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  • © 2016

BioInformation Processing

A Primer on Computational Cognitive Science

Authors:

  • Uses the principles of computation in neural systems to develop approximations for neural computation
  • Proposes network models of computation based on models of emotion arising from musical and painting data
  • Uses graphical computational tools for exploring neural models
  • Includes supplementary material: sn.pub/extras

Part of the book series: Cognitive Science and Technology (CSAT)

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Table of contents (23 chapters)

  1. Front Matter

    Pages i-xxxv
  2. Introductory Matter

    1. Front Matter

      Pages 1-1
    2. BioInformation Processing

      • James K. Peterson
      Pages 3-15
  3. Diffusion Models

    1. Front Matter

      Pages 17-17
    2. The Diffusion Equation

      • James K. Peterson
      Pages 19-37
    3. Integral Transforms

      • James K. Peterson
      Pages 39-44
    4. The Time Dependent Cable Solution

      • James K. Peterson
      Pages 45-58
  4. Neural Systems

    1. Front Matter

      Pages 59-59
    2. Mammalian Neural Structure

      • James K. Peterson
      Pages 61-82
    3. Abstracting Principles of Computation

      • James K. Peterson
      Pages 83-105
    4. Second Messenger Diffusion Pathways

      • James K. Peterson
      Pages 107-116
    5. Second Messenger Models

      • James K. Peterson
      Pages 117-136
    6. The Abstract Neuron Model

      • James K. Peterson
      Pages 137-171
  5. Models of Emotion and Cognition

    1. Front Matter

      Pages 173-173
    2. Emotional Models

      • James K. Peterson
      Pages 175-182
    3. Generation of Music Data: J. Peterson and L. Dzuris

      • James K. Peterson
      Pages 183-204
    4. Modeling Compositional Design

      • James K. Peterson
      Pages 227-250
    5. Networks of Excitable Neurons

      • James K. Peterson
      Pages 251-276
    6. Training the Model

      • James K. Peterson
      Pages 277-284

About this book

This book shows how mathematics, computer science and science can be usefully and seamlessly intertwined. It begins with a general model of cognitive processes in a network of computational nodes, such as neurons, using a variety of tools from mathematics, computational science and neurobiology. It then moves on to solve the diffusion model from a low-level random walk point of view. It also demonstrates how this idea can be used in a new approach to solving the cable equation, in order to better understand the neural computation approximations. It introduces specialized data for emotional content, which allows a brain model to be built using MatLab tools, and also highlights a simple model of cognitive dysfunction.

Authors and Affiliations

  • Dept of Mathematical Sciences, Clemson University, Clemson, USA

    James K. Peterson

About the author

Dr. James Peterson is an Associate Professor in Mathematical Sciences and Biological Sciences at Clemson University, USA. His formal training is in mathematics but he has worked as an aerospace engineer and a software engineer also. He enjoys working on very hard problems that require multiple disciplines to make sense out of and he reads, studies and plays in cutting edge areas a lot as part of his interests.

Bibliographic Information

Buy it now

Buying options

eBook USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access