Biophysics of Computation: Information Processing in Single Neurons
by Christof Koch
Oxford University Press: New York, New York, 1999. 562 pages and 221 illustrations.
ISBN 0-19-510491-9
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 single-authored textbook focuses on the repertoire of computational operations available to individual nerve cells.
| 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 Appendix A: Passive Membrane Parameters Appendix B: A Minimprimer on Linear Systems Analysis Appendix C: Sparse Matrix Methods for Modeling Single Neurons |
Each chapter ends with a recapitulation of the material presented. The ultimate chapter presents a summary view of “neuron-style” computation and a list of strategic questions for research.
The Passions of Christof Koch 