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One of the most striking features of Coordination Dynamics is its interdisciplinary character. The problems we are trying to solve in this field range from behavioral phenomena of interlimb coordination and coordination between stimuli and movements (perception-action tasks) through neural activation patterns that can be observed during these tasks to clinical applications and social behavior. It is not surprising that close collaboration among scientists from different fields as psychology, kinesiology, neurology and even physics are imperative to deal with the enormous difficulties we are facing when we try to understand a system as complex as the human brain. The chapters in this volume are not simply write-ups of the lectures given by the experts at the meeting but are written in a way that they give sufficient introductory information to be comprehensible and useful for all interested scientists and students.
This book brings together scientists from all over the world who have defined and developed the field of Coordination Dynamics. Grounded in the concepts of self-organization and the tools of nonlinear dynamics, appropriately extended to handle informational aspects of living things, Coordination Dynamics aims to understand the coordinated functioning of a variety of different systems at multiple levels of description. The book addresses the themes of Coordination Dynamics and Dynamic Patterns in the context of the following topics: Coordination of Brain and Behavior, Perception-Action Coupling, Control, Posture, Learning, Intention, Attention, and Cognition.
foreword by Hermann Haken For the past twenty years Scott Kelso's research has focused on extending the physical concepts of self- organization and the mathematical tools of nonlinear dynamics to understand how human beings (and human brains) perceive, intend, learn, control, and coordinate complex behaviors. In this book Kelso proposes a new, general framework within which to connect brain, mind, and behavior.Kelso's prescription for mental life breaks dramatically with the classical computational approach that is still the operative framework for many newer psychological and neurophysiological studies. His core thesis is that the creation and evolution of patterned behavior at all levels--from neurons to mind--is governed by the generic processes of self-organization. Both human brain and behavior are shown to exhibit features of pattern-forming dynamical systems, including multistability, abrupt phase transitions, crises, and intermittency. Dynamic Patterns brings together different aspects of this approach to the study of human behavior, using simple experimental examples and illustrations to convey essential concepts, strategies, and methods, with a minimum of mathematics. Kelso begins with a general account of dynamic pattern formation. He then takes up behavior, focusing initially on identifying pattern-forming instabilities in human sensorimotor coordination. Moving back and forth between theory and experiment, he establishes the notion that the same pattern-forming mechanisms apply regardless of the component parts involved (parts of the body, parts of the nervous system, parts of society) and the medium through which the parts are coupled. Finally, employing the latest techniques to observe spatiotemporal patterns of brain activity, Kelso shows that the human brain is fundamentally a pattern forming dynamical system, poised on the brink of instability. Self-organization thus underlies the cooperative action of neurons that produces human behavior in all its forms.
An examination of how widely distributed and specialized activities of the brain are flexibly and effectively coordinated. A fundamental shift is occurring in neuroscience and related disciplines. In the past, researchers focused on functional specialization of the brain, discovering complex processing strategies based on convergence and divergence in slowly adapting anatomical architectures. Yet for the brain to cope with ever-changing and unpredictable circumstances, it needs strategies with richer interactive short-term dynamics. Recent research has revealed ways in which the brain effectively coordinates widely distributed and specialized activities to meet the needs of the moment. This book explores these findings, examining the functions, mechanisms, and manifestations of distributed dynamical coordination in the brain and mind across different species and levels of organization. The book identifies three basic functions of dynamic coordination: contextual disambiguation, dynamic grouping, and dynamic routing. It considers the role of dynamic coordination in temporally structured activity and explores these issues at different levels, from synaptic and local circuit mechanisms to macroscopic system dynamics, emphasizing their importance for cognition, behavior, and psychopathology. Contributors Evan Balaban, György Buzsáki, Nicola S. Clayton, Maurizio Corbetta, Robert Desimone, Kamran Diba, Shimon Edelman, Andreas K. Engel, Yves Fregnac, Pascal Fries, Karl Friston, Ann Graybiel, Sten Grillner, Uri Grodzinski, John-Dylan Haynes, Laurent Itti, Erich D. Jarvis, Jon H. Kaas, J.A. Scott Kelso, Peter König, Nancy J. Kopell, Ilona Kovács, Andreas Kreiter, Anders Lansner, Gilles Laurent, Jörg Lücke, Mikael Lundqvist, Angus MacDonald, Kevan Martin, Mayank Mehta, Lucia Melloni, Earl K. Miller, Bita Moghaddam, Hannah Monyer, Edvard I. Moser, May-Britt Moser, Danko Nikolic, William A. Phillips, Gordon Pipa, Constantin Rothkopf, Terrence J. Sejnowski, Steven M. Silverstein, Wolf Singer, Catherine Tallon-Baudry, Roger D. Traub, Jochen Triesch, Peter Uhlhaas, Christoph von der Malsburg, Thomas Weisswange, Miles Whittington, Matthew Wilson
This comprehensive edited treatise discusses the neurological, physiological, and cognitive aspects of interlimb coordination. It is unique in promoting a multidisciplinary perspective through introductory chapter contributions from experts in the neurosciences, experimental and developmental psychology, and kinesiology. Beginning with chapters defining the neural basis of interlimb coordination in animals, the book progresses toward an understanding of human locomotor control and coordination and the underlying brain structures and nerves that make such control possible. Section two focuses on the dynamics of interlimb coordination and the physics of movement. The final section presents information on how practice and experience affect coordination, including general skill acquisition, learning to walk, and the process involved in rhythmic tapping.
This indispensable sourcebook covers conceptual and practical issues in research design in the field of social and personality psychology. Key experts address specific methods and areas of research, contributing to a comprehensive overview of contemporary practice. This updated and expanded second edition offers current commentary on social and personality psychology, reflecting the rapid development of this dynamic area of research over the past decade. With the help of this up-to-date text, both seasoned and beginning social psychologists will be able to explore the various tools and methods available to them in their research as they craft experiments and imagine new methodological possibilities.
The SAGE Handbook of Social Cognition is a landmark volume. Edited by two of the field′s most eminent academics and supported by a distinguished global advisory board, the 56 authors - each an expert in their own chapter topic - provide authoritative and thought-provoking overviews of this fascinating territory of research. Not since the early 1990s has a Handbook been published in this field, now, Fiske and Macrae have provided a timely and seminal benchmark; a state of the art overview that will benefit advanced students and academics not just within social psychology but beyond these borders too. Following an introductory look at the ′uniqueness of social cognition′, the Handbook goes on to explore basic and underlying processes of social cognition, from implicit social cognition and consciousness and meta-cognition to judgment and decision-making. Also, the wide-ranging applications of social cognition research in ′the real world′ from the burgeoning and relatively recent fields of social cognitive development and social cognitive aging to the social cognition of relationships are investigated. Finally, there is a critical and exciting exploration of the future directions in this field. The SAGE Handbook of Social Cognition will be an indispensable volume for any advanced student or academic wanting or needing to understand the landscape of social cognition research in the 21st century.
This volume concerns the longstanding intellectual puzzle of how individuals overcome their biological, neural, and mental finitude to achieve sociality. It explores how humans take each other into account, coordinate their actions, and are able to share their inner states and to communicate. Sophisticated views on the bases of sociality are detailed at the level of neural mechanisms, perception and memory, motivation, communication and dialog, culture, and evolution. These insights have been inspired by major strides and exciting new developments in disciplines as far afield as ethology, evolutionary ecology, neuroscience, cognition, memory, developmental and social psychology, psycholinguistics, philosophy, robotics, and sociology. The volume is the first to bridge these disciplinary boundaries to lay the foundations for an integrated and general conceptualization of the bases of sociality and its implications for psychology. Each contribution presents different levels of the grounding of sociality and will further stimulate novel approaches to linking different layers of sociality, from the neural to the cultural level.
Many statistical and methodological developments regarding fractal analyses have appeared in the scientific literature since the publication of the seminal texts introducing Fractal Physiology. However, the lion’s share of more recent work is distributed across many outlets and disciplines, including aquatic sciences, biology, computer science, ecology, economics, geology, mathematics, medicine, neuroscience, physics, physiology, psychology, and others. The purpose of this special topic is to solicit submissions regarding fractal and nonlinear statistical techniques from experts that span a wide range of disciplines. The articles will aggregate extensive cross-discipline expertise into comprehensive and broadly applicable resources that will support the application of fractal methods to physiology and related disciplines. The articles will be organized with respect to a continuum defined by the characteristics of the empirical measurements a given analysis is intended to confront. At one end of the continuum are stochastic techniques directed at assessing scale invariant but stochastic data. The next step in the continuum concerns self-affine random fractals and methods directed at systems that entail scale-invariant or 1/f patterns or related patterns of temporal and spatial fluctuation. Analyses directed at (noisy) deterministic signals correspond to the final stage of the continuum that relates the statistical treatments of nonlinear stochastic and deterministic signals. Each section will contain introductory articles, advanced articles, and application articles so readers with any level of expertise with fractal methods will find the special topic accessible and useful. Example stochastic methods include probability density estimation for the inverse power-law, the lognormal, and related distributions. Articles describing statistical issues and tools for discriminating different classes of distributions will be included. An example issue is distinguishing power-law distributions from exponential distributions. Modeling issues and problems regarding statistical mimicking will be addressed as well. The random fractal section will present introductions to several one-dimensional monofractal time-series analysis. Introductory articles will be accompanied by advanced articles that will supply comprehensive treatments of all the key fractal time series methods such as dispersion analysis, detrended fluctuation analysis, power spectral density analysis, and wavelet techniques. Box counting and related techniques will be introduced and described for spatial analyses of two and three dimensional domains as well. Tutorial articles on the execution and interpretation of multifractal analyses will be solicited. There are several standard wavelet based and detrended fluctuation based methods for estimating a multifractal spectrum. We hope to include articles that contrast the different methods and compare their statistical performance as well. The deterministic methods section will include articles that present methods of phase space reconstruction, recurrence analysis, and cross-recurrence analysis. Recurrence methods are widely applicable, but motivated by signals that contain deterministic patterns. Nonetheless recent developments such as the analysis of recurrence interval scaling relations suggest applicability to fractal systems. Several related statistical procedures will be included in this section. Examples include average mutual information statistics and false nearest neighbor analyses.
An innovative, multifaceted approach to scientific experiments as designed by and shaped through interaction with the modeling process The role of scientific modeling in mediation between theories and phenomena is a critical topic within the philosophy of science, touching on issues from climate modeling to synthetic models in biology, high energy particle physics, and cognitive sciences. Offering a radically new conception of the role of data in the scientific modeling process as well as a new awareness of the problematic aspects of data, this cutting-edge volume offers a multifaceted view on experiments as designed and shaped in interaction with the modeling process. Contributors address such issues as the construction of models in conjunction with scientific experimentation; the status of measurement and the function of experiment in the identification of relevant parameters; how the phenomena under study are reconceived when accounted for by a model; and the interplay between experimenting, modeling, and simulation when results do not mesh. Highlighting the mediating role of models and the model-dependence (as well as theory-dependence) of data measurement, this volume proposes a normative and conceptual innovation in scientific modeling—that the phenomena to be investigated and modeled must not be precisely identified at the start but specified during the course of the interactions arising between experimental and modeling activities. Contributors: Nancy D. Cartwright, U of California, San Diego; Anthony Chemero, U of Cincinnati; Ronald N. Giere, U of Minnesota; Jenann Ismael, U of Arizona; Tarja Knuuttila, U of South Carolina; Andrea Loettgers, U of Bern, Switzerland; Deborah Mayo, Virginia Tech; Joseph Rouse, Wesleyan U; Paul Teller, U of California, Davis; Michael Weisberg, U of Pennsylvania; Eric Winsberg, U of South Florida.