- Häftad (Paperback)
- Antal sidor
- New e.
- OUP USA
- 216 line figures 5 halftones
- figs. 5halftones
- 235 x 165 x 27 mm
- Antal komponenter
- 49:B&W 6.14 x 9.21 in or 234 x 156 mm (Royal 8vo) Perfect Bound on White w/Gloss Lam
- 900 g
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Biophysics of Computation
Information processing in single neurons
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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.
Fler böcker av Christof Koch
Bloggat om Biophysics of Computation
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