Computational Neuroscience: Neural Dynamics

This course provides an introduction into the theoretical behavioral 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 will include tutorial modules the provide mathematical foundations. Theoretical concepts will be exposed in reference to a number of experimental model systems which will include the coordination of movement, postural and configurational stability, the perception of motion, and elementary forms of spatial cognition. In the spirit of Braitenberg´s "synthetic psychology", autonomous robots will be used to illustrate some of the ideas.

Exercises will be integrated into the lectures. They will 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.



Course type
Winter Term 2014/2015


Takes place every week on Thursday from 14:15 to 16:00 in room NB 3/57.
First appointment is on 09.10.2014
Takes place every week on Thursday from 16:15 to 17:00 in room NB 3/57.
First appointment is on 16.10.2014
Takes place on 25.02.2015 from 10:00 to 12:00 in room NB 3/57.


Exercises are corrected and held by Oliver Lomp. Details on grading are available in the course rules below.


Details on the requirements for the exercise are given in the course rules below. Please register for the exam with our secretaries.


A good book to look up some mathematics related to dynamical systems: Edward R. Scheinerman's Invitation to Dynamical Systems (available as a free download). Note that only some parts of that book are relevant for the lecture.

If you are interested, you can also find more literature on the homepage of our robotics school. However, this isn't necessarily relevant to the course.


Exercises Exercise 05: Population Code (due November 27)
Exercises Exercise 06: DFT Reading (due December 12)
Lecture slides Lecture 05: Neural Dynamics Tutorial 2 (Gregor Schöner, October 30/November 6)
Exercises Exercise 04: Neueral Dynamics Readings (due November 20)
Exercises Exercise 05 Literature
Lecture slides Additional Material: This paper provides a survey over the main themes of the lecture course.
Lecture slides Lecture 07: DFT Tutorial
Lecture slides Lecture 04: Neural Dynamics Tutorial (Gregor Schöner, Octorber 30)
Exercises Exercise 04 Literature
Lecture slides Lecture 06: DFT Tutorial
Exercises Exercise 03: Neural Dynamics (due November 6)
Lecture slides Lecture 03: Dynamical Systems Tutorial (Gregor Schöner, October 23)
Lecture slides Course Rules
Lecture slides Lecture 00: Organization (Gregor Schöner, October 9, 2014)
Lecture slides Lecture 01: Introduction (Gregor Schöner, October 9, 2014)
Lecture slides Lecture 02: Braitenberg (Gregor Schöner, October 9, 2014)
Exercises Exercise 06 Literature
Exercises Exercise 01: Braitenberg (due October 23)
Exercises Exercise 02: Tangent Bifurcation (due October 30)

The Institut für Neuroinformatik (INI) is a central research unit of the Ruhr-Universität Bochum. We aim to understand the fundamental principles through which organisms generate behavior and cognition while linked to their environments through sensory systems and while acting in those environments through effector systems. Inspired by our insights into such natural cognitive systems, we seek new solutions to problems of information processing in artificial cognitive systems. We draw from a variety of disciplines that include experimental approaches from psychology and neurophysiology as well as theoretical approaches from physics, mathematics, electrical engineering and applied computer science, in particular machine learning, artificial intelligence, and computer vision.

Universitätsstr. 150, Building NB, Room 3/32
D-44801 Bochum, Germany

Tel: (+49) 234 32-28967
Fax: (+49) 234 32-14210