Computational Neuroscience: Neural Dynamics

The results of the Exam have been posted on NB3. Students from Dortmund can contact me (Jean-Stephane) per email to get the results if you want to avoid making the trip. Certificates are now available in our administrative office (Sekretariat) NB3/32 (check the office hours). You can inspect the results of the exam on Friday 10.3. at 14h in room NB3/72.

This course provides an introduction into a neural process accounts for perception, motor control, and simple forms of cognition. The vantage point is the dynamical systems approach, which emphasizes the evolution in time of behavior and of neural activation patterns as the basis for understanding how neural networks together with sensory and motor systems generate behavior and cognition. 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 that provide some of the mathematical foundations. Theoretical concepts will be exposed in reference to a number of experimental model systems such as the perception of motion, visual and spatial working memory, movement planning, and others. In the spirit of Braitenberg´s "synthetic psychology", autonomous robots will be 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 analysis of theoretical models and their relationship to experiment, all on the basis of the theoretical framework exposed in the main lectures. Learning to produce scientific texts with appropriate illustrations and documenting mathematical ideas is one of the learning goals of the course.

Some of the exercises refer to readings, scientific papers that students will study to do the exercises. Learning to read and understand research papers is another learning goal of the course.



Course type
6 CP
Winter Term 2016/2017


Takes place on 16.02.2017 from 14:15 to 16:00 in room NB 3/ 57 .
Takes place every week on Thursday from 14.15 to 16.00 in room NB 3/57.
First appointment is on 20.10.2016
Last appointment is on 09.02.2017
Takes place every week on Thursday from 16.15 to 17.00 in room NB 3/57.
First appointment is on 27.10.2016
Last appointment is on 09.02.2017


This course requires some basic math preparation, typically as covered in two semesters of higher mathematics (functions, differentiation, integration, differential equations, linear algebra). The course does not make extensive use of the underlying mathematical techniques, but uses the mathematical concepts to express scientific ideas. Students without prior training in the relevant mathematics may be able to follow the course, but will have to work harder to familiarize themselves with the concepts.


Exercises are corrected and held by Jean-Stéphane Jokeit. Details on grading are available in the course rules below.


The course will be based on selected chapters of a textbook (Dynamic Thinking: A Primer on Dynamic Field Theory by Schöner, G., Spencer, J, and the DFT Research Group, Oxford University Press). The first two chapters are available for download in the course materials below. These and others will also serve as readings for some of the exercises. 

For the mathematical background in dynamical systems an excellent resource is a book that is available online as a free download (thanks to the author's generosity): Edward R. Scheinerman's Invitation to Dynamical Systems.  This book covers both discrete and continuous time dynamical systems, while in the course we will only make use of continuous time dynamical systems formalized as differential equations. 


Document Rules for credit
Lecture slides Organizational information
Lecture slides Introduction
Lecture slides Braitenberg vehicles
Exercises Exercise 1: Braitenberg vehicle
Document Chapter 1 of the textbook
Document Chapter 2 of the textbook
Lecture slides Neural Dynamics: Introduction
Exercises Essay Exercise
Lecture slides Neurophysics tutorial
Lecture slides Second part of neural dynamics lecture with discussion of inputs/coding
Exercises Exercise 3: Simulator
Document Template MATLAB code for numerics exercise
Lecture slides DFT tutorial part 1
Exercises Exercise 4: population code
Document Reading for Exercise 4
Lecture slides DFT tutorial part 2
Exercises Exercise 5: DFT reading and simulation exercise
Lecture slides DFT tutorial part 3
Lecture slides DFT tutorial part 4
Exercises Exercise 6: Amari oscillator
Document Article by Amari (1977) supporting Exercise 6
Lecture slides DFT account of A not B effect, link to motor behavior
Exercises Exercise 7: Dynamical systems thinking in development
Document Article supporting Exercise 7
Lecture slides Learning
Lecture slides Higher dimensional fields: visual search, binding, coordinate transforms
Lecture slides Research program embodied cognition and cognitive robotics
Lecture slides Information about the exam
Lecture slides Summary of main points for the exam

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