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Encyclopedia of Computational NeuroscienceFrom Springer
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The annual Computational Neuroscience Meeting (CNS) began in 1990 as a small workshop called Analysis and Modeling of Neural Systems. The goal of the workshop was to explore the boundary between neuroscience and computation. Riding on the success of several seminal papers, physicists had made "Neural Networks" fashionable, and soon the quantitative methods used in these abstract model networks started permeating the methods and ideas of experimental neuroscientists. Although experimental neurophysiological approaches provided many advances, it became increasingly evident that mathematical and computational techniques would be required to achieve a comprehensive and quantitative understanding of neural system function. “Computational Neuroscience” emerged to complement experimental neurophysiology.
The Encyclopedia of Computational Neuroscience, published in conjunction with the Organization for Computational Neuroscience, will be an extensive reference work consultable by both researchers and graduate level students. It will be a dynamic, living reference, updatable and containing linkouts and multimedia content whenever relevant.
- Sales Rank: #9930591 in Books
- Published on: 2015-02-24
- Original language: English
- Number of items: 4
- Dimensions: 10.30" h x 7.50" w x 7.10" l,
- Binding: Hardcover
- 3180 pages
Review
“This is the best single stand alone reference concerning the mathematical and statistical modeling of neural systems and neurobiology. … The references, diagrams, in color photos, and formulae are complete. … The book should help all students and senior investigators alike. I endorse the science of this outstanding reference.” (Joseph J. Grenier, Amazon.com, June, 2015)
About the Author
Dr. Ranu Jung is the Wallace H. Coulter Eminent Scholars Chair of Biomedical Engineering at Florida International University, where her research concerns neural engineering and computational neuroscience. Dr. Dieter Jaeger is Professor in the Department of Biology at Emory University in Atlanta, Georgia. His research examines how neurons in the basal ganglia and in the cerebellum process their inputs, in order to understand the motor function of basal ganglia and cerebellar networks.
Most helpful customer reviews
1 of 1 people found the following review helpful.
Computer and Math Modeling of the PNS and CNS
By Joseph J Grenier
Encyclopedia of Computational Neurosciences
Springer New York Berlin Heidelberg
Reviewer: Joseph J Grenier MD PhD
This is the best single stand alone reference concerning the mathematical and statistical modeling of neural systems and neurobiology. The book has a prestigious authorship in an A-Z format. The references, diagrams, in color photos, and formulae are complete. Nuclei, dendrites, single neuron and populational neuronal units are carefully discussed. The illustrations are one of the best aspects of this 3500 page tome.
Auditory, visual, somatosensory, motor, and, association systems are a good part of the discussion here. The balance of vestibular and proprioceptive models are discussed and their relationship to the afferent and efferent populations included.
Biophysics of single neurons is described with relationship to ion channel mechanics also. The Nernst-Planck and Hodgkin Huxley models are treated with respect. Bayesian, thermodynamic, and physical theories are applied in a multidimensional manner. I think this is a tribute to the excellent editorship here. Models of the basal ganglia, hippocampus, primary visual cortex, and thalamus are discussed with the Watson & Crick theories covered. David Marr’s vision theories are also discussed. Circuit analysis is complete here. Working and practical models of memory and hearing devoted to their own specific chapters.
The physics of cerebrovascular blood flow and metabolism is a devoted to separate sections of the book’s chapters. Imaging techniques and wiring diagram explanations are an excellent presentation throughout the books.
The book should help all students and senior investigators alike. I endorse the science of this outstanding reference.
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