Principles of Neural Information Theory - Computational Neuroscience and Metabolic Efficiency - Grand Format

Edition en anglais

Note moyenne 
The brain is the most complex computational machine known to science, even though its components (neurons) are slow and unreliable compared to a laptop... Lire la suite
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Résumé

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 determine the neuroanatomical microstructure of the eye and brain.

Caractéristiques

  • Date de parution
    15/05/2018
  • Editeur
    Sebtel Press
  • ISBN
    978-0-9933679-2-2
  • EAN
    9780993367922
  • Format
    Grand Format
  • Présentation
    Broché
  • Nb. de pages
    200 pages
  • Poids
    0.318 Kg
  • Dimensions
    15,2 cm × 22,9 cm × 1,1 cm

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L'éditeur en parle

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.

À propos de l'auteur

Biographie de James V Stone

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

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