Module PY4310-KP04

Models of learning and decision-making (LernEntsch)


Duration

1 Semester

Turnus of offer

each summer semester

Credit points

4

Course of studies, specific fields and terms:

  • Master Psychology - Clinical Psychology and Psychotherapy 2027, optional subject, psychology
  • Master Psychology - Clinical Psychology and Psychotherapy 2022, optional subject, psychology

Classes and lectures:

  • Models of learning and decision making (seminar, 2 SWS)

Workload:

  • 30 hours in-classroom work
  • 90 hours private studies

Contents of teaching:

  • Introduction into the basic principles and background of computational modeling.
  • Models of learning (i.e. Rescorla-Wagner-Model and adaptations)
  • Models for decision making (i.e. Drift-diffusion-Models)
  • General principles in model comparison and parameter estimation
  • Application in the research of mental disorders (Anxiety disorders, Psychosis and Depression)
  • Practical exercises on data simulation (among other things) to illustrate the respective models discussed in the content-related topic blocks.

Qualification-goals/Competencies:

  • Students gain in-depth insights into the principles and methods of computational modeling.
  • Students can understand and evaluate studies that make use of the learned computational models.
  • Students understand the relevance of computational modeling for the research on mental disorders.

Grading through:

  • written homework

Literature:

  • Farrell, & Lewandowski (2018) : Computational Modeling of Cognition and Behavior Cambridge: Cambridge University Press
  • Wilson, R. C., & Collins, A. G. (2019) : Ten simple rules for the computational modeling of behavioral data. eLife, 8. https://doi.org/10.7554/eLife.49547
  • Friston, K. J., Stephan, K. E., Montague, R., & Dolan, R. J. (2014) : Computational psychiatry: The brain as a phantastic organ. The Lancet Psychiatry, 1(2), 148–158.

Language:

  • German and English skills required

Notes:

Admission requirements for taking the module:
- None

Admission requirements for participation in module examination(s):
- Co-design of a session; academic performance is to be provided as active contributions to the discussion and participation in the practical exercise sessions.

Module Exam(s):
- PY4310-L1: Models of Learning and Decision Making, Term Paper, 100% of the module grade

Last Updated:

28.11.2025