Biophysics of Computation
Information processing in single neurons
Series: Computational Neuroscience Series;
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Product details:
- Edition number New ed
- Publisher OUP USA
- Date of Publication 2 December 2004
- ISBN 9780195181999
- Binding Paperback
- No. of pages588 pages
- Size 233x177x27 mm
- Weight 871 g
- Language English
- Illustrations 5 halftones and numerous line figures 0
Categories
Long description:
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 be encoded in the voltage across the membrane, in the intracellular calcium concentration, or in the timing of individual spikes.
Key topics covered include the linear cable equation; cable theory as applied to passive dendritic trees and dendritic spines; chemical and electrical synapses and how to treat them from a computational point of view; nonlinear interactions of synaptic input in passive and active dendritic trees; the Hodgkin-Huxley model of action potential generation and propagation; phase space analysis; linking stochastic ionic channels to membrane-dependent currents; calcium- and potassium-currents and their role in information processing; the role of diffusion, buffering and binding of calcium, and other messenger systems in information processing and storage; short- and long-term models of synaptic plasticity; simplified models of single cells; stochastic aspects of neuronal firing; the nature of the neuronal code; and unconventional models of sub-cellular computation.
This book serves as an ideal text for advanced undergraduate and graduate courses in cellular biophysics, computational neuroscience, and neural networks, and will appeal to students and professionals in neuroscience, electrical and computer engineering, and physics.
Table of Contents:
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 coupling
Computing with neurons - a summary
