Principles of Neural Information Theory

Computational Neuroscience and Metabolic Efficiency

By:

James V Stone

Format:

Hardback

Series:

Tutorial Introductions

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Description

The brain is the most complex computational machine known to science, even though its components (neurons) are slow and unreliable compared to a laptop computer. In this richly illustrated book, Shannon's mathematical theory of information is used to explore the metabolic efficiency of neurons, with special reference to visual perception. Evidence from a diverse range of research papers is used to show how information theory defines absolute limits on neural efficiency; limits which ultimately determine the neuroanatomical microstructure of the eye and brain. Written in an informal style, with a comprehensive glossary, tutorial appendices, explainer boxes, and a list of annotated Further Readings, this book is an ideal introduction to cutting-edge research in neural information theory.

Author Biography:

Dr James Stone is an Honorary Reader in Vision and Computational Neuroscience at the University of Sheffield, England.

Release date Australia

May 26th, 2018

Author

James V Stone

Series

Tutorial Introductions

Pages

214

Edition

annotated edition

Audience

General (US: Trade)

Illustrations

150 illustrations

Dimensions

152x229x13

ISBN-13

9780993367960

Product ID

28152179

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