Biophysics of computation : information processing in single neurons /

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Bibliographic Details
Author / Creator:Koch, Christof, 1956-
Imprint:New York : Oxford University Press, 1999.
Description:1 online resource (xxiii, 562 pages) : illustrations.
Language:English
Series:Computational neuroscience
Computational neuroscience.
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/11125329
Hidden Bibliographic Details
ISBN:9780199760558
0199760551
0195104919
9780195104912
0195181999
9780195181999
1280595094
9781280595097
9786613624925
6613624926
Notes:Includes bibliographical references (pages 503-552) and index.
English.
Print version record.
Summary:Neural network research often builds on the fiction that neurons are simple linear threshold units, completely neglecting the highly dynamic and complex nature of synapses, dendrites, and voltage-dependent ionic currents. Biophysics of Computation: Information Processing in Single Neurons challenges this notion, using richly detailed experimental and theoretical findings from cellular biophysics to explain the repertoire of computational functions available to single neurons. The author shows how individual nerve cells can multiply, integrate, or delay synaptic inputs and how information can b.
Other form:Print version: Koch, Christof, 1956- Biophysics of computation. New York : Oxford University Press, 1999 0195104919

MARC

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245 1 0 |a Biophysics of computation :  |b information processing in single neurons /  |c Christof Koch. 
260 |a New York :  |b Oxford University Press,  |c 1999. 
300 |a 1 online resource (xxiii, 562 pages) :  |b illustrations. 
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490 1 |a Computational neuroscience 
504 |a Includes bibliographical references (pages 503-552) and index. 
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520 |a Neural network research often builds on the fiction that neurons are simple linear threshold units, completely neglecting the highly dynamic and complex nature of synapses, dendrites, and voltage-dependent ionic currents. Biophysics of Computation: Information Processing in Single Neurons challenges this notion, using richly detailed experimental and theoretical findings from cellular biophysics to explain the repertoire of computational functions available to single neurons. The author shows how individual nerve cells can multiply, integrate, or delay synaptic inputs and how information can b. 
505 0 |a The membrane equation --Linear cable theory -- Passive dendritic trees -- Synaptic input -- Synaptic interactions in a passive dendritic tree -- The Hodgkin-Huxley model of action potential generation -- Phase space analysis of neuronal excitability -- Ionic channels -- Beyond Hodgkin and Huxley: calcium and calcium-dependent potassium currents -- Linearizing voltage-dependent currents -- Diffusion, buffering and binding -- Dendritic spines -- Synaptic plasticity -- Simplified models of individual neurons -- Stochastic models of single cells -- Bursting cells -- Input resistance, time constants, and spike initiation -- Synaptic input to a passive tree -- Voltage-dependent events in the dendritic tree -- Unconventional computing -- Computing with neurons: a summary -- Appendix A: Passive membrane parameters -- Appendix B: A miniprimer on linear systems analysis -- Appendix C: Sparce matrix methods for modeling single neurons. 
546 |a English. 
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650 0 |a Action potentials (Electrophysiology)  |0 http://id.loc.gov/authorities/subjects/sh85000721 
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