Cognitive computational models of information sampling under threat
Information sampling is a requirement in many threat-related scenarios. This project deals with optimal information sampling in an ethological computer game, and approximative shortcuts that biological agents may use.
Computational modelling of human fear memory
The goal of the project is to improve computational/biophysical models of autonomic nervous system readouts of human fear memory.
Predicting search trajectories in a computer game
The goal of this project is to understand human cognition in a computer game and predict behaviour of individual humans.
The emergence of subjective feelings during foraging under predation threat
Non-human approach-avoidance conflict tests are classic paradigms to elicit anxiety-like behaviours, and mimick aspects of foraging for food while under threat of predation. We have recently translated this class of paradigms to humans (e. g. Bach et al. 2014, Current Biology; Korn et al. 2017, Biological Psychiatry). However, it is unclear how behaviour in this paradigm relates to subjective feeling.

Powered by  SiROP - the academic career network