Neural Networks and Brain Function
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Product details:
- Publisher OUP Oxford
- Date of Publication 23 October 1997
- ISBN 9780198524328
- Binding Paperback
- No. of pages428 pages
- Size 240x168x25 mm
- Weight 733 g
- Language English
- Illustrations halftones, numerous line figures, tables 0
Categories
Short description:
This book aims to describe the types of computation that can be performed by biologically plausible neural networks, and to show how these may be implemented in different systems in the brain. Suitable for researchers, graduate students and advanced undergraduates in the fields of neuroscience and artificial intelligence, this is an accessible introduction to the fascinating problems of how the brain works and how our behaviour is produced.
MoreLong description:
The aim of this book is to describe the types of computation that can be performed by biologically plausible neural networks, and to show how these may be implemented in different systems in the brain. Neural Networks and Brain Function is structured in three sections, each of which addresses a different need in the market. The first section introduces and describes the operation of several fundamental types of neural network. The second section describes real neural networks in several brain systems, and shows how it is becoming possible to construct theories about how some parts of the brain work; it also provides an indication of the different neuroscience and neurocomputation techniques that will need to be combined to ensure further rapid progress in understanding how parts of the brain work. The third section, a collection of appendices, introduces the more formal quantitative approaches to many of the networks described. This is a clearly written and thoughtfully structured introduction to a fascinating and complex field of neuroscience. It will be a key text for researchers, graduate students and advanced undergraduates in the field, particularly for those without a background in computer science.
...a fascinating groundwork for researchers stydying how the human brian works and how behaviour is produced.
Table of Contents:
Ch. 1. Introduction
Ch. 2. Pattern Association Memory
Ch. 3. Autoassociation Memory
Ch. 4. Competitive Networks, Including Self-Organizing Maps
Ch. 5. Error-Correcting Networks: Perceptrons, Backpropagation of Error in Multilayer Networks, and Reinforcement Learning Algorithms
Ch. 6. Hippocampus and Memory
Ch. 7. Pattern Association in the Brain: Amygdala and Orbitofrontal Cortex
Ch. 8. Cortical Networks for Invariant Pattern Recognition
Ch. 9. Motor Systems: Cerebellum and Basal Ganglia
Ch. 10. Cerebral Neocortex
Appendix 1. Introduction to Linear Algebra for Neural Networks
Appendix 2. Information Theory
Appendix 3. Pattern Associators
Appendix 4. Autoassociators
Appendix 5. Recurrent Dynamics
