Research areas

• – Computational neuroscience
• – Neural reinforcement learning

Methodological and/or psychotherapeutic expertise

• – Neural reinforcement learning

Short biography

Peter Dayan is a Director at the MPI for Biological Cybernetics and a Professor at the University of Tübingen. His interests include affective decision making, neural reinforcement learning and computational psychiatry.

Relevant publications

• Zamfir, E., Dayan, P. (2022). Interactions between attributions and beliefs at trial-by-trial level: Evidence from a novel computer game task. PLoS Comput Biol, 18(9):e1009920. doi:10.1371/journal.pcbi.1009920
• Barnby, J.M., Raihani, N., Dayan, P. (2022). Knowing me, knowing you: Interpersonal similarity improves predictive accuracy and reduces attributions of harmful intent. Cognition, 225:105098. doi:10.1016/j.cognition.2022.105098
• Kumar, P., Dayan, P., Wolfers, T. (2024). From Complexity to Precision—Charting Decision-Making Through Normative Modeling. JAMA Psychiatry, 81(2):117-118. doi:10.1001/jamapsychiatry.2024.0117
• Kind, A., Dayan, P. (2024). Two sub-cultures of explanatory computational psychiatry. Molecular Psychiatry. doi:10.1038/s41380-024-02639-w
• Barnby, J.M., Dayan, P., Bell, V. (2023). Formalising social representation to explain psychiatric symptoms. Trends in Cognitive Sciences, 27:317-332. doi:10.1016/j.tics.2022.12.004
• Roelofs, K., Dayan, P. (2022). Freezing revisited: Coordinated autonomic and central optimization of threat coping. Nature Reviews Neuroscience. doi:10.1038/s41583-022-00608-2
• Gagne, C., Dayan, P. (2022). Peril, Prudence and Planning as Risk, Avoidance and Worry. J Math Psychology. doi:10.1016/j.jmp.2021.102617
• Mancinelli, F., Roiser, R., & Dayan, P. (2021). Internality and the internalisation of failure: Evidence from a novel task. PLoS Comput Biol. doi:10.1371/journal.pcbi.1009134
• Schulz, E., Dayan, P. (2020). Computational Psychiatry for Computers. iScience, 23(12):101772. doi:10.1016/j.isci.2020.101772
• Dezfouli, A., Griffiths, K., Ramos, F., Dayan, P., Balleine, B.W. (2019). Models that learn how humans learn: The case of decision-making and its disorders. PLoS Comput Biol, 15(6):e1006903. doi:10.1371/journal.pcbi.1006903
• Hula, A., Vilares, I., Lohrenz, T., Dayan, P., Montague, P.R. (2018). A model of risk and mental state shifts during social interaction. PLoS Comput Biol. doi:10.1371/journal.pcbi.1005935
• Bach, D.R., & Dayan, P. (2017). Algorithms for survival: a comparative perspective on emotions. Nature Reviews Neuroscience. doi:10.1038/nrn.2017.35
• Huys, Q.J., Guitart-Masip, M., Dolan, R.J., & Dayan, P. (2015). Decision-Theoretic Psychiatry. Clinical Psychological Science. doi:10.1177/2167702614562040
• Huys, Q.J., Daw, N.D., & Dayan, P. (2015). Depression: A Decision-Theoretic Analysis. Annual Review of Neuroscience. doi:10.1146/annurev-neuro-071714-033928
• Dayan, P., Dolan, R.J., Friston, K.J., & Montague, P.R. (2015). Taming the shrewdness of neural function: Methodological challenges in computational psychiatry. Current Opinion in Behavioral Sciences. doi:10.1016/j.cobeha.2015.09.009

Relevant funded research projects

• - Simons Foundation: International Brain Lab