The handbook of brain theory and neural network

It's been a half century since such pioneers as Warren McCulloch and Donald Hebb, and, particularly in the last decade, brain theory has been in flower, intertwining with both neurophysiology and artificial neural networks. Boiling it down and concentrating it, as this handbook does so successfully,is likely to set the stage for something even more interesting.

At long last neural computation, as a wide interdisciplinary field, has found its universal, intellectual home. Under one roof we have all that we wanted to know from the biological to the matehmatical, from experiment to theory, from applications to abstract models, from robots to philosophy.

The awesome product of an awesome task, this book will take us into the 21st Century with a wide and enlightened overview of computational neuroscience—and a healthy respect for the constraints that the real brain imposes on our models.

Arbib has done what urgently needed to be done and what probably no one else could do. This revised Handbook of Brain Theory provides useful new data and and updates key concepts in neuroscience. It will be an indispensable guide for exploring the essentials of brain science. Michael A. Arbib and James J. Warren S. Search Search.

Share Share Share email. Editors Michael A. Arbib Michael Arbib has played a leading role at the interface of neuroscience and computer science ever since his first book, Brains, Machines, and Mathematics. Awards Choice Outstanding Academic Title, McCulloch Cart Buying Options. Dramatically updating and extending the first edition, published in , 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?

Once again, the heart of the book is a set of almost 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. 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 articles, compared to the 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 articles on new topics.

We present a point of view that has emerged in the recent years from a combination of … Expand. Coding visual images of objects in the inferotemporal cortex of the macaque monkey. Journal of neurophysiology. Highly Influential. View 4 excerpts, references background and results. Visual properties of neurons in inferotemporal cortex of the Macaque. View 3 excerpts, references background and methods. On the relations between the direction of two-dimensional arm movements and cell discharge in primate motor cortex.

The Journal of neuroscience : the official journal of the Society for Neuroscience. View 1 excerpt, references methods.

Neural encoding of individual words and faces by the human hippocampus and amygdala. View 1 excerpt, references background. Columns for visual features of objects in monkey inferotemporal cortex. What Is the Goal of Sensory Coding? Mathematics, Computer Science. Neural Computation.