Mathematical Psychology

In the first three semesters of studying psychology, you have learned about a wide variety of perceptual, cognitive and motor processes. What you have not learned about is that some highly complex processes can be captured and explained using simple mathematical or computer models.

This class will introduce you to this powerful approach through a  combination of interactive theory lectures and hands-on computer lab
exercises. The lectures will introduce a diverse range of topics in perception, decision making, learning and memory; and methods such as
psychophysics, signal detection theory and neural network modeling. The computer labs will introduce scientific programming in Matlab based on realistic examples of psychological research. In the the class project, students will design their own experiment, and then implement and analyze it using Matlab. The integration of theory and practice in this class will help students learn the abstract theory and how to use computers to run and analyze their future experiments, such as in their Bachelor and Master projects.

This class is open to Bachelor students of other disciplines who would like to see mathematical and computational tools applied to the analysis and description of cognitive processes.



Course type
Summer Term 2019


Takes place every week on Monday from 10:00 to 12:00 in room NB 3/72.
First appointment is on 01.04.2019
Last appointment is on 08.07.2019
Takes place every week on Friday from 10:00 to 12:00 in room IA 0/69 (PC-Pool 2).
First appointment is on 05.04.2019
Last appointment is on 12.07.2019


Basic knowledge of perception, decision making, learning and memory, e.g., “Cognition I + II”, “Learning”. Previous programming experience is not strictly required.

Assessment: report (homework, class project), presentation (class project)
Course material: Blackboard (sign-up required)

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