Neural Networks and Brain Function by Edmund RollsNeural Networks and Brain Function by Edmund Rolls

Neural Networks and Brain Function

byEdmund Rolls, Alessandro Treves

Paperback | October 1, 1997

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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 whichaddresses 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 someparts 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 formalquantitative 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 thosewithout a background in computer science.
Edmund T. Rolls is in the Department of Experimental Psychology, University of Oxford. Alessandro Treves is at International School of Advanced Studies, Cognitive Neuroscience Division, Trieste.
Title:Neural Networks and Brain FunctionFormat:PaperbackDimensions:428 pages, 9.45 × 6.61 × 0.98 inPublished:October 1, 1997Publisher:Oxford University Press

The following ISBNs are associated with this title:

ISBN - 10:0198524323

ISBN - 13:9780198524328


Table of Contents

Ch. 1. IntroductionCh. 2. Pattern Association MemoryCh. 3. Autoassociation MemoryCh. 4. Competitive Networks, Including Self-Organizing MapsCh. 5. Error-Correcting Networks: Perceptrons, Backpropagation of Error in Multilayer Networks, and Reinforcement Learning AlgorithmsCh. 6. Hippocampus and MemoryCh. 7. Pattern Association in the Brain: Amygdala and Orbitofrontal CortexCh. 8. Cortical Networks for Invariant Pattern RecognitionCh. 9. Motor Systems: Cerebellum and Basal GangliaCh. 10. Cerebral NeocortexAppendix 1. Introduction to Linear Algebra for Neural NetworksAppendix 2. Information TheoryAppendix 3. Pattern AssociatorsAppendix 4. AutoassociatorsAppendix 5. Recurrent Dynamics

Editorial Reviews

`...a fascinating groundwork for researchers stydying how the human brian works and how behaviour is produced.'ASLIB 63/8 August 98.