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Computational Models for Neuroscience: Human Cortical Information Processing
 
 
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Computational Models for Neuroscience: Human Cortical Information Processing [Hardcover]

Robert Hecht-Nielsen (Editor), Thomas McKenna (Editor)
5.0 out of 5 stars  See all reviews (1 customer review)

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Book Description

1852335939 978-1852335939 January 31, 2003 1st Edition.
Understanding how the human brain represents, stores, and processes information is one of the greatest unsolved mysteries of science today. The cerebral cortex is the seat of most of the mental capabilities that distinguish humans from other animals and, once understood, it will almost certainly lead to a better knowledge of other brain nuclei. Although neuroscience research has been underway for 150 years, very little progress has been made. What is needed is a key concept that will trigger a full understanding of existing information, and will also help to identify future directions for research. This book aims to help identify this key concept. Including contributions from leading experts in the field, it provides an overview of different conceptual frameworks that indicate how some pieces of the neuroscience puzzle fit together. It offers a representative selection of current ideas, concepts, analyses, calculations and computer experiments, and also looks at important advances such as the application of new modeling methodologies. Computational Models for Neuroscience will be essential reading for anyone who needs to keep up-to-date with the latest ideas in computational neuroscience, machine intelligence, and intelligent systems. It will also be useful background reading for advanced undergraduates and postgraduates taking courses in neuroscience and psychology.

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Product Details

  • Hardcover: 320 pages
  • Publisher: Springer; 1st Edition. edition (January 31, 2003)
  • Language: English
  • ISBN-10: 1852335939
  • ISBN-13: 978-1852335939
  • Product Dimensions: 9.2 x 6.3 x 0.9 inches
  • Shipping Weight: 1.4 pounds (View shipping rates and policies)
  • Average Customer Review: 5.0 out of 5 stars  See all reviews (1 customer review)
  • Amazon Best Sellers Rank: #1,769,639 in Books (See Top 100 in Books)

 

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9 of 15 people found the following review helpful:
5.0 out of 5 stars Cerebral Cortex Mystery Solved!, March 6, 2003
By A Customer
This review is from: Computational Models for Neuroscience: Human Cortical Information Processing (Hardcover)
Chapter 4 of this book is the pot of gold: A concrete, detailed description of how the cerebral cortex works. Thinking relies upon an operation which could be called confabulation (in the chapter it is called concensus building). THIS IS NOT REASONING (at least in any classical sense). Yet, because the simple kind of knowledge used (antecedent support probabilities) is exhaustive, concensus building yields excellent conclusions. This cortical theory also shows why AI has failed: reasoning is too difficult and requires too much knowledge of an expensive type. Cortex gets by with a much simpler type of knowledge (which only concerns pairs of object and action attributes, not n-tuples) which, while it is needed in huge quantities, is easy to obtain. An implication of this corticl theory is that we can now proceed to develop successful AI by adopting this cortical design. The theory is illustrated by means of computer thinking experiments that yield compelling results (and which readers can replicate).
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Inside This Book (learn more)
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
human brain mapping, cognitive modeling, feature attractor network, test dendrites, nonlinear synaptic transmission, state synaptic response, other principal dendrites, neurointeractive process, token neurons, transponder neurons, phrase analyzers, elementary environmental conditions, transition neurone, nonlinear synapses, standardized tokens, dynamical mechanics, synaptic transfer function, facilitating synapses, adjacent minicolumns, depressing synapses, synaptic parameters, synaptic dynamics, viable subset, associationist mechanism, feature attractors
Key Phrases - Capitalized Phrases (CAPs): (learn more)
New York, Oxford University Press, Biological Cybernetics, Neural Computation, Psychological Review, Plenum Press, Van Essen, Academic Press, Cambridge University Press, World Scientific, Brain Res, Brain Sci, Behavioral Neuroscience, Lecture Notes, References Abeles, Artificial Intelligence, San Diego, Annu Rev Neurosci, The Organization of Behavior, Post Pre, University of London, Large-Scale Neuronal Theories of the Brain, Technical Report, Proc Natl Acad Sci, Cognitive Sciences
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Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
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