Dekorationsartikel gehören nicht zum Leistungsumfang.
Sprache:
Englisch
112,95 €*
Versandkostenfrei per Post / DHL
Lieferzeit 1-2 Wochen
Kategorien:
Beschreibung
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 textfor 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.
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 textfor 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. 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 textfor 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.
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 textfor 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.
Inhaltsverzeichnis
- 1: The membrane equation
- 2: Linear cable theory
- 3: Passive dendritic trees
- 4: Synaptic input
- 5: Synaptic interactions in a passive dendritic tree
- 6: The Hodgkin-Huxley model of action-potential generation
- 7: Phase space analysis of neuronal excitability
- 8: Ionic channels
- 9: Beyond Hodgkin and Huxley: calcium, and calcium-dependent potassium currents
- 10: Linearizing voltage-dependent currents
- 11: Diffusion, buffering, and binding
- 12: Dendritic spines
- 13: Synaptic plasticity
- 14: Simplified models of individual neurons
- 15: Stochastic models of single cells
- 16: Bursting cells
- 17: Input resistance, time constants, and spike initiation
- 18: Synaptic input to a passive tree
- 19: Voltage-dependent events in the dendritic tree
- 20: Unconventional coupling
- 21: Computing with neurons - a summary
Details
Erscheinungsjahr: | 1999 |
---|---|
Genre: | Biologie, Importe |
Rubrik: | Naturwissenschaften & Technik |
Medium: | Taschenbuch |
Inhalt: |
XXIII
562 S. |
ISBN-13: | 9780195181999 |
ISBN-10: | 0195181999 |
Sprache: | Englisch |
Einband: | Kartoniert / Broschiert |
Autor: | Koch, Christof |
Hersteller: | Oxford University Press |
Verantwortliche Person für die EU: | Oxford University Press España S.A., El Parque Empresarial San Fernando de Henares, Avendia de Castilla 2, E-28830 Madrid, product.safety@oup.com |
Maße: | 234 x 156 x 31 mm |
Von/Mit: | Christof Koch |
Erscheinungsdatum: | 01.01.1999 |
Gewicht: | 0,881 kg |
Inhaltsverzeichnis
- 1: The membrane equation
- 2: Linear cable theory
- 3: Passive dendritic trees
- 4: Synaptic input
- 5: Synaptic interactions in a passive dendritic tree
- 6: The Hodgkin-Huxley model of action-potential generation
- 7: Phase space analysis of neuronal excitability
- 8: Ionic channels
- 9: Beyond Hodgkin and Huxley: calcium, and calcium-dependent potassium currents
- 10: Linearizing voltage-dependent currents
- 11: Diffusion, buffering, and binding
- 12: Dendritic spines
- 13: Synaptic plasticity
- 14: Simplified models of individual neurons
- 15: Stochastic models of single cells
- 16: Bursting cells
- 17: Input resistance, time constants, and spike initiation
- 18: Synaptic input to a passive tree
- 19: Voltage-dependent events in the dendritic tree
- 20: Unconventional coupling
- 21: Computing with neurons - a summary
Details
Erscheinungsjahr: | 1999 |
---|---|
Genre: | Biologie, Importe |
Rubrik: | Naturwissenschaften & Technik |
Medium: | Taschenbuch |
Inhalt: |
XXIII
562 S. |
ISBN-13: | 9780195181999 |
ISBN-10: | 0195181999 |
Sprache: | Englisch |
Einband: | Kartoniert / Broschiert |
Autor: | Koch, Christof |
Hersteller: | Oxford University Press |
Verantwortliche Person für die EU: | Oxford University Press España S.A., El Parque Empresarial San Fernando de Henares, Avendia de Castilla 2, E-28830 Madrid, product.safety@oup.com |
Maße: | 234 x 156 x 31 mm |
Von/Mit: | Christof Koch |
Erscheinungsdatum: | 01.01.1999 |
Gewicht: | 0,881 kg |
Sicherheitshinweis