Principles of Neural Information Theory - Computational Neuroscience and Metabolic Efficiency

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.

About the author

Visiting Professor, University of Sheffield, UK.

Product details

• Authors: James V Stone, James V. Stone
• Publisher: Tutorial Introductions
• Languages: English
• Product format: Paperback / Softback
• Released: 15.05.2018
• EAN: 9780993367922
• ISBN: 978-0-9933679-2-2
• No. of pages: 214
• Dimensions: 152 mm x 229 mm x 12 mm
• Weight: 318 g
• Series: Tutorial Introductions
• Subjects: Guides; Natural sciences, medicine, IT, technology > IT, data processing > IT; Informationstheorie, entropy; Shannon