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- About this book
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Computational neuroscience is best defined by its focus on understanding the nervous systems as a computational device rather than by a particular experimental technique. Accordinlgy, while the majority of the papers in this book describe analysis and modeling efforts, other papers describe the results of new biological experiments explicitly placed in the context of computational issues. The distribution of subjects in Computation and Neural Systems reflects the current state of the field. In addition to the scientific results presented here, numerous papers also describe the ongoing technical developments that are critical for the continued growth of computational neuroscience.
Computation and Neural Systems includes papers presented at the First Annual Computation and Neural Systems meeting held in San Francisco, CA, July 26--29, 1992.
- Table of contents (80 chapters)
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Self-Organising Ion Channel Densities: The Rationale for ‘Anti-Hebb’
Pages 3-7
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A Modified Hodgkin-Huxley Spiking Model with Continuous Spiking Output
Pages 9-17
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The Neurone as a Nonlinear System: A Single Compartment Study
Pages 19-23
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Unsupervised Hebbian Learning and the Shape of the Neuron Activation Function
Pages 25-29
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A Method for Estimating the Neural Input to a Neuron using the Ionic Current Model
Pages 31-35
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Table of contents (80 chapters)
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Bibliographic Information
- Bibliographic Information
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- Book Title
- Computation and Neural Systems
- Editors
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- Frank Eeckman
- James M. Bower
- Copyright
- 1993
- Publisher
- Springer US
- Copyright Holder
- Springer Science+Business Media New York
- eBook ISBN
- 978-1-4615-3254-5
- DOI
- 10.1007/978-1-4615-3254-5
- Hardcover ISBN
- 978-0-7923-9349-8
- Softcover ISBN
- 978-1-4613-6431-3
- Edition Number
- 1
- Number of Pages
- XIII, 539
- Topics
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