This text charts the progress made in recent years in many specific areas related to the following two questions: how does the brain work?; and how can we build intelligent machines? The handbook covers the entire range of topics involved in brain theory and neural networks, from detailed models of single neurons, analyses of different biological neural networks and connectionist studies of psychology and language to mathematical analyses of a variety of abstract neural networks and technological applications of adaptive, artificial neural networks. The main part of the text, Part Three, contains 267 articles by leaders in the various fields, arranged alphabetically by title. The first two parts are designed to help readers orient themselves to this vast range of material. Part One introduces several basic neural models, explains how the present study of brain theory and neural networks integrates brain theory, artificial intelligence and cognitive psychology, and provides a tutorial on the concepts essential for understanding neural networks as dynamic, adaptive systems. Part Two provides entry into the many articles of Part Three through an introductory "Meta-Map" and 23 road maps, each of which tours all the Part Three articles on the chosen theme.
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"This revised *Handbook of Brain Theory* provides useful new data and and updates key concepts in neuroscience. It will be an indispensable guide for exploring the essentials of brain science."--Masao Ito, RIKEN Brain Science InstitutePlease note: This quote is for promotional materials only, not for the book jacket.
Michael Arbib has played a leading role at the interface of neuroscience and computer science ever since his first book, Brains, Machines, and Mathematics. From Neuron to Cognition provides a worthy pedagogical sequel to his widely acclaimed Handbook of Brain Theory and Neural Networks. After thirty years at University of Southern California he is now pursuing interests in "how the brain got language" and "neuroscience for architecture" in San Diego.
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