You'll find here a list of additional material to help you understand the course and go deeper in the concepts.

This is a selection and by no means exhaustive. You shouldn't expect the exam to be constrained by this.

(most of this is adapted from previous years)

General reading



The Kandel is a great source of information about many aspects of neuroscience (see above). Some additional reading:

Neural Coding

  • An amazing review about spike-triggered average and related techniques can be found in the following paper:
    Schwartz O, Pillow JW, Rust NC, Simoncelli EP. (2006). Spike-triggered neural characterization. Journal of Vision, 6(4):484-507
  • Liam Paninski’s notes on the statistical analysis of neural data are also particularly relevant for this part of the course

Here are some additional papers selected by R. Williamson:


  • Dayan and Abbott cover Biophysics thoroughly. The notation is different from the lecture though.
  • Dynamical Systems in Neuroscience is also a good source of information, specifically for the Phase plan analysis and an overview of many neuron models.
  • Spike Neuron Models by W. Gerstner and W. Kistler covers all those models as well. The mathematical derivations are well explained and it covers population dynamics too. Scholarpedia
  • Here are Peter Latham's handwritten notes. He used them to teach the course, but they are a few years old right now, so the material does not correspond well to the lectures anymore. But they could be used as a supplement for the course. They are probably impossible to understand without going to the course and may contain mistakes.
    • Lecture 1 - passive neurons and Hodgkin Huxley
    • Lecture 2 - simplified model, suitable for nullcline analysis
    • Lecture 3 - a little philosophy, and nullcline analysis
    • Lecture 4 - passive dendrites and axons
    • Lecture 5 - synapses
    • Lecture 6 - also synapses (but an older set of notes)
    • Lecture 7 - philosophy and phase plane analysis
    • Lecture 8 - grand summary of biophysics