Introduction to Computational Neuroscience
Last update: April 12th, 2017
Lecturer and Tutors
Lectures and Tutorials: Prof. Dr.-Ing. Stefan Glasauer
- 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
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.