Principles of Neural Coding

Rodrigo Quian Quiroga, Stefano Panzeri

May 6, 2013 by CRC Press
Reference - 663 Pages - 34 Color & 179 B/W Illustrations
ISBN 9781439853306 - CAT# K12460

USD$169.95

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Features

  • Contains chapters written by world-class experts in the field of neural coding
  • Covers much of the latest developments in this area
  • Includes a large number of references in each chapter to encourage additional study
  • Presents the methodologies to study the activity of large neuronal populations

Summary

Understanding how populations of neurons encode information is the challenge faced by researchers in the field of neural coding. Focusing on the many mysteries and marvels of the mind has prompted a prominent team of experts in the field to put their heads together and fire up a book on the subject. Simply titled Principles of Neural Coding, this book covers the complexities of this discipline. It centers on some of the major developments in this area and presents a complete assessment of how neurons in the brain encode information. The book collaborators contribute various chapters that describe results in different systems (visual, auditory, somatosensory perception, etc.) and different species (monkeys, rats, humans, etc). Concentrating on the recording and analysis of the firing of single and multiple neurons, and the analysis and recording of other integrative measures of network activity and network states—such as local field potentials or current source densities—is the basis of the introductory chapters.

  • Provides a comprehensive and interdisciplinary approach
  • Describes topics of interest to a wide range of researchers

The book then moves forward with the description of the principles of neural coding for different functions and in different species and concludes with theoretical and modeling works describing how information processing functions are implemented. The text not only contains the most important experimental findings, but gives an overview of the main methodological aspects for studying neural coding. In addition, the book describes alternative approaches based on simulations with neural networks and in silico modeling in this highly interdisciplinary topic. It can serve as an important reference to students and professionals.