Introduction to Computational Neuroscience Winter 2007
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Tentative course outline:

  1. Single compartment neurons – passive properties

  2. The behavior and modeling of ion channels

  3. The Hodgkin-Huxley action potential

  4. The diversity of voltage gated ion channels, and effects upon neuron spiking

  5. The cable equation

  6. Compartmental models of neurons; the NEURON simulation environment

  7. Models of synapses, including facilitation and depression

  8. Reduction of the Hodgkin-Huxley model to an integrate and fire neuron

  9. Implementing integrate and fire neuron models

  10. Coupled integrate and fire neuron models – mutual excitation and inhibition

  11. The autapse – a simple recurrent memory

  12. Firing rate models

  13. The Hopfield associative memory

  14. The cellular basis of synaptic plasticity

  15. Long-term potentiation

  16. Hebbian learning

  17. The BCM rule

  18. Information theory