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Principles of Neural Information Theory

- Computational Neuroscience and Metabolic Efficiency

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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.

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  • Sprog:
  • Engelsk
  • ISBN:
  • 9780993367960
  • Indbinding:
  • Hardback
  • Sideantal:
  • 214
  • Udgivet:
  • 26. maj 2018
  • Udgave:
  • Størrelse:
  • 236x159x20 mm.
  • Vægt:
  • 474 g.
  • 8-11 hverdage.
  • 27. november 2024

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Beskrivelse af Principles of Neural Information Theory

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.

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