Sebastian Gluth, PhD (Universität Hamburg)

Professor and Head of General Psychology
Department of Psychology and Human Movement Science
Universität Hamburg

The computational mechanisms of inferring hidden preferences from observing decision processes

*virtual event only*

Zoom Link:

Meeting ID: 968 4714 7440


Humans are an inherently social species, and they have remarkable capacities to infer hidden knowledge, beliefs, and preferences from observing the behavior of their conspecifics. However, the underlying computational mechanisms of these processes are still debated. We hypothesize that humans simulate the decisions of others with their own mind to predict and learn from their observations. To test this hypothesis, we asked participants to infer the social preferences of others based on observing different choice processes (choices vs. response times). Remarkably, we found that people are able to infer the social preferences of others even if only response times (but not choices) were revealed. A reinforcement learning model that uses an internal model to map the observed choice dynamics onto inferred preferences is able to explain the learning effect. Overall, our results are consistent with the hypothesized simulation account of understanding other people’s decisions.

Speaker Bio 

Sebastian Gluth studied Psychology at the Humboldt-University in Berlin. After obtaining a PhD from the Department of Systems Neuroscience in Hamburg, he worked as a postdoc and assistant professor for Decision Neuroscience at the University of Basel in Switzerland. Recently, he moved back to the University of Hamburg and is now professor for General Psychology at the Department of Psychology. In his research, Sebastian studies the cognitive and neural basis of value-based decision making and reward-based learning. In particular, he seeks to understand the dynamics of decisions using computational models of evidence accumulation in combination with multiple measurement tools such as eye-tracking, EEG and fMRI.


Apr 11 2023


2:40 PM - 4:00 PM


Categories: Dean for Science Lecture