The conference from which this book derives took place in Tsukuba, Japan in March 2004. The fifth in a continuing series of conferences, this one was organized to examine dynamic processes in "lower order" cognition from perception to attention to memory, considering both the behavioral and the neural levels. We were fortunate to attract a terrific group of con tributors representing five countries, which resulted in an exciting confer ence and, as the reader will quickly discover, an excellent set of chapters. In Chapter 1, we will provide a sketchy "road map" to these chapters, elu cidating some of the themes that emerged at the conference. The conference itself was wonderful. We very much enjoyed the vari ety of viewpoints and issues that we all had the opportunity to grapple with. There were lively and spirited exchanges, and many chances to talk to each other about exciting new research, precisely what a good confer ence should promote. We hope that the readers of this book will have the same experience—moving from careful experimental designs in the cogni tive laboratory to neural mechanisms measured by new technologies, from the laboratory to the emergency room, from perceptual learning to changes in memory over decades, all the while squarely focusing on how best to explain cognition, not simply to measure it. Ultimately, the goal of science is, of course, explanation. We also hope that the reader will come away absolutely convinced that cognition is a thoroughly dynamic, interactive system.

An introduction to computational modeling for cognitive neuroscientists, covering both foundational work and recent developments. Cognitive neuroscientists need sophisticated conceptual tools to make sense of their field’s proliferation of novel theories, methods, and data. Computational modeling is such a tool, enabling researchers to turn theories into precise formulations. This book offers a mathematically gentle and theoretically unified introduction to modeling cognitive processes. Theoretical exercises of varying degrees of difficulty throughout help readers develop their modeling skills. After a general introduction to cognitive modeling and optimization, the book covers models of decision making; supervised learning algorithms, including Hebbian learning, delta rule, and backpropagation; the statistical model analysis methods of model parameter estimation and model evaluation; the three recent cognitive modeling approaches of reinforcement learning, unsupervised learning, and Bayesian models; and models of social interaction. All mathematical concepts are introduced gradually, with no background in advanced topics required. Hints and solutions for exercises and a glossary follow the main text. All code in the book is Python, with the Spyder editor in the Anaconda environment. A GitHub repository with Python files enables readers to access the computer code used and start programming themselves. The book is suitable as an introduction to modeling cognitive processes for students across a range of disciplines and as a reference for researchers interested in a broad overview.

An introduction to the application of dynamical systems science to the cognitive sciences. Dynamical Cognitive Science makes available to the cognitive science community the analytical tools and techniques of dynamical systems science, adding the variables of change and time to the study of human cognition. The unifying theme is that human behavior is an "unfolding in time" whose study should be augmented by the application of time-sensitive tools from disciplines such as physics, mathematics, and economics, where change over time is of central importance. The book provides a fast-paced, comprehensive introduction to the application of dynamical systems science to the cognitive sciences. Topics include linear and nonlinear time series analysis, chaos theory, complexity theory, relaxation oscillators, and metatheoretical issues of modeling and theory building. Tools and techniques are discussed in the context of their application to basic cognitive science problems, including perception, memory, psychophysics, judgment and decision making, and consciousness. The final chapter summarizes the contemporary study of consciousness and suggests how dynamical approaches to cognitive science can help to advance our understanding of this central concept.

In neurophysiology, the emphasis has been on single-unit studies for a quarter century, since the sensory work by Lettwin and coworkers and by Hubel and Wiesel, the cen tral work by Mountcastle, the motor work by the late Evarts, and so on. In recent years, however, field potentials - and a more global approach general ly - have been receiving renewed and increasing attention. This is a result of new findings made possible by technical and conceptual advances and by the confirma tion and augmentation of earlier findings that were widely ignored for being contro versial or inexplicable. To survey the state of this active field, a conference was held in West Berlin in August 1985 that attempted to cover all of the new approaches to the study of brain function. The approaches and emphases were very varied: basic and applied, electric and magnetic, EEG and EP/ERP, connectionistic and field, global and local fields, surface and multielectrode, low frequencies and high frequencies, linear and non linear. The conference comprised sessions of invited lectures, a panel session of seven speakers on "How brains may work," and a concluding survey of relevant methodologies. The conference showed that the combination of concepts, methods, and results could open up new important vistas in brain research. Included here are the proceedings of the conference, updated and revised by the authors. Several attendees who did not present papers at the conference later ac cepted my invitation to write chapters for the book.

"This book describes a new theoretical approach--Dynamic Field Theory (DFT)--that explains how people think and act"--

A groundbreaking book from Simon Haykin, setting out the fundamental ideas and highlighting a range of future research directions.

The shared platform of the articles collected in this volume is usedto advocate a dynamical systems approach to cognition. It is arguedthat recent developments in cognitive science towards an account ofembodiment, together with the general approach of complexity theoryand dynamics, have a major impact on behavioral and cognitivescience.

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.

A comprehensive treatment of cognitive radio networks and the specialized techniques used to improve wireless communications The human brain, as exemplified by cognitive radar, cognitive radio, and cognitive computing, inspires the field of Cognitive Dynamic Systems. In particular, cognitive radio is growing at an exponential rate. Fundamentals of Cognitive Radio details different aspects of the human brain and provides examples of how it can be mimicked by cognitive dynamic systems. The text offers a communication-theoretic background, including information on resource allocation in wireless networks and the concept of robustness. The authors provide a thorough mathematical background with data on game theory, variational inequalities, and projected dynamic systems. They then delve more deeply into resource allocation in cognitive radio networks. The text investigates the dynamics of cognitive radio networks from the perspectives of information theory, optimization, and control theory. It also provides a vision for the new world of wireless communications by integration of cellular and cognitive radio networks. This groundbreaking book: Shows how wireless communication systems increasingly use cognition to enhance their networks Explores how cognitive radio networks can be viewed as spectrum supply chain networks Derives analytic models for two complementary regimes for spectrum sharing (open-access and market-driven) to study both equilibrium and disequilibrium behaviors of networks Studies cognitive heterogeneous networks with emphasis on economic provisioning for resource sharing Introduces a framework that addresses the issue of spectrum sharing across licensed and unlicensed bands aimed for Pareto optimality Written for students of cognition, communication engineers, telecommunications professionals, and others, Fundamentals of Cognitive Radio offers a new generation of ideas and provides a fresh way of thinking about cognitive techniques in order to improve radio networks.

Advancing the dynamical approach as the methodological frame best equipped to guide inquiry in the field's two main research programs - the symbolic and connectionist approaches - Marco Giunti engages a host of questions crucial not only to the science of cognition, but also to computation theory, dynamical systems theory, philosophy of mind, and philosophy of science.