Description
Book SynopsisNeural 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 an
Table of Contents1. 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
