Introduction to Neuroinformatics

HS 2013

The material for the fall semester 2013 can be found here.

Introduction to Neuroinformatics

HS 2012


We have a mailing list for this lecture, that you are welcome to use to organize study groups or discuss the exercises. You can subscribe here.


19.09.12 Rodney Douglas Neuroinformatics
26.09.12 Rodney Douglas Membrane Potentials Exercise Solution
03.10.12 Rodney Douglas Passive (Cable) Membrane Properties Exercise Solution
10.10.12 Rodney Douglas Action Potentials Exercise Solution
17.10.12 Rodney Douglas Synapse 1 Exercise Solution
24.10.12 Michael Pfeiffer Plasticity/Learning Exercise Solution
31.10.12 Matthew Cook Perceptron Learning Algorithm Exercise Solution
07.11.12 Kevan Martin Nervous System Organization Exercise Solution
14.11.12 Kevan Martin Synapse 2 Exercise Solution
21.11.12 Michael Pfeiffer Rate/Event Coding Exercise Solution
28.11.12 Matthew Cook Hopfield Networks Exercise Solution
05.12.12 Matthew Cook Feed-Forward Networks Exercise Solution
12.12.12 Matthew Cook Interacting Neural Populations Exercise Solution
19.12.12 Giacomo Indiveri Neuromorphic VLSI


The exercises take place every Wednesday between 12:00 and 12:45, right after the lecture. We will discuss the exercise sheet distributed the week before. For this to work, we ask you to try to solve the exercise sheet on your own and come up with questions if something is unclear. You can submit your homework and we will correct it.

Tutorial on Electrical Circuits

We will organize a tutorial on electrical circuits to refresh your memory. The points covered will be:
  • Electrical Charges
  • Voltage
  • Current
  • Ohm's Law
  • Resistor Circuits
  • Kirchhoff's Laws
  • Capacitors
The tutorial will take place on Thursday, the 18th of October, 1pm in building Y21, floor D, room 86a.

Suggested literature:

  • Kandel, Schwartz & Jessell: Principles of Neural Science and Behavior
  • Johnston & Wu: Foundations of Cellular Neurophysiology
  • Dyan & Abbot: Theoretical Neuroscience
  • Koch: Biophysics of Computation
  • Nichols, Martin & Wallace: From Neuron to Brain
  • Gerstner & Kistler: Spiking Neuron models
  • Hertz, Krogh, Palmer: Introduction to the Theory of Neural Computation
  • Bishop: Pattern Recognition and Machine Learning


  • Register electronically in the ETH/Uni course catalogue.
  • To obtain the testat (the course attendance confirmation), you have to attend at least 11 of the 14 lectures. This is required to qualify for the exam.
  • Hand-in of exercises is voluntary, but welcome.
  • For the exam, the performance is assessed in a final 15 minute oral examination (English).
  • Both lecture and exercises are examination material.
  • The oral exam will take place during the examination session early next year. The dates will be fixed by the ETH/Uni and cannot be adapted individually.
Class notes of the previous year (HS 2011).

Models of Computation

FS 2013

The class hasn't started, yet.