Biophysics of Computation: Information Processing in Single Neurons (Computatio,

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Item specifics

Condition
Like New: A book in excellent condition. Cover is shiny and undamaged, and the dust jacket is ...
Book Title
Biophysics of Computation: Information Processing in Single Neur,
Narrative Type
Electrical & Electronics
Genre
N/A
Topic
Electrical & Electronics
Intended Audience
N/A
ISBN
9780195104912
Category

About this product

Product Identifiers

Publisher
Oxford University Press, Incorporated
ISBN-10
0195104919
ISBN-13
9780195104912
eBay Product ID (ePID)
834764

Product Key Features

Number of Pages
592 Pages
Publication Name
Biophysics of Computation : Information Processing in Single Neurons
Language
English
Subject
Neuroscience, Life Sciences / Neuroscience, General
Publication Year
1998
Type
Textbook
Subject Area
Science, Medical
Author
Christof Koch
Series
Computational Neuroscience Ser.
Format
Hardcover

Dimensions

Item Height
1.2 in
Item Weight
35.3 Oz
Item Length
6.7 in
Item Width
9.3 in

Additional Product Features

Intended Audience
College Audience
LCCN
97-051390
Dewey Edition
22
Series Volume Number
No. 1
Illustrated
Yes
Dewey Decimal
573.8534
Table Of Content
1. The Membrane Equation2. Linear Cable Theory3. Passive Dendritic Trees4. Synaptic Input5. Synaptic Interactions in a Passive Dendritic Tree6. The Hodgkin-Huxley Model of Action-Potential Generation7. Phase Space Analysis of Neuronal Excitability8. Ionic Channels9. Beyond Hodgkin and Huxley: Calcium, and Calcium-Dependent Potassium Currents10. Linearizing Voltage-Dependent Currents11. Diffusion, Buffering, and Binding12. Dendritic Spines13. Synaptic Plasticity14. Simplified Models of Individual Neurons15. Stochastic Models of Single Cells16. Bursting Cells17. Input Resistance, Time Constants, and Spike Initiation18. Synaptic Input to a Passive Tree19. Voltage-Dependent Events in the Dendritic Tree20. Unconventional Coupling21. Computing with Neurons -- A Summary
Synopsis
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. Biophysics of Computation: Information Processing in Single Neurons 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., 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. This textbook rectifies the situation by focusing on the repertoire of computational operations available to individual nerve cells. The author suggests how information can be encoded in the voltage across the membrane, in the intracellular calcium concentration, and in the timing of individual spikes, or nerve impulses. Key topics include the linear cable operation, passive dendritic trees and dendritic spines, chemical and electrical synapses and how to treat them from a computational point of view, nonlinear interactions 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 of 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 neuronal code and unconventional models of computation involving molecules, puffs of gas, or neuropeptides. Each chapter ends with a recapitulation of the material presented, and the ultimate chapter presents a summary view of 'neuron-style' computation, ending with a list of strategic questions for research., Addressing questions at the interface of biophysics and computational theory, this book explores how information is encoded in single neurons. The book is designed as an advanced text for members of the neuroscience, electrical and computer engineering, and physics communities. It focusses centrally on the character of computation carried out by individual neurons using synapses, dendrites, and voltage-dependent ionic currents.
LC Classification Number
QP357.5.K63 1999

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