Dramatically updating and extending the first edition, published in 1995, the second edition of The Handbook of Brain Theory and Neural Networks presents the enormous progress made in recent years in the many subfields related to the two great questions: How does the brain work? and, How can we build intelligent machines?
Once again, the heart of the book is a set of almost 300 articles covering the whole spectrum of topics in brain theory and neural networks. The first two parts of the book, prepared by Michael Arbib, are designed to help readers orient themselves in this wealth of material. Part I provides general background on brain modeling and on both biological and artificial neural networks. Part II consists of "Road Maps" to help readers steer through articles in part III on specific topics of interest. The articles in part III are written so as to be accessible to readers of diverse backgrounds. They are cross-referenced and provide lists of pointers to Road Maps, background material, and related reading.
The second edition greatly increases the coverage of models of fundamental neurobiology, cognitive neuroscience, and neural network approaches to language. It contains 287 articles, compared to the 266 in the first edition. Articles on topics from the first edition have been updated by the original authors or written anew by new authors, and there are 106 articles on new topics.
Comprehensive text charts the progress made in recent years in answering the questions 'How does the brain work?' and 'How can we build intelligent machines?' Articles are presented in alphabetical order by title. Part one covers background, part two, brain theory and neural networks, and part three includes the articles. Previous edition: c1995.
About the Author
Michael A. Arbib is University Professor; Fletcher Jones Professor of Computer Science; and Professor of Neuroscience, Biomedical Engineering, Electrical Engineering, and Psychology at the University of Southern California.