Computational Neuroscience: Neural Dynamics

NUMMER: 310001
KÜRZEL: CompNeND
MODULBEAUFTRAGTE:R: Prof. Dr. Gregor Schöner
DOZENT:IN: Prof. Dr. Gregor Schöner
FAKULTÄT: Institut für Neuroinformatik (RUB)
SPRACHE: Englisch
SWS: 3 SWS
CREDITS: 6 CP
WORKLOAD: 180 h
ANGEBOTEN IM: jedes Wintersemester

BESTANDTEILE UND VERANSTALTUNGSART

a) Vorlesung Computational Neuroscience:
Neural Dynamics (310001)
b) Übung (310011)

PRÜFUNGEN

FORM: schriftlich oder mündlich
ANMELDUNG:
DATUM: 0000-00-00
BEGINN: 00:00:00
DAUER:
RAUM:

LERNFORM

Vorlesung mit Übung

LERNZIELE

∙ Gain experience in interdisciplinarity bridging computer science and cognitive science.
∙ Learn the concepts and methods of nonlinear dynamical systems in a concrete applied
context.
∙ Improve familiarity with methods of quantitative natural science, including measurement,
graphing observables as a function of experimental control parameters and using
models to interpret data.
∙ Read scientific literature.

INHALT

This course provides an introduction into the theoretical cognitive and functional neurosciences
from a particular theoretical vantage point, the dynamical systems approach. This
approach emphasizes the evolution in time of behavioral and neural patterns as the basis of
their analysis and synthesis. Dynamic stability, a concept shared with the classical biological
cybernetics framework, is one cornerstone of the approach. Instabilities (or bifurcations) extend
this framework and provide a basis for understanding flexibility, task specific adjustment,
adaptation, and learning. The course includes tutorial modules that provide mathematical
foundations. Theoretical concepts are expounded in reference to a number of experimental
model systems which include the coordination of movement, postural stability, the perception
of motion, and elementary forms of embodied cognition. In the spirit of Braitenberg´s
"synthetic psychology", autonomous robots are used to illustrate some of the ideas.
Exercises are integrated into the lectures. They consist of elementary mathematical exercises,
the design of (thought) experiments and their analysis, and the design of simple artificial
systems, all on the basis of the theoretical framework exposed in the main lectures.
One exercise takes the form of an essay for which participants read a scientific paper and
answer questions in a longer illustrated text.

VORAUSSETZUNGEN CREDITS

Bestandene schriftliche oder mündliche Prüfung

LITERATUR

1. Martin Braun: Differential equations and their applications, Springer Verlag, New York,
1993
2. Gregor Schöner and Scott Kelso: Dynamic Pattern Generation in Behavioral and Neural
Systems. Science 239: 1513-1520 (1988)
3. Gregor Schöner: Dynamical Systems Approaches to Cognition. In: The Cambridge
Handbook of Computational Psychology,
4. Ron Sun, (ed.), Cambridge University Press (2008), pages 101-126