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Information theory and the brain / edited by Roland Baddeley, Peter Hancock, Peter Földiák.

Contributor(s): Material type: TextTextPublisher: Cambridge : Cambridge University Press, 2000Description: 1 online resource (xiii, 344 pages) : digital, PDF file(s)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9780511665516 (ebook)
Other title:
  • Information Theory & the Brain
Subject(s): Additional physical formats: Print version: : No titleDDC classification:
  • 612.8/2 21
LOC classification:
  • QP363.3 .I54 2000
Online resources:
Contents:
1. Introductory Information Theory and the Brain / Roland Baddeley -- pt. 1. Biological Networks. 2. Problems and Solutions in Early Visual Processing / Brian G. Burton. 3. Coding Efficiency and the Metabolic Cost of Sensory and Neural Information / Simon B. Laughlin, John C. Anderson and David O'Carroll / [and others]. 4. Coding Third-Order Image Structure / Mitchell Thompson -- pt. 2. Information Theory and Artificial Networks. 5. Experiments with Low-Entropy Neural Networks / George Harpur and Richard Prager. 6. The Emergence of Dominance Stripes and Orientation Maps in a Network of Firing Neurons / Stephen P. Luttrell. 7. Dynamic Changes in Receptive Fields Induced by Cortical Reorganization / German Mato and Nestor Parga.
Summary: Information Theory and the Brain deals with an expanding area of neuroscience which provides a framework for understanding neuronal processing. It is derived from a conference held in Newquay, UK, where a select group of scientists from around the world met to discuss the topic. This book begins with an introduction to the basic concepts of information theory and then illustrates these concepts with examples from research over 40 years. Throughout the book, the contributors highlight current research from four different areas: 1) biological networks, 2) information theory and artificial networks, 3) information theory and psychology, 4) formal analysis. Each section includes an introduction and glossary covering basic concepts. This book will appeal to graduate students and researchers in neuroscience as well as computer scientists and cognitive scientists. Neuroscientists interested in any aspect of neural networks or information processing will find this a very useful addition to the current literature in this rapidly growing field.
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Title from publisher's bibliographic system (viewed on 05 Oct 2015).

1. Introductory Information Theory and the Brain / Roland Baddeley -- pt. 1. Biological Networks. 2. Problems and Solutions in Early Visual Processing / Brian G. Burton. 3. Coding Efficiency and the Metabolic Cost of Sensory and Neural Information / Simon B. Laughlin, John C. Anderson and David O'Carroll / [and others]. 4. Coding Third-Order Image Structure / Mitchell Thompson -- pt. 2. Information Theory and Artificial Networks. 5. Experiments with Low-Entropy Neural Networks / George Harpur and Richard Prager. 6. The Emergence of Dominance Stripes and Orientation Maps in a Network of Firing Neurons / Stephen P. Luttrell. 7. Dynamic Changes in Receptive Fields Induced by Cortical Reorganization / German Mato and Nestor Parga.

Information Theory and the Brain deals with an expanding area of neuroscience which provides a framework for understanding neuronal processing. It is derived from a conference held in Newquay, UK, where a select group of scientists from around the world met to discuss the topic. This book begins with an introduction to the basic concepts of information theory and then illustrates these concepts with examples from research over 40 years. Throughout the book, the contributors highlight current research from four different areas: 1) biological networks, 2) information theory and artificial networks, 3) information theory and psychology, 4) formal analysis. Each section includes an introduction and glossary covering basic concepts. This book will appeal to graduate students and researchers in neuroscience as well as computer scientists and cognitive scientists. Neuroscientists interested in any aspect of neural networks or information processing will find this a very useful addition to the current literature in this rapidly growing field.

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