Stone, J.V. (2018) In the light of evolution. In: Principles of Neural Information Theory: Computational Neuroscience and Metabolic Efficiency. Sebtel Press , Sheffield, England , pp. 1-8. ISBN 9780993367922
Abstract
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.
Metadata
Item Type: | Book Section |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2018 Sebtel Press. All rights reserved. No part of this book may be reproduced or transmitted in any form without written permission from the author. The author asserts his moral right to be identified as the author of this work in accordance with the Copyright, Designs and Patents Act 1988. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Science (Sheffield) > Department of Psychology (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 14 Mar 2018 10:54 |
Last Modified: | 20 Oct 2021 16:12 |
Status: | Published |
Publisher: | Sebtel Press |
Refereed: | Yes |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:128384 |