Introduction to Computational Neuroscience

Last update: April 12th, 2017

Lecturer and Tutors

Lectures and Tutorials: Prof. Dr.-Ing. Stefan Glasauer

Administration: Dipl.-Ing. Michael Balszun

General Information

  • Lecture each Tuesday from 09:45 to 11:15
  • Tutorial each Tuesday from 11:30 to 12:15
  • Room: 3999
  • Start date: 25.04.2017

Final exam

The final exam (written form) is scheduled for:

25.07.2017 at 10:00 (Room: 3999)

The details for the final exam will be announced in the lecture.

Closed book exam - a pocket calculator might be helpful.

Do not forget to register for the final exam via TUM-Online!


The lecture demonstrates the methods for analysis and modelling of neurons, neuronal systems, and behavior.


Spiking neurons, resting membrane potential, ion channels, action potential, Hodgkin-Huxley model, phase plane analysis, leaky integrate-and-fire model, synaptic transmission, synaptic plasticity.

Neural networks: perceptron, Hebb's learning rule, Hopfield networks. Analysis of spike trains (reverse correlation) and firing rate (regression and system identification).

Optimal estimation: minimum variance, maximum likelihood, maximum a-posteriori, mechanisms of sensory fusion. Modelling of sensorimotor systems.