Niklas Georg Bürgi

Niklas Georg Bürgi is a postdoctoral researcher in the Department of Computational Neuroscience at the Max Planck Institute for Biological Cybernetics, working in Peter Dayan's group. His research integrates behavioral experiments, neuroimaging, and computational modeling to understand social learning and interaction in both healthy individuals and those with mental disorders.

Research Interests: His work centers on computational social cognition, particularly mentalization—the ability to infer others' thoughts—and how it adapts during reciprocal interactions. He investigates how these processes are altered in depression and other psychiatric conditions, combining clinical psychology with advanced neuroimaging and modeling techniques. His research bridges human and artificial intelligence, aiming to uncover mechanistic accounts of social inference.

The recent publications highlight a strong trend toward understanding the neural and computational basis of social cognition, with applications in computational psychiatry. His work employs fMRI, machine learning, and game-theoretic paradigms to decode social belief updates and brain network dynamics in depression.

Scientific Awards:

• Annual award for excellent scholarly work by the University of Zurich (for PhD dissertation)

Advising and Grants: While no formal students or grants are listed, his research has been supported through institutional funding at the Max Planck Institute and the Zurich Center for Neuroeconomics. He has collaborated with leading researchers in neuroeconomics and clinical psychiatry, suggesting active involvement in interdisciplinary projects and mentorship through research collaboration.

Labs and Teams: He is currently part of Peter Dayan’s group at the Max Planck Institute for Biological Cybernetics. Previously, he was a PhD student in Christian Ruff’s group at the Zurich Center for Neuroeconomics (ZNE). His work has involved collaborations with teams in psychodynamic therapy research, neuropsychopharmacology, and healthy aging, indicating a broad interdisciplinary network.