Computational Neuroscience: A Comprehensive Approach

Jianfeng Feng

October 20, 2003 by Chapman and Hall/CRC
Reference - 656 Pages - 171 B/W Illustrations
ISBN 9781584883623 - CAT# C3626
Series: Chapman & Hall/CRC Mathematical and Computational Biology

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  • Balances the theoretical and experimental aspects of the field with chapters written by biologists as well as mathematicians
  • Covers all levels of modeling, from atomic-level modeling of single channels to modeling visual attention
  • Addresses cutting-edge topics such as calcium activity and learning rules
  • Includes a chapter on modeling motor control that helps close the gap between sensory input and motor output
  • Proposes a model for neural microcircuits that challenges traditional approaches to neural coding and suggests new ways of modeling cognitive processing
  • Summary

    How does the brain work? After a century of research, we still lack a coherent view of how neurons process signals and control our activities. But as the field of computational neuroscience continues to evolve, we find that it provides a theoretical foundation and a set of technological approaches that can significantly enhance our understanding.

    Computational Neuroscience: A Comprehensive Approach provides a unified treatment of the mathematical theory of the nervous system and presents concrete examples demonstrating how computational techniques can illuminate difficult neuroscience problems. In chapters contributed by top researchers, the book introduces the basic mathematical concepts, then examines modeling at all levels, from single-channel and single neuron modeling to neuronal networks and system-level modeling. The emphasis is on models with close ties to experimental observations and data, and the authors review application of the models to systems such as olfactory bulbs, fly vision, and sensorymotor systems.

    Understanding the nature and limits of the strategies neural systems employ to process and transmit sensory information stands among the most exciting and difficult challenges faced by modern science. This book clearly shows how computational neuroscience has and will continue to help meet that challenge.