| NUMMER: | 310504 |
| KÜRZEL: | CompNeVM |
| MODULBEAUFTRAGTE:R: | Prof. Dr. Laurenz Wiskott |
| DOZENT:IN: | Prof. Dr. Laurenz Wiskott |
| FAKULTÄT: | Fakultät für Informatik |
| SPRACHE: | Englisch |
| SWS: | 4 SWS |
| CREDITS: | 5 CP |
| ANGEBOTEN IM: | jedes Sommersemester |
PRÜFUNGEN
| FORM: | digital schriftlich |
| TERMIN: | Siehe Prüfungsamt. |
LERNFORM
This course is given with the flipped/inverted classroom concept. First, the students work
through online material by themselves. In the lecture time slot we then discuss the material,
find connections to other topics, ask questions and try to answer them. In the tutorial time
slot the newly acquired knowledge is applied to analytical exercises and thereby deepened. I
encourage all students to work in teams during self-study time as well as in the tutorial.
LERNZIELE
After the successful completion of this course the students:∙ know basic neurobiological facts about the visual system and the hippocampus,
∙ know a number of related models and methods in computational neuroscience,
∙ understand the mathematics of these methods,
∙ can communicate about all this in English.
INHALT
This lecture covers basic neurobiology and models of selforganization in neural systems, inparticular addressing
Learning and self-organization
∙ Hebbian Learning
∙ Neural learning dynamics and constrained optimization
∙ Dynamic field theory
Vision
∙ Receptive fields
∙ Neural maps
∙ Hippocampus
∙ Navigation
∙ Episodic memory
∙ Hopfield Network
VORAUSSETZUNGEN CREDITS
Bestandene Modulabschlussprüfung
EMPFOHLENE VORKENNTNISSE
The mathematical level of the course is mixed but generallyhigh. 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, ...).