Principles of Neural Information Theory: Computational Neuroscience and Metabolic Efficiency Contributor(s): Stone, James V. (Author) |
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ISBN: 0993367925 ISBN-13: 9780993367922 Publisher: Tutorial Introductions OUR PRICE: $47.45 Product Type: Paperback - Other Formats Published: May 2018 |
Additional Information |
BISAC Categories: - Computers | Information Theory - Science | Life Sciences - Neuroscience - Medical | Neuroscience |
Series: Tutorial Introductions |
Physical Information: 0.45" H x 6" W x 9" (0.64 lbs) 214 pages |
Descriptions, Reviews, Etc. |
Publisher 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. |
Contributor Bio(s): Stone, James V.: - Dr James Stone is an Honorary Reader in Vision and Computational Neuroscience at the University of Sheffield, England. |