SS 2014 (310504/310514)

Computational Neuroscience: Vision and Memory

Lecture and Tutorial
Prof. Dr. Laurenz Wiskott

Lecture (2 SWS, 2 credit points): Tuesdays 12:15-13:45 o'clock in the large INI seminar room NB 3/57. First time 08.04.2014.
Tutorial (2 SWS, 4 credit points): Tuesdays 10:30-12:00 o'clock in the large INI seminar room NB 3/57. First time 15.04.2014.

Language: This course is given in English.

Goal: (i) The students should get to know a number of models and methods in computational neuroscience. (ii) They should understand the mathematics of these methods.

Content: This lecture covers models of selforganization in neural systems, in particular addressing vision (receptive fields, neural maps, invariances) and associative memory (Hopfield network).

Requirements: The mathematical level of the course is mixed but generally high. The tutorial is almost entirely mathematical. Mathematics required include calculus (functions, derivatives, integrals, differential equations, ...), linear algebra (vectors, matrices, inner product, orthogonal vectors, basis systems, ...), and a bit of probability theory (probabilities, probability densities, Bayes' theorem, ...).

Exam: This course will be concluded with an oral exam.

Lecture and Tutorial

#	date	Topic
1	2014-04-09	Introduction
2	2014-04-15	Hebbian Learning
3	2014-04-22	Optimization - Analytical Methods
4	2014-04-29	From Neural Dynamics to Constrained Optimization 1
5	2014-05-06	From Neural Dynamics to Constrained Optimization 2
6	2014-05-13	Visual Receptive Fields 1
7	2014-05-20	Visual Receptive Fields 2
8	2014-05-26	Neural Fields
9	2014-06-03	Neural Map Formation
10	2014-06-17	Hopfield Networks 1
11	2014-06-24	Hopfield Networks 2
12	2014-07-01	Hippocampus SFA Theory of Grid Cell Formation 1
13	2014-07-08	SFA Theory of Grid Cell Formation 2
14	2014-07-15	SFA Theory of Grid Cell Formation 3 Summary and Review of the Course

Laurenz Wiskott, http://www.ini.rub.de/PEOPLE/wiskott/