Neuronal Dynamics: Python Exercises¶
This documentation is automatically generated documentation from the corresponding code repository hosted at Github. The repository contains python exercises accompanying the book Neuronal Dynamics by Wulfram Gerstner, Werner M. Kistler, Richard Naud and Liam Paninski.
Contents¶
- Introduction
- Exercises
- 1. Setting up Python and Brian
- 2. Leaky-integrate-and-fire model
- 3. The Exponential Integrate-and-Fire model
- 4. AdEx: the Adaptive Exponential Integrate-and-Fire model
- 5. Dendrites and the (passive) cable equation
- 6. Numerical integration of the HH model of the squid axon
- 7. FitzHugh-Nagumo: Phase plane and bifurcation analysis
- 8. Hopfield Network model of associative memory
- 9. Type I and type II neuron models
- 10. Oja’s hebbian learning rule
- 11. Network of LIF neurons (Brunel)
- 12. Spatial Working Memory (Compte et. al.)
- 13. Perceptual Decision Making (Wong & Wang)
- Python exercise modules
- License