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
  • Quickstart
  • Requirements
  • Disclaimer
  • Bug reports
• Installation
  • Using pip
  • Using conda
  • Start a Jupyter notebook
  • Links
• Exercises
  • 1. Leaky-integrate-and-fire model
  • 2. The Exponential Integrate-and-Fire model
  • 3. AdEx: the Adaptive Exponential Integrate-and-Fire model
  • 4. Dendrites and the (passive) cable equation
  • 5. Numerical integration of the HH model of the squid axon
  • 6. FitzHugh-Nagumo: Phase plane and bifurcation analysis
  • 7. Hopfield Network model of associative memory
  • 8. Type I and type II neuron models
  • 9. Oja’s hebbian learning rule
  • 10. Network of LIF neurons (Brunel)
  • 11. Spatial Working Memory (Compte et. al.)
  • 12. Perceptual Decision Making (Wong & Wang)
• Package index
  • Subpackages
  • Module contents
• License

Indices and tables

• Index
• Module Index
• Search Page