Lecture Series, 14./15./17. September 2009

Computational Neuroscience

Richard Kempter, Jakob Heinzle, Susanne Schreiber, Martin Nawrot


Prof. Dr. Richard Kempter
Dr. Jakob Heinzle
Dr. Susanne Schreiber
Prof. Dr. Martin Nawrot

Dates: 14/15/17 September 2009

Morning lectures: 9:15-10:45h and 11:00-12:30h
Afternoon lectures: 13:30-15:00 and 15:15-16:45h

A break of up to 15 minutes might be added to each lecture. A slightly different schedule can be agreed upon on a day-by-day basis.

Lecture Hall of the Bernstein Center for Computational Neurosciences Berlin, Haus 6, Philippstr. 13.

The course provides an introduction into selected basic concepts of Computational Neuroscience. The participating students will get to know examples of computational models on several levels of abstraction, from single cells to large networks, including some aspects of learning and neural coding. The main goal is to teach specific fundamental computational principles that are often encountered in cortical processing.

Some basic math on the level of a high-school diploma / Abitur, i.e. elementary functions such as cosine, sine, and the exponential function is necessary. You should be able to calculate derivatives, and you should know what an integral is. You should be able to solve simple equations with one unknown. Please consult your old math school books or some elementary algebra books. Familiarity with some basic neuroscience concepts is also required. For instance, we assume that you know what a neuron is.

Tentative Schedule and Course Material:

You might want to check this web page occasionally for updates.

Date Time Topic Course MaterialLecturer
Mathematics Exercises, Solutions Jakob Heinzle
14.09. Morning 1 Introduction to Computational Neuroscience Introduction Richard Kempter
Morning 2 Models of single neurons (membranes, integrate-and-fire) Membranes and IaF Jakob Heinzle
Afternoon 1 Models of single neurons (type I and II, McCulloch-Pitts) Jakob Heinzle
Afternoon 2 The neural code Neural Code Richard Kempter
15.09. Morning 1 Models of single neurons (Hodgkin-Huxley) Hodgkin-Huxley Susanne Schreiber
Morning 2 Models of single neurons (resonance and oscillations) Susanne Schreiber
Afternoon 1 Models of neural networks (feed-forward) Networks Richard Kempter
Afternoon 2 Models of neural networks (recurrent) Richard Kempter
16.09. (no lectures)
17.09. Morning 1 Models and analysis of spike trains Martin Nawrot
Morning 2 Models and analysis of spike trains Martin Nawrot
Afternoon 1 Models of plasticity Plasticity Richard Kempter
Afternoon 2 Models of plasticity Richard Kempter

Background material:

P. Dayan and L.F. Abbott (2001) Theoretical Neuroscience. MIT Press, Cambridge, Massachusetts.

Mark F. Bear, Barry Connors, and Michael Paradiso (2001) Neuroscience: Exploring the Brain. Lippincott Williams and Wilkins, Baltimore, MD.

Thomas P. Trappenberg (2002) Fundamentals of Computational Neuroscience. Oxford University Press, Oxford, UK.

Churchland, P. & Sejnowski, T. (1994). The Computational Brain. MIT Press, Cambridge, MA.
Last update: Sep-17-2009

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