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. Dr James Stone is an Honorary Reader in Vision and Computational Neuroscience at the University of Sheffield, England.
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EAN: 9780993367960
UPC: 9780993367960
ISBN: 9780993367960
MPN: N/A
Book Title: Principles of Neural Information Theory: Computati
Item Length: 22.9 cm
Subject Area: Information Science
Item Height: 229 mm
Item Width: 152 mm
Author: James V Stone
Publication Name: Principles of Neural Information Theory: Computational Neuroscience and Metabolic Efficiency
Format: Hardcover
Language: English
Publisher: Tutorial Introductions
Subject: Medicine, Technology, Biology
Publication Year: 2018
Type: Textbook
Item Weight: 454 g
Number of Pages: 214 Pages
