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The Dynamic Neuron

Author: John Smythies
Publisher: MIT Press
ISBN: 9780262264679
Size: 26.26 MB
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A comprehensive review of current research on synaptic plasticity. The traditional model of synapses as fixed structures has been replaced by a dynamic one in which synapses are constantly being deleted and replaced. This book, written by a leading researcher on the neurochemistry of schizophrenia, integrates material from neuroscience and cell biology to provide a comprehensive account of our current knowledge of the neurochemical basis of synaptic plasticity. The book presents the evidence for synaptic plasticity, an account of the dendritic spine and the glutamate synapse with a focus on redox mechanisms, and the biochemical basis of the Hebbian synapse. It discusses the role of endocytosis, special proteins, and local protein synthesis. Additional topics include volume transmission, arachidonic acid signaling, hormonal modulation, and psychological stress. Finally, the book considers pharmacological and clinical implications of current research, particularly with reference to schizophrenia and Alzheimer's disease.

The Handbook Of Brain Theory And Neural Networks

Author: Michael A. Arbib
Publisher: MIT Press
ISBN: 0262011972
Size: 32.17 MB
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This second edition presents the enormous progress made in recent years in the many subfields related to the two great questions: how does the brain work? and, How can we build intelligent machines? This second edition greatly increases the coverage of models of fundamental neurobiology, cognitive neuroscience, and neural network approaches to language. (Midwest).

Methods In Neuronal Modeling

Author: Christof Koch
Publisher: MIT Press
ISBN: 9780262112314
Size: 60.93 MB
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This book serves as a handbook of computational methods and techniques for modeling the functional properties of single and groups of nerve cells.

The Neurobiology Of Neural Networks

Author: Daniel Gardner
Publisher: MIT Press
ISBN: 9780262071505
Size: 75.37 MB
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This timely overview and synthesis of recent work in both artificial neural networks and neurobiology seeks to examine neurobiological data from a network perspective and to encourage neuroscientists to participate in constructing the next generation of neural networks. Individual chapters were commissioned from selected authors to bridge the gap between present neural network models and the needs of neurophysiologists who are trying to use these models as part of their research on how the brain works.Daniel Gardner is Professor of Physiology and Biophysics at Cornell University Medical College.Contents: Introduction: Toward Neural Neural Networks, Daniel Gardner. Two Principles of Brain Organization: A Challenge for Artificial Neural Networks, Charles F. Stevens. Static Determinants of Synaptic Strength, Daniel Gardner. Learning Rules From Neurobiology, Douglas A. Baxter and John H. Byrne. Realistic Network Models of Distributed Processing in the Leech, Shawn R. Lockery and Terrence J. Sejnowski. Neural and Peripheral Dynamics as Determinants of Patterned Motor Behavior, Hillel J. Chiel and Randall D. Beer. Dynamic Neural Network Models of Sensorimotor Behavior, Eberhard E. Fetz.

A Dynamic Systems Approach To The Development Of Cognition And Action

Author: Esther Thelen
Publisher: MIT Press
ISBN: 9780262700597
Size: 51.15 MB
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"A radical departure from most of current cognitive development theory.... Nativists, structuralists, empiricists and social constructivists will disagree with different parts of this book. Yet this landmark volume is essential reading for all of them." -- Annette Karmiloff-Smith and Mark H. Johnson, "Nature" A Dynamic Systems Approach to the Development of Cognition and Action presents a comprehensive and detailed theory of early human development based on the principles of dynamic systems theory. Beginning with their own research in motor, perceptual, and cognitive development, Thelen and Smith raise fundamental questions about prevailing assumptions in the field. They propose a new theory of the development of cognition and action, unifying recent advances in dynamic systems theory with current research in neuroscience and neural development. In particular, they show how by processes of exploration and selection, multimodal experiences form the bases for self-organizing perception-action categories. Thelen and Smith offer a radical alternative to current cognitive theory, both in their emphasis on dynamic representation and in their focus on processes of change. Among the first attempt to apply complexity theory to psychology, they suggest reinterpretations of several classic issues in early cognitive development. The book is divided into three sections. The first discusses the nature of developmental processes in general terms, the second covers dynamic principles in process and mechanism, and the third looks at how a dynamic theory can be applied to enduring puzzles of development. Cognitive Psychology series

From Animals To Animats 7

Author: Bridget Hallam
Publisher: MIT Press
ISBN: 9780262582179
Size: 22.57 MB
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Proceedings of the Seventh International Conference on Simulation of Adaptive Behavior The Simulation of Adaptive Behavior Conference brings together researchers from ethology, psychology, ecology, artificial intelligence, artificial life, robotics, computer science, engineering, and related fields to further understanding of the behaviors and underlying mechanisms that allow adaptation and survival in uncertain environments. The work presented focuses on robotic and computational experimentation with well-defined models that help to characterize and compare alternative organizational principles or architectures underlying adaptive behavior in both natural animals and synthetic animats.

Dynamic Patterns

Author: J. A. Scott Kelso
Publisher: MIT Press
ISBN: 9780262611312
Size: 34.60 MB
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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.

Advances In Neural Information Processing Systems 19

Author: Bernhard Schölkopf
Publisher: MIT Press
ISBN: 0262195682
Size: 70.98 MB
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The annual conference on NIPS is the flagship conference on neural computation. It draws top academic researchers from around the world & is considered to be a showcase conference for new developments in network algorithms & architectures. This volume contains all of the papers presented at NIPS 2006.

Self Organizing Map Formation

Author: Klaus Obermayer
Publisher: MIT Press
ISBN: 9780262650601
Size: 32.21 MB
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This book provides an overview of self-organizing map formation, including recent developments. Self-organizing maps form a branch of unsupervised learning, which is the study of what can be determined about the statistical properties of input data without explicit feedback from a teacher. The articles are drawn from the journal Neural Computation.The book consists of five sections. The first section looks at attempts to model the organization of cortical maps and at the theory and applications of the related artificial neural network algorithms. The second section analyzes topographic maps and their formation via objective functions. The third section discusses cortical maps of stimulus features. The fourth section discusses self-organizing maps for unsupervised data analysis. The fifth section discusses extensions of self-organizing maps, including two surprising applications of mapping algorithms to standard computer science problems: combinatorial optimization and sorting. Contributors J. J. Atick, H. G. Barrow, H. U. Bauer, C. M. Bishop, H. J. Bray, J. Bruske, J. M. L. Budd, M. Budinich, V. Cherkassky, J. Cowan, R. Durbin, E. Erwin, G. J. Goodhill, T. Graepel, D. Grier, S. Kaski, T. Kohonen, H. Lappalainen, Z. Li, J. Lin, R. Linsker, S. P. Luttrell, D. J. C. MacKay, K. D. Miller, G. Mitchison, F. Mulier, K. Obermayer, C. Piepenbrock, H. Ritter, K. Schulten, T. J. Sejnowski, S. Smirnakis, G. Sommer, M. Svensen, R. Szeliski, A. Utsugi, C. K. I. Williams, L. Wiskott, L. Xu, A. Yuille, J. Zhang