The Computational Brain

Front Cover
MIT Press, 1994 - Medical - 544 pages
3 Reviews

How do groups of neurons interact to enable the organism to see, decide, and move appropriately? What are the principles whereby networks of neurons represent and compute? These are the central questions probed by The Computational Brain. 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. The Computational Brain is the first unified and broadly accessible book to bring together computational concepts and behavioral data within a neurobiological framework.

Computer models constrained by neurobiological data can help reveal how -- networks of neurons subserve perception and behavior -- bow their physical interactions can yield global results in perception and behavior, and how their physical properties are used to code information and compute solutions. The Computational Brain focuses mainly on three domains: visual perception, learning and memory, and sensorimotor integration. Examples of recent computer models in these domains are discussed in detail, highlighting strengths and weaknesses, and extracting principles applicable to other domains. Churchland and Sejnowski show how both abstract models and neurobiologically realistic models can have useful roles in computational neuroscience, and they predict the coevolution of models and experiments at many levels of organization, from the neuron to the system.

The Computational Brain addresses a broad audience: neuroscientists, computer scientists, cognitive scientists, and philosophers. It is written for both the expert and novice. A basic overview of neuroscience and computational theory is provided, followed by a study of some of the most recent and sophisticated modeling work in the context of relevant neurobiological research. Technical terms are clearly explained in the text, and definitions are provided in an extensive glossary. The appendix contains a précis of neurobiological techniques.

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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Review: The Computational Brain

User Review  - Jian - Goodreads

this book just push psychology to a new level:-) Read full review

Review: The Computational Brain

User Review  - Goodreads

this book just push psychology to a new level:-) Read full review

Contents

Neuroscience Overview
17
A short list of brain facts
48
Computational Overview
61
Linear associators
77
Learning in neural nets
96
Recurrent nets
115
What good are optimization procedures to neuroscience?
130
Thumbnail sketch of the mammalian visual system
148
Cells and circuits
281
Back to systems and behavior
295
Modules and networks
316
Sensorimotor Integration 3 31
337
Computation and the vestibuloocular reflex
353
Time and time again
379
Modeling the neuron
399
Concluding and Beyond
413

What is so special about distribution?
163
A neurocomputational study
183
Computational models of stereo vision
199
From mystery to mechanism
221
Concluding remarks
237
Cells Circuits Brains and Behavior
239
Mechanisms of neuronal plasticity
254
Appendix Anatomical and Physiological Techniques
427
Singleunit recording
440
Glossary
457
References
479
Index
525
Copyright

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About the author (1994)

Patricia Smith Churchland is UC President's Professor of Philosophy at the University of California, San Diego, and Adjunct Professor at the Salk Institute.

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.

Bibliographic information