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Computational Brain

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ISBN-10: 0262531208

ISBN-13: 9780262531207

Edition: N/A

Authors: Patricia S. Churchland, Terrence J. Sejnowski, Tomaso A. Poggio

List price: $45.00
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Description:

The Computational Brain is the first unified and broadly accessible book to bring together computational concepts and behavioral data within a neurobiological framework. Churchland and Sejnowski address the foundational ideas of the emerging field of computational neuroscience, examine a diverse range of neural network models, and consider future directions of the field. A Bradford Book. Computational Neuroscience series
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Book details

List price: $45.00
Publisher: MIT Press
Publication date: 2/3/1994
Binding: Paperback
Pages: 558
Size: 7.25" wide x 10.00" long x 1.25" tall
Weight: 2.398
Language: English

Patricia S. Churchland is professor emerita of philosophy at the University of California, San Diego, and an adjunct professor at the Salk Institute. Her books include "Brain-Wise" and "Neurophilosophy". In 1991, she was awarded a MacArthur Fellowship.

Terrence J. Sejnowski is Francis Crick Professor, Director of the Computational Neurobiology Laboratory, and a Howard Hughes Medical Institute Investigator at the Salk Institute for Biological Studies and Professor of Biology at the University of California, San Diego.

Series Foreword
Preface
Introduction
Neuroscience Overview
Introduction
Levels in Nervous Systems
Structure at Various Levels of Organization
A Short List of Brain Facts
Computational Overview
Introduction
Looking Up the Answer
Linear Associators
Constraint Satisfaction: Hopfield Networks and Boltzmann Machines
Learning in Neural Nets
Competitive Learning
Curve Fitting
Feedforward Nets: Two Examples
Recurrent Nets
From Toy World to Real World
What Good are Optimazation Procedures to Neuroscience?
Models: Realistic and
Abstract
Concluding Remarks
Selected Readings
Selected Journals
Representing the World
Introduction
Constructing a Visual World
Thumbnail Sketch of the Mammalian Visual System
Representing in the Brain: What Can We Learn from the Visual System?
What Is So Special About Distribution?
World Enough and Time
Shape From Shading: A Neurocomputational Study
Stereo Vision
Computational Models of Stereo Vision
Hyperacuity: From Mystery to Mechanism
Vector Averaging
Concluding Remarks
Selected Readings
Plasticity: Cells, Circuits, Brains, and Behavior
Introduction
Learning and the Hippocampus
Donald Hebb and Synaptic Plasticity
Memories are Made of This: Mechanisms of Neuronal Plasticity
Cells and Circuts
Decreasing Synaptic Strength
Back to Systems and Behavior
Being and Timing
Development of Nervous Systems
Modules and Networks
Selected Readings
Sensorimotor Integration
Introduction
Leechnet
Computation and the Vestibulo-Ocular Reflex
Time and Time Again
The Segmental Swimming Oscillator
Modeling the Neuron
Concluding Remarks
Concluding and Beyond
Afterword
Appendix Anatomical and Physiological Techniques
Permanent Lesions
Human Studies
Animal Models
Reversible Lseions and Microlesions
Imaging Techniques
Gross Electrical and Magnetic Recording
Single-Unit Recording
Anatomical Tract Tracing
Notes
Glossary
References
Index