). The present experiment was designed to further examine the interaction between vision and kinesthesis in the control of bimanual movements in a circle drawing task. Verschueren et al. (1999) have argued that in tasks such as bimanual circle drawing, the spatial and temporal characteristics of the movements are independently controlled. Disruption of proprioception through tendon vibration increased the phase offset between the limbs suggesting that synchronisation between the limbs is dependent on proprioceptive information. There is also some evidence that visual information can offset reduced proprioception in a hemiparetic limb following stroke. Sathian et al. (2000) applied a technique involving placing a mirror vertically at the patient's midline (midsagittal plane) (see also Altschuler, et al., 1999). During mirror therapy the patient makes bilateral movements and is instructed to look at the mirror reflection of their unimpaired limb rather than at their paretic limb. Improvement in the motor functioning of the affected limb both during and after mirror therapy was reported. It was suggested that the mirror provides patients with 'proper' visual input and may substitute for the decreased or absent proprioceptive input from the impaired arm. The aim of the present study was to examine the effect of illusory visual feedback provided by a mirror on the bimanual coordination of healthy subjects. Bimanual circle drawing was chosen because previous studies have shown strong manual asymmetries in performance of this task, with the non-dominant hand exhibiting poorer performance than the dominant hand and being the initiator of most

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spontaneous transitions between coordination modes (see Cattaert et al., 1999). Of particular interest was whether the performance of the nondominant hand would improve when it was unseen and subjects view a reflection of their dominant limb performing the task. A further question was whether during asymmetrical (anti-phase) coordination, illusory visual information indicating that the two hands are circling symmetrically (in-phase) would trigger a phase transition in the unseen hand. Method Twelve right-handed subjects performed a continuous bimanual circling task in symmetrical (left hand clockwise, right hand anticlockwise) and asymmetrical (both hands anticlockwise) coordination modes. Visual feedback was manipulated using three vertical screens placed in the midsagittal plane thereby separating the left and right limbs at the midline. In the Normal condition a transparent screen allowed full vision of both hands; in the Occluded condition an opaque screen occluded vision of one hand during circling; and in the Illusory condition a mirrored screen not only occluded one hand but provided a reflection of the seen hand circling. An equal number of trials in each condition were performed with the subjects' head positioned on either the left side or right side of the screen. The combination of orientation (2), visual feedback (3), and coordination mode (2), yielded 12 experimental conditions. Five trials (20 sec. each) were presented for each condition. An auditory metronome paced movements at 1.5 Hz and finger trajectories were recorded with an Optotrak position sensor system. Results The percentage of asymmetrical trials in which a phase transition occurred was significantly greater in the Illusory feedback condition (38%) than in the Occluded (14%) or Normal (9%) feedback conditions. A further breakdown of transitions in the Illusory condition revealed that the majority of the direction reversals were effected through the unseen hand, whether it was the non-dominant (100% of transitions) or dominant (64% of transitions) hand. Temporal coupling (relative phase) between the hands was not affected by the visual feedback manipulations, although anti-phase coordination was more

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stable (uniformity of relative phase) when one hand was unseen (occluded and illusory feedback conditions) than under normal feedback conditions.

Figure 1. Mean aspect ratio for dominant and non-dominant hand movements across the three visual feedback conditions during symmetrical circling. An aspect ratio of 1 indicated a perfect circle, an aspect ratio of 0 a straight line.

With regard to the spatial characteristics of the hand movements, trajectory circularity (aspect ratio) was higher in the normal (.73) than in the occluded (.70) or illusory (.64) feedback conditions. Of particular interest was the effect of illusory visual feedback on non-dominant hand performance during symmetrical circling (the mirror-therapy effect). A significant 3-way interaction between Visual Feedback, Hand, and Orientation, F(2,20) = 1.18, p<.01 for aspect ratio is shown in Figure 1. For the Right-Side Orientation, aspect ratio of the non-dominant (left) hand decreased when it was occluded and showed a further decrease

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when subjects viewed their dominant hand in the mirror. Interestingly, the dominant hand also showed a significant decrease in circularity under the illusory feedback condition. For the Left-Side Orientation, the dominant (right) hand showed significant decreases in aspect ratio to the level of the non-dominant hand under the occluded and illusory feedback conditions. Discussion The present study confirms the important role of visual information in the coordination of bimanual movements. Incongruence between visual and kinesthetic feedback frequently resulted in a phase transition by the unseen hand. The results also indicated that the manipulation of visual information had a stronger effect on the spatial characteristics than the temporal aspects of bimanual movements. There was no evidence that viewing the mirror reflection of one limb enhanced the performance of the unseen limb. Rather spatial performance of the unseen hand (dominant or non-dominant) significantly decreased in the illusory compared to the normal visual feedback condition. References Altschuler, E. L., Wisdom, S. B., Stone, L., Foster, C., Galasko, D., Lewellyn, M. E., & Ramachandran, V. S. (1999). Rehabilitation of hemiparesis after stroke with a mirror. The Lancet, 353, 20352036. Cattaert, D., Semjen, A., & Summers, JJ. (1999). Simulating a neural cross-talk model for between-hand interference during bimanual circle drawing. Biological Cybernetics, 81, 343-358. Kelso, J.A.S. (1995). Dynamic patterns: The self-organization of brain and behavior. Cambridge, MA: MIT Press. Mechsner, F., Kerzel, D., Knoblich, G., & Prinz, W. (2001). Perceptual basis of bimanual coordination. Nature, 414, 69-73. Sathain, K., Greenspan, A.I., & Wolf, S.L. (2000). Doing it with mirrors: A case study of a novel approach to neurorehabilitation. Neurorehabilitation and Neural Repair, 14, 73-76. Verschueren, S.M.P., Swinnen, S.P., Cordo, P.J., & Dounskaia, N.V., (1999). Proprioceptive control of multijoint movement: bimanual circle drawing. Experimental Brain Research, 127, 182-192.

Studies in Perception and Action VII S. Rogers & J. Effken (Eds.) ©2003 Lawrence Erlbaum Associates, Inc.

The Ecological Meaning of Spatial Symmetry in Bimanual Motor Coordination T.-C. Chan, C.-Y. Tse, H.-Y. Yue, & L.-Y. Fan The Chinese University of Hong Kong When the oscillation frequency of two swinging fingers is systematically increased, only the in-phase mode is found stable (Kelso, 1981). Oscillation in the anti-phase mode will shift to the in-phase mode beyond a critical frequency. Competing explanations have been suggested for such a critical phase shift. Cohen (1971) asserted that there is stronger coupling between bilateral identical muscles (homologous). However, Mechsner, Kerzel, Knoblich, and Prinz's (2001), revealed that spatial symmetry is a more comprehensive explanation. In one of their, experiments, in-phase movement with non-homologous muscle was found to be more stable than anti-phase movement with homologous muscle. In the current experiments, we explored the ecological meaning of spatial symmetry with bilateral movement. Usually, when one hand moves in a task, the non-task hand would move concomitantly in a direction to keep body balance. This counterbalancing function would constrain bimanual coordination in spatial symmetry. This constraint may occur as a reflex, particularly when postural stability is compromised. Second, for frequently occurring tasks such as grasping or holding, the power strokes for both hands are inward-bound. Even nontask oscillation may refer to such grasping behavior with the inward stroke being more forceful. The more forceful strokes of the swing would synchronize with each other. We suspected that these two constraints underline spatial symmetry in coordination. Experiment 1 To explore the effect of posture equilibrium in bimanual coordination, we had participants swung their forearms left and right rhythmically in two different conditions of posture equilibrium: unstable

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and stable. If postural equilibrium has an effect on bimanual motor coordination, the critical frequency was expected to be lower in the unstable condition. Method Eleven undergraduates of the Chinese University participated in this experiment. All of them were right-handed. To measure the trajectory and thus the phase difference between the two forearms in continuous motion, an Optotrak 3020 was used. An emitter was attached to each fist for movement tracking. The sampling rate was 200 Hz. Two computers were used, one for recording the coordinates of emitters, and the other for acting as a metronome with the Wave program. In each trial of the experiment, participants swung their forearms horizontally at a specific range of metronome frequency. Four frequency ranges (1.6 to 2.2 Hz, 2.0 to 2.6 Hz, 2.4 to 3.0 Hz, 2.8 to 3.4 Hz) were used. In all ranges, frequency increased with a step of .1 Hz for 7 sec. Participants started in each trial by moving their forearms simultaneously to one side (anti-phase mode) and tried to maintain the phase. Participants were informed that the frequency would increase during the course of the trial and they were required to follow it to the best of their ability even if it could only be maintained with in-phase coordination. Participants took part in both conditions in random order. In the stable condition, participants sat on a swivel stool with their feet resting on the ground to increase stability. In the unstable condition, participants sat on the same swivel stool with their legs crossed and off the ground. Postural stability could thus be upset easily in moving the two forearms in the same direction. From the data of all the ranges, we computed the actual frequency of oscillation of each hand at which the phase difference shifted from anti-phase coordination to in-phase coordination. Results The experiment was a repeated-measure factorial design of stability (2) x hand (2). The means of the critical frequency were 2.53 (left hand) and 2.55 (right hand) for the stable condition and 2.28 (left hand) and 2.42 (right hand) for the unstable condition. Analysis of variance (ANOVA) on the critical frequency showed that only the effect of stability was significant [F(l,10) = 5.269,p<.05], indicating that state

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transition occurred at a lower frequency in the unstable condition as anticipated. Experiment 2 To explore the effect of task constraint on bimanual coordination, we had participants oscillate their index fingers left and right rhythmically to strike two poles. With anti-phase task condition, both index fingers struck the two poles in moving in the same direction (i.e., rr, or 11). With in-phase task condition, the two fingers struck the two poles in moving in opposite directions (rl or lr). With anti-phase coordination, power strokes of both fingers would concur in anti-phase task, whereas they would be in alternation in in-phase task. If the power strokes tend to synchronize together, anti-phase task would secure a higher critical frequency. Method The apparatus was similar to that used in Experiment 1, except that emitters were fixed at the tip of the index fingers of participants. Also, a board with two steel poles fixed on the surface was used for the task. Nine undergraduates of the Chinese University were recruited for this experiment. All of them were right-handed. Participants struck vertical poles with their index fingers. There were four conditions randomly assigned for each participant: rr, ll, lr/rl, and nn, where r represents striking the pole with rightward movement, 1 with leftward movement, and n represents no pole being struck in any direction. In each trial, participants tried to maintain the anti-phase coordination with the frequency of the metronome. We computed for analysis the actual critical frequency for each hand under each condition for each participant. Higher critical frequency was expected to be maintained in rr, and 11 conditions than in rl/lr or nn conditions. Results This experiment was a repeated-measures factorial design of condition (4) x hand (2). The mean critical frequencies of the left and right hand for the four conditions were 3.33 and 3.57 for 11, 2.98 and 3.13 for Ir/rl, 3.26 and 3.44 for rr, and 2.71 and 3.02 for nn. Analysis of variance (ANOVA) showed that the effect of condition was significant,

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F(3,24) = 3.946, p<..03, indicating that task constraint has an effect on the critical phase shift. Post hoc analysis showed significant differences between 11 and nn (p< .05), and rr and nn (p < .02). The difference between lr/rl and other conditions was not significant, possibly because participants adapted a strategy of striking the two poles in alternation. Discussion Results from the above experiments showed that stability in bimanual anti-phase coordination is related to postural equilibrium and task constraint. Increased postural disequilibrium prompts the critical phase shift earlier to increase equilibrium. Also, tasks with power strokes of both hand concur at anti-phase can maintain a higher critical frequency. The effect of task constraint probably reflects the steepening of the slope of the potential well (Park, Collins, & Turvey, 2001) in antiphase coordination. Thus, the location of the attractor does not change but the stability is increased. The two constraints, posture equilibrium and task constraint, underlie the preference for spatial symmetry in bimanual coordination. Acknowledgement. This research is supported by an RGC grant (#2120154) from HK awarded to the first author. References Cohen, L. (1971). Synchronous bimanual movement performance by homologous and non-homologous muscles. Perceptual and Motor Skills, 32, 639-644 Kelso, J. A. S. (1981). On the oscillatory basis of movement. Bulletin of the Psychonomic Society, 18, 63. Mechsner, F., Kerzel, D., Knoblich, G., & Prinz, W. (2001). Perceptual basis of bimanual coordination. Nature 414 (6859), 69-73. Park, H., Collins, D. R., Turvey, M. T. (2001). Dissociation of muscular and spatial constraints on patterns of interlimb coordination. Journal of Experimental Psychology: Human Perception and Performance, 27(1), 32-47

Studies in Perception and Action VII S. Rogers & J. Effken (Eds.) ©2003 Lawrence Erlbaum Associates, Inc.

Musculoskeletal Dynamics of the Wrist During Rhythmic Activity Arne Ridderikhoff1, C. (Lieke) E. Peper1, Richard G. Carson2, Peter J. Beek1 1

Vrije Universiteit, Amsterdam, The Netherlands 2 The University of Queensland, Australia

Peper and Carson (1999) reported an experiment in which subjects performed two rhythmic tasks: an isometric task involving the generation of alternating flexion-extension torques around a restrained wrist and a dynamic task involving smooth oscillatory flexion-extension movements. Both tasks were performed unimanually as well as bimanually under two pacing conditions (1.0 and 1.4 Hz). The musculoskeletal dynamics of the two tasks differs with respect to the type of muscular contraction, and with respect to the mechanical interactions between antagonist muscles. These differences may affect the temporal relationship between the control signal (EMG) and task-relevant output (torque or movement). This relationship was analyzed in the present study. Methods The analysis focussed on the unimanual (i.e., isometric and dynamic) trials. EMG records were rectified and low-pass filtered (cutoff frequency: 15 Hz) to obtain linear envelopes. Delays between these linear envelopes and the torques or movements were calculated for each of these conditions by computing the cross-correlation function. Using principal component analysis, a set of typical time-series was obtained for each condition. The thus obtained time-series for flexor and extensor EMG were used as input for a mechanical model consisting of 4 Hill-type muscles (2 flexors and 2 extensors) and a hinge joint (see Figure 1). Parameters and model equations were taken from the literature (e.g., Lemay & Crago, 1996; Van Soest & Bobbert, 1993). Simulations of the isometric task (conducted for both tempo conditions)

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allowed for relating EMG amplitude (E(t)) to the amplitude of the model input signal as aE(t)b, which involved optimization of 2 parameters per muscle group. Subsequently, joint stiffness and damping were optimized in simulations of the dynamic task (again for both tempos).

Figure 1. Top: The main components of the model. Dotted lines indicate the relations and processes that are involved in the dynamic task only. Bottom: Comparison between simulations (dashed) and experiment (solid) for both tasks. For the dynamic task the results obtained with zero stiffness and damping are also indicated (dotted).

Results The EMG was leading the isometric torque by 116 ms (1.0 Hz) and 114 ms (1.4 Hz), respectively, and the movement by 261 ms (1.0 Hz) and 239 ms (1.4 Hz). This difference in delays has implications for the simultaneous, bimanual coordination of these different tasks. For example, a relative phase of 52-63° between the neural control signals of homologous muscles would be required to achieve in-phase coordination (i.e., 0° phase difference) at the behavioral level. Mechanical analysis showed that an oscillatory movement and the corresponding torque are 180° out of phase. For the dynamical task this implied EMG-torque delays of 720 ms (1.0 Hz) and 610 ms (1.4 Hz), which was considerably larger than the electromechanical delays

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observed for the isometric task (116 ms and 114 ms, respectively) and did not correspond to typical values reported in the literature (e.g., Vos et al., 1991). However, the optimized model adequately reproduced these relations between EMG signals and the resulting torques and movements at both frequencies (r > .9, see Figure 1). The estimated joint stiffness (K = -0.61 Nm/rad) and damping (B = -0.12 Nm/rad/s) were comparable to values reported in the literature (e.g., Milner & Cloutier, 1998), and could largely account for the difference in delays (see Figure 2). In addition, reported effects of additional stiffness or mass on wrist oscillations (Baldissera et al., 1991) could also be accounted for by the model (not shown).

Figure 2. Top: The effect of joint stiffness and damping on the phase-shift (Df) between muscle torque and joint angle as a function of movement frequency. From the phase shifts at 1.0 and 1.4 Hz the contribution of the joint dynamics to the total delay can be calculated (AT). Bottom: contribution of muscle dynamics to the delay between EMG and muscle torque (black) and the contribution of joint dynamics to the delay between muscle torque and joint angle (gray).

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Discussion The analyses revealed that the musculoskeletal dynamics have a profound influence on the temporal relation between muscle activity (EMG) and the associated behavioral output. The model used for the dynamics in question allows for an explicit connection between the neural output signal and the observed behavior, so that changes in the system's properties can be evaluated in terms of the model's (temporal) input-output relation. Systematic manipulations of the system may reveal how the nervous system adapts to changes in this relation, thereby providing essential information for an understanding of the neuromuscular aspects of rhythmic (interlimb) coordination. References Baldissera, F., Cavallari, P., Marini, G. & Tassone, G. (1991). Differential control of in-phase and anti-phase coupling of rhythmic movements of ipsilateral hand and foot. Experimental Brain Research, 83, 375-380. Lemay, M.A. & Crago, P.E. (1996). A dynamical model for simulating movements of the elbow, forearm, and wrist. Journal of Biomechanics, 29, 1319-1330. Milner, T.E. & Cloutier, C. (1998). Damping of the wrist joint during voluntary movement. Experimental Brain Research, 122, 309-

317. Peper, C.E. & Carson, R.G. (1999). Bimanual coordination between isometric contractions and rhythmic movements: an asymmetric coupling. Experimental Brain Research, 129,417-423. Van Soest, A.J. & Bobbert, M.F. (1993). The contribution of muscle properties in the control of explosive movements. Biological Cybernetics, 69, 195-204.

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Recruitment in a Synchronisation Task: A Coalition of Constraints Lorene Milliex, Sarah Calvin, Jean-Jacques Temprado & Thelma Coyle Universite de la Mediterranee, Marseille, France Interlimb coordination dynamics has currently been studied in tasks involving the displacement of moving components in one plane of motion. In this context, phase transitions are considered as a re-ordering of the same biomechanical degrees of freedom (d.f), giving rise to an abrupt change of coordination pattern (e.g. anti-phase to in-phase). Another type of phase transition has been observed by Kelso and coworkers (1993) in bimanual coordination, that is the recruitment of new d.f. In these experiments, subjects performed abduction/adduction rhythmic movements of the index in the horizontal plane (X dimension). As oscillation frequency increased, movements spontaneously emerged in the vertical plane (Y dimension). Fink et al. (2000) showed that this spatial re-organization depended on the stability of the coordination pattern in the initial X dimension. Indeed, the recruitment was predominantly observed when subjects performed the anti-phase pattern (i.e., the least stable). However, the results of a recent study by Carson et al. (2001) suggested that the recruitment of a new plane of motion with increasing frequency was imposed by the structure of neuromuscularskeletal system. Thus, the question arises of how muscular and informational constraints interact in the process of recruitment of a new d.f.. This issue was addressed in the present experiment. Method Seven right-handed adults volunteered for this experiment. They performed a synchronization task, consisting of coordinating either the abduction or adduction of the right index with an auditory stimulus. These two coordination patterns were performed at different frequencies (1 Hz to 4 Hz). Haptic information was provided at the reversal points, either in coincidence (coincident condition) or counterphased

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(counterphased condition) with the auditory metronome. A reference condition without haptic information was also performed by participants. Results and Discussion Five Variables were analyzed: the relative phasing (RP) between index movement on the X dimension and the signal and its variability, the number of transitions and the transition frequency and the recruitment of the Y dimension (figure 1).

Figure 1. Raw trajectories of the finger movement in the x-y plane showing the gradual recruitment of a new d.f.

Stability on the X-dimension. A three-way (pattern x condition x frequency) ANOVA was carried out on these variables. Results showed that providing haptic information differentially affected the global dynamics of each pattern on the horizontal plane. For the adduction pattern, in the counterphased condition, the RP variability significantly increased with respect to the other conditions (figure 2). This pattern also showed more transitions than the abduction pattern. On the other hand, the stability of the abduction pattern was not affected by the informational conditions. However, it should be noted that even if no change was observed in RP variability in the different conditions, the abduction pattern exhibited more transitions in the counterphased condition than in the two other conditions.

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Figure 2. RP variability before transition of the adduction pattern in the three informational conditions.

Recruitment. The recruitment of the Y dimension of motion depended on both the informational condition and the pattern. For the coincident condition, the magnitude of the recruitment of both patterns was equivalent. On the other hand, in the reference and the counterphased conditions, the magnitude of the recruitment was lower for the adduction pattern (i.e. the least stable on the X dimension) than for the (most stable) abduction pattern (figure 3). Conclusion The results of this study showed that for the least stable coordination pattern (adduction), which displayed more transitions on the X dimension, the recruitment of the Y dimension was of lower magnitude. On the other hand, the most stable abduction pattern displayed fewer transitions but recruited more the Y dimension. Such a trade-off between phase transitions and recruitment suggested that both processes provide a means to improve the flexibility of the neuromusculo-skeletal system and to deal with a loss of stability of coordination pattern on the X dimension.

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Figure 3. Magnitude of recruitment before transition in the three informational conditions for each pattern. References Carson, R.G. & Riek, S. (2001). Changes in muscle recruitment patterns during skill acquisition. Experimental Brain Research, 138, 7187. Fink, P.W., Kelso, J.A.S., Jirsa, V.K. & DeGuzman, G.C. (2000). Recruitment of degrees of freedom stabilizes coordination. Journal of Experimental Psychology: Human Perception and Performance, 26(2), 671-692. Kelso, J.A.S., Buchanan, J.J., De Guzman, G.C. & Ding, M. (1993). Spontaneous recruitment and annihilation of degrees of freedom in biological coordination. Physics Letters A, 179, 364-371. Kelso, J.A.S., Fink, P.W., Delaplain, C.R. & Carson, R.G. (2001). Haptic information stabilizes and destabilizes coordination dynamics. Proceedings of the Royal Society of London B, 268, 1207-1213.

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Intention and Attention in Gestural Coordination: Asymmetric HKB Model Paul Treffner & Mira Peter Griffith University, Australia To what extent could natural language have evolved from manual gestures? Increasingly, research is indicating that Broca's area is implicated in manual gesture perception as well as articulatory gesture production (Corballis, 2002). We approach speech-hand coordination from a dynamical systems perspective (Tuller & Kelso, 1984) with special interest in how attention and laterality entail stability and function. In particular, the issue of intended vis-a-vis perceived speechhand synchrony is addressed. Method Ten right-handers (RH) and 12 left-handers (LH) synchronized either speech (/ba/-/ba/-/ba/...) or finger tapping with a pacing signal while simultaneously moving the other articulator in either a 1:1 inphase or anti-phase manner as a metronome was increased in frequency from 1.2 to 2.8 Hz (10 cycles per frequency plateau; 0.1 Hz increments). Participants attended to tapping or speech. Kinematic data from finger and jaw were collected. Using cross-spectral coherence, a mean estimate of relative phase across all frequency plateaus (prior to any phase transition from anti-phase) was used to quantify speech-hand coordination. Continuous relative phase was used to derive standard deviation of relative phase. When the finger lead the jaw, -180°
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Figure 1a. Effect of frequency, intended phase, and hand (L, R) on phase shift and variability in right-handers (RH).

Results All reported ANOVA and post hoc tests as well as results from regressions are significant at the p<.05 level (or less). For in-phase coordination, for both RH and LH, there was a negative average phase shift for both right and the left hand (finger lead over jaw) and it was greater for the right than for the left hand. Thus, both RH and LH groups acted similarly with respect to the right hand. In contrast, for anti-phase coordination, RH and LH performed differently. For RH, their positive phase shift (jaw lead over finger) was of comparable magnitude for the right and the left hand (jaw lead). For LH, there was also a positive phase shift but only for the right hand—for the left hand they exhibited a negative phase shift (finger lead). Thus, anti-phase speech-hand coordination using the left hand distinguished RH from LH.

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Figure 1b. Effect of frequency, intended phase, and hand (L, R) on phase shift and variability in right-handers (RH).

For in-phase coordination and the left hand, the increase in frequency produced a decrease in negative phase shift and a switch to a positive phase shift and increasingly so (i.e., Df changed from undershooting to overshooting 0°, e.g., see RH in Figure 1). For the right hand, Df undershot 0°. In anti-phase coordination, the increase in frequency resulted in a decrease in positive phase shift and an increase in negative phase shift and increasingly so (i.e., relative phase changed from undershooting 180° to overshooting 180°), for both right and left hands. The SD(f) was similar for RH and LH and was greater for antiphase than for in-phase for both the right and the left hand. For in-phase, phase variability was comparable for the right and the left hand for both RH and LH. However, for anti-phase coordination variability was greater for the left than for the right hand in LH. Importantly, phase

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variability decreased with the increase in required frequency (Fig. 1). Although the linear trend was not always significant for anti-phase coordination, the quadratic trend was so for both the right and the left hand of both RH and LH. This may be due to the stabilising factor of attention. Effects of attention were also revealed in the patterning and degree of absolute phase shift. Although for LH and in-phase coordination there was no difference in the magnitude of phase shift when attention was directed to either speech or tapping, for anti-phase coordination, greater shift was observed when attention was directed to tapping than to speech. Additionally, when attention was on tapping, a greater phase shift was observed for anti-phase coordination than for inphase. For RH, phase shift also tended to be greater when attention was on tapping than on speech. Thus, the effects of attention were most pronounced for the less stable anti-phase coordination. Similarly, the aspect of speech-hand coordination that was most "susceptible" to cognitive intervention (via a shift in the attractors for anti-phase) was when tapping was synchronized with the metronome. Our results lend support to the proposal that attention can stabilize and shift the stable states of coordinated perception-action (Riley et al., 1997). Discussion The current results on RH and LH can be accommodated by the extended asymmetric HKB model (Treffner & Turvey, 1995, Equation 1).

Figure 2 depicts the evolution of a viable model from origins in the canonical HKB model with assumed noise, increasing pacing frequency (decreasing bla) and biomechanical finger-jaw eigenfrequency difference, (Dw; Figure 2(a) and 2(b) through incorporation of a fixed attention factor (d; Figure 2(c)), and increasing attention (dstep; Figure 2(d)), and through incorporation of a constant phase offset or bias (p) that captures the intentional synchrony associated with one's perception and production of the timing underlying synchronous events (i.e., perceptual- or "p"-centres"; Figure

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2 (e). The final model (Fig. 2F) incorporates the hitherto unmotivated asymmetric c-term which "pulls and stretches" the profiles of Figure 2E in opposite directions such that the attractors increasingly approach and overshoot f= 180°, and increasingly undershoot f= 0°/360° (cf. Fig. 1).

Figure 2. Evolution of asymmetric HKB equation (see text for details).

The asymmetric HKB equation with phase-offset (Trefmer & Peter, 2002) lends insight into the continually decreasing phase shift (due to increasing attention) as frequency increases, as well as the near-

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U-shaped SD(f) profiles found by others studying the influence of attention on coordination dynamics (Temprado et al., 1999; Zanone et al., 2001). The regressions of Figure 1 confirm a close correspondence between the frequency at which minimum variability (minimum of Ufunction) and minimal phase shift (Dw = 0) occurs. This frequency underlies comfort mode states and corresponds to the cardinal in-phase and anti-phase attractors. Perception-action synchrony during speechhand coordination evolves according to the asymmetric attentional HKB model—provided an "intentional asynchrony" (phase offset) is incorporated. Perceptual synchrony does not imply actual synchrony, although, functionally, synchrony may exist. Importantly, such functional synchrony evolves according to lawful dynamics, and therefore affords gestural coordination and ultimately communication. References Corballis, M. (2002). From hand to mouth: The origins of language. Princeton University Press. Riley, M. A., Amazeen, E. L., Amazeen, P. G., Treffher, P. J. & Turvey, M. T. (1997). Effects of temporal scaling and attention on the asymmetric dynamics of bimanual coordination. Motor Control, 1,263-283. Temprado, J. J., Zanone, P. G., Monno, A. & Laurent, M. (1999). Attentional load associated with performing and stabilizing preferred bimanual patterns. Journal-of-ExperimentalPsychology: Human Perception and Performance, 25, 15791594. Treffher, P. J. & Peter, M. (2002). Intentional and attentional dynamics of speech-hand coordination. Human Movement Science, 21, 641-697. Treffher, P. J. & Turvey, M. T. (1995). Handedness and the asymmetric dynamics of bimanual rhythmic coordination. Journal of Experimental Psychology: Human Perception and Performance, 27,318-333. Tuller, B. & Kelso, J.A.S. (1984). The timing of articulatory gestures: Evidence for relational invariants. Journal of the Acoustical Society of America, 76,1030-1036. Zanone, P. G., Monno, A., Temprado, J. J., & Laurent, M. (2001). Shared dynamics of attentional cost and pattern stability. Human Movement Science, 20, 765-789.

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Bi-Manual Haptic Attention Marie-Vee Santana The Procter & Gamble Co., Cincinnati, OH, USA Previous research has shown that participants can accurately perceive whole and partial extents of a non-visible object. This haptic ability is constrained by Iij, the inertia tensor, a 3 x 3 matrix that quantifies resistances to rotation. The moments of inertia quantify resistances to rotation about x, y, and z axes, while products of inertia quantify the resistances to rotation in directions perpendicular to the preceding axes. Whole length perceptions are a single-valued function of the largest moment of inertia, Ixx, while partial length perceptions are a single-valued function of the largest moment of inertia, Ixx, and a product of inertia, ly, (see Turvey & Carello, 1995). These dependencies were examined in the present work in the context of dual-task performance. Experiment 1 was designed to explore the limits of haptic perception by asking participants to perform two tasks simultaneously: A quasi-rhythmic task_— wielding two rods, one in each hand — and a perceptual task —perceiving an extent of one rod. Participants in Experiment la reported the whole extent (tip to tip) of the rod whereas participants in Experiment 1b reported the partial extent (from the point of grasp forward). Experiments 2 and 3 were designed to eliminate any added demands on the haptic system and to further control and manipulate the rhythmic task. Experiment 4 evaluated whether perceptions of whole and partial length were perceptually independent in the presence of a simultaneous rhythmic task. Experiment 1 Six rods were used: Two each at 30 (26.5 g), 60 (39.5 g), and 90 (57.3 g) cm. A 50-g mass was attached to each rod at 1/4 of its length. Half the time, the mass on the right-hand rod was in the front of the point of grasp and the mass on the left rod was in the back. For the remaining trials the configuration was reversed. Participants sat in a chair with both arms extended to either side and occluded from view. Length judgments were obtained using magnitude production. On each

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trial, participants directed their attention to either the right or the left rod and wielded both rods until they had reached a length judgment. Participants in Experiment la reported the whole length of the rod while participants in Experiment 1b reported the partial length. Participants successfully perceived whole length—perceived whole length increased with actual whole length for both hands [F(2,10) = 15.17, p < .001; F(2, 10) = 9.26, p < 0.05, respectively]. Furthermore, the expected dependencies onIxx,were found (r2 = 0.95, p < .001). Perceived partial length increased with actual partial length for both hands [F(2,10) = 13.73, p < .001; F(2,10) = 18.65, .001, respectively]. However, the expected dependencies on Ixx and Iyz were not found, suggesting a change in the usage of physical quantities relevant for perception when dualtasking. Experiments 2 and 3 Methods: Five rods ranging from 40 to 80 cm long and from 24.5 to 68.8 g were used. Participants in Experiment 2 wielded the attended rod while in Experiment 3 participants held the attended rod still. The quasirhythmic task from Experiment 1 was replaced with a Fitts' Law task to ensure that participants constantly wielded the rods, and to manipulate task difficulty. Because the rhythmic task was made more rigorous, the perceptual reports (of whole and partial length in both experiments) were obtained using magnitude estimation. A 60-cm rod outside the experimental set was used as a standard. In the magnitude estimation task, perceptions were measured in terms of mean % longer responses (the percentage of times participants perceived the experimental rod as longer than the standard). Three pairs of paper targets (widths: 2, 4, 8 cm; height: 20 cm) separated by three different on-center distances (8, 12, 24 cm) produced three levels of index of difficulty, ID (Fitts, 1954). ID is a function of the width of the targets and the distance between them. ID was a between subjects variable. All other design details were as in Experiment 1. There were 3 ID groups: Easy (ID = 0), Intermediate (ID = 2), and Hard (ID = 4). Results: For Experiment 2, a main effect of length [F(4, 60) = 188.77, p<0.001] suggested that participants discriminated the experimental rods from the standard. Lengths were distinguished for both partial [F(4, 60) = 119.88, p<0.0001) and whole [F(4, 60) = 116.62, p<0.0000l] length

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tasks. The effects of ID were seen in the 3-way attended hand (right vs. left) x length x ID interaction [F(8, 60) = 3.02, p < 0.06], suggesting that for the hardest ID level, mean % longer responses were higher when the dominant hand was attended and steadily increased for all five rod lengths. For Experiment 3, a main effect of length [F(4, 60) = 142.81, p<0.0001) suggested that participants successfully discriminated the experimental rods from the standard. ANOVA on the combined data of Experiments 2 & 3 with exploration type (wielding vs. holding) and ID as between factors revealed that more mean % longer responses were obtained when participants held the perceived rods still.

Experiment 4 Because the typical tensorial dependencies were not observed in Experiment 1, this experiment investigated whether partial and whole length perceptions were independent or if partial length perceptions depended on whole length perceptions in the presence of a quasirhythmic task. There were three whole (50, 75, and 100 cm) and three partial (10, 20, and 30 cm) lengths. The design and analysis followed Gamer's (1962) complete identification design. Participants performed the same rhythmic task as in Experiments 2 and 3. The perceptual independence analysis revealed that partial and whole length judgments were perceptually independent under dual-task conditions. Summary In the presence of a rhythmic task, perceived whole length was a function of Ixx but perceived partial length was not a function of Ixx and lyz. Holding the attended rod while wielding the unattended rod improved correct responses relative to wielding the attended rod. Finally, although partial length perception seemed to have deteriorated (i.e., the typical tensorial dependencies were not observed), partial and whole length perceptions were perceptually independent when dualtasking. Acknowledgements: This research was conducted as part of the author's doctoral dissertation at the University of Connecticut supported by NSF grants SBR 93-09371 and SBR 94-22650.

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References Fitts, P. M. (1954). The information capacity of the human motor system in controlling the amplitude of movement. Journal of Experimental Psychology, 4 7, 381 -391. Garner, W. R. (1962). Uncertainty and structure as psychological concepts. New York: Wiley. Turvey, M. T. and Carello, C. (1995). Dynamic touch. In W. Epstein & S. Rogers (Eds.), Handbook of perception and cognition: Vol. 5, Perception of space and motion (pp. 401-490). New York: Academic Press.

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Heaviness Perception Depends on Movement Claudia Carello, Kevin Shockley, Steven Harrison, Michael Richardson, and M. T. Turvey CESPA, University of Connecticut, Storrs, CT, U.S.A. The haptic perceptual system gives rise to situations in which a physical description F does not match a psychological description Y. In the classic size-weight illusion, the perceived heaviness of an object of a given mass decreases as the 3-D size of the object increases. In a complementary phenomenon, so-called weight metamers (cf. Turvey, Whitmyer, & Shockley, 2001), two different masses are perceived as equally heavy if "packaged" in the right 3-D size. These many: 1 and l:many mappings are rendered 1:1, however, when F is described with respect to an object's mass distribution as well as its mass (Amazeen & Turvey, 1996). These properties relate to the object's resistances to rotational and translational acceleration, respectively. The haptic system's role in controlling actions is central to this reconceptualization. Sensitivity to rotational dynamics is important to modulating the level and patterning of muscular forces needed to move an object in a controlled fashion. This link to controlling movement was examined in the present research. Experiment 1—Are Heaviness Metamers for Sliding Different from Those for Wielding? Everyday interactions with grasped objects (e.g., lifting, carrying, and maneuvering books, forks, etc.) typically consist of translations and rotations, combining forces proportional to an object's resistance to translation—its mass M—and torques scaled to an object's resistance to rotation—its inertia tensor Ik. Heaviness metamers for wielded objects emerge from the appropriate combination of M and Ik (Shockley, Grocki, Carello, & Turvey, 2001). But if rotation is precluded and an object is simply translated, then Ik should not be accessible and, hence, not be a factor in how difficult that object is to

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move. Free wielding was compared with translation restricted to the saggital plane (Figure la). Participants explored "tensor objects" configured to cross two levels of M and two levels of Ik (see Shockley et al., 2001). Perceived heaviness HP was indicated by magnitude estimation relative to a standard.

Figure 1. (a) Tensor objects could be pushed smoothly on supports that prevented rotation, (b) Objects that were heaviness metamers for wielding were not metamers for pushing, (c) Objects that were heaviness metamers for pushing were not metamers for wielding.

An ANOVA on mean HP revealed two interactions: Exploration x Rotational inertia, F(l, 9) = 45.10, p<.0001, and Exploration x Translational inertia, F(l, 9) = 54.96, p<.0001. Objects that were equivalent with respect to Ik comprised heaviness metamers for wielding but not for sliding (Figure 1b); objects that were equivalent with respect to M comprised heaviness metamers for sliding but not for wielding (Figure lc) Experiment 2—Is perceived heaviness affected by the number of hands? If constraints on movement are relevant to the haptic perception of heaviness, then the biomechanical capacity for generating forces ought to matter. An object wielded with two hands should be perceived as lighter than that object wielded with one hand.

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Figure 2. (a) A tensor object grasped with two hands, (b) Perceived heaviness is affected by the number of hands wielding the standard and by the number of hands wielding the target.

This conjecture was examined in an experiment in which participants made heaviness judgments of a target object (wielded with one or two hands) relative to a standard object (wielded with one or two hands). For two-handed wielding, the right hand grasped the object in the typical manner and the left hand enfolded it (Figure 2a). This ensured that twohanded wielding took place about the same origin O as one-handed wielding, preserving Ik over the two conditions. An ANOVA revealed the usual influences of M and Ik on HP. Additionally, the number of hands wielding the standard mattered, F(1, 20) = 9.63, p<.0l (Figure 2b)—because a one-handed standard felt heavy, target objects compared to it felt lighter than those compared to the same object wielded with two hands. And, similarly, target objects wielded with two hands felt lighter than those same objects wielded with one hand. These interacted with Ik, F(l, 20) = 4.52, p<.05, indicating that the influence of rotational inertia was modulated by a participant's biomechanical capacity for generating forces. Conclusion Although the inclination in psychology has been to treat physical and mathematical entities—weight, shape, distance—as the objects of perception, Gibson (1966) introduced the notion ofqffbrdance to emphasize the importance of behavior in defining the proper natural kinds for perception. The present experiments indicate that a putatively

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singular property such as heaviness is more properly construed as "heaviness while doing X" or "moveable in a particular way." The physical basis for the haptic perception of affordances is the hand-held object's mass and mass distribution taken with reference to the forceproducing neuromuscular system. Acknowledgment. This research was supported by National Science Foundation Grant SBR 00-04097. References Amazeen, E., & Turvey, M. T. (1996). Weight perception and the haptic size-weight illusion are functions of the inertia tensor. Journal of Experimental Psychology: Human Perception and Performance, 22, 213-232. Gibson, J. J. (1966). The senses considered as perceptual systems. Boston: Houghton Mifflin. Shockley, K., Grocki, M., Carello, C, & Turvey, M. T. (2001). Somatosensory attunement to the rigid body laws. Experimental Brain Research, 136, 133-137. Turvey, M. T., Whitmyer, V., & Shockley, K. (2001). Explaining metamers: Right degrees of freedom, not subjectivism. Consciousness and Cognition, 10, 105-116.

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Contribution of the Inertia Tensor to Manual Multi-Joint Pointing Delphine Bernardin1, Brice Isableu1, Gilles Dietrich2 & Jacques Cremieux3 1 2

Center for Research in Sport Sciences, University of Paris XI Faculte des Sciences du Sport (UFR STAPS), Universite de la Mediterranee

Pointing at a target involves the co-perception of the arm and the target. This research was directed at determining the contribution of the inertia tensor to the proprioceptive control of pointing. Recent studies have suggested that the inertia tensor, a physical property whose values are time- and coordinate-independent, rather than joint angles and gravitational torque, may be the relevant invariant used to perceive and control the orientation of our limbs (Pagano et al., 1996; Pagano and Turvey, 1995). The inertia tensor describes the distribution of the arm's mass, i.e., the resistance of the limb to rotations in different directions. Earlier research has suggested that the principal arm's axis of rotation e3 (i.e., the eigenvector of the inertia tensor) specifies the orientation of the arm toward the target. By breaking the coincidence between the inertial eigenvector and the longitudinal axis of the arm, it is possible to test whether the perception of limb orientation is a function of the limb's eigenvectors or of its geometric articular orientation. We examined the generalizability of the inertia tensor hypothesis to unconstrained multi-joint arm movements. Based on the observation of interindividual variability in a previous study (Pagano et al., 1996), two pointing behavioral responses were expected when e3 shifted away (left or right) from the arm's longitudinal axis: 1) the directional control of the arm toward the target conforms to the inertia tensor hypothesis. In this case, the arm's inertia eigenvector is aligned onto the target (see figure la). 2) If, on the other hand, people point with their arm's longitudinal axis, then the gap between the finger and the target tends to be reduced toward 0 (see Figure Ib), thus respecting the

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initial instruction. This alternative pointing behavior could be based on articular geometry.

Figure 1. a) Reaching a target is a function of the limb's eigenvector, b) Reaching a target is a function of the limb's articular geometry.

Method Participants (N = 13) held a rod so that it was horizontal and perpendicular to the arm (see Figure 1). Masses were placed on this stem at 28 cm from the centre of the hand either symmetrically (the z eigenvector remains aligned with the longitudinal axis of the arm) or asymmetrically (left or right) allowing rotating the z eigenvector. We modified the mass distribution of the arm by varying the relative weight of the masses (100 g, 200 g, and 500 g) at either end of the rod. The Hanavan biomechanical model (1964) was used to compute the eigenvector of the inertia tensor. The predicted individual deviations when the arm was fully extended were in average equal to 1.5°, 2.7° and 6.1° respectively, depending on mass and inertia of the participant's arm. Participants could see the pointing target (a vertical line), but not the arm-rod system. Under these conditions, participants were instructed to point as accurately as possible towards the target. 3D arm movements were recorded via a six-camera motion capture VICON system, at a sampling rate of 60 Hz. Results and discussion Figure 2 shows the correlation between predicted and actual pointing direction, with predictions derived from the inertia tensor.

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Figure 2: Mean of pointing bias observed as a function of the theoretical eigenvector orientations values: y = .058 + .316 * X; R2 = .388 (3 mass conditions; 3 deviation conditions) p<.0001. The thick line illustrates the theoretical perfect fit between predicted values and outcomes.

The slope of the actual vs. predicted curves shows that the non-visual pointing was influenced by the inertia eigenvector of the arm-rod system. Therefore, the inertial properties of the limb seem relevant during a task involving multi-joint arm movements. However, the observed deviations were less than the predicted values (mainly for the heavier masses). In addition, important interindividual variability (see Figure 2) was found to exist. We suggest that this variability reflects differential modes of pointing directional control. Indeed, the range of the individual slopes values confirmed this result (from R2 = 0.14 to R2 = 0.66). This implies a certain amount of redundancy in the control modes available to bring the arm onto the target. Some participants (individual R2 near 0.66) clearly used the eigenvector orientation as a reference for pointing (e3 aligned onto the target, see Figure la). A direct coupling of the arm system onto the inertia tensor indicates that these participants have "diagonalized" the mass distribution of the arm-rod system toward the target, which implies that the inertia products (resistances to rotation) have been reduced toward zero. For these participants, the act of pointing consists of

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directing the arm along the minimal resistance pathway. For other participants, however (see Figure 1b and Figure 2; individual R2 near 0.14), there is not a single factor explaining the accuracy of the pointing performance (z arm aligned onto the target). The arm's directional control could well be explained from articular geometries, but we cannot reject the hypothesis that these participants were exploiting the inertia tensor. Indeed, it may be the case that the perceived deviation of the inertia eigenvector was compensated for by the participants, by holding at a high value the inertia products on the basis of muscular efforts (torque generation). Perspectives The next step of this research will consist of modelling the kinematics of e3 during the reaching movement (i.e., as a function of time). Kinematic analyses need indeed to be performed in order to clarify whether the alignment of the arm onto the target reflects earlier adaptive corrections (e.g., at the onset of the pointing) based on the inertia tensor. References Hanavan, E. P. (1964). A mathematical model of the human body. AMRL-TR-64-102, AD-608-463. Aerospace Medical Research Laboratories, Wright-Patterson Air Force Base, Ohio. Pagano, C.C., Garrett, S.R., & Turvey, M.T. (1996). Is limb proprioception a function of the limb's inertial eigenvector? Ecological Psychology, 8,43-69. Pagano, C.C., & Turvey, M.T. (1995). The inertia tensor as a basis for the perception of limb orientation. Journal of Experimental Psychology: Human Perception and Performance, 21, 10701087.

Transfer of Calibration in Dynamic Touch: Length and Sweet-Spot Perception Rob Withagen1 and Claire F. Michaels1,2 1

Institute for Fundamental and Clinical Movement Sciences, Vrije Universiteit, Amsterdam, The Netherlands 2 Center for the Ecological Study of Perception and Action, University of Connecticut, USA

An important first step in developing a theory of calibration in perception is establishing the object of calibration. In an earlier study, we (Withagen & Michaels, 2003) surmised that calibration applies to perceptual laws, which describe the relation between the perceptual variable exploited and the perception. In the present experiments we tested this hypothesis by asking whether there is transfer of calibration between length perception by dynamic touch and sweet spot perception by dynamic touch. Cooper, Carello, and Turvey (1999) demonstrated that these perceptions are independent of each other, suggesting that they are governed by different perceptual laws. Thus, if calibration applies to perceptual laws, no transfer of calibration between length and sweet spot perception is expected. Experiment 1 Experiment 1 tested whether the calibration of length perception transfers to perception of the location of the center of percussion (sweet spot). We used 10 homogeneous, wooden rods that differed in length. A pretest-calibration-posttest design was used. The test phases each consisted of 10 length trials and 10 sweet spot trials. In the length trials, the participants were to position a cube at the felt distance reachable with the unseen, hand-held rod; in the sweet-spot trials, the cube was to be positioned to be optimally hittable. The calibration phase consisted of 6 length trials, in which the participant's judgment was followed by visual feedback. To induce a recalibration, the feedback indicated that the rod was longer than had been reported during the test phase. (Fed back "reachable distance" was based on the slope and intercept of a regression line relating that participant's perceived vs. actual length on the pretest: actual length*(slope plus .5) plus intercept.

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Results We computed the regressions of perceived length versus actual length, and perceived sweet spot versus actual length for each participant for each test phase. The slopes averaged across participants are depicted in Figure 1. A repeated-measures analysis of variance (ANOVA) on the slopes with condition (pretest, posttest) and task (length, sweet spot) as factors revealed recalibration in slope (slope increased in the direction of the feedback) F(l, 5) = 85.15,p < .001; a main effect of task, F(l, 5) = 7.88, p <.05, meaning that sweet-spot perception is scaled differently to actual length from length perception to actual length; and no interaction, F(1, 5) = .26, n.s., indicating transfer of calibration. A similar ANOVA on the intercepts revealed no significant effects.

Figure 1. The slopes averaged across participants for each test phase and each task in Experiment 1. The error bars indicate one standard deviation.

Experiment 2 Experiment 2 tested whether the calibration of sweet-spot perception transfers to length perception. We used 10 homogeneous, aluminum rods that differed in length. The procedure was the same as that of Experiment 1, except that the calibration phase consisted of 6 sweet-spot trials. To induce recalibration, feedback was again based on the participant's pretest perceived sweet-spot vs. actual-length

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regression: actual length*(slope minus .3) plus intercept. The feedback was given by positioning the cube at "the best place to hit the cube".

Figure 2. The slopes averaged across participants for each test phase and each task in Experiment 2. The error bars indicate one standard deviation.

Results We again computed the regressions of perceived length versus actual length, and perceived sweet spot versus actual length for each participant for each test phase. The slopes averaged across participants are depicted in Figure 2. A repeated-measures ANOVA on the slopes with condition and task as factors revealed a significant decrease in the slope, in keeping with the direction of the feedback, F(l, 7) = 43.05,p< .001; a main effect of task, F(l, 7) = 38.62, p<.001; and a marginally significant interaction, F(l, 7) = 3.91, p < .1. Closer inspection of the results suggested that 4 participants showed no transfer and 4 showed complete transfer. An ANOVA on the intercepts revealed only a marginally significant effect of task, F(l, 7) = 5.58, p < .1, indicating that recalibration of the intercept did not occur.

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Discussion We assumed that perception of the sweet spot is not based on the perception of length (cf. Cooper, et al., 1999), but that both are directly perceived in a manner captured by different perceptual laws. Our hypothesis that calibration is specific to a perceptual law predicted, therefore, no transfer from a sweet-spot task to a length task or vice versa. The discovery of such transfer leads us to reject the hypothesis of calibration's specificity to a perceptual law. Given the individual differences, it may be that the object of calibration depends on the aspects of the feedback information to which the perceiver attends. In the feedback over trials, information is available that specified that the rods were homogeneous. Because the sweet spot of a homogenous rod is at 2/3 of its length, the feedback in both experiments contains information about both the length and sweet spot of the rod. It seems that all participants detected this information when fed back on length perception, but only half did so when fed back on sweet spot perception. References Cooper, M. M., Carello, C., & Turvey, M.T. (1999). Further evidence of perceptual independence (specificity) in dynamic touch. Ecological Psychology, 11, 269-281. Withagen, R., & Michaels, C.F. (2003). Transfer of calibration in length perception by dynamic touch. Manuscript submitted for publication.

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Postural Sway Decreases During Performance of a Digit Rehearsal Task Michael A. Riley, Aimee A. Baker, and Jennifer M. Schmit Department of Psychology University of Cincinnati Postural control seems to be a highly automatic behavior that requires minimal, if any, attentional control. Recent studies (see Woollacott & Shumway-Cook, 2002) have shown, however, that postural control carries an attentional cost. Cognitive performance varies inversely with the difficulty of balance conditions, and postural control is affected when performing concurrent cognitive tasks. The latter effects range from decreased (e.g., Maylor et al., 2001) to increased postural stability (e.g., Vuillerme et al., 2000) during cognitive task performance. The inconsistent effects of cognition on postural stability may be due to procedural artifacts. Some studies used cognitive tasks that required participants to vocally respond during postural measurement. Yardley et al. (1999) suggested that vocalization may produce changes in postural sway that are unrelated to cognitive or attentional demands. Other tasks have required participants to visually fixate a stimulus (e.g., Hunter & Hoffman, 2001). Stoffregen et al. (1999) showed that the ocular demands of fixation induce adaptive reductions in sway, which could be mistaken for a cognitive effect. We used a short-term memory (STM) task that avoided those potential sources of artifact. Participants were shown a random digit string. The digits were removed, and participants subvocally rehearsed the digits during postural sway measurement. Immediately afterwards, participants reported as many of the digits they could remember. We tailored STM task difficulty to each participant's STM capacity by measuring participants' digit spans. We manipulated STM task difficulty by varying digit string length. We expected postural sway to vary as a function of the STM task.

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Method Twenty-three undergraduates (13 females, 10 males) from the University of Cincinnati received course credit for participation. All had normal or corrected-to-normal vision and reported no history of balance disorder or orthopedic injury. Postural sway was measured at 100 Hz using a Bertec 4060-NC force platform and AM-6701 amplifier (Bertec Corporation, Columbus, OH) with Datapac 2000 software (Run Technologies, Inc., Mission Viejo, CA) running on a PC. Sway variability was operationalized as the within-trial standard deviation of the center of pressure (COP; roughly, the point location of a weighted average of the sum of vertical ground reaction forces at the force plate) in the anterior-posterior (AP) and medial-lateral (ML) axes. Stimuli were presented using Microsoft PowerPoint on a 36.8 x 25.4 cm LCD monitor, positioned at eye-level at a distance of 1.23 m in front of the participant. Digits were displayed in 72-point font, subtending 0.95° of vertical visual angle. We administered the Digit Memory Test (Turner & Ridsdale, 1997) to determine each participant's digit span. The maximum number of digits correctly recalled served as the number of digits displayed in the difficult condition. Half of the maximum yielded the digit string length for the easy condition (rounded down in the case of an odd maximum) and the midpoint between the easy and difficult conditions yielded the medium condition. Participants stood barefoot with their feet side-by-side. The force plate was covered with 10.16 cm of foam. During postural measurement participants closed their eyes. The rationale for using the eyes-closed, foam condition was that cognitive effects would presumably be maximized under less-stable balance conditions. Four repetitions of each condition (no task, easy, medium, difficult) were performed in random order (16 total trials). On each trial a digit string was presented on the monitor for 10 s. Participants studied the string until the slide disappeared. At that point participants closed their eyes and rehearsed the digits while standing relaxed with their arms hanging naturally at their sides. During this period postural sway was measured for 30 s, after which participants were prompted to recall the digits.

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Results Separate repeated-measures ANOVAs were conducted for AP and ML sway variability. A significant STM task effect was found for AP sway, F(3,22) = 5.15, p < 0.01. Sway was generally greater in the no-task and easy conditions (0.96 cm and 1.01 cm, respectively; those means did not differ from each other) than in the medium and difficult conditions (0.88 cm and 0.92 cm, respectively; those means did not differ from each other). Tukey tests revealed less variability in the medium and difficult conditions than in the easy condition (p = .0004 and p = .008, respectively). No other comparisons were significant. There were no significant effects for ML sway. Digit recall was scored for errors (incorrect order, omissions, or intrusions). The overall error rate was 9.4% (total of 2 errors in the easy condition, 7 in medium, & 17 in difficult). Repeated-measures ANOVA revealed a significant STM task difficulty effect, F(2,46) = 3.79,p < .05. When trials with incorrect responses were omitted, the pattern of postural sway results did not change (but the post-hoc comparison for AP sway between the no-task and medium conditions was not significant according to the Tukey test, p > .0083). Discussion Postural sway was reduced when participants performed the medium and difficult digit rehearsal tasks, relative to when performing an easy digit task. Postural sway did not differ between the easy condition and a no-task condition. The observed interplay between STM and postural control supports the view that postural control is not a reflexive, automatic behavior (Riccio & Stoffregen, 1988). The results contradict attention theories that assume a limited pool of cognitive resources (e.g., Kahneman, 1973). Resource theories predict that when task demands exceed resources during dual-tasking, performance at one or both tasks will decline. Resource theories cannot account for improved performance (i.e., reduced sway) while dualtasking. A possible explanation for the results is that ordinarily some attention is directed to postural control, but the attention has a detrimental effect. Releasing postural control from attentional focus when attention must be directed elsewhere allows postural control to fimction more automatically and efficiently (Hunter & Hoffman, 2001; Vuillerme et al., 2000). That possibility is consistent with results

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showing enhanced postural stability when participants adopt an external (relative to an internal) focus of attention (McNevin & Wulf, 2002). References Hunter, M. C, & Hoffman, M. A. (2001). Postural control: visual and cognitive manipulations. Gait and Posture, 13, 41-48. Kahneman, D. (1973). Attention and effort. Englewood Cliffs, N. J.: Prentice-Hall. Maylor, E. A., Allison, S., & Wing, A. M. (2001). Effects of spatial and nonspatial cognitive activity on postural stability. British Journal of Psychology, 92, 319-338. McNevin, N. H., & Wulf, G. (2002). Attentional focus on suprapostural tasks affects postural control. Human Movement Science, 27,187'-202. Riccio, G. E., & Stoffregen, T. A. (1988). Affordances as constraints on the control of stance. Human Movement Science, 7, 265-300. Stoffregen, T. A., Smart, L. J., Bardy, B. G., & Pagulayan, R. J. (1999). Postural stabilization of looking. Journal of Experimental Psychology: Learning, Memory, & Cognition, 25, 1641-1658. Turner, M., Ridsdale, J. (1997). The digit memory test. Retrieved October 15,2002, from http://www.dyslexia-inst.org.uk Vuillerme, N., Nougier, V., & Teasdale, N. (2000). Effects of a reaction time task on postural control in humans. Neuroscience Letters, 291, 77-80. Woollacott, M., & Shumway-Cook, A. (2002). Attention and the control of posture and gait: a review of an emerging area of research. Gait and Posture, 16, 1-14. Yardley, L., Gardner, M., Leadbetter, A., & Lavie, N. (1999). Effect of articulatory and mental tasks on postural control. Neuroreport, JO, 215-219.

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Modeling Phase Transitions in Human Posture Paul Fourcade, Benoit G. Bardy & CSdrick Bonnet Center for Research in Sport Sciences, University of Paris XI Recently, we have proposed a dynamical account of pattern formation in the multi-segment control of stance (e.g., Bardy et al, 2002). In various experiments, during which standing participants were instructed to maintain a constant distance between their heads and a visual target that oscillates along the line of sight, we have shown that postural states can be understood as attractors in the postural space (ankle-hip relative phase (frel close to in phase at low frequencies and close to anti-phase at high frequencies), and that changes between states resemble selforganized, non-equilibrium phase transitions, exhibiting critical fluctuations, hysteresis, and critical slowing down (see Bardy, 2003 for a review). In this contribution, our goal is to create a mixed, or 'compound', model of human posture that captures these nonlinearities. The biologically plausible model is composite in the sense that it is a mechanical model that links joints and segments with units of mass and length to produce the self-organized signatures observed at the behavioural level. We develop below the main aspects of the model and evaluate its ability to generate the behavioural data. The model The mechanical model is a double-inverted pendulum. The human body is represented as two non-deformable segments, one representing the head-trunk system rotating around the hips, the other representing the thigh-legs system rotating around the ankles. Segment masses m1 and m2 are located at the level of the centers of mass. Their position from the two rotation axis are designed by l1 and 12 (Figure la). Articular and muscular stiffness are represented by two angular springs. Stiffness coefficients were estimated at 1000 N.m.rad-1 for the ankles and 500 N.m.rad-1 for the hips (Farley et al., 1999). Damping terms were considered to be zero at the hips, but increased non-linearly at the

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ankles with target frequency in order to maintain the center of mass above the feet. Oscillations of the body were produced by a constantamplitude torque acting at the ankles, counterbalanced by a resistive torque acting at the hips in order for the feet to be kept in contact with the ground. Simulations Modes and transition'. Simulations of the double pendulum indicate the presence of two ankle-hip coordinative patterns accompanying the continuous increase of target frequency (see Figures 1 and 2): an in-phase mode for frequency values lower than 0.3 Hz (frel close to 25°), and an anti-phase mode for frequency values higher than 0.5 Hz (frel close to 180°). The anticipatory movements of the ankles are due to the friction term. A transition from in phase to anti-phase, without intermediate state, can be observed at a target frequency of about 0.5 Hz, the exact value depending on the stiffness coefficients and the torque value.

Figure 1. A double-inverted pendulum tracking the oscillations of a target;

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Figure 2 Amplitudes of ankle angle (black line) and hip angle (gray line) as a function of target frequency.

Hysteresis: Simulations also indicate a hysteresis effect, with transitions from in-phase to anti-phase (as target frequency increased) appearing at a higher frequency than transition from anti-phase to inphase (as target frequency decreased). The difference between the two transition frequencies (the region of hysteresis) was approximately 0.1 Hz, similar to what was found in the behavioral data (see Figure 3a). Critical fluctuations and critical slowing down: Critical fluctuations were assessed in the model by adding a pseudo-white-noise term, centered around 1 Hz, in both equations of motion (active and resistive torques). This produced an increase in the variability of frel prior to the transition, evidencing the loss of stability in that region. Critical slowing down (expressed by the relaxation time trel taken by the system to return to its stable state following a perturbation) was assessed by reversing the sign of active and resistive torques far from or close to the transition region (Figure 3b). Similar to what was found with human data, trel increased in the vicinity of the transition, suggesting that the postural system loses its stability in that region.

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Figure 3. a) Hysteresis region between Up (solid iinel) and Down (dotted line) conditions; b) Simulated relative phase frel following a sudden perturbation at time t = 10 s, showing an abrupt deviation from and a smooth return to the 30° stable state. Relaxation time trel was calculated by fitting an exponential function on frel data following the perturbation.

Conclusion The mechanical model captured the five hallmarks of selforganization that have been observed in standing humans involved in supra-postural activities (Bardy et al., 2002). This accuracy suggests that it is possible, and we would say necessary, to root the general organizational principles accompanying movement control into the biomechanical (or neuro-physiological) substrates of specific biological systems, such as the postural system. It also suggests that an intermediate position on the structural-phenomenological line (c.f, Beek et al., 1998) can be useful for modeling human movement. References Bardy, B. G. (2003). Postural coordination dynamics in standing humans. In V. K. Jirsa and J. A. S. Kelso (Eds.) Coordination Dynamics: Issues and Trends, Vol 1: Applied Complex Systems. New York: Springer Verlag, in press. Bardy, B. G., Oullier, O., Bootsma, R. J., Stoffregen, T. A. (2002).

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Dynamics of human postural transitions. Journal of Experimental Psychology: Human Perception and Performance, 28,499-514. Beek, P. J., Peper, C. E., Daffertshofer, A., Van Soest, A., Meijer, O. G. (1998). Studying perceptual-motor actions from mutually constraining perspectives. In: A. A. Post, J. R. Pijpers, P. Bosch, and M. S. J. (Eds.) Models in Human Movement Sciences (pp. 93-111) Enschede, NL: PrintPartners Ipskamp. Farley, C. T., Morgenroth, D. C. (1999). Leg stiffness primarily depends on ankle stiffness during human hopping. Journal of Biomechanics, 32, 267-273.

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Sports Expertise Influences Learning of Postural Coordination Caroline Ehrlacher1, Benoit G. Bardy1, Elise Faugloire1, & Thomas A. Stoffregen2 'Center for Research in Sport Sciences, University of Paris XI, France 2 Human Factors Research Laboratory, University of Minnesota, USA

Inspired by Bernstein (1967), Bardy et al. (1999) studied coordination between the hips and ankles. Measuring the relative phase of hip and ankle rotations, they observed the emergence of two coordination modes: in-phase (frel = 20°) for small values of the target's amplitude or frequency, and antiphase (frel =180°) for high values. These postural patterns can be considered as attractor states of the postural system, representing the whole features of non-equilibrium transitions. The pre-existing motor landscape can have an important part in establishing the postural system dynamics. Zanone and Kelso (1992) reported that the acquisition of a bi-digital (frel of 90° induced a reorganization of pre-existing patterns toward the new attractor. Similar results have been recently obtained for posture (Faugloire et al., 2003). From these works we see that there appears to be an interaction between the features of initial patterns and the destabilization caused by new learning: (1) when pre-existing patterns are very stable, it is difficult to shift to a new pattern (strong competition), (2) when pre-existing patterns are less stable, the shift is easier (weak competition), (3) a novel pattern that is close to a pre-existing pattern may be reinforced (cooperation). We tested these hypotheses when participants learned a new pattern of hip-ankle coordination in stance (frel = 90°). We varied the pre-existing stability by selecting participants with different types of sports expertise (gymnasts exhibited very stable coordination, while coordination was weaker in contemporary dancers). We also evaluated persons whose pre-existing coordination is close to the to-be-learned

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pattern (expert swimmers in the Butterfly stroke).1 Two additional groups served as controls, as described below. Method Experimental groups. Nineteen women volunteers participated in the five groups. The learning groups were Gymnasts, Swimmers, Dancers, and Non-athletes. A pre-test, two learning phases, and a post-test, were distributed over two days. For pre-test and post-test, the task was to move the head to track fore-aft oscillation of a visible target. There were four trials for each of two target oscillation frequencies: 0.25 Hz and 0.7 Hz. The to-be-learned coordination was 90°. It was first explained, then freely repeated over 15 trials for each session. Control group. Subjects executed 27 trials of the tracking task on one day, corresponding on the total number of trials for each learning group on the second day. Apparatus and measures. Two BIOMETRICS electro-goniometers were placed on left ankle and hip to register their angular displacements. MATLAB was used to obtain the point estimate of relative phase frel between ankle and hip, and its standard deviation, SDf rel . Two selection criteria were used to select trials for statistical analysis: (1) the number of cycles registered in the trial 7 < n < 13, (2) the Raleigh test p<.05. The Raleigh test indicates whether the distribution of circular data is directional (i.e. non-random). Inter-groups and inter-conditions differences in (frel (per cycle) and SDfrel (per trial) were evaluated using the Watson-Williams test. Results Experimental vs control groups. The non-learning control group exhibited changes in relative phase between pre-test and post-test for low-frequency, Watson-Williams F(1,166) = 5.51, p<.05, mainly because in the post-test data more trails met the inclusion criteria, X2(1) = 20.02, p<.05. Thus, coordination produced at low frequency tended to become 1

Using digital analysis of videotape, we determined that for high-level competitive swimmers, during swimming, hip-ankle frel = 70° (point estimate).

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directional with repetitions. In the pre-test, there were no differences between the non-learning control group and any of the learning groups. In the post-test, they differed, F>44.0, p<.05, indicating that learning of the new coordination influenced the stability of the pre-existing pattern.

Figure 1. Frequency distributions of relative phase per cycle per condition (learning, pre-test, post-test) per group. Distributions are represented in a polar way, by 20° intervals, in percentage of total distribution (each concentric circle represents 4% of the distribution).

Learning groups The learning period. We compared the first and last five trials from the learning period. In each group, participants exhibited the novel coordination: Frequency distributions (Figure 1) show a 90° peak frequency. They also exhibited a second peak at 160-180°, indicating the influence of the pre-existing, antiphase pattern. There were also important differences between groups. Gymnasts were unique in that they exhibited no changes in (frel or SDfrel between the first and last five trials. The value of SDfrel was lower for gymnasts than for other groups across the learning period, F>8.9,p<.05. Pre-test /post-test comparisons. For each group, there were prepost differences for both frequencies, for frel, F>22.0, p< .05 and for SDfrel, F>11.0, p<.05. Therefore, the pre-existing patterns were destabilized by learning of the new pattern (Figure 1).

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Differences between groups were also apparent. Alone among groups, dancers exhibited no pre-post changes in relative phase, they also had greater stability for post-test (SDf rel ) than any other group, F>7.06, p<.05. Finally, the relative phase of swimmers differed from the other groups, at the higher target frequency, F>20.0,p<.05. Indeed in the post-test, the swimmers produced the new postural pattern for both frequency conditions. Discussion We examined links between sport expertise and the learning of a novel pattern postural coordination. Participants' actual movements were distributed bimodally, oscillating between the to-be-learned mode (frel = 90°) and the pre-existing antiphase mode (frel = 180°). We believe that this reflects competition between the dynamics of the novel and preexisting patterns. This was also evident at post-test, where participants continued to oscillate between the two patterns. Experts postural dynamics seem to influence the learning by modulating this competition. The 70° postural attractor that Butterfly swimmers exhibit while in the water appears to have facilitated the acquisition of a similar phase relation (90°) in stance (cooperation), so much so that it overwhelmed the antiphase mode (180°) that previously had characterized their stance. In future studies, we will use a closedloop visual feedback system that permits us to provide continuous, realtime feedback to participants about their performance. This should afford a more refined and detailed understanding of the postural dynamics. Acknowledgments. This study was conducted with support from the French Ministere de la Recherche, Fond National pour la Science (IUF 2002:2006), and from the University of Paris XI. References Bardy, B. G., Marin, L., Stoffregen, T. A., & Bootsma, R. J. (1999). Postural coordination modes considered as emergent phenomena. Journal of Experimental Psychology: Human Perception and Performance, 25, 1284-1301. Bernstein, N. (1967). The coordination and regulation of movement.

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Zanone, P. G., & Kelso, J. A. S. (1992). Evolution of behavioral attractors with learning: Non equilibrium phase transitions. Journal of Experimental Psychology: Human Perception and Performance, 18,403-421.

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The Dynamics of Learning New Postures Elise Faugloire1 & Thomas A. Stoffregen2 1

Center for Research in Sport Sciences, University of Paris Sud XI, France 2 Human Factors Research Laboratory, University of Minnesota, USA In previous research we have examined the emergence of coordination modes between the hips and ankles in standing posture (e.g. Bardy et al., 1999; 2002). Only two coordination modes were observed: an in-phase mode (ankle-hip relative phase about 20°), and an anti-phase mode (ankle-hip relative phase close to 180°). In the present study, our aim was to analyze the dynamical aspects of learning a new postural coordination, that is, one that has not been observed in our previous research. We also examined the possible influence of the newly-learned coordination on the stability of pre-existing coordination modes. In a dynamical perspective, we predicted that the learning of a new coordination pattern would lead to the destabilization of existing patterns (e.g., Zanone & Kelso, 1992). In addition, the ease of learning should be influenced by the stability of pre-existing, spontaneous patterns (the more stable the initial mode, the more difficult would be the learning of a new postural coordination). Method Fifteen participants carried out the three parts of the experiment over two consecutive days, using a pre-test/post-test design. In the pretest participants executed a tracking task, maintaining a constant distance between the head and a visible target that oscillated in their anterior-posterior axis (Figure 1). They were asked to perform this task using only ankle and hip movements. We measured angular displacements of these joints with two electrogoniometers connected to a DATALINK interface (Biometrics, Inc.). By calculating the ankle-hip relative phase (Frel) and its standard deviation (SDFrel, i.e., its stability), we identified the emergent postural coordination used in this supra-

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postural task. In the second part of the experiment, participants learned a novel coordination between ankles and hips, namely 135° relative phase. They were shown an example of the desired pattern (schematic drawing and demonstration), and then attempted to reproduce it over thirty trials (fifteen each day), with ten cycles per trial. After every third trial, graphic feedback was provided, illustrating in the state space (ankle angle vs. hip angle) the discrepancy between the performed and the desired postural pattern. The final part repeated the pre-test tracking task to assess the effects of learning on pre-existing patterns.

Figure 1. Apparatus for the pre-test and post-test.

To control for possible effects of fatigue, a second group of nine subjects performed nineteen trials of the tracking task, in a single session (the same number of trials as performed in one day by the experimental group). Results We used circular statistics to compare both Frel and SDFrel distributions for the different experimental conditions, using WatsonWilliams F tests. The learning period was analyzed in terms of Early, Middle, and Late trials. Between these three sets of trials, we observed a gradual shift of ankle-hip relative phase, from Frel * 180° (the pre-existing pattern) toward 135° (the to-be-learned pattern), along with decreasing movement time, and increasing stability. Contrary to what we expected, there was no correlation between the stability of the pre-existing pattern (Frel »180°) and the rate at which the new pattern was learned.

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For the Experimental Group, the post-test value of Frel (162.11°) was smaller than the pre-test value (179.36°), F(l, 764) =11.11, p<.05. The post-test value of SDFrel (49.83°) was greater than the pre-test value (39.95°), F(l, 86) = 5.66, p<.05. For the control group, pre-post differences were not significant. Thus, the pre-post changes in the preexisting pattern for the Experimental Group can be attributed to the learning phase. Individual analysis revealed important differences in the type of post-test destabilization. Participants whose pre-test stability was high showed a loss of initial coordination stability in the post-test, while those with low pre-test stability showed a change in relative phase in the posttest. Figure 2 shows the pre-test and post-test Frel and SDFrel for the initially stable and initially unstable participants. Each point represents a Frel value per cycle. The bold arrows indicate the Frel mean vectors and indicate their 95% confidence intervals.

Figure 2. (A) Pre-test and post-test data for initially stable participants. (B) Pretest and post-test data for initially unstable participants.

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Discussion The results confirm that participants can learn a novel mode of postural coordination, and that such learning destabilizes existing modes. Initial stability of the pre-existing coordination does not seem to define the learning rate but rather the nature of the destabilization. In fact, our results do not corroborate our hypothesis that the learning rate would change inversely with the stability of the pre-existing attractor. On the other hand, we observed a relation between this initial stability and the nature of the destabilization (mean relative phase vs. stability). The loss of stability due to learning evolved with the initial stability of the spontaneous pattern, whereas the change in the mean relative phase was inversely correlated with this initial stability. This result seems to suggest that the more stable is the initial attractor, the more resistant it is to being disturbed by learning of a new coordination mode. References Bardy, E.G., Marin, L., Stoffregen, T.A., & Bootsma, R.J. (1999). Postural coordination modes considered as emergent phenomena. Journal of Experimental Psychology: Human Perception and Performance, 25, 1284-1301. Bardy, B.G., Oullier, O., Bootsma, R.J., & Stoffregen, T.A. (2002). The dynamics of human postural transitions. Journal of Experimental Psychology: Human Perception and Performance, 28, 499-514. Zanone, P.O., & Kelso, J.A.S. (1992). Evolution of behavioral attractors with learning: Nonequilibrium phase transitions. Journal of Experimental Psychology: Human Perception and Performance, 75,403-421.

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An Intentional Dynamics Assessment Procedure for Discrete Tasks Tjeerd Boonstra1, Steven Harrison2, Michael J. Richardson2 and Robert Shaw2 1

Vrije University, Amsterdam, Netherlands CESPA, University of Connecticut, Storrs, USA

2

An alternative method is proposed which aims to assess goaldirected behavior in an intrinsic action-scaled manner. The advantage of using an intrinsic measure is that abilities are scaled to the task setting. It is therefore possible to compare the scores of different people across situations. In this approach the success of performing a task is determined by one's ability to pick up the right information and to control one's actions in the intended way. Thus, goal directed action is constrained by both the task setting and the goal. Shaw and KinsellaShaw (1988) introduced the notion of a task defined as a bounded set of alternative paths in space-time (called an omega cell). By definition, the omega cell comprises paths that share a common goal but are graded in the directness with which they approach the goal. They further postulated that when an actor performs a task in the intended manner, a quantity, called the total generalized action (TGA), is defined which is conserved over each of the alternative goal-paths. Consider: Ordinary action is work integrated over time. This action is the sum of two components: useful action which is work in the goal direction and useless action which is not. The ecological construal of useful action has two further components: control as the kinetic action (goal-directed work already done) and information that specifies the potential action (goal-directed work still to be done). Because this ecological (task dependent) form of action involves both information and control components, we call this generalized action; because kinetic and potential action have to be summed, we call this the total generalized action. Just as in ordinary physics, where only the total energy is conserved, so in ecological physics only the total generalized action can be.

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A simple computer task is presented to set out the basic principles of this approach and show how an intrinsic measure of goaldirected behavior might be applied to a real world task. In the task, participants are presented with six simulated dots, which move with speeds determined by a constant velocity (specific to each dot) and a general stochastic term. The participant's task is to adjust the speed of the dots so that each moves with an equal speed. Control is exerted though discrete individual manipulations, adjusting the speed of individual dots. At each level of difficultly (determined by the strength of the stochastic factor) the participant is restricted to a set number of manipulations, each resulting in a monetary cost. Consequently, the participant's goal is to equalize the speed of the dots whilst minimizing monetary loss. Analysis Given the task constraints, and a set of initial conditions, it is possible to compute the paths of the task omega cell. In this case, the omega cell contains all those series of adjustments that make the speed of the six dots the same while maximally minimizing loss of money. To determine the impact of each adjustment, the TGA was computed before and after each adjustment. The TGA is the sum of the information and the control potential (Shaw & Kinsella-Shaw, 1988). The goal-path in this example is actually the bundle of paths leading to one of the target states (six equal speeds) while using the minimal amount of money possible. It can be shown that the TGA is conserved over changes of position along each goal-path. The difference in TGA before and after the adjustment was scaled to the differences of all possible adjustments. In the present task when the TGA is negative, the number of adjustments minimally needed to reach the target was greater than those required without total monetary loss (the participants are unable to complete the task). This results in a score between -1 and 1. The score of-1 means that the adjustment was as bad as possible in that situation (i.e., useless action) while the score of 1 means the best adjustment (i.e., only useful action). The TGA expressed in money units: Generalized-actionmoneyft) = money-to-target(t) + money-to-spend(t)

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Results In order to assess whether the TGA is an effective intrinsic performance measure, each participant's TGA score was examined for each adjustment made. Although the task was designed to increase in difficulty over both changing level and adjustments, the measure of TGA, as predicted, was observed to remain invariant, suggesting that participant scores were indeed scaled to the constraints of the current situation. In other words, participants (on average) were attuned to the ostensibly specified target state, and tended to follow either the optimal or sub-optimal goal path (where sub-optimal means there was a small amount of useless action associated with the path). Conclusion The current task provides a simple experimental illustration of the validity of the basic claim of intentional dynamics: By considering all goal-paths as a bounded space-time region (an omega cell), a quantity, TGA, can be shown to be conserved, that is, to be path independent (as is the defining characteristic of energy conservation). Conservations are of crucial importance to the development of any science since they provide a stable basis for all other measures. We propose that the TGA of intentional dynamics offers such a conservation for ecological psychology in so far as goal-directed actions are concerned. References Ackerman, P. L. and Cianciolo, A. T. (2000). Cognitive, perceptualspeed, and psychomotor determinants of individual differences during skill acquisition. Journal of Experimental Psychology: Applied, Vol. 6(4), 259-290. Kugler, P.N., Shaw, R.E., Vicente, K.J. & Kinsella-Shaw, J.M. (1992). Inquiry into intentional systems I: Issues in ecological physics. Psychological Research, 52, 98-121 Shaw, R. E. & Kinsella-Shaw, J.M. (1988). Ecological mechanics: A physical geometry for intentional constraints. Human Movement Science, 7, 155-200. Starkes, J. L. & Lindley, S. (1994). Can we hasten expertise by video simulations? Quest, 46,211-222.

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Measuring Exploratory Learning with Minimal Instruction as Drift Endre £. Kadar1, Botond Virginas2 & Judith Effken3 'University of Portsmouth, UK 2 British Telecom, UK 3 University of Arizona, USA Recently, Effken and Kadar (2001) proposed that exploratory learning in a computer display control task could be viewed as a random walk process with increasing bias (i.e., a diffusion process with increasing drift). Effken and Kadar used a virtual hemodynamic control system to test this hypothesis. Participants in the experiment were asked to maintain cardiac output at a specified target level via the administration of simulated drugs that had differing effects on cardiac output. Runs were defined as the continuous administration of the same drug. Runs towards the target (ideal) cardiac output became increasingly longer and more frequent as learning progressed with fewer, shorter runs being made away from the target. Essentially, drug administration was 'hit or miss' (i.e., random) at the beginning of the session, but became more systematic or non-random as learning progressed. Effken and Kadar's findings are consistent with a diffuse control model of learning characterised by increasing bias. Based on these preliminary results, it appears that a diffuse control strategy, which comprises randomness (diffusion) mixed with increasing goal-bias (drift), may offer a promising new model of exploratory learning. Kadar, Maxwell, Stins and Costall (2002) argued similarly that the seemingly random meandering patterns in various motor-learning tasks (e.g., adaptation to a 90° visual rotation) can also be explained by such a diffuse control strategy. Their findings suggested that Drift was a particularly sensitive measure to assess gradual changes during learning. Encouraged by these results, the present research further tested the effectiveness of the Drift measure in Effken and Kadar's (2001) display control task.

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Method Three males and two females, undergraduates at the University of Portsmouth, participated in this study.

Figure 1. The symptom window of the simulated hemodynamic system. Gray areas represent green target zones; black areas represent red danger zones.

Figure 1 depicts the display. Pressure changes are shown as changes in the horizontal dimensions of three interconnected balloons. Blood flow changes are shown as a change in the vertical dimensions of the bellows-like icon labeled 'Ventricle'. Twenty different scenarios were created by combining variations in heart strength and resistance, using a range of clinically reasonable values. The scenarios were generated such that five scenarios fell into each of the four quarters of the two-dimensional drug space, Heart Strength vs. Resistance (e.g., high heart strength - high resistance, low heart strength - high resistance, etc.). Each scenario was presented in two blocks of twenty trials, but the presentation order was randomized within each block. The order of trials was also randomized for each participant. Participants were allowed to combine drugs that increased or decreased heart strength or resistance for treatment. We discovered in a pilot experiment that the combined drug task was very difficult to learn by free

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exploratory behavior, so minimal instruction was provided to facilitate learning. Specifically, participants were told that an imbalance between the lower two balloons (Figure 1) can be corrected by a drug for resistance, and the ventricle icon could be primarily controlled by drugs for heart strength. Results and discussion Exploratory patterns were highly erratic during the early stages of learning and few trials were successful. During the second block, some successful trials were produced by each participant. To assess learning, every run (response to a particular drug intervention) in a trial was converted into a drift value (i.e., the change in distance from the goal, or symptom free area, during the run). Then we selected, from each block of trials, two sets (trials 6-10, and 16-20) and compared the drift values for the sets (S1, S2, S3, and S4). Figure 2a shows the gradual increase of average drift toward the goal state for the four sets of trials along with a gradual decrease in standard deviation. An analysis of variance (ANOVA) revealed marginally significant differences for Drift among the trial sets (F(3,80) = 2.40, p = 0.07).. There were also obvious differences in the strategies participants used. For instance, in early trials participants found it very difficult to select the correct amount of drug needed for various symptoms. Consequently, run lengths and drift values showed a great deal of variability.

Figure 2. (a) Average Drift values with error bars for the four sets of trials, (b) Mean frequency of good turns for the same four sets of trials.

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To eliminate the effect of variance in run length, we also tested directional changes with respect to the goal. We measured the frequency of positive runs (i.e., runs with positive drift) within each trial. An ANOVA showed a significant difference in the four sets of trials (F(3,24) = 4.85, p<0.05). Figure 2b shows the mean frequency of correct turns per trial for the same four sets of trials (a .5 value = 50% correct turns). Conclusion These findings lend further support for treating exploratory learning as an increasingly Biased Random Walk process. Drift and the derived directional measures are shown to be sensitive to gradual changes. The negative drift value and the close to 50% frequency for S1 seem surprising, but these values could be explained by a minor error in the instructions (i.e., the direction for increasing or decreasing resistance was wrongly specified). Although drift seems to capture the gradual changes at the very early stages of learning, as it did in motor learning, the present study suggest that learning display control may be more difficult than motor learning, perhaps in part because of some inherent nonlinearity in the underlying simulation or because there are differences in the response time of for various drugs. In any case, gauging the required length of runs to solve a specific problem seems to be more demanding task than assessing the distance of a target in simple motor learning tasks. References Effken, J, & Kadar, E.E. (2001). Learning as a progressive biasing of a random walk process: Towards an ecological theory of exploratory learning. Ecological Psychology, 13, 1-30. Kadar, E.E., Maxwell, J.P. & Costall, A. (2002). Drifting toward a diffuse control model of exploratory learning: A comparison of global and within-trial performance measures. Biological Cybernetics. 87, 1-9.

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Experimental Investigations of the Emergence of Communication Procedures Bruno Galantucci1,2, Michael J. Richardson , Carol A. Fowler1'2 1

Haskins Laboratories, New Haven, CT, USA 2 University of Connecticut, CT, USA

The idealization in which an abstract "speaker/hearer" represents the linguistic competence of all speakers of a language has contributed much to an understanding of linguistic systematicities, but little to an understanding of how language emerges and evolves in natural contexts. Achieving the latter understanding requires an experimental method for investigating language as public communicative action. To our knowledge, no such method exists. Our method focuses on how communication emerges from the exchange of visual signals between adults. This method supports rapid emergence of novel between-person communication systems, with properties reflecting task constraints that are under experimental control. Method We created a two-dimensional videogame with interconnecting computers. Players A and B each control, from different sites, the motions of an agent in a four-room environment (Figure la). A player sees only one room at a time with each room marked by its own shape. When in the same room both agents are visible to both players, but not otherwise (Figure Ib). Players communicate with magnetic pens on digitizing pads. The resultant tracings are relayed to the communication panels of both players and quickly fade. The pad is parameterized to function like a seismograph (Figure 1c); familiar forms are transformed into time series (Figure le) that vary with the velocity profile of the drawing movement (Figure 1d).

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Figure 1. A) The four rooms. B) Three game sequences, with the top displays showing player A's view and the bottom displays showing players B's view: (i) players start in diagonally opposite rooms and win by moving to the bottom left room; (ii) players start in adjacent rooms and lose by moving to the rooms below their starting positions; (iii) the pantomime in which player A moves back and forth between rooms to convey the meaning of the 'I go' signal (two dots/lines) to player B. C) Seismograph. D) Tracings on the pad produce different outcomes depending on how they are drawn. E) Visual traces generated by drawing letters, numbers and common shapes. F) The vocabularies developed by the pairs.

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We studied two pairs of players (P1 and P2). Players in a pair did not know the other's identity. For each player, there was an experimenter nearby encouraging him/her to express any thoughts or observations relevant to the game. Players started the game in different rooms; their goal was to get their agents into the same room with no more than one room change per agent (Figure 1, Bi and Bii). Performance superior to chance (50%) required communicating information about the location of one's agent and/or intended movements. Once that occurred, the game reduced to an easy win. The players had a common score with two points added for a win and four subtracted for a loss. Results In different ways, both pairs converged quickly on signaling systems that supported successful performance. Soon after beginning the game, pairs established a first point of convergence: 1.

Work on the most urgent need. For all players that was to code names for the rooms. Competing signs for rooms were prominent initially but gave way, in both pairs, to a single sign when, eventually, a player imitated the other's sign:

2. Do not engage in extended "monologues". When your partner produces something that you know how to imitate, imitate it. The players of both pairs converged on a coding scheme based on the agents' typical trajectories (Fig. 1F). In both pairs the reason for an elected sign was apparent only to its originator. For the non-originator, the signs were conventional tokens, with meanings related to the locations of the individual rooms. For example, whereas P1's originator used curved trajectories that closely resembled the agent's motions, the partner, unaware of the trajectories' rationale, persisted in making the curves right angled, creating signs that were easier to produce and to distinguish. Eventually, the originator of the signs adopted these modified signs. Two principles: 3. The choice of signs is not crucial. What matters is agreeing on a sign and using it consistently to indicate a referent.

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4. The forms that facilitate convergence are perceptually distinct and produced by simple motor sequences. The communication procedure at this juncture accommodated the need to signal initial positions. That was sufficient for success when agents began in adjacent rooms. When they began in nonadjacent rooms, success depended on signs for future location or movement. P1 solved the problem with pantomimes identifying the events requiring new signs. On several occasions, when both agents occupied the same room, one player crossed the doorway repeatedly, alternating between the signs for the "present" and "next" rooms. Following such crossings, the pantomime was repeated with the addition of two dots between the room signs (Figure 1Biii). Over repetitions, the other player realized that two dots stood for movement. 5. To create new forms, converge on an action sequence that illustrates a new meaning, then attach a linguistic form to it. At this point current and future locations could be communicated by the "present location-move-next location" sequence of signs. Left unspecified was who should move. Using pantomime, one player of P1 twice repeated the "present location-two dots-next location" sequence, while executing the action that the sequence of signs expressed. Soon after, the player introduced "present location-three dots-next location" and did not move. The extra dot came to mean you and the new sequence meant you move. The 'two dots' sign now meant / move. Here we see a strategy for maintaining an established convergence: 6. To code further details of an event you know how to code, make distinctions in the forms you already have and attach values to them using pantomime. Players in P2 began each game by repeating the sign for the current room. Then, one player followed that by the sign for the intended next room. If the signaled move would lead to a win (players were in adjacent rooms), the other player would signal the current position, signaling agreement, and await the other player's arrival. If the signed move required that both players move, the other player signed "present room" followed by the sign for the agreed-upon "next room".

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7. Communication procedures adapt flexibly to the particulars of a task and to the different predispositions of the players. There are many equivalent ways to create and maintain procedures that guarantee achievement of the goal; success and mutual agreement determine the choice. Conclusions Our results suggest that experimental study of the emergence of communication is possible. They also suggest that the method presented here, extended and refined, can lead to an understanding of how a task, its environmental settings and a need to cooperate jointly shape the emergence of communication systems. Acknowledgments, We thank Michael Turvey, Michael StuddertKennedy, Andrea Scarantino and Ruth Millikan for helpful discussions and comments. Supported by funds from the UCONN and NICHD.

Studies in Perception and Action VII S. Rogers & J. Eflken (Eds.) ©2003 Lawrence Erlbaum Associates, Inc.

'Mind the Gap': False Memories as a Case of Event Cognition Matthew P. Gerrie and Maryanne Garry Victoria University of Wellington, New Zealand The exploding literature on false memories often assumes that people generate images that are confused with genuine experience (Johnson, Hashtroudi & Lindsay, 1993), a process known as source confusion. Ecological approaches suggest that such an account of false memories is unnecessary (Jenkins, Wald & Pittenger, 1986). However, neither the traditional nor the Jenkins et al. approaches capture an essential quality of real-life false memory experiences: they unfold in full motion. In the experiments we describe here, we draw on Jenkins et al.'s (1986) research to ask whether people can develop false memories of more realistic full-motion events. We filmed a woman making a sandwich, and used Reed, Montgomery, Palmer and Pittenger's (1995) protocol to segment the movie into action units. We removed some of those segments, and later examined event memory by showing subjects a mix of seen and missing segments. In Experiment 2, we investigated the source confusion account of false memories, as well as the relative importance of clips, using Reed et al.'s cruxes. Experiment 1 Method Six raters saw a movie of a woman making a peanut butter and jelly sandwich and divided it into 10 action unit clips. Three clips (17 sec) were removed and the remainder shown to subjects. Session 1. Subjects watched the 94 sec movie containing 7 segments. Session 2. Subjects returned 24 hours later. They watched a mix of old clips they had seen; missing clips that had been removed; and control clips depicting peripheral actions. After each clip, subjects reported

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whether they recognized it from session 1, and rated their confidence (15). Results Figure 1 shows that subjects recognized old clips very well, and rejected control clips. However, they falsely recognized missing clips at a rate higher than that for controls, t(30) = 9.58, p<.01. Thus, subjects reported having seen an average of 11 seconds (18%) of an event that they had not. Recognition confidence was high for both old and missing clips, 4.3 (SD = 0.68) and 3.7 (SD = 0.82).

Figure 1. Mean proportion of "yes" responses to each clip type.

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Discussion Subjects often claimed they had seen full-motion action units missing from an event, simply as a result of seeing the superordinate event. Recall that a source monitoring explanation suggests that when subjects viewed the video, they imagined the missing segments and later confused this "internally manufactured" information with genuine experience. In Experiment 2, half of our subjects were specifically instructed to imagine the missing segments and half were prevented from imagining. Experiment 2 Method The procedure was the same as in Experiment 1, except that after watching the video, Imagine subjects imagined the entire event (without missing segments) for Imin 30sec, while No imagine subjects solved word puzzles.

Figure 2. Mean proportion of 'yes' responses for clip type in each Imagination condition.

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Figure 3. Mean proportion of 'yes1 responses to each clip type for both the Crux and Imagination conditions.

Results Figure 2 shows two important findings. First, the results mirror those of Experiment 1. Second, the pattern was the same in both conditions. In other words, imagination had no effect on how subjects responded to clips they had seen and those they had not (F(2,78) = .04). To establish whether some segments were more critical to the event than others, 11 independent raters determined the cruxes and noncruxes of the event. The clips rated most "crucial" were categorized as cruxes, while those rated most "not crucial" were categorized as noncruxes. We calculated the proportion of subjects who claimed to have seen each clip, then classified these clips according to whether they were old or missing. Those results are displayed in Figure 3. Subjects

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tended to recognize old cruxes and missing noncruxes, suggesting that some aspects of the event were more important than others. As before, imagination had no effect on this pattern. Discussion Taken together, the results of Experiments 1 and 2 suggest that it is not an imagination-induced source confusion that causes false memories. Instead, it is the extent to which people see a subordinate action as essential to the overall purpose of the event. References Jenkins, J.J., Wald, J., & Pittenger, J.B. (1986). Apprehending pictorial events. In V. McCabe & G.J. Balzano (Eds.) Event Cognition: An Ecological Perspective. New Jersey: Lawrence Erlbaum Associates. Johnson, M.K., Hashtroudi, S., & Lindsay, D.S. (1993). Source monitoring. Psychological Bulletin, 114,3-28. Reed, E. S., Montgomery, M., Palmer, C. & Pittenger, J. (1995). Method for studying the invariant knowledge structure of action: Conceptual organization of an everyday action. American Journal of Psychology, 108, 37-65. Roediger, H.L., & McDermott, K.B. (1995). Creating false memories: Remembering words not presented in lists. Journal of Experimental Psychology: Learning, Memory & Cognition, 21, 803-814.

Studies in Perception and Action VII S. Rogers & J. Efflcen (Eds.) ©2003 Lawrence Erlbaum Associates, Inc.

Feature Detection: An Adequate Meta-Theory for Fear Responding? Andrew D. M. Dickie1 & Ottmar V. Lipp2 1

School of Human Movement Studies, University of Queensland, Australia. 2 School of Psychology, University of Queensland, Australia.

Recent research has revealed resistance to extinction of pointed gun stimuli within differential conditioning experiments. This appears to undermine the phylogenetic account of the preparedness of phobic stimuli (Hugdahl & Johnsen, 1989; Flykt, 1999, cited in Ohman & Mineka, 2001) through its implication that ontogenetically fear-relevant stimuli are prepared with respect to Pavlovian-style association with fear. However, in this paper we consider an alternate possibility; namely, that this evidence is merely reflective of an inadequate operationalisation of the variables laid out in the phylogenetic theory. The comparison of snakes and pointed guns as representatives of the categories of phylogenetically and ontogenetically fear-relevant stimuli may not constitute a valid comparison of the two categories. These operationalisations are dependent upon the variables that one posits as the means by which preparedness effects are elicited - the meta-theory of phobia acquisition. The meta-theory implicit within previous experiments in fear-relevance holds that the identity, in a categorical sense, of the focal object within a given stimulus is the determinant of the preparedness of the stimulus. Ohman and colleagues (e.g. Ohman, Flykt & Esteves, 2001) even speculate that the preparedness of stimuli may be based upon their possession of certain primitive visual features, e.g. sinusoidal shapes in the case of snakes (phylogenetically fearrelevant). If, however, one posits a less discrete variable for the activation of preparedness effects, the problem posed by the incongruous data from experiments with pointed guns disappears.

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The proposed alternate meta-theory suggests it is the stimulus' ability to be configured as active, malign and dangerous that results in preparedness effects in fear-conditioning processes. This assumption maintains the conclusions of previous reasoning based on evolutionary theory; namely, that prepared stimuli with respect to fear are likely to be the result of evolutionary selection pressures. The only difference is the model's assumption that preparedness arises from an adaptation to an abstract property of stimuli (subjective threat value), rather than separate adaptations to specific characteristics of categories of stimuli. This, if anything, constitutes a more valuable adaptation than that previously postulated. As a test of this theory, participants performed an array task in the vein of Ohman and colleagues' array search task (e.g. Ohman, Flykt & Esteves, 2001), using gun and plier stimuli. It was hypothesised that attentional biases would be observed in the experiment to held, pointed gun stimuli, as these should embody the greatest threat to participants. It was further hypothesised that this attentional bias would facilitate the solution of trials in which these stimuli were the targets and cause a decrement in responding on trials in which they were distractors, resulting in a significant difference between the reaction times for these two trial types. Method Participants were 47 University of Queensland students (26 female, 22 male) who were unselected with respect to either general anxiety or specific phobia. Students received course credit for their participation. Participants responded to a series of arrays with a button press indicating that images were from either the "same" category, or from "different" categories. The arrays consisted of nine pictures arranged on a computer monitor in a regular rectangular matrix. In some of the trials one of the pictures was of a different category than the others ("different" trial), whereas in the rest pictures came from the same category ("same" trial). The stimuli for the task were images of handguns and plier sets, the orientation of which was manipulated (pointed vs. non-pointed), along with the presence of the hand of an operator within the image (held vs. non-held) (see Figure 1). Pointed images consisted of the item being pointed down its longest axis at the observer, whereas in the non-pointed condition, this axis was set at

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approximately 45° to the direction of viewing. The full stimulus set consisted of 72 pictures: these pictures instantiated a fully crossed 2 (item; gun vs. pliers) x 2 (heldness; held vs. non-held) x 2 (pointedness; pointed vs. non-pointed) design, with nine different images in each condition. The full task comprised 450 array tasks, but was split into two halves counterbalanced for order. Every image was included as a deviant against every possible background type on nine occasions - once in every position in the matrix - to account for target position effects. Reaction time and error data were recorded for each participant. Results and Discussion It became apparent after data collection that the simplicity and homogeneity of the stimuli would be an issue. DiLollo, Kawahara, Zuvic and Visser (2001) propose that the solution of visual search trials is facilitated by such homogeneity. In order to address this factor a reduced data set was analysed, discounting conditions in which the pointedness and heldness of the deviant did not match the background. Error data revealed no evidence of speed accuracy trade-offs for the experiment. Reaction time data is displayed in Figure 2. For the purposes of this article, only deviant trial data will be reported. Within the held, pointed background condition, no difference was revealed between the two item categories on deviant trials. Thus, the predicted attentional bias to held pointed guns was not observed. Within the held, non-pointed condition, however, gun deviants amongst plier backgrounds were found more quickly than plier deviants amongst gun backgrounds, t (45) = 6.43,p<0.01. This result suggests the presence of an attentional bias for held, non-pointed guns. Despite the failure of the hypotheses to be supported, this result does not indicate conclusively that the manipulation of threat value is a fruitless endeavour. Results obtained by DiLollo at al. (2001) support the notion that the homogeneity of the stimuli resulted in the use of a search strategy by participants that did not concern the identity of the stimuli, but rather concerned their shape relative to their context. This conclusion is given support by the fact that the condition that intuitively appeared to be most heterogeneous - the held, non-pointed condition - demonstrated what could be interpreted as an attentional bias effect. The use of this evidence as support for the fear relevance of gun stimuli would require a change of the initial hypothesis to include held non-pointed guns as fear-

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relevant stimuli - a reasonable prospect. An alternate explanation for the failure to observe attentional bias where hypothesised is the possible difficulty in identifying some stimuli when presented in non-canonical views (e.g. Palmer, Rosch & Chase, 1981). Both possibilities are currently the subject of further studies.

References Di Lollo, V., Kawahara, J., Zuvic, S.M. & Visser, T.A.W. (2001). The preattentive emperor has no clothes: A dynamic redressing. Journal of Experimental Psychology: General, 130(3), 479-492. Hugdahl, K. & Johnsen, B.H. (1989). Preparedness and electrodermal fear conditioning: Ontogenetic vs. phylogenetic explanations. Behavioural Research and Therapy, 27, 269-278.

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Ohman, A., Flykt, A. & Esteves, F. (2001). Emotion drives attention: Detecting the snake in the grass. Journal of Experimental Psychology: General, 130 (3), 466-478. Ohman, A. & Mineka, S. (2001). Fears, phobias and preparedness: Toward an evolved module of fear learning. Psychological Review, 108 (3), 483-522. Palmer, S., Rosch, E. & Chase, P. (1981). Canonical perspective and the perception of objects. In J. Long and A. Baddeley (Eds.), Attention and performance IX. (pp. 135-151). Hillsdale, NJ: Lawrence Erlbaum Associates.

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"Perception for Inhibition": A Dorsal-frontal Pathway for Sensorimotor Regulation? Shim-nan Yang Brain Science Institute, RDCEN, Japan One important issue concerning response inhibition is the process by which it is generated. Studies previously reported indicate that inhibition of eye movements can be initiated by a short-latency, automated, and hemifield-specific mechanism (Yang and McConkie, 2001). Here we report results of studies on the nature of the process underlying this type of inhibition. Hazard levels of saccade frequency at different times for the critical fixation in reading are calculated to reflect the momentary level of saccadic activity. Experiment 1 Method In the first study, normal text was read but occasionally replaced with X's during saccades, which was not visible to subjects. A second, visible display change (X's to normal text, X's to nonwords) occurring 75ms following fixations was used to generate inhibition. Results Figure 1 shows the change in the ratio of the hazard level of the experimental conditions to that of the control condition (X's to X's) for both forward and regressive saccades. It shows that the display change resulted in a very short-latency (< 100ms), short-lived (about 150ms) and bi-directional (forward and regressive) inhibition. The degree of suppression and the function of the effect were symmetrical over a period of 100 to 125ms. After that the effect of inhibition dissipated. This effect is quite different from the early inhibition observed by Yang and McConkie (2001), which shows a longer latency (175 to 225ms) and is limited to forward saccades.

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Figure 1. Ratios of occurring saccades for experimental conditions compared to the display condition with X's only.

Experiment 2 Method In the second study, the same type of display change was made during saccades, so there would be no detection of the display change itself. Subjects were instructed to ignore the occurrence of whole-page nonwords, but to inhibit eye movements when strings of S's are detected. This allows the comparison between the effect of the targeted inhibition and that generated by deliberate inhibition. Results Figure 2 shows the hazard curves for the Control, Ignore, and the Stop conditions. Surprisingly, similar early inhibition was observed in both types of experimental condition (Ignore or Stop) and there was only a very small and insignificant effect of intentional inhibition. Also,

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there is no inhibitory effect on regressive saccade, suggesting the effect of nonselective inhibition.

Figure 2. Hazard curves of forward saccades for different conditions during the critical fixation.

Experiment 3 Method In the third study, no visual display change is involved but some critical words were replaced with alternate words that created reading difficulty. The hazard levels of first fixations on these words were calculated. Since no display change is involved, the effect is related to higher-level psycholinguistic processes. Figure 3 shows the hazard curves of the control and five experimental conditions. The patterns of inhibition are much like those reported in study 2, but with the latency of inhibition reflecting the time needed for detection of this type of reading difficulty. The onset times observed seem to be too short to reflect the full analysis of the text and to allow enough time for response decision. Again, there is no effect on regressive saccades. Results These results show that the occurrence of inhibition described here is not due to purely visual, perceptual, or cognitive processes. It

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displays three important properties: (a) the inhibition is of relatively short latency in relation to the difficulty presented; (b) it is directionally specific and long-lasting; (c) it is independent of deliberate control of eye movements.

Figure 3. Hazard curves of forward saccades for different types of psycholinguistic difficulty during the critical fixation.

Discussion We propose that the observed inhibition is the result of evaluating partial information at multiple levels of perceptuo-cognitive processing, bypassing much of the ventral pathway (Goodale & Milner, 1992). It is likely mediated by the dorsal-frontal circuitry involving the frontal eye field, which explains both the short latency and the directionally selective inhibition (Sommer & Istvan, 2000). We think this mechanism serves as a way of regulating responses in an expedient and recourse-free manner. This can be explained as "Perception-forInhibition" from an ecological perspective, indicating how featural information can be directly accessed to elicit speedy control of behavior without complete recognition of the stimulus.

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References Goodale, M. A. & Milner, A. D. (1992). Separate visual pathways for perception and action. Trends in Neurosciences, 15(1), 20-25. Sommer M. A. & Istvan, R.H. (2000). Composition and topographic organization of signals sent from the frontal eye field to the superior colliculus. Journal ofNeurophysiology, 83, 1979-2001. Yang, S.-N., & McConkie, G.W. (2001). Eye movements during reading: a theory of saccade initiation times. Vision Research, 41, 3567-3585.

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Mobile Phones and Driving: Affordances and Attention Andrew Petersen1'2, Paul Treffner1, & Rod Barrett2 !

CAV lab, School of Information Technology Biomechanics Lab, School of Physiotherapy and Exercise Science Griffith University, QLD, Australia

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It is becoming clear that adverse cognitive activity can detrimentally affect concurrent driving performance. That speech interacts with manual coordination has also been demonstrated (Corballis, 2002; Trefmer & Peter, 2002). This research investigates how anticipatory control and coordination is compromised while maintaining a hands-free mobile phone conversation. Issues remain as to precisely which aspects of the perception-action cycle for driving are affected by concurrent speech on a mobile phone. Methods Nine novice drivers (average age = 18.4 years) holding provisional licenses (average driving experience =19 months) were tested at the Holden Performance Driving Centre's closed circuit driving track (Fig. la) using a Holden Commodore vehicle instrumented with a range of biomechanical sensors and G.P.S. (Trefmer et al., 2002). Participants completed two laps without phone conversations in order to develop familiarity with the track (Figure Ib). For safety reasons, a driving instructor remained in the passenger seat during all testing. Conversations involved presentation of two numbers from a track-side researcher that required an appropriate reply from the driver and were quantified according to amount of information reduction (Pellecchia & Turvey, 2001). Conversations consisted of either 2-digit reversal (Cl; e.g., "one, two"..."two, one"; 0 bits), summation (C2; e.g., "one, two"..."three"; 2.7 bits), or categorization of a resultant 2-digit number (C3; < 50 or > 50 and also whether odd or even, e.g., "one, two"..."less than, even"; 4.5 bits). A condition of no conversation (NC) acted as a control. Participants listened to the track-side researcher via a

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microphone/earphone attached to the right ear. Dialogue was maintained for the full length of a lap.

Figure 1. (a) Aerial view of Holden Performance Driving Centre, (b) GPS data indicating cornering hairpin (A), obstacle avoidance (B, C), and controlled braking (D) sections of track.

Driving tasks consisted of cornering (at SOkmhr"1 the driver approaches a right-hand hairpin corner that required deceleration for comfortable travel); controlled braking (at 80kmhr-1 the driver must decelerate and stop before a stationary car at a traffic light—simulated by a line of boxes); and obstacle avoidance (approaching at 50kmhr-1 the manoeuvre involves left-hand approach towards an obstacle followed by a swerve to the right and recovery back to the left lane). Drivers were informed that they could use the full width of the track. Three trials of each condition were completed and task order was randomized. The hypotheses tested were, (1) conversing on a mobile phone will detract from a driver's ability to control a vehicle compared to when driving in silence, (2) conversation level will detract from a driver's ability to control a vehicle, and (3) driving while engaged in a categorization conversation will affect driving the most. Analysis of variance with repeated measures was used to address the first hypothesis, while planned comparisons (simple and Helmert contrasts) were used to address the second and third hypotheses. Simple contrasts compared the dependent measure associated with a particular conversation level against the NC condition. The Helmert contrasts tested the hypothesis that conversation affects driving regardless of conversation type by comparing the combined mean (C-all) from C1,

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C2, and C3, against the NC reference. Dependent measures included various kinematic and kinetic measures as well as time to contact (tau) and tau-dot at the initiation of braking (with tau measured to corner entry or front of boxes). Results During cornering, the position when the accelerator pedal was released was marginally closer to the corner for C-all (65.19 m) compared to NC (68.92 m), F(l,8) = 4.01, p = 0.08. The distance from the corner at which initial brake depression occurred was marginally significant (50.11, 47.02, 45.11, and 47.80 m, for NC, Cl, C2, C3, respectively), F(3,24) = 2.90, p = 0.06, and was closer for C-all (46.64 m) compared to NC (50.11 m), F(l,8) = 8.90, p < 0.05. Under conversation, drivers were preparing for the corner later than without conversation. The temporal value of tau when braking was initiated was shorter for C-all (2.37 s) than for NC (2.53 s), F(l,8) = 7.15, p < 0.05, and was marginally shorter for C3 (2.34 s) than for NC (2.53 s), F(l,8) = 4.94, p = 0.06. Drivers did not anticipate the upcoming corner and may have misjudged the comer's affordances for safe travel while conversing compared to when not. With respect to controlled braking, the distance to the boxes when the driver depressed the brake was not significant. However, the type of deceleration for NC (tau-dot = 0.53) was less harsh compared to C-all (tau-dot = 0.55); F(l,8) = 5.97,p < 0.05. Similarly, NC (tau-dot = 0.53) was less harsh than C3 (tau-dot = 0.56), F(l,8) = 5.87, p < 0.05. Braking was harsher when conducting a mobile phone conversation. For the obstacle avoidance task, average approach velocity to the obstacle course entrance was marginally significant (51.13, 49.81, 50.54, and 50.34 kmhr1, for NC, Cl, C2, C3, respectively), F(3,24) = 2.88, p = 0.06, and C-all (50.34 kmhr-1) was lower than NC (51.13 kmhr*), .F(l,8) = 8.30, p< 0.05. Subsequent planned comparisons indicated that when comparing C-all to NC, the average velocity was lower between entry marker and the central obstacle (47.52 vs. 49.05 kmhr-1), F(l,8) = 5.33, p = 0.05, between the obstacle and the exit marker (46.99 vs. 48.42 kmhr-1), F(l,8) = 6.48,p< 0.05, and that the average departure velocity was lower (50.43 vs. 51.48 kmhr-1, F(l,8) = 14.17,p< 0.05. The results support the oft-reported effect of driving slower during conversation.

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Regarding lateral forces experienced during obstacle avoidance, the first peak g-force associated with the initial obstacle avoidance turn was not significant, although the time of the peak was later for C-all compared to NC (3.21 vs. 3.14 sec), F(l,8) = 6.41, p < 0.05. For the second peak g-force, when the driver steered around the obstacle, the planned comparison between NC and C-all was marginally significant (0.48 vs. 0.44 g), F(l,8) = 4.85, p = 0.06, as was that between NC and C3, (0.48 vs. 0.44 g), F(l,8) = 4.86, p = 0.06. The timing of this second peak was later for C-all compared to NC (4.82 vs. 4.68 sec, respectively), F(l,8) = 9.90,p < 0.05. This continued with the timing of the third peak which was later for C-all compared to NC (6.36 vs. 6.12 sec, respectively), F(l,8) = 7.29, p < 0.05. Conversation entailed a later onset of lateral g-forces, corresponds with trie lower velocity results, and suggests a delayed and/or slower anticipatory response under critical conditions such as obstacle avoidance. Discussion Although a main effect of conversation level (Hypothesis 2) was typically not found (the novice drivers exhibited high variability), the results from the planned comparisons suggest that it is not difficulty of conversation, but conversation per se that affects driving (Hypothesis 1), even though the most complex task (categorization) was often different from no conversation (Hypothesis 3). Speaking on a hands-free mobile phone while driving affects critical components of the perception-action cycle. Anticipatory coordination and control actions are compromised when one's attention is directed away from the critical task of pickingup specificational information about the affordances of the open road. References Corballis, M. (2002). From hand to mouth: The origins of language. Princeton University Press. Pellecchia, G. L., & Turvey, M. T. (2001). Cognitive activity shifts the attractors of bimanual rhythmic coordination. Journal of Motor Behavior, 33, 9-15. Treffner, P. J., Barrett, R., & Petersen, A. J. (2002). Stability and skill in driving. Human Movement Science, 21, 749-784.

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Treffher, P. J., & Peter, M. (2002). Intentional and attentional dynamics of speech-hand coordination. Human Movement Science, 21, 641-697.

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A Comparison of Real Catching with Catching in a CAVE Joost C. Dessing, C. (Lieke) E. Peper, & Peter J. Beek Vrije Universiteit, Amsterdam, The Netherlands In examining how interceptive actions are guided by optical information, it is important to control (and manipulate) optical variables in dedicated experiments. Although virtual reality (VR) is a potentially powerful tool in this context, technical issues have severely limited its usefulness in experimental settings (Tarr & Warren, 2003). Whereas today's VR systems may be adequate for studying reaching (Bingham et al., 2001), navigation (Tarr & Warren, 2003) and perceptual judgement tasks (Zaal & Michaels, in press), their usefulness in investigations of interception tasks (involving object manipulation) remains to be established. Although Rushton and Wann (1999) reported realistic grasping movements in VR, when tactile sense of the ball was provided by another ball attached to the hand, a full comparison of real catching and catching in VR is required to assess the usefulness of VR systems in catching research. To this end, three experiments were performed, involving both real approaching balls and identical approaches simulated in a VR environment. Methods In the 'real' experiments balls were swung toward the subject, who was instructed to either catch or 'grasp' it. Grasping involved making a catching movement, while the ball's motion was blocked just before the interception point (IP) and the subject grasped a ball that was already attached to the palm of the hand. In the VR experiment the same grasping task was performed in a CAVE (Cave Automated Virtual Environment, a 3.05 x 3.05 x 3.05 m room whose floor, front and side walls consist of projection screens). Subjects (N = 8, stereoacuity >80 s arc"1) were seated with their heads in a chinrest. The right hand could be moved in a lateral direction along a horizontal bar. White balls (diameter 8 cm) were presented

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against a black background (flight time: 1.56 s). Two initial ball positions (IBP), three initial hand positions (IHP), and three IPs were used, all on the right side of the subject. Using the recorded hand movements (Optotrak), the moment of movement initiation (Tjni) and the constant error of the final hand position (i.e., hand position at the ideal moment of catch/grasp) were determined. Both are widely used variables in the catching literature. Since recent empirical and theoretical studies of interceptive actions (cf. Dessing et al., 2002) have highlighted systematic changes in movement direction, the amount of movement directed away from the final hand position (ALnp) and the number of movement reversals (MRs) were calculated as well. The smoothness of the movement was quantified by the normalized integral of the absolute jerk (NintJerkabs) and the number of velocity peaks. A 3 x 2 x 3 x 3 repeated measures ANOVA was used (post-hoc: paired-samples t-tests). For the sake of brevity, we only report significant differences (p<0.05) between the Experiments. Data is represented in the text as (mean; standard deviation). Results Experiment had a significant main effect on Tjni (F(2,14) = 5.90), NintTerkab, (F(2,14) = 15.68) and ALHP (F(2,14) = 5.13). Initiation occurred significantly later in the CAVE (1.01; 0.17 s) than for catching (0.86; 0.16 s) and grasping (0.91; 0.20 s). NinUerkabs was significantly lower in the CAVE (19.9; 7.1 m s'3) than for catching (40.2; 9.5 m s'3) and grasping (32.1; 15.9 m s"3): indeed, there were significantly less velocity peaks in the CAVE (1.38; 0.32), than for catching (2.15; 0.25) and grasping (1.68; 0.47) (x2(2,8) = 14.25). ALHP was significantly higher for catching (6.5; 3.5 cm) than in the CAVE (3.1; 2.8 cm): there were significantly less MRs (%2(2,8) = 10.75) in the CAVE (0.33; 0.27) than for catching (0.77; 0.16) and grasping (0.55; 0.35). Significant three-way interaction effects on ALHp revealed that (a) IP had a significant effect for both IBPs in the CAVE, while for catching and grasping it was only significant for the IBP closest to the subject (Figure 1A-C); (b) for all three experiments the IP x IHP interaction was similar, but of a different magnitude (Figure 1D-F).

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Figure 1. The Experiment x IP x IBP (A-C) and Experiment x IP x IMP interaction (E-F) for DLHP. Error bars indicate standard errors. The numbers 1-3 (IP, IMP) and 1-2 (IBP) refer to the position relative to the subject (1: closest to the body).

Discussion Compared to real catching, movements in the CAVE were initiated later, were smoother (less velocity peaks) and more directly aimed at the final hand position (less MRs). Because both smoothness and MR amplitude are a function of movement time (Lee et al., 1997; Dessing et al., 2002), the latter effects may partially result from the delayed initiation in the CAVE. In addition, these effects may also have been mediated by the (although nonsignificant) difference between real catching and grasping (note that, necessarily, the grasping task was also used in the CAVE experiment). Despite these quantitative differences, the qualitative effects for ALHp were similar for real catching and catching in the CAVE (see Figure 1). Thus, provided that enough statistical power can be achieved, it might be possible to corroborate these essential trends in performance in a CAVE experiment. In conclusion, catching in reality and in the CAVE differ quantitatively, which might be attributable to differences in movement

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initiation. Therefore, a test of explicit models for catching cannot be performed in the CAVE without reservations. References Bingham, G.P., Bradley, A., Brailey, M., & Vinner, R. (2001). Accommodation, occlusion and disparity matching are used to guide reaching: a comparison of actual versus virtual environments. Journal of Experimental Psychology: Human Perception and Performance 27, 1314-1334. Dessing, J.C., Bullock, D., Peper, C.E. & Beek, P.J. (2002). Prospective control of manual interceptive actions: comparative simulations of extant and new model constructs. Neural Networks 15, 163179. Lee, D., Port, N.L., Geogopoulos, A.P. (1997). Manual interception of moving targets. II. On-line control of overlapping submovements. Experimental Brain Research 116,421-433. Rushton, S.K., & Wann, J.P. (1999). Weighted combination of size and disparity: a computational model for timing a ball catch. Nature Neuroscience 2, 186-190. Tarr, M.J., & Warren, W.H. (2003). Virtual reality in behavioral neuroscience and beyond. Nature Neuroscience 5, 1089-1092. Zaal, F.T.J.M., & Michaels, C.F. (in press). Information for catching fly balls: Judging and intercepting virtual balls in a CAVE. Journal of Experimental Psychology: Human Perception and Performance.

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Task-Constraints and Movement Possibilities Influence the Timing of Hitting Simone Caljouw1, John van der Kamp1, & Geert Savelsbergh1'2 Vrije Universiteit Amsterdam Manchester Metropolitan University

2

To hit a ball accurately to a target, actors must contact the ball at the right time with the right spatial orientation and velocity of the end-effector (hand or implement). Therefore, precise coordination between visual information about the ball's trajectory and the effector movement is necessary to prepare for impact. Descriptive work on the duration of hitting movements revealed that the initiation of the swing occurred roughly at a constant time before the ball reached the actor (i.e. time-to-contact, or TTC). Hubbard and Seng (1954) observed remarkably constant swing times in baseball batting irrespective of the speed of the pitch. These data suggest that the timing of a constant swing movement could be controlled by gearing initiation to a critical value of an information source that co-varies with TTC, for example, the relative rate of expansion (Lee, 1976). However, other hitting-experiments showed that actors adapt their timing to the approach speed of the ball, i.e., movements are initiated at a shorter time before contact in response to faster approaching balls (e.g. Gray, 2002; Tresilian & Lonergan, 2002). These effects of ball speed on timing show that participants often do not use critical values of information sources that co-vary with TTC to regulate swing initiation. Instead they may use information such as the absolute rate of expansion and the rate of constriction of the gap between effector and ball, as was found for the regulation of one-handed catching (Caljouw, Van der Kamp, & Savelsbergh, 2003). The adaptation of timing to ball speed is often accompanied by speedcoupling, that is, covarying the movement velocity with the speed of the approaching ball.

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In many experiments it was found that participants increase their movement velocity to intercept faster approaching objects (e.g. Tresilian & Lonergan, 2002). A decrease in movement duration is always accompanied by an increase in movement velocity when the movement amplitude is constant (i.e. goal distance). By enforcing the distance to be covered by the ball after contact, we created a conflict between the demands of ball speed and impact requirements in hitting. A fast ball induces high movement velocity and hence high impact, which may contradict with low impact task constraints such as the requirement to propel the ball towards a near goal. The reported experiments aimed to assess how participants deal with these contradictory task constraints. Experiment 1: The effect of ball approach speed and impact constraints on timing Participants (N = 9) had to perform one-dimensional hitting movements over a fixed distance (45 cm) in the frontal plane to balls approaching on a head-on collision course (Figure 1).

Figure 1. Participants had to hit a ball (0 7.5 cm) moving with constant velocity at eye height with an oblong object (2.5 cm) attached to an aluminum rod (43.5 cm) mounted on a trolley. The trolley could be displaced in one-dimension (1 on ball path).

Placed on a trolley, participants had to intercept balls approaching at different constant speeds (1 & 2 m/s) without any constraints on the impact (i.e., no specified goal) and in the second part, participants had to propel the ball towards a goal at 105 cm from the interception point. The results showed that the timing of the interceptive action (i.e., initiation of the hit before impact) was significantly affected by ball speed when the hitting movement was not directed to a goal. In

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contrast, a constant time-to-impact strategy was found when the movement velocity at contact was constrained (Figure 2, left panel).

Figure 2. Movement time of the forward hit as a function of ball speed (1 vs. 2 m/s) and condition (goal vs. no-goal), for hitting movements with (right) and without backswing (left).

Experiment 2: The effect of a backswing on timing In a second experiment, participants (N = 10) were forced to make a backswing movement. The setup for this experiment was similar to Experiment 1, except for the initial location of the hitting device on the track. At the beginning of each trial, the effector was positioned at the interception point, so participants first had to move away from the interception point before hitting the ball with an appropriate impact velocity. The results showed that the timing covaried with ball speed for both conditions, i.e. with and without constraints on the impact velocity (Figure 2, right panel). This was accomplished by adjusting the amplitude of the backswing, since the amplitude was found to be smaller in response to faster approaching balls. Discussion These results suggest that task-constraints and movement possibilities, such as whether or not aiming for a goal and hitting with or without backswing, influence the information-movement coupling. The processes of change that may underlie the adaptation of the action to task constraints entail either a change in optical variables that

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participants pick up to temporally regulate their movement or a change in the control law that links the optical variable to the movement. References Caljouw, Van der Kamp, & Savelsbergh (2003). Catching optical information for the regulation of timing. Experimental Brain Research (submitted). Gray, R. (2002). Behavior of baseball players in a virtual batting task. Journal of Experimental Psychology: Human Perception and Performance, 28(5), 1131-1148. Hubbard, A. W., & Seng, C. N. (1954). Visual movements of batters. Research Quarterly, 25,42-57. Lee, D. N. (1976). A theory of visual control of braking based on information about time-to-collision. Perception, 5(4), 437-459. Tresilian, J. R., & Lonergan, A. (2002). Intercepting a moving target: effects of temporal precision constraints and movement amplitude. Experimental Brain Research, 142(2), 193-20.

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Perception-Action Coupling and Expertise in Interceptive Actions Cyrille Le Runigo & Nicolas Benguigui Center for Research in Sport Sciences, University of Paris XI In opposition to the operational timing hypothesis (Tydesley & Whiting, 1975), it has been indicated repeatedly that expertise in ball sports may result from a specific ability to continuously couple the movement of the racket to the approaching ball (e.g., Bootsma & van Wieringen, 1990). McLeod (1987) suggested that this ability could exist even in situations where the ball trajectory undergoes unexpected changes: The shorter the visuo-motor delay, the greater the accuracy of interception by experts. The goal of this experiment was to test whether experts in ball sports were better in their ability to adapt their responses in situations where the object velocity (not trajectory) changed suddenly during the approach. Method Participants (N = 20) included ten expert tennis players and ten non-experts. The device consisted of a runway (4 m length) with 200 light-emitting diodes (LEDs) that simulated the linear motion of an object toward a target situated at the right-end of the runway, and a cart that could slide along a horizontal track perpendicular to the runway. Participants had to intercept the simulated moving object with their right hand holding the cart. The movement was limited to a 0.80 m portion of the track. A customized data acquisition system detected the position of the sliding cart on its track and recorded the kinematics of the hand and the accuracy of the responses. Three different approaches were tested, involving the same initial speed of 2 m/s. In 50% of the trials, the speed remained constant until the end of the track (constant velocity). In the remaining 50%, the speed changed 400 ms before the requested moment of contact, either to 1 m/s (deceleration) or to 3 m/s (acceleration).

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Data analysis Dependent variables included (1) the constant error (CE), corresponding to the time (in ms) between the arrival of the stimulus and the time of contact, with negative signs for early contact and positive signs for late contact, and (2) the visuo-motor delay (VMD), corresponding to the time elapsed between the (occurrence of the) change in stimulus velocity and the change in the cart's movement. This last change was detected using a threshold for acceleration or deceleration, calculated for each participant. CE was analyzed in an Expertise x Velocity ANOVA with Expertise (Experts, Non-experts) as a between-subjects variable and Velocity (Constant, Acceleration, Deceleration) as a within-subjects variable. VMD was analyzed in a different Expertise x Velocity ANOVA, with Expertise (Experts, Nonexperts) as a between-subjects variable and Velocity (Acceleration, Deceleration) as a within-subjects variable. A Newmann-Keuls post hoc test was used for a posteriori comparisons. An alpha level of .05 was used for all statistical tests. Results For CE, the results indicate an interaction between Expertise and Velocity, F(2, 36) = 12.23. Post hoc analyses showed that experts were more accurate than non-experts in both conditions of speed variation (35 ms and -132 ms for deceleration and +23 ms and +68 ms for acceleration, respectively), whereas no difference occurred in the constant velocity condition. For VMD, the results revealed significant main effects of Expertise, F(l, 14) = 92.95, and Velocity, F(l, 14) = 42.88. VMD was shorter for experts than for non-experts in both conditions (206 ms vs. 269 ms for deceleration, 148 ms vs. 211 ms for acceleration). The shorter VMD in experts indicates a faster adaptation of the movement to the sudden change in stimulus velocity, and may explain part of the difference in response accuracy. Complementary information is given in Figure 1, which represents the velocity of the cart in five trials by two representative participants, one expert and one non-expert. In the acceleration condition (Figures la and Ib), the velocity peaks produced by the expert are higher than those produced by the novice (around 2.2 m/s vs. 1.2 m/s). This result reveals

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a better coupling for the expert and may also explain why CE was reduced. This difference in speed does not seem to exist in the deceleration condition. However, adaptive changes in the final portion of the movement (acceleration of the cart) are clearly evident in that condition for the expert (Figure Ic) but not for the novice (Figure Id). This final acceleration of the hand also contributes to the better result obtained for the experts in terms of CE, for a clear relation was found to exist between CE and the acceleration of the cart in the final portion in all three velocity conditions.

Figure 1. Cart velocity profiles for five representative trials of one expert (above) and one novice (below) in the acceleration (left) and deceleration (right) conditions. The vertical line indicates the moment of change in velocity; the vertical ellipse illustrates the zone in which movement corrections occurred. The time remaining before contact after the change in velocity depended on the actual speed of the stimulus after that change.

Conclusion These results confirm those obtained by McLeod (1987) and extend them to a sudden change in approach velocity. Experts' performance was less affected by this change. The observed better accuracy can be explain by a shorter VMD and the consecutive better

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adaptation in the movement patterns. Both results are compatible with an optimization of the perception-action coupling during expertise. References Bootsma, R. J., & van Wieringen, P. C. W., (1990). Timing an attacking forehand drive in table tennis. Journal of Experimental Psychology: Human Perception and Performance, 16,21-29. McLeod, P. (1987). Visual reaction time and high-speed ball games. Perception, 16,49-59 Tydesley, D. A., & Whiting, H. T. A. (1975). Operational timing. Journal of Human Movement Studies, 1, 172-177.

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Binocular Depth Vision in the Timing of One-Handed Catching Liesbeth Mazyn1, Geert Savelsbergh3'4, Gilles Montagne2, & Matthieu Lenoir1 'Ghent University, Belgium Universite de la Mediterranee, France 3 Vrije Universiteit, Amsterdam, The Netherlands 4 Manchester Metropolitan University, UK 2

The timing of interceptive actions like catching is based upon predictive visual information on the time before the arrival of an oncoming object. Several information sources (both monocular and binocular) contribute to the temporal regulation of a catch. Three experimental paradigms allow conclusions regarding the role of binocular depth vision: the use of a telestereoscope, a device that makes an object look closer than it really is, the use of virtual reality, and the comparison of catching performance under monocular and binocular viewing conditions (Bennett et al., 2000; Rushton & Wann, 1999; Savelsbergh & Whiting, 1992). These experiments confirm the conclusion that binocular information sources facilitate the temporal control of intercepting movement and give rise to superior performance. In these studies however stereoscopic viewing was manipulated in participants with normal stereopsis. The aim of the present study was to assess the role of monocular and binocular information sources in normal participants and in participants with a congenital or early-onset deficiency in stereopsis. The underlying hypothesis was that participants having a lifetime experience with a lack of stereopsis might have developed a compensatory superior monocular vision strategy as compared to normal participants. Method Two groups of 9 Physical Education students (7 males and 11 females equally divided among both groups) between 18 and 23 years of age with normal or corrected-to-normal visual acuity participated in this

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experiment. The STEREO+ group scored normally on the Titmus Fly Stereotest (40 sec of arc or better), while the subjects of the STEREOgroup all had very weak stereopsis (> 800 sec of arc). Participants caught 2 blocks of 30 tennis balls launched at 14.6 m/s from a Singly Promatch launching machine, one block under monocular and one block under binocular vision. The order of blocks was randomized over participants. Before starting each catch, participants held their catching hand near the shoulder with thumb and index finger together. All trials were recorded with a Sony CCD-TRV94E Hi8 camera (25Hz) from the medial side of the catching arm. Three-dimensional kinematics of the catch were recorded by means of an 7-camera Infrared recording system (Qualisys) at 240 Hz. Position data from reflective markers on the top of the thumb and index finger were filtered at 10 Hz. The percentage of successful catches, movement time of the catch (opening and closing of the hand), and time of initiation of the hand closure before ball-hand contact were analysed with a 2 (monoversus binocular) x 2 (stereo- versus stereo+) ANOVA with repeated measures on the first factor. Results Catching performance was better under binocular than under monocular vision (F(l,8) = 48.30, p<.001), but a significant interaction effect occurred between level of stereopsis and visual condition (F(l,8) = 10.78, p<.001). Whereas subjects with normal stereopsis performed better binocularly than in the monocular condition (p<.01), subjects with weak stereopsis performed similarly under both visual conditions (Figure 1). Analysis of the kinematic variables revealed a significant effect for the time of onset of the hand closure prior to contact (F(l,8) = 10.78, p<.01). The STEREO+ group started the grasp earlier when catching binocularly as compared to the monocular condition (p<.01). For subjects from the STEREO- group, no differences in initiation time of hand closure appeared between the two visual conditions (Fig. 2). For movement time, no effect of visual condition (F(l,8) = 2.13, n.s.) or interaction between visual condition and stereopsis (F(l,8) = 2.31, n.s.) was found.

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Figure 1. Interaction between stereopsis level and visual condition on catching performance.

Figure 2. Interaction between stereopsis level and visual condition on time of grasp initiation.

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Discussion Despite their life-time experience with a lack of binocular depth vision, the STEREO- subjects seem not to have compensated for this deficiency by depending more on other information sources like tau or concordant information from both monocular views. Especially when the temporal constraints get rather severe, as was the case in the present experiment, retinal disparity could be held responsible for the superior binocular performance. These findings could imply the flexible use of information sources: for the temporal control of intercepting skills subjects are relying on a combination of both monocular and binocular sources, or they have the ability to switch very easily from monocular sources in monocular catching to binocular information when performing under normal visual conditions. The outperformance of binocular catching in subjects with normal stereoscopic vision seems to be connected with the earlier initiation of their grasp. Therefore it could be stated that the decrease in performance when catching monocularly or by subjects with a lack of stereopsis is due to timing errors: the ball bounces away from the hand and out of reach of the closing fingers, leading to an unsuccessful catch. So some kind of binocular information source apparently contributes in the temporal control of the initiation of the grasp. References Bennett, S. J., van der Kamp, J., Savelsbergh, G. J. P., & Davids, K. (2000). Discriminating the role of binocular information in the timing of a one-handed catch - The effects of telestereoscopic viewing and ball size. Experimental Brain Research, 135, 341347. Rushton, S. K. & Wann, J. P. (1999). Weighted combination of size and disparity: a computational model for timing a ball catch. Nature Neuroscience, 2, 186-190. Savelsbergh, G. J. P. & Whiting, H. T. A. (1992). The acquisition of catching under monocular and binocular conditions. Journal of Motor Behavior, 24, 320-328.

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How Do We Reach and Grasp a Virtual Image? T. Fukui, A. Ishii, & T. Inui Department of Intelligence Science and Technology Kyoto University, Japan To reach and grasp an object properly, we have to recognize the position of our moving limb using visual and proprioceptive information, and perceive the properties of a target object through visual and tactile information. We gain tactile feedback when we touch the surface of an object, and its feedback is thought to be critical for the control of grasping. We therefore examined how the lack of tactile input when grasping affects the kinematics of hand shaping and wrist displacement, and whether online visual information would be able to compensate for a lack of tactile input. To investigate this issue, we developed an experimental system using a virtual reality (VR) technique. We compared the properties of prehension movements to a computer-generated target with prehension movements to a real object, and with pantomimed movements. Pantomimed movements are defined as the movements "directed to remembered object" (Goodale et al., 1994). We also refer to the validity of VR in studies on grasping. Method Eight right-handed subjects participated in the present experiment. As illustrated in Figure 1, a target object was shown 30cm ahead of and 21cm over the starting hand position. The size of the target cylinder was llcm high and 6cm in diameter. A computer-generated virtual object and a wooden real object were used as targets. The virtual object was shown on a CRT display, and subjects viewed it binocularly through liquid crystal shutter glasses (Crystal Eyes). The wooden real object was presented on a stand in the same position as the virtual object. The kinematics of the wrist trajectory and the distance between the

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subject's thumb and middle finger were measured using an electromagnetic motion tracking sensor (FASTRAK) and CyberGlove.

Figure 1. Schematic illustration of the experimental setup. comfortably on a chair at a table.

Participants sat

Participants were told to place their right hand in the starting position before each trial and to begin each trial with the tips of the thumb and index (also middle) finger of the right hand touching each other. They were instructed to reach and grasp the cylinder under five conditions. (1) Normal prehension to a real object (normal condition); (2) prehension to a real object, but when touching the surface of object, doing so as softly as possible (soft touching condition); (3) prehension to a 3D-image (virtual condition); (4) pantomimed movements viewing the object placed 15cm to the left of the midline from the participant's perspective (pantomime "with cue" condition); (5) pantomimed movements after eliminating the target object (pantomime "without cue" condition). The aim of condition (2) was to make participants control their grasping spontaneously (not relying on tactile feedback). Movements were executed with online visual information. Subjects were told to move at a "normal speed for everyday life." Experimental trials were organized into five blocks. Each block consisted of 16 trials in each condition. The order of experimental conditions was counterbalanced across participants.

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Results We here report the results of measurement of the maximum velocity of wrist and the amplitude of overshoot. The amplitude of overshoot was defined as the difference between maximum finger aperture and the value of finger aperture when hand enclosure was stopped. These parameters were submitted to an ANOVA. The Newmann-Keuls post-hoc test (p<0.05) was used. Maximum velocity (MV) Statistical significance was not reached (F(4,28) = 2.458, p = 0.069). However there was a trend for MV of movement to a real object (normal: 87.2 cm/s. soft touching: 81.9 cm/s) to be faster than that of pantomimed movement ("with cue": 79.1 cm/s. "without cue": 78.0 cm/s), as Goodale et al. (1994) demonstrated. MV of the virtual condition (83.3 cm/s) was shown to lie between these two values.

Figure 2. Mean amplitudes of overshoot (n=8). Error bars represent the standard error of mean values. (N: normal, ST: soft touching, WC: pantomime "with cue", WOC: pantomime "without cue", V: virtual).

Amplitude of overshoot (AO) Mean amplitudes of overshoot in each condition are shown in Figure 2. Experimental conditions affected AO (F(4,28) = 3.421, /?<0.05). The values for soft touching and pantomimed ("with cue" and "without cue") conditions were significantly smaller than that for the normal condition (p<0.05). AO of the virtual condition was not significant for any other conditions. However, for three participants,

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their values in the virtual and normal conditions were remarkably similar. For example, participant K's values were 2.45 cm in the normal condition and 2.66 cm in virtual one. Discussion While the finding that AO in the virtual condition was not the same as that in normal condition may reflect the importance of tactile feedback, the lack of tactile feedback when grasping can be compensated for by online visual information quite well, as AO in the virtual condition was remarkably similar to that in the normal condition in some participants. The knowledge that "one cannot grasp a virtual cylinder" probably affected each participant's performance; that is, the affordance of virtual images may be different for each actor. However, when participants are provided with "proper instructions" and online visual information, the VR technique will be valid for investigating the kinematics of prehension movements. Acknowledgments. This work was supported by the "Research for the Future Program", administered by the Japan Society for the Promotion of Science (Project No. JSPS-RFTF99P01401) References Goodale, M. A., Jakobson, L. S., & Keillor, J. M. (1994). Differences in the visual control of pantomimed and natural grasping movements. Neuropsychologia, 32,1159-1178.

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Movement Sequences for Cracking an Egg Aya Takahashi, Koji Hayashi, & Masato Sasaki The University of Tokyo, Japan Bernstein (1996) described actions as a sequence of movements with an object directed at achieving a goal or solving a problem. Schwartz et al. (1991) studied a patient who was initially unable to execute a simple sequence of movements needed to conduct activities of daily living, but improved over time. To learn more how actions on an object with unique surface characteristics are sequenced by normal and brain damaged individuals, we observed individuals cracking eggs. Method Eight adults were asked to crack an egg on the edge of a bowl. With careful observation, we were able to classify their actions into a sequence of two different movements, "exploration" and "impact." Exploration, which occurs first, entails the actor's tapping the egg against the bowl to measure the shell's hardness. The actor then strikes the egg against the bowl with enough force to break it, the impact stage. Results Figure 1 shows a series of egg-bowl collisions made by eight adults while cracking eggs. The mean number of movements was 3.88 and there is a clear distinction between exploration and impact. We also analyzed the sound of the collision of the eggs against the bowl. Figure 2 shows S3's sound spectra. The horizontal axis represents frequency and the vertical axis power. As shown in Figure 1, we classified the first movement as exploration and the subsequent movements as impact. The sound spectrums show a difference in pattern between the first movement and the second and third movements, which supported our earlier observation of two distinct movements in cracking an egg.

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Figure 1. Sequence of movements to crack an egg for eight adults.

Figure 2. S3's sound spectra when cracking an egg.

We also observed a 42 year-old male, MM, who suffered a traumatic brain injury in November 2000, which left him unable to organize his actions. Figure 3 shows the sequence of movements involved in his various attempts to crack an egg from September 2001 to June 2002. MM required more movements to crack an egg (M = 22.57) than normal adults and sometimes alternated exploratory and impact movements.

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Figure 3. A sequence of movements made by MM when cracking an egg. Note: Exploration includes exploration with non-contact against the bowl.

Figure 4 (a) shows the first 8 sound spectra in the egg cracking trial from November 1st. MM's two types of movements were not clearly differentiated. By the seventh session in June 2002, exploration and impact could be clearly differentiated. Figure 4 (b) shows the first 8 sound spectra, which suggest that five exploratory movements preceded his first impact movement. Although MM still required more movements to crack an egg than normal adults, the two different types of movements are easily distinguished.

Figure 4 a) Sound spectra from MM's November 1st egg cracking trials.

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Figure 4 b) Sound spectra from MM's June egg cracking trials. Discussion

Bernstein (1996) argued that actions consisted of "different movements that replace each other systematically," and that the movements are "related to each other by the meaning of the problem" (p. 146). Our findings indicate that adults adaptively explored the eggshell surface by tapping it against the bowl before hitting it sufficiently hard to actually crack it. MM, whose exploration and impact were initially disorganized because of his brain injury, seemed to improve in his egg cracking ability when his movements had two clearer different movements that adaptively related to each other to crack an egg. This suggests that, over time, MM began to learn to explore perceptually the egg's hardness characteristics in order to appropriately organize his subsequent striking actions. References Bernstein, N. A. (Ed.). (1996). Dexterity and its development. Mahwah, NJ: Lawrence Erlbaum Associates. Schwartz, M.F., Reed, E.S., Montgomery, M., Palmer, C., and Mayer, N.H. (1991). The quantitative description of action disorganization after brain damage: A case study. Cognitive Neuropsychology, 8(5), 381-414.

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Tau Guidance for Mobile Soccer Robots Joe Leonard, Paul Treffner, & John Thornton Complex Active Visualisation (CAV) Lab Griffith University, QLD, Australia Traditional approaches to mobile robot guidance have utilised an internal model of the environment constructed from sensor data in order to plan a course of action. Although this approach has been challenged by behaviour-based robotics (e.g., Brooks, 1991), the creation of "smart perceptual instruments" that attempt to directly couple perception and action has been seriously addressed by the ecological robotics paradigm founded upon Gibson's ecological optics (Duchon et al., 1995). We explore the possibility of using tau information for guidance of a mobile robot. More specifically, an attempt to implement some of the navigation techniques using tau as outlined by Lee (1998) was undertaken. Problems encountered during implementation and possible solutions are given. Although Lee introduced the concept of using tau (f) for the guidance of movement (Lee, 1998) and although tau is usually said to represent the time to closure of a gap, this is not entirely true. A negative tau represents the time to closure of the gap, while a positive tau represents the time since the closure of the gap (i.e., the gap is opening). A gap can represent a distance, an angle, a difference in force or any other gap. The information on time to closure provided by a sensor can therefore be used to control the closure of a gap and thus to guide movement. Lee also introduced the idea of guidance through tau coupling in which the ratio of taus of different gaps are kept invariant. Method Here we are concerned with three of the techniques discussed by Lee in which tau may be used as a technique for guidance and how they may be implemented in a system of mobile robots. The first technique has been designated as guidance by "infinite tau" (Figure la). By keeping constant the angle between the orientation of the robot and the

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target direction, the tau of this angle is infinite (i.e., the gap, D, neither closes nor opens but remains constant while velocity, V, diminishes; tau = D/V). The result of keeping this angle constant is that the robot will drive towards the target, spiralling around the target without ever actually reaching it. The second technique involves keeping constant the change in the rate of gap closure, tau-dot ( f ) (Figure Ib). By keeping this rate constant the robot steers in an intercepting course towards the target. The third guidance technique uses tau coupling (Lee, 1998). Figure Ic shows an example of controlling the time to closure of two angles to provide guidance to a target point. In this example a reference point is required. The gaps coupled include the gap between the robot's orientation and the angle from the robot to the target point (ROG), and the gap between the angles from the robot to a reference point and the robot to the target point (MOG). As can be seen from figure Ic, by maintaining TROG + TMOG = 0 ^e r°bot w^ maintain a circular path intercepting the target. Also evident from Lee's work (1998) is that further information is available. If TROG + IMOG > 0 the robot is outside of the arc, and if TROG + IUOG< 0, the robot is inside the arc. The three techniques discussed above were implemented on a Yujin YSR-A type robot soccer system. The system provides considerable information to the controller including details of orientations, velocities, and positions of all objects on the field. For this implementation, the only information used by the controller was the orientation of the robot, the angle from the robot to the target (in this case an orange ball), and in the case of the coupled tau implementation, the angle from the robot to a reference point. All other potential information was ignored as per the principles of smart perceptual instruments. Results The infinite tau technique was implemented and performed well and the robot maintained a consistent spiral towards the goal. Due to the physical nature of the robots, tight circles are difficult to maintain and eventually the robot began to move off the spiral in a "chaotic" fashion. However the robot would regain its path and begin to spiral back in towards its target point again. This same pattern was observed consistently. The technique, although never reaching its target, is useful

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for the robot soccer domain as it enables the robot to place itself behind its target (a ball) in order to manoeuvre it towards a goal. Problems remained with implementation of the two remaining techniques. Since the system used for implementation contained a noise component in the visual information received, errors were contained in the measurement of angles. When measuring the rates of changes of angles, such errors were magnified, which made guidance based upon f information inconsistent and ineffective. Similar problems were incurred when attempting to couple two closures (coupled tau).

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Conclusions As discussed, the use of tau (especially its change over time) requires reliable sensors. Many robotic systems, including the one in which this research was implemented, contain a significant amount of noise due to imperfections in the sensors. Although some initially promising results were obtained, the reliability of the optic information prevented successful implementation of some techniques. Current work on the system involves the implementation of a Savitzky-Golay (Press et al., 1988) smoothing filter to provide more reliable data. Upon completion, further work is planned for investigating mobile robot guidance techniques that utilise invariants within an agent-environment context.

References Brooks, R. (1991). Intelligence without representation. Artificial Intelligence, 47, 139-159. Duchon, A., Warren, W., & Kaelbling, L. (1995). Ecological robotics: Controlling behavior with optical flow. In J. Moore & J. Lehman (Eds.), Proceedings of the 17th annual conference of the cognitive science society, (pp. 164-169), Mahwah, NJ: Lawrence Erlbaum Associates. Lee, D. (1998). Guiding movement by coupling taus. Ecological Psychology, 10,221-250. Press, W., Teukolsky, S., Vetterling, W., & Flannery, B. (1988). Numerical recipes in C: The art of scientific computing. Cambridge, MA: Cambridge University Press.

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Stereoscopic 3D Visualisation Using Gaze-Contingent Volume Rendering: Exploratory Perception in Action Mike Jones & Paul Treffner Complex Active Visualisation (CAV) Lab Griffith University, QLD, Australia Across many fields of science, such as biomedical imaging and geophysical mapping, there is a need to visualise 3D stereo volumetric (voxel) data. In a gaze-contingent display (GCD) the image changes in response to shifts in the observer's gaze (Geisler & Perry, 1999; Saida & Ikeda, 1979) and is usually dependent upon some form of eye-tracking. The principle difficulty in conventional volumetric visualisation methods—which globally adjust how opaque or transparent different data voxels appear—is of maintaining sufficient partial-opacity to see all the features of interest, but not so much that those features deep within the volume are hidden by those near the observer. Gaze-contingency allows opacity to be spatially varied throughout the volume and continually modified as the viewer fixates at different positions. As with normal binocular vision, whatever is fixated is seen clearly, while the surrounding volume is rendered fainter, but still provides spatial context (as with peripheral vision). Precisely because the context is rendered with less acuity, it does not compete for visual attention as the in-focus section of the display. This is quite unlike standard stereoscopic displays that render all regions of the volume with equal acuity. Implementing a gaze-contingent display requires linking a suitable rendering algorithm with a gaze- or eye-tracking system. Implementing an effective gaze-contingent display therefore invites a careful consideration of human perception qua visual exploration. Past work involved construction of a stereoscopic gaze-tracked display prototype (Jones, 1999; Jones & Nikolov, 2000). Here we consider how the perception-action approach offers a useful framework within which to extend this class of instrument and apply it to real visualisation tasks.

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Method Figure 1 shows the mirror-stereoscope GCD. Two LCD displays (24" diagonal; 1920 x 1200 pixels; response time = 25 ms) are reflected by cold mirrors (that reflect visible and transmit infrared (IR) light) and provide a 3D view with a screen-eye distance of 300 mm. IR-sensitive video cameras behind the mirrors capture images of each eye under suitable illumination, and constitute the gaze-tracker.

Figure 1. Prototype mirror-stereoscope

A multitude of algorithms exist for rendering 3D voxel data, with direct volume rendering (DVR) algorithms generally providing the greatest flexibility in lighting and shading. Region-enhanced DVR (REDVR) algorithms apply a weighting function, Q, around a moving point, which locally modulates the rendering by, for example, making those regions close to the point more opaque than those further away (Jones & Nikolov, 2000). RE-DVR images generated from the Chapel Hill Volume Rendering Test Data Set are shown in Figure 2. The tracking system must measure the observer's fixation position in 3D with sufficient accuracy to position the enhanced region. A pupil-centre corneal-reflection (PCCR) technique was applied to measure each eye's gaze direction, with left/right-eye triangulation used to estimate 3D position. During a calibration phase an observer fixated in turn upon each of a set of bright point targets within a 120 mm wide wire-frame cube. Tracking parameters were adjusted to minimize rms error distance between the known and the reconstructed target positions.

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Figure 2. Direct volume rendering (left) and region-enhanced direct volume rendering (right).

Across targets separated by 75 mm in each of the three Cartesian axes, rms errors of 3.0 mm and 7.5 mm were obtained in the lateral and axial directions, respectively. According to a perception-action perspective, exploratory action includes eye movements and is necessary to reveal the optical invariants supporting perception, which, in turn, invites new exploratory movements. Information constrains action and this is true of visual exploration as well as physically moving through the world. A GCD offers the possibility of introducing into this loop a controlled and monitored component, to better understand the processes involved. Since visual exploration involves a series of head movements, eye saccades, fixations and pursuit movements, each region of a scene scrutinised may have associated changes in contrast, brightness, hue, and texture elements. It is suggested that the (higher-order) invariants underlying such optical changes can specify affordances for the eyehead-body visual system that seeks information at the scale of ecological optics. Visually constraining where an observer looks might be possible using marginal rendering changes to subtly direct the ocular system to seek resolution and look at features of interest. Prompting systems are relevant to many semi-automatic systems where algorithms search data for particular features or abnormalities. In many applications the consequences of missing an abnormality are considered unacceptable and detection thresholds are thus set low resulting in a high falsepositive rate. Worse, if used to abruptly prompt a human observer the high alarm rate itself can mask situations requiring expert human

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scrutiny. Less obtrusive prompting (e.g., gaze-contingent focus), however, would be less likely to mask abnormal situations. Our approach involves changing the GCD's affordances and monitoring how visual exploration changes (e.g., by using the observer's scan-paths or sequences of successive fixations). Gaze-contingent affordances would be controlled between experimental conditions, for example, allowing the rendered image to respond to the observer's eye or head position and analysing the spatio-temporal distributions of fixation positions (Treffner & Kelso, 1999). Several key questions can further be addressed using this approach. What is the extent of the workspace (visual volume) through which an observer searches? Is the scrutinised region reduced or expanded when compared to without enhancement? During visual search, does the scan path involve small segments directing the observer towards local regions within the enhanced region? Is orientation maintained and is the observer aware of where he or she is with respect to landmarks? What benefits accrue from allowing head movements in addition to eye movements? Conclusions The perception-action framework is considered a useful paradigm for GCD development. Many questions addressed by the ecological approach can potentially help address issues of visualisation and virtual environments, while the latter can refine our understanding of the dual nature of information in relation to active observation. The design of GCDs provides an ability to optically vary the affordances provided by a scene such that they are defined as Gibson always implied—with respect to the organism. Acknowledgement. We wish to acknowledge the support of the Royal Society's Paul Instrument Fund for a grant allowing construction of the stereoscopic gaze-tracked display. References Jones, M. G. (1999). United Bristol Healthcare NHS Trust. Method and apparatus for displaying volumetric data. British Patent: 99124338.0; US Patent: 09/579,814. European Patent: 00304381.7.

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Jones, M. G. & Nikolov, S. G. (2000). Region-enhanced volume visualization and navigation. Proceedings of International Society for Optical Engineering (SPIE), Medical Imaging 2000 (Image Display and Visualization), 3976,454-465. Saida, S. & Ikeda, M. (1979). Useful visual field size for pattern perception. Perception andPsychophysics, 25, 119-125. Geisler, W. S. & Perry, J. S. (1999). Variable-resolution displays for visual communication and simulation. The Society for Information Display, 30,420-423. Treffher, P. J. & Kelso, J. A. S. (1999). Dynamic encounters: Longmemory during functional stabilization. Ecological Psychology, 11, 103-137.

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Does Exploration Promote Convergence on Specifying Variables? Alen Hajnal1, Claire F. Michaels1, and Frank T. J. M. Zaal2 'CESPA, University of Connecticut, USA Human Movement Sciences, University of Groningen, The Netherlands

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Michaels and de Vries (1998) asked perceivers to estimate peak pulling-force in computer-generated stick figures. A major finding was that participants changed over blocks of trials in the variables exploited and that they gradually attuned themselves to more useful kinematic variables after practice with feedback. One concern with such experiments is whether they are sufficiently natural; if not, the phenomena revealed, which ostensibly concern learning, may simply reflect adaptation to the curious computer displays. A characteristic of these displays and participants' interactions with them is that the perceiver is a passive recipient of stimulation. In Gibson's (1966) terms, the stimulation is imposed stimulation, in contrast to the stimulation in more natural settings, which is often stimulation obtained through exploration. Our goal in the present contribution was to ask whether perceptual learning in this force-judgment task is fostered by exploration. Our reasoning was as follows: A participant's goal is to become an expert in judging force. If we regard exploration as a fundamental activity of perceptual systems that yields information suitable to guide action, then analogously, exploration may yield information that guides learning. Our hypothesis was that if participants can generate their own stimuli, then they would converge on the better variable more quickly. Allowing individuals to generate their own stimuli puts interesting demands on experimental design, namely, that it is potentially difficult to discern whether any observed effect is due to choosing of the displays or whether it is due to the chosen displays. To keep these effects separate, we used a design in which participants were yoked in triplets. An Explorer was able to manipulate kinematic parameters of the upcoming display; an Observer saw the manipulated parameters and the displays; the Control participant saw only the display.

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Method Stick-figure displays of a human engaging in a bimanual standand-pull task were generated on an Apple Macintosh computer. Each trial consisted of three identical pulling cycles. Perceivers were asked to estimate the percentage of maximal pulling force exerted by the stick figure. The experiment consisted of a pretest block, three training blocks and a posttest block. Each block comprised 36 trials. Fifteen undergraduate students from the University of Connecticut were randomly assigned to one of three groups (Explorers, Observers, and Controls). In the pretest and posttest, participants watched the stick-figure displays and entered their judgment on a slider whose ends were labeled 0% and 100%; there was no feedback. In the training blocks, the Explorers manipulated parameter sliders (labeled displacement and velocity) that determined the stick-figure kinematics for the upcoming display (namely maximal displacement and velocity of the puller's center of mass). The yoked Observer was shown the slider positions selected by the Explorer. The Control saw only the stick-figure kinematics. After seeing the stick-figure kinematics, all participants entered their judgments and then received feedback on accuracy. Participants were run one at a time; instructions to Explorers and Observers emphasized attending to the relation between stick-figure movement and force. Results and Discussion Correlations between judgment and force were computed for each participant on each block, and their Z-scores were submitted to a one-between (Group) by one-within (Blocks 1 -5) analysis of variance. Figure 1 shows the average of correlations between judgment and force across blocks of trials for all three conditions. A significant effect of blocks of trials was found F(4, 48) = 18.21, /7<.0001; on average, participants' judgments correlated more highly with force on later blocks than on earlier blocks. The interaction between blocks of trials and condition was also significant, F(8, 48) = 2.34, ;?<.03. Explorers exhibited the most extreme performance of all groups; they showed the biggest improvement in performance, reaching the highest level by the third block, but deteriorated, to end up as the least successful group on the posttest. Participants in the Observer group and the Control condition

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Figure 1. Average correlations of judgements and force given as a function of blocks and conditions.

showed only marginal improvement between the pretest and the first training block. However their improvement was steady, and they lost little ground in the posttest, unlike the Explorer group. One possible reason for the decline is that, contrary to instructions, Explorers may have focused on the (task-irrelevant) relationship between the sliders and judgment, instead of paying attention to the relationship between stick-figure kinematics and judgment. There are two indications that Explorers failed to learn to perceive relative pulling force. First, the average judgment-force correlation in the posttest was smaller than those for the other groups. Second, an analysis of which kinematic variables informed judgment revealed that the Explorer group showed less convergence towards

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specifying variables than did the Observers and Controls. Correlations between judgments on the posttest and the various kinematic variables revealed that only 2 of the 5 Explorers had converged on a variable permitting accurate performance (i.e., a location in the displacementvelocity space), whereas in the other two groups, 9 of the 10 participants converged on such a variable. It is interesting to note that if one looked only at the first three blocks of trials, one would conclude that exploration did foster learning; the accuracy of Explorers' force judgments were better than those of the other participants. It now appears, however, that their explorations revealed how slider position informed of force but not how stick-figure kinematics informed of force. Conclusions The present study showed that exploration boosts performance to a certain extent; however, the boost did not conform to the explicit task demand. Perhaps what is needed is to offer participants a manner of exploration that fits more naturally with the stick-figure kinematics. Further research is needed to find a manipulation that might be useful in guiding attention to the relevant information. Being able to successfully exploit such a manipulation is part of expertise. The general lesson is that both improvement in performance and attunement in the information landscape may rely on a specific form of exploration; permitting simple manipulation on the part of the participant is not enough. Appropriate exploration is needed for one to navigate a task's information landscape, but designing a controlled laboratory version is not simple. References Gibson, J. J. (1966). The senses considered as perceptual systems. Boston, MA: Houghton-Mifflin. Michaels, C. F., & de Vries, M. M. (1998). Higher-order and lowerorder variables in the visual perception of relative pulling force. Journal of Experimental Psychology: Human Perception and Performance, 24, 526-546.

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Evidence for Two Visual Pathways: Differences in Walking and Talking Perceived Distance Sheena Rogers, Jeffrey Andre & Rebecca Brown School of Psychology, James Madison University, Harrisonburg, Virginia, USA Are there one or two visual pathways? In the late 1960s, Schneider (1969) and others proposed functionally separate, cortical and sub-cortical visual processing tracks: one for localization and one for identification of an object. Since then it has been shown that different processing "streams" also exist solely in the cortex. A similar distinction has been proposed by Milner & Goodale (1995): one (dorsal) stream for visually-guided action and one (ventral) stream for visual awareness of the world. The two streams are functionally and neuroanatomically distinct: visual information that will shape perceptual awareness travels in a ventral stream to the inferior temporal cortex, whereas visual information that guides actions travels dorsally to the posterior parietal cortex. There is evidence that, despite marked inaccuracies of verbal reports about spatial layout, people can nevertheless navigate and interact successfully with their environment, suggesting that the two streams encode layout differently and independently (e.g., Leibowitz, Guzy, Peterson & Blake, 1993; Proffitt, Bhalla, Gossweiler & Midgett, 1995). Earlier experiments typically relied on verbal reports of perception on the assumption that visual processing results in a single representation easily accessed by conscious processes. Most of the evidence for the familiar inaccuracies in the perception of spatial layout (e.g., underestimation of distance) comes from these studies. More recent experiments, employing action-based measures, seem to suggest that perceivers apprehend layout more accurately than was previously thought. The present experiment provides evidence for this distinction by testing people's ability to estimate distance in two separate ways: an action-based blind-walking task and a traditional verbal report of

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distance. Estimates were made in two separate environments: indoors in a gymnasium and outdoors on an athletic training field. We expected that the different environments would provide different sources of information for distance (eg indoors, linear perspective is provided by the edges of the room, and gradients of texture compression are less subtle than on astroturf). If the location influences the two dependent variables differently, then we have obtained evidence that the two types of report are independent of each other, suggesting that separate visual pathways have resulted in separate 'perceptions', and that the two do not access a single representation of spatial layout. Method Seventeen university students (11 female, 6 males) with no selfreported visual pathologies volunteered in the experiment. Experimental Design. Participants were tested in a 2 x 2 x 6 repeatedmeasures paradigm. The independent variables were Walking Environment (indoors v. outdoors), Type of Response (verbal report of distance v. distance walked blind-folded), and Target Distance (5, 10, 15, 20, 30 and 60 ft). Distances were reported and measured in feet. Materials/Location. We designed a walking course, much like a miniature golf course, which connected target distances as randomly ordered straight pathways, oriented in varied directions. Pathways could also be walked in two directions (out and in). The same walking-course design was used in both the Outdoor (a large, flat, athletic training field covered with astroturf) and Indoor (a gymnasium floor slightly larger than a full-size basketball court) environments. The pathways were not visible to the participants. Pathway junctions were discreetly marked with tape. Targets were marked with a 10-inch high, orange sports cone. Participants were blindfolded using modified welding goggles. Procedure. Prior to testing, participants were given practice walking while blindfolded. They were instructed to walk at a normal pace and ensured of their safety throughout the experiment. On a given trial, participants raised the goggles' visor, saw the target cone located at one of the target distances, and gave a verbal estimate of the distance to the cone in feet. They then closed the visor and walked towards the cone, stopping when they believed they had reached it. An experimenter

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walked beside the participant at all times to ensure safety, and to measure the distance walked. Another experimenter removed the cone before the participant reached it. The order of pathway Distances were randomized and used twice each for a total of 12 trials in both the Indoors and Outdoors conditions. The order of Walking Environments was counterbalanced across participants. Results Responses were averaged for each distance and converted into a percentage of the target distance (e.g., over 100% indicates that participants walked further than the target distance). Some responses from one of the participants were greater than 3 standard deviation from the mean, and were removed from further analysis (N = 16). A three-factor ANOVA confirmed a significant main effect of Response Type [F (1,15) = 14.38, p< .01], and a significant Environment x Response interaction [F (1,15) = 8.85, p < .01]. Figure 1 shows that participants were always more accurate when blind-walking (distances walked were mostly between 90% and 100% of the actual target distance whereas verbal reports were at best only 80-85%). Importantly, while blind-walking accuracy was not affected by Walking Environment, verbal reports were less accurate Outdoors than Indoors and the difference between the two response types was more pronounced. Discussion Findings from both Outdoor and Indoor conditions show a functional distinction between the accuracy of verbal and action estimates of distances from 5 ft to 60 ft, suggesting the existence of separate visual pathways for visually-guided action and for the verbal report of perceptual awareness. At all distances, participants were more accurate when blind-walking to a previously seen target than when making sighted verbal estimates of distance. Blind walking was very accurate both Indoors and Outdoors. Indoor verbal estimates were more accurate than outdoor verbal estimates (although verbal reports outdoors were not as badly underestimated as in our earlier study, Andre & Rogers, 2002).

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Figure 1. Perceived distance as a function of target distance and type of response for Outdoor (top graph) and Indoor (bottom graph) environments. Below 100% indicates under-estimation of distance. Error bars = ±1 SEM.

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Participants could have (consciously or unconsciously) incorporated the basketball courts' known dimensions when giving verbal estimates, or it may be that the indoor gym environment provides more visual information for distance than does an open, astroturf field. Whatever the reason for this finding, the contrasting finding that environment does not affect blind-walking accuracy is telling. It would suggest that the two types of response are independent of each other and do not access a single representation (as some, e.g., Philbeck & Loomis, 1997, have suggested). In a related finding, outdoor blind-walking participants did not show the large increases in inter-subject variability with increasing distance that we found for verbal estimates, lending additional support for a distinction between the two streams of visual processing. References Andre, J., & Rogers, S. (2002). Perceivers walk the walk but talk short: Evidence for two visual pathways in distance perception. Journal of Vision, 2(7), 60a, http://journalofvision.Org/2/7/60/, DOI10.1167/2.7.60. Leibowitz, H. W., Guzy, L. T., Peterson, E. & Blake, P. T. (1993). Quantitative perceptual estimates: verbal versus nonverbal retrieval techniques. Perception, 22, 1051-1060. Milner, A.D. & Goodale, M.A. (1995). The visual brain in action. Oxford: Oxford University Press. Philbeck J.W. & Loomis, J.M. (1997). Comparison of two indicators of perceived egocentric distance under full-cue and reduced-cue conditions. Journal of Experimental Psychology: Human Perception and Performance, 23(1), 72-85. Proffitt, D. R., Bhalla, M., Gossweiler, R. & Midgett, J. (1995). Perceiving geographical slant. Psychonomic Bulletin & Review, 2,409-428. Schneider, G. E. (1969). Two visual systems: Brain mechanisms for localization and discrimination are dissociated by tectal and cortical lesions. Science, 163, 895-902.

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Linguistic Background and Perception of an Ambiguous Figure: New Findings Kristelle Hudry, Philippe Lacherez, Jack Broerse, & David Mora The University of Queensland, Australia A number of theorists (e.g., Parncutt, 1994; Wong & Barlow, 2000) have proposed that characteristics of known auditory patterns are learned by an individual as they develop, to form an auditory template to which incoming information may be matched. One current line of investigation concerns the role of exposure to the speaking voice in determining perceptions of pitch under ambiguous circumstances. In Deutsch's (1991, 1994; Deutsch, Kuyper & Fisher, 1987; Deutsch, North & Ray, 1990; Ragozzine & Deutsch, 1994) tritone paradox procedure, two artificially synthesised tones are presented in sequence, separated by the musical interval of a tritone. When a set of twelve such tones is created (one for each note in the musical octave), and each possible pair presented on several occasions, some pairs are heard more often as descending, and others are heard more often as ascending. Moreover, the profile for a given individual is found to differ from that of other individuals. Deutsch has typically defined individuals by their "peak pitch," or the first tone of the pair which is heard most often as descending (for details see Deutsch et al., 1987). Of perhaps most interest is Deutsch's (1991, 1994; Deutsch et al., 1987; Deutsch et al., 1990; Ragozzine & Deutsch, 1994) finding that this peak pitch may also differ reliably between speakers from different linguistic groups. Repp (1997), however, has argued that these differences may be artifacts of the procedures employed, and that the characteristics of the tones (in terms of the envelope or function used to create the tones) may better predict people's responses in this task. He has also argued that there is a need to examine the role of contextual effects brought about by the order of presentation of the stimuli. This study aimed to obtain a profile of Australian listeners, to enable comparison with different linguistic groups. In addition, the

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tones were presented in four different spectral envelope conditions (for details see Repp, 1997) under three different methods of presentation. Method The participants were 55 Brisbane residents (aged 18 to 51). Tones were generated with Csound on a Sun™ Spare-10 Workstation, and presented on an IBM personal computer with a Pentium™ II 300Mhz processor and a Creative Sound™ 64 Sound Blaster card. The tones were presented to listeners via a set of stereo headphones (BEST SH-50GT). Tones were generated using the procedure described by Deutsch (1987) using envelopes centred on c4, f#4, Cs, and f#5 (envelopes 1,2, 3 and 4 respectively) Participants were administered the tritone paradox procedure under one of 3 conditions. Participants in group 1 (n - 36) were presented with the tones in blocks, such that each block consisted of tones from only one envelope, each tone pair presented once (e.g., Deutsch et al., 1987). The order of the blocks was rotated as a Latin square. Within each block the order of the pairs was random, with the restriction that no tone pair should be presented in direct succession with the same pair played in the opposite order (e.g., c-f# followed by f#-c). The same fixed random order was presented to all participants. In group 2 (n = 11) each block consisted of 4 repetitions for each tone pair, a different envelope being used in each block (e.g., Dawe, Platt & Welsh, 1998). The blocks were presented in the same fixed order, envelope 1 first, followed by envelopes 2, 3, and 4 in that order. A different random order within blocks was administered to each participant. Participants in group 3 (« = 8) were presented with all 48 tone pairs in random order. Eight repetitions of each tone pair were presented. Only the first 4 observations have been included here, to facilitate comparison with the other groups. The same fixed random order was presented to all participants. Results and Discussion Figure 1 shows the profiles obtained under each of the three experimental procedures. A different pattern of results was observed in group 2 than that observed in groups 1 and 3.

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Figure 1. Number of 'down' responses (out of a possible 4), for tone pairs beginning with the indicated note. The envelopes used were those previously used by Deutsch (e.g., Deutsch, Kuyper, & Fisher, 1987) and Rebb (e.g., 1997).

In groups 1 and 3, a consistent pattern of responding occurs across envelopes. Thus overall participants responded with a "peak pitch" of around A#/B in each condition. Although some individuals did differ from the group, overall, the majority had a peak pitch within 1 or 2 semitones of A#. It is worth noting that this is a novel profile that has not been observed before. In group 2, however, a very different pattern is found, with each envelope showing an entirely different pattern and a different peak pitch. Since this is the group that were presented with each envelope as a separate block, it seems likely that the difference observed results from maintaining the envelope context over a given experimental phase. What this means for the tritone paradox is unclear. While the profiles shown in groups 1 and 2 do show remarkable consistency, the existence of context and envelope effects in this sample suggests that more needs to be known about this paradigm before speculations with regard to linguistic differences can be entertained.

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References Dawe, L. A., Platt, J. R., & Welsh, E. (1998). Spectral-motion aftereffects and the tritone paradox among Canadian subjects. Perception and Psychophysics, 60,209-220. Deutsch, D. (1991). The tritone paradox: An influence of language on music perception. Music Perception, 8, 335-347. Deutsch, D. (1994). The tritone paradox: Some further geographical correlates. Music Perception, 12,125-136. Deutsch, D., Kuyper, W.L., & Fisher, Y. (1987). The tritone paradox: Its presence and form of distribution in a general population. Music Perception, 5, 7-9. Deutsch, D., North, T., & Ray, L. (1990). The tritone paradox: Correlate with the listener's vocal range for speech. Music Perception, 7, 371-384. Parncutt, R. (1994). Template-matching models of musical pitch and rhythm perception. Journal of New Music Research, 23, 145167. Ragozzine, F. & Deutsch, D. (1994). A regional difference in perception of the tritone paradox within the United States. Music Perception, 12, 213 -225. Repp, B.H. (1997). Spectral envelope and context effects in the tritone paradox. Perception, 26, 645-665. Wong, W., & Barlow, H. (2000). Tunes and templates. Nature, 404, 952-953.

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Behavior of a Harbor Porpoise in an Unfamiliar Environment Yoshiko Honno1, Kiyohide Ito2, Takashi Matsuishi1, Masahiro Okura3 & Masato Sasaki3 1

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Hokkaido University, Japan Future University-Hakodate, Japan 3 University of Tokyo, Japan

Blind humans are known to use echolocation in perception and action (e.g., Ito, 1999; Stoffregen & Pittenger, 1995). Dolphins and porpoises also use echolocation, but the behavior of these species has been little studied. Research on echolocation often focuses on discrimination of sizes and shapes, using methods from classical psychophysics (Au, 1993). We believe that complete understanding of the auditory abilities of porpoises and dolphins will require studies of perception-action. In this contribution, we report a preliminary study of this kind. When an animal finds itself suddenly in a new habitat, one of its first priorities will be to differentiate safe and unsafe locomotor paths that are available in the new habitat. We studied the exploratory behavior of a porpoise that found itself in a novel environment. Our main purpose was to ascertain what types of exploratory acts the porpoise used in the new situation, and how its behavior changed over time. Method A male harbor porpoise (125 cm long, called "Naoto") was accidentally caught in a net off Usujiri-port, Hokkaido, Japan in spring, 2002. We placed him in a cylindrical pool (6 m diameter, 1.2 m average water depth) in the Usujiri Fisheries Station at Hokkaido University. Naoto did not have very serious health problems. Naoto's behavior was recorded using video camera stationed on the 2nd floor of a building beside the pool. Recording was continuous for

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the first 49h 20m during which Naoto was in the pool. For the following 10 days, Ih 30m recordings were made three times per day, beginning at 4:15, 10:15, and 16:30. For analysis, we selected 4-minute segments of videotape in which Naoto's behavior was clearly visible. For the initial 49 hours, we selected one segment per hour. For the remaining 10 days, we selected one segment from each Ih 30min recording session. The 4-minute segments were transferred to a computer for analysis. For each 4-minute segment of videotape, we measured the distance through which Naoto swam, and we evaluated the number and type of head movements that he used. We identified three distinct types of head movements. These were Halting (small amplitude movements), Smooth (large amplitude, continuous motion), and Transitive (a sustained sequence including both halting and smooth components). After omitting indeterminable acts, we computed the mean number of each type of head movement per minute. After the observation period Naoto was moved to Otaru Aquarium for further study. Results Swimming Distance (Figure la). We used swimming distance as a measure of the porpoise's overall activity level. Naoto was relatively quiescent during his first three hours in the pool. After that, swimming increased significantly. A one-way repeated measures ANOVA on the mean swimming distance over each of the first two days and the after revealed significant differences among days (F(2) = 16.43, /K0.05). Head movements (Figure Ib). The three types of head movement appeared differentially over time. On the first day in the pool, all three types of head movement were present. Over time, the halting movements decreased, so that they were essentially absent on the 2nd and 3rd days. In contrast, smooth movement was continuously observed for the second day. A one-way repeated measures ANOVA on the number of head movements as a function of days revealed significant differences between the first day and the second day, and between the 2nd and subsequent days (F(2) = 12.18,^<0.05). The correlation coefficient between smooth movement and swimming distance was 0.80, and between halting movement and swimming distance was -0.73. Each of these differed significantly from 0,p<.05.

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Figure 1 (a) Swimming distance and number of head movements as a function of time in hours.

Figure 1 (b) Occurrence of different types of head movement, as a function of time in hours.

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Discussion Our analysis revealed substantial changes in the behavior of Naoto in its first three days in an environment that differed dramatically from its natural habitat. These differences may reflect changes in exploratory activity as the animal became familiar with its new environment. If so, then it seems clear that whole body movements (swimming distance) and head movements were used to gain information about the new environment. This type of activity would be consistent with Gibson's (1966) claim that perceptual exploration often incorporates movements of the entire body, and not solely of receptor surfaces. In particular, head movements may have been used to facilitate both visual and auditory exploration. Our results suggest that halting head movements may have a uniquely exploratory character, and that smooth and transitive movements may be related to the control of activity within a familiar environment. This study is the first step of our plan of systematic research on perception and action in the harbor porpoise. In future studies, we will investigate affordance perception and the information used to detect affordances. Acknowledgements. Our research was partly supported by the South Hokkaido Promotion Foundation. We are grateful to Thomas A. Stoffregen for helpful comments and correction of English words, undergraduate students for assistance of observation, and Kagosima for porpoise treatment. References Au, W. W. L. (1993). The Sonar of Dolphins. New York: SpringerVerlag. Gibson, J. J. (1966). The senses considered as perceptual systems. Boston: Houghton-Mifflin. Ito, K. (1999). Detection of occluding edges by the use of echolocation. Studies in Perception and Action V, 52-56. Stoffregen, T. A., & Pittenger, J. B. (1995). Human echolocation as a basic form of perception and action. Ecological Psychology, 7, 181-216.

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What is the Sound of One Rod Dropping? Jeffrey B. Wagman CESPA, University of Connecticut, USA Perceptual learning (PL) refers to an increased ability to selectively direct attention to task-specific higher-order patterns of stimulation (E. J. Gibson, 1969; Michaels & Carello, 198; Michaels & de Vries, 1998; Runeson, Juslin, & Olson, 2000; Wagman, Shockley, Riley, & Turvey, 2001). To the extent that higher-order variables provide information about environmental properties, attunement to higher-order variables should lead to a perceptual scale that is appropriately anchored. Such anchoring has been termed "calibration" (cf. Wagman et al., 2001) and can be quantified with absolute error. AE = 2 J X j - D \ / n , (where */ is perceived magnitude, D is actual magnitude and n is the number of trials). Regardless of whether this attunement occurs, however, practice in a perceptual task should also lead to a perceptual scale that is applied more precisely (Wagman et al., 2001). This precision can be quantified by variable error, VE = •y2^(*; ~ ^)2 / n (where M is the average judgment for a given actual magnitude). We investigated attunement and calibration in auditory PL. Recently, Carello, Anderson, & Peck (1998) found that participants could perceive length of wooden rods by listening to them strike the floor. Although actual rod length was a successful predictor of perceived length, length itself is a geometric property and cannot affect the vibratory structure in the acoustic array (cf. Carello, Wagman, & Turvey, in press). Carello et al. (1998) found that in lieu of this variable or a host of acoustically based variables, a parsing of the rod's resistance to rotational acceleration (quantified by Iy, its inertia tensor) accounted for almost all of the variance in perceived length. This higher-order quantity has several advantages. First, it has been shown to constrain perception via dynamic touch (Carello & Turvey, 2000; Wagman & Carello, 2001). Secondly, rotational inertia is a mechanical property and thus has the potential to affect the vibratory structure of the acoustic

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array. Third, it has been shown to be the basis for perceptual learning via dynamic touch (Wagman et al., 2001). The purpose of the present experiment is to see if the ability to direct attention improves in the same way in auditory perceptual learning as it does in haptic perceptual learning (cf. Wagman et al., 2001). Method The experiment consisted of 27 pre-test trials, 27 training trials, and 27 post-test trials. In both the pre- and post-tests, participants were seated next to an occlusion curtain, and one of nine rods was dropped to the floor from a height of 72 cm. Participants were instructed to report an impression of rod length by means of magnitude production (see Figure 1).

Figure 1a. The experimental paradigm.

Figure 1b. Participants showed an initial attunement to lxx. This attunement became more pronounced in the KR condition.

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During the training trials, participants in the Extended Practice (EPR) condition repeated the task using the same objects as in the pretest, participants in the Knowledge of Results (KR) and No Knowledge of Results (NO KR) conditions repeated the task with a different set of objects. Participants in the KR condition were additionally given the opportunity to visually compare their perceptual reports to actual object magnitudes on every trial. The post-test was always identical to the pretest. Results Evaluation of Attunement. Regression analysis revealed that in the pretest, all perceivers showed initial attunement to Ixx (the inertial variable that provides information about length). Both in the KR and NO KR conditions, the variance accounted for by Ixx in log perceived length increased from roughly 88% in the pre-test to 93% in the post-test. There was no such increase in the EPR condition (86% in both pre- and posttests, see Figure 1). Evaluation of Calibration. AE decreased from pre- to post-test only in the KR condition [F(2, 66) = 3.33, p < .05]. VE tended to decrease from pre- to post-test. However, this difference was only marginally significant [F(l, 66) = 2.67, p = .10] (see Figure 2). The fact that AE decreased only when KR was given and VE decreased regardless of KR is in accordance with previous observations (see Gibson, 1969; Wagman et al., 2001). These findings provide further support that the perceptual process of differentiation (i.e., "genuine perceptual learning" E. J. Gibson, 1969) may be separable from (and occur independently of) the cognitive process of adjusting a conceptual scale, but not vice versa.

Figure 2. Absolute error for pre- and post-tests in each of the three conditions (left) and variable error for pre and post-tests collapsed over condition (right).

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Conclusion These results suggest that the attunement and calibration hypotheses apply to auditory perceptual learning much as they apply to visual perceptual learning (Michaels & de Vries, 1998; Runeson et al., 2000) and haptic perceptual learning (Wagman et al., 2001). They further suggest the applicability of the inertia tensor as a higher-order perceptual variable relevant to perception of affordances by means other than dynamic touch. References Carello, C., Anderson, K. L., & Peck, A. (1998). Perception of object length by sound. Psychological Science, 9, 211-214. Carello, C., Wagman, J. B., & Turvey, M. T. (in press). Acoustic specification of object properties. In J. Anderson & B. Anderson (Eds). Moving Image Theory: Ecological Considerations, Carbondale, BL: Southern Illinois Press. Gibson, E. J. (1969). Principles of perceptual learning and development. New York: Appleton. Gibson, J. J. (1966) The senses considered as perceptual systems. Boston: Houghton Mifflin. Michaels, C. F. & Carello, C. (1981). Direct perception. New York: Prentice Hall. Michaels, C. F. & de Vries, V. M. (1998). Higher order and lower order variables in the visual perception of relative pulling force. Journal of Experimental Psychology: Human Perception and Performance, 24, 526-546. Runeson S., Juslin, P., & Olsson, H. (2000). Visual perception of dynamic properties: cue heuristics versus direct-perceptual competence. Psychological. Review, 107,525-555. Wagman, J. B., Shockley, K., Riley, M. A., & Turvey, M. T. (2001) Attunement, calibration, and exploration in fast haptic perceptual learning. Journal of Motor Behavior. 33, (4) 323327.

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A New Look at Situational Awareness: The Essential Ingredients for Modeling Perceiving and Acting by Animate and Robot Agents Organizers: Robert E. Shaw & William Mace We take it that to understand animals perceiving and acting in the world, or to model perceiving and acting in the world, whether in ecological science, cognitive science, neuroscience, or robotics, one must analyze goal directed tasks. We propose a minimal list of potential sources of variability present in any task. All modeling strategies should address them if they are to have a handle on all the relevant sources of degrees of freedom. An explicit characterization of "situational awareness" by agents should be of specific interest to those who would reduce the "loans" taken out on extrinsic factors. The three "packages" of variables suggests one way to make intrinsic many factors that govern the success or failure of a goal-directed task that might otherwise be left extrinsic and unaccounted for. Following numerous papers by Shaw and various students and colleagues, we propose these three sets of concepts. On one hand, considering all of these surely can be quite daunting, but it is important to note that we do not believe that this list is a beginning that will grow indefinitely. When elaborated, this set has the property of closure, which we take to be not only desirable, but necessary. 1. Four types of information and control for an agent - exterospecific, propriospecific, expropriospecific, and proexterospecific forms of information. 2. Four modes of action - Exploratory, Preparatory, Performatory, Consummatory. 3. Global and local control in environment. As further material to illustrate such concepts, Alex Zelinsky will describe new forms of interaction now possible between humans and the world. These have been made possible using motion capture technology such as eye tracking and gesture tracking devices.

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A third demonstration will involve the Griffith University robot soccer team which will show how cooperativity in mobile robots remains a difficult but worthwhile and exciting challenge for those of us struggling to come to terms with the relation between autonomy, intentionality, and perception-action phenomena.

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A Precis of a Position to be Elaborated in the Workshop on the Challenges and Promises of an Ecological Approach to Robotics 'Robert E. Shaw and 2William Mace 'CESPA, University of Connecticut, USA 2 Trinity College, Hartford, USA Is a theory of ecological robotics possible?1 It is generally recognized that the most serious impediment to progress in robotics is how to design autonomous agents that not only can perform given tasks competently in specific environments but, more importantly, can learn or develop a broader competence for effective performance on many tasks across diverse real-world environments. Because each robot body will differ slightly in structural design and functional detail, the exact duplication of evolutionary contexts is impossible. Evolutionary Ecological Robotics, (EER), is suggested as the name of the hybrid field that brings Evolutionary Robotics together with Ecological Psychology. Indeed, an effort has already begun in this regard (see Effken & Shaw, 1992). In 2002 an evolutionary robotics conference was held in Fukui, Japan with the stated goal of furthering this effort. Progress reports describing on-going Evolutionary Robotics projects were presented: Example projects included the evolution of real-world obstacle-avoiding flying or rolling robots, robots that walk over uneven terrain, and simulated robots that adapt to dynamic environments, such as RoboCup soccer, or highway traffic. Nearly all of the projects were concerned with Evolutionary Robotics adapted to real or simulated dynamical environments, and thus could profit from the development of Evolutionary Ecological Robotics. The natural question to ask is, can

1

An extended discussion of the topics in this paper appears on the ICPA 12 Web site, http://www.int.gu.edu.au/%7Es227447/ICPA-conf/index.htm

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ecological psychology furnish a general account of autonomous agents to complement Evolutionary Robotics? We shall expect Evolutionary Ecological Robotics to provide methods and concepts for understanding autonomous agents that exhibit effective performance in real-world task environments. Effective performance does not mean optimal performance, but only that performance be tolerant, that is, successful to a limited but practical degree. The degree of effective performance is defined relative to some practical criterion for success—thus in the case of an evolutionary hardware device, it either learns or evolves so as to satisfy a kind of Fitness Function. Indeed, finding a proper ecological interpretation of this Fitness Function will prove to be the key by which we can formulate a theory of Evolutionary Ecological Robotics relevant to our problem. Evolving ecological robots with affordance-effectivity fits Ecological psychology argues that effective learning is shaped by selective evolutionary pressures which guarantee a commensurability between an animal's action capabilities and what the environment demands of adaptive acts. That is to say, the agent's effectivities (control-relevant task-constraints) must match the environmental affordances (invariant environmental properties specific that provide causal and informational support for a potential goal-directed activity). It should be clear from the definitions given above that a measure of an agent's competence in reaching a goal is synonymous with how well the task affordances are matched by the agent's effectivities. The evolution of such competence can be construed as a Genetic Algorithm-driven Evolutionary Hardware process, where the degree of match required plays the role of the Fitness Function. The greater the affordance-effectivity match in a given generation, the better the Fitness Function score. More specifically, imagine a population of robots whose members are endowed with the same type of chips (evolvable hardware) and which share the same Fitness Function for a given task. Assume that this population is partitioned into several sub-populations, with each sub-population being assigned to a different environmental situation. The environmental situations belong to a range of task-situations over which one would like an autonomous agent to be competent. Consider an ecologized version of Thompson's (1998) suggestion for how to evolve autonomous agents with broad

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competencies: Let each situation-specific sub-population of robots evolve according to the same Fitness Function. Because they share the same Fitness Function, over many generations, the emerging selection pressure evolves robots that all can exploit the same affordances. They do the same task, but do so in different ways because their effectivities were attuned to different situations. Thus the different strains of selection pressure will produce a class of circuit designs that support different effectivities but realize the same task-specific affordance. The common affordance defines an invariant structure over all the robots and reflects those properties most stable over change in situation. The distinct effectivities, by contrast, provide the perspective structure specific to properties that are unstable over change in situation. Thus a robot whose field programmable gate array (FPGA) circuit evolved for one task situation may not work properly when transferred to a new situation. To construct a robot that can solve the same task in different situations, the trick will be to couple all the different circuits into a single super-FPGA endowed with all the situation-specific, embodiment-specific, competencies. A new tractability Any equation set adequate to express the defining characteristics of either affordances or effectivities would have too many dimensions to be solved in closed form. Their context-sensitivity makes them truly intractable in the mathematical sense. But, here, by interpreting affordances and their matching effectivities in terms of Evolutionary Robotics, we have a constructive argument for their scientific tractability. They can be reliably evolved, even if not formally or mechanistically described. It may be that the robotics field has run up against what might be called the von Neumann barrier to mathematical tractability. Von Neumann (1966) conjectured that there may exist a barrier to tractability that a theorist encounters in trying to state explicitly how systems of even moderate complexity work. By complexity, he was not referring to how complicated a system is as determined by counting parts; rather he was referring to how competent the system was in a variety of real-world contexts, that is, how many effectivities (goaldirected behaviors) it was able to perform. When the complexity barrier is reached, he argued, the best model of such systems may not be mathematical or verbal but the system itself. This prompts the question:

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Is the deep level of physical detail that Evolutionary hardware modules engage and exploit with their rich digital-analog dynamics already on the wrong side of this tractability barrier? By its very nature, the conjecture cannot be formally proven since it tries to relate a mathematical domain to a nonmathematical domain—a semantic rather than formal problem. Still, the example of Evolutionary hardware may be informal evidence of its validity. If so, then Evolutionary Ecological Robotics methods demonstrating that a complex system can, in principle, be evolved to have certain competencies (specific affordance-effectivity matches) may offer another kind of tractability. The case for history machines Where ordinary hardware is characterized by states and state transitions, Evolutionary hardware, instead, is characterized by configurations and their histories (a history is defined as a succession of epochs, where a historical epoch is a segment of history preserved between a pair of generations). This thesis of Evolutionary Ecological Robotics, or any other evolutionary system for that matter; asserts that any evolutionary system is best described by its unfolding histories rather than by transitions over states. Indeed, given the tractability barrier, there may be no other choice. States, however, may be used where they specify directly the history to which the states, like symbols, refer (and thus are semantically grounded). The developing Evolutionary hardware strategy (see, Higuchi et al., 1995; Thompson, 1998; Nolfi & Floreano, 2000) when merged with ecological psychology yields the basic ingredients for an Evolutionary Ecological Robotics (EER). Earlier, a case was made that EER is both valid and (practically) tractable. To the extent that this is so, then, to that extent, it counters the Minsky (1967) and Wells (2002) claim that history machines are useless because they are too ill-defined and cumbersome to use. To reiterate Shaw & Todd (1981), we claim that history-driven machines not only are tractable (again, in a practical if not formal sense), but in many important ways can surpass state-controlled systems, especially, in modeling how systems (e.g., robots) evolve the competence for learning to solve real-world tasks. For instance, Thompson (1998) shows how systems based on evolutionary principles (e.g., Evolutionary hardware) can explore circuit designs that transcend

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the scope of conventional ones. These circuits, being less constrained in spatial structure than ordinary silicon chips, exhibit considerably richer dynamics than usual. For having more freedom, they achieve greater sensitivity to the properties of the physical medium in which the circuit is implemented. This results in a circuit that is better tailored to exploit all of the characteristics available in an implementation medium. The late Robert Rosen in his seminal book, Life Itself, makes a strong case for the logic and design of biological systems being quite different from that of programmable machines (Rosen, 1991). Until the advent of evolvable hardware, machines could be endowed with artificial intelligence only through a human's intervention as designer and programmer. Now, it seems, we have systems that can evolve their own intelligence but which may not be so much artificial as ecological. If so, then evidence to support Rosen's case is evolving. References Brooks, R. (1991). New approaches to robotics. Science, 253, 12271232. Effken, J. & Shaw, R. E. (1992). Ecological perspectives on the new artificial intelligence. Ecological Psychology, 4, 247-270. Future Emerging Technologies. (FET Robotics Work Group 2002). Information Society Technologies (1ST). (See IST/FET website.) Harvey, I., Husbands, P., Cliff, D., Thompson, A., & Jacobi, N. (1997). Evolutionary robotics: The Sussex approach. Robotics and Autonomous Systems, 20, 205-224. Higuchi, T., Niwa, T., Iba, H., Hirao, H., Furuya, T, & Mandrick, B. (1995). Evolving hardware with genetic learning: A first step toward a Darwin machine. In J-A, Meyer, H. L. Roitblat, and S.W. Wilson (Eds.). From animals to animats 2. Proceedings of the international conference on simulation of adaptive behavior. Cambridge, MA: MIT Press. Minsky, M. L. (1967). Computation: finite and infinite machines, Englewood Cliffs, NJ., Prentice-Hall. Neumann, J. von (1966). The theory of self-reproducing automata. Urbana: University of Illinois Press. Pollack, J., Lipson, H., Ficici, S., Funes, P., Hornby, G., & Watson, R. (2000). Evolutionary techniques in physical robotics. http://demo.cs.brandeis.edu/edu/icesOO.html

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Rosen, R. (1991). Life itself: A comprehensive inquiry into the nature, origin, and fabrication of life. New York: Columbia University Press. Thompson, A. (1998). Hardware evolution: Automatic design of electronic circuits in reconfigurable hardware by artificial evolution. London: Springer-Verlag. Tuci, E., Quinn, M., and Harvey, I. (undated WWW paper). An evolutionary ecological approach to the study of learning behaviour using a robot based model. Yao, X. and Higuchi, T. (October, 1996). Promises and challenges of evolvable hardware. First international conference on evolvable systems: from biology to hardware. Tsukuba, Japan.

Studies in Perception and Action VII S. Rogers & J. Effken (Eds.) © 2003 Lawrence Erlbaum Associates, Inc.

Toward Smart Cars with Computer Vision for Integrated Driver and Road Scene Monitoring Alexander Zelinsky Seeing Machines Pty Ltd, Canberra, Australia This paper presents the results from an Intelligent Transport System (ITS) project that integrates automated driver monitoring and lane tracking systems. The experimental results from the integration of the lane tracker and the driver monitoring system are presented with an analysis of the driver's visual behavior in several different driving scenarios. Studies for road traffic authorities worldwide estimate that about 30% of all fatal car crashes can be attributed to driver inattention and fatigue. Numerous studies have been performed to analyze signs of driver fatigue through the measurement of the visual demand on the driver. This is often through frame-by-frame analysis or infrared corneal-reflection technologies. While these studies produce valuable results, they are often time consuming and too unreliable for many research purposes. An ITS project has recently been initiated at The Australian National University (ANU) and Seeing Machines which has focused on autonomous driver monitoring and autonomous vehicle control to aid the driver. The major aim of this project has been the development of a system of cooperating internal and external vehicle sensors for understanding the behavior of a driver. Understanding what the driver looks at is only the first step in investigating the psychology of the driver. Research into the context in which distractions occur and the effect they have on the driver's ability to control the vehicle is an important part of this investigation. This paper presents the results from the initial phase of this study where a lane tracker was developed using a computer vision based system fusing multiple visual cues. The lane tracker was integrated with a driver monitoring system developed by Seeing Machines called faceLAB, to investigate the visual behavior of the driver in a number of common driving scenarios. The lane tracker was tested in autonomous

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driving experiments in a number of situations, including along a freeway and along a road with no lane markings. Experiment Setup The experimental vehicle is a 1999 Toyota Landcruiser 4WD that has been fitted with several actuation devices to control steering, acceleration and braking. Vision is the main form of sensing used on the vehicle, which has two different vision platforms installed. A passive set of stereo cameras is mounted on the dashboard facing the driver and is used as part of the faceLAB system for driver monitoring.

Figure 1. The experimental vehicle.

An active stereo vision platform, called Cedar, designed at ANU, carries 4 cameras - one pair used for stereovision in the near-field, and one pair for far-field stereo experiments and for mid-field to farfield scene coverage. Various other sensors have been fitted to the vehicle including a Global Positioning System (GPS), Inertial Navigation Sensor (INS), and a laser range finder. Figure 1 shows the vehicle, faceLAB camera set and a picture of the Cedar sensor platform that is mounted in place of the rear view mirror. Lane Tracking Despite many impressive results from lane trackers in the past, such as work of Dickmans with the VAMROS project, and the Carnegie-Mellon Universities NAVLAB project, it is clear that no single cue can perform reliably in all situations. The lane tracking system presented in this paper dynamically allocates computational resources over a suite of cues to robustly track the road in a variety of situations. Bayesian theory is used to fuse the cues while a scheduler intelligently allocates computational resources to the individual cues based on their

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performance. A particle filter is used to control hypothesis generation of the lane location. Each cue is specifically developed to work independently from the other cues and is customized to perform well under different situations (i.e. edge based lane marker tracking, area based road tracking, color based road tracking, etc.). Cues are allocated CPU time based on their performance and the computation time each cue requires. A number of metrics are used to evaluate the performance of each cue with respect to both the fused result and the individual result of the cue. Additionally, the framework of the lane tracker was designed to allow the cues to run at different frequencies enabling slow running (but valuable) cues to run in the background. A dual phase particle filter system is used to reduce the search space for the lane tracker. The first particle filter searches for the road width, the lateral offset of the vehicle from the center line of the road and the yaw of the vehicle with respect to the center line of the road. The second particle filter captures the horizontal and vertical road curvature in the mid- to far-field ranges.

Figure 2. Output of the lane tracker.

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Figure 2 shows the output of the lane tracker in several different situations using 4 different cues. In all situations, the cues used were a mixture of cues suited solely to marked roads or unmarked roads and cues suited to both. Green lines indicate the hypothesis with the highest probability while the red lines indicate the mean of the samples. Top left, top right and bottom left show different situations on a marked road including shadows and passing cars, while bottom right shows the tracker working on unmarked road. All tests were performed with 4 cues including an edge-based lane marker cue, an area-based color detection cue, an edge-based color detection cue, and a maximumlikelihood road-width cue. FaceLAB is a driver monitoring system developed by Seeing Machines. It uses a passive stereo pair of cameras mounted on the dashboard of the vehicle to capture 60Hz video images of the driver's head. These images are processed in real-time to determine the 3D position of matching features on the driver's face. The features are then used to calculate the 3D pose of the person's face +/-lmm, +/- Ideg as well as the eye gaze direction +/- 3deg, blink rates and eye closure.

Figure 3. Integration of the Lane Tracker and FaceLAB

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Combining the gaze direction captured by FaceLAB and the parameterized lane model determined by the lane tracker, we can track the visual behavior of the driver relative to the road. Calculating the intercept of the eye gaze vectors with the road plane will determine whether the person is looking at the road, parallel with the road, to the right of the road or to the left of the road. Additionally, the visual scan patterns of the driver can be recorded with emphasis on fixation points and saccade movements to different regions in the scene. Figure 4 shows the segmentation of the driver visual attention areas for the experiments.

Figure 4. Segmentation of driver visual attention areas. Results

A series of experiments were conducted to test the integrated system in different driving environments: • Highway driving with little traffic • Suburban driving with medium levels of traffic • Inner city with heavy levels of traffic • Outer city with high curvature roads

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Preliminary results are shown in Figure 3 for two different scenarios. Outer city driving with high curvature roads, and highway driving. The results showed that drivers have different focus-of-attention patterns for roads that have different types of curvature. It is possible to discriminate between highway driving and right, left curvature roads by analyzing the histogram of behavior of the driver's visual attention.

The full-length paper will present the experimental results of the lane tracking system with an analysis of the particle filter and cue fusion algorithms used. Additionally, results from the integrated driver monitoring and lane tracking system will be presented focusing on the driver's visual behavior with respect to viewing the road.

Author Index A Andre Amazeen, E Amzeen, P Amorim

E 182 41 41 1

B Baker Bardy Barrett Beek Benguigui Bernadin Bonnet Boonstra Broerse Brown Buekers

95 99, 104 140 65, 145 153 87 99 113 187 182 45

69 45 149 83 65 61 69 87

D Dessing Dietrich Dickie

.116 104

F Fan Faugloire Fourcade Fukui Fowler

61 104,109 99 161 120

G Galantucci Garry Gerrie Geuze

120 125 125 49

H

c Calvin Camachon Caljouw Carello Carson Chan Coyle Cremieux

Effken Ehrlacher

145 87 130

Hajnal Harrison Hayashi Honno Hudry

178 83,113 165 191 187

I Inui Isableu Ishii Ito

161 87 161 191

214

Author Index

J Jarraya Jones Juricevic

P

1 173 34, 37

Peper Peter Petersen

65, 145 73 140

K R Kadar Kagerer Kim Kennedy Krumins Kubovy

116 57 25,29 34,37 15 19

187 53 157 169 153 130 19

M

Mace Makeig Matsuishi Mazyn Michaels Milliex Montagne Mora

199,201 9 191 157 91,178 69 45, 157 187

O

Okura Owen

83, 113, 120 65 95 41 19,182

s

L

Lacherez Laurent Lenoir Leonard Le Runigo Lipp Lunsford

Richardson Ridderikhoff Riley Ringenbach Rogers

191 9

Saburi Salesse Santana Sasaki Savelsbergh Schmit Shaw Shockley Snyder Stoffregen Strother Summers

13 53 79 165, 191 149,157 95 113, 199,201 83 5 104, 109 19 57

T

Takahashi 165 Temprado 53,69 Thornton 169 Treffner ...15, 73, 140, 169, 173 Tse 61 Turvey 83

Studies in Perception & Action VII

V vanderKamp Verheul Virginas

149 49 116

W Wade-Ferrell Wagman Withagen

57 195 91

Y

Yang Yue

135 61

Z Zaal Zelinsky

178 205

215

Keyword Index A Acoustic array, 195 Action, 165 Action system, 191 Adjacent order, 25 Affordances, 83, 140 Amplitude, 41 Animation, 13 Articular geometry, 87 Asymmetry, 49 Attention, 73, 79, 95, 140 bias, 130 divided, 79 Attunement, 178, 195 Auditory perception, 187, 191, 195 Australia, 187 Automaticity, 95 B Backswing, 149 Balance, 95 Bimanual coordination, 41,49,57,61 Binocular vision, 15, 157 Biological motion, 1, 5, 9,13 Biomechanics, 13 Blind-walking, 182 C Calibration, 91, 195 Catching, 145, 157 Circle drawing, 41 Communication, 73, 120 Computer vision, 205

Control mechanism, 45 Conversation, 73, 120, 140 Cooperation, 120 Coordination, 104, 109 bimanual, 41,49, 57, 61 unimanual, 41, 61, 69 hand-foot, 53 dynamics, 41, 53, 61, 65, 69, 73, 149 Correlation, 49 Coupling, 149 Crux, 125 D Damping, 65 Delay, 65 Depth perception, 15, 173 Descriptive study, 191 Disorganization, 165 Display change, 135 control, 116 Distance perception, 182 Distortion, 34 Divided attention, 79 Driving, 140, 205 Dynamic occlusion, 29 touch, 79, 91 Dynamical approach, 104 Dynamics, 109 E Ecological Evolutionary Robotics, 201

Studies in Perception & Action VII

perception and cognition 113,116, 120, 125, 135 robotics, 169,201 Emergence, 120 EMG, 65 Emotion, 9 Events, 125 Evolutionary ecological robotics, 201 Expertise, 104, 153 Exploration, 165, 173, 178 Exploratory learning, 116 perception, 173 Eye movement, 135, 173 tracker, 205

F FaceLab, 205 Fear-relevant stimuli, 130 Feature detection, 130 Pitts' Law, 79 Forelengthening, 37 Foreshortening, 37 Form and shape perception, 5 Frequency, 41 Frontal eye shield, 135

217

H Hand-foot coordination, 53 Haptic perception, 79, 83 Harbor porpoise, 191 Head movement, 191 Heading direction, 29 Heaviness, 83 Hidden surfaces, 25 History machines, 201 Hitting, 149 HKB model, 73

I Imagination, 125 Inertia tensor, 87 Informational and neuromuscular constraints, 69 Information-movement, 149 Inhibition, 135 Intention, 73 Interception, 153 Interpersonal interaction, 120 Invariant, 13 Invariant structure, 201 Inverted pendulum, 99

K

G

Kinesthetic feedback, 57

Gallop, 49 Gaze direction, 19, 29 Gesture, 73 Goal-directed behavior, 113 Goal-oriented locomotion, 45 Grasping, 145, 161

L Lane tracker, 205 Language, 120 Learning, 104, 109, 113 Logical structure, 25

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Keyword Index

M Memory, 1, 125 Metamers, 83 Modeling, 99 Mona Lisa effect, 19 Motion perception, 5 Motor learning, 45, 116 Movement, 83 Multi-frequency, 49 Multi-joint pointing, 87

O Online visual information, 161 Optic flow, 29, 169 P Pantomimed movements, 161 Perception-action, 145, 153, 157, 161,165, 173,199,201 Perceptual laws, 91 learning, 195 Perspective 25, 34, 37, 201 Phobia, 130 Pictures, 19,34,37 Plane of convergence, 15 Plant visualization, 15 Point-light display 1, 5, 9 Posture, 99,104, 109 control, 95 transitions, 99 Pulling force, 178

R Random walk, 116 Reaching, 161

Recruitment of degrees of freedom, 69 Representational momentum, 1 Rhythm, 65 Robot navigation, 169 Robotics, 169, 199,201 Running, 13

S Saccade hazard, 135 Search, 130 Short-term memory, 95 Situational awareness, 199 Smart cars, 205 Social perception, 5, 9 Specifying variables, 178 Stereopsis, 15, 173 Stiffness, 65 Surface corrugation, 29 Swimming distance, 191 T

Task constraints 149 tau guidance, 169 Texture, 29 Timing, 145, 149 Transfer, 45 of calibration, 91 Tritone paradox, 187 Two visual systems, 135, 182 U

Unimanual coordination, 41, 61,69

Studies in Perception & Action VII

V

Virtual reality, 145, 161 Visual angle, 34 feedback, 57 perception, 1, 5, 9, 13, 15, 19,25,29,34,37, 130,135, 145, 149, 153, 157, 161, 169,173, 178, 182 Visuo-spatial coupling, 53

W Walking, 13

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Studies in Perception and Action VII: Twelfth International Conference on Perception and Action : July 13-18, 2003, Gold Coast, Queensland, Australia

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