A foundation model to predict and capture human cognition

Marcel Binz (), Elif Akata, Matthias Bethge, Franziska Brändle, Fred Callaway, Julian Coda-Forno, Peter Dayan, Can Demircan, Maria K. Eckstein, Noémi Éltető, Thomas L. Griffiths, Susanne Haridi, Akshay K. Jagadish, Li Ji-An, Alexander Kipnis, Sreejan Kumar, Tobias Ludwig, Marvin Mathony, Marcelo Mattar, Alireza Modirshanechi, Surabhi S. Nath, Joshua C. Peterson, Milena Rmus, Evan M. Russek, Tankred Saanum, Johannes A. Schubert, Luca M. Schulze Buschoff, Nishad Singhi, Xin Sui, Mirko Thalmann, Fabian J. Theis, Vuong Truong, Vishaal Udandarao, Konstantinos Voudouris, Robert Wilson, Kristin Witte, Shuchen Wu, Dirk U. Wulff, Huadong Xiong and Eric Schulz
Additional contact information
Marcel Binz: Helmholtz Center
Elif Akata: Helmholtz Center
Matthias Bethge: University of Tübingen
Franziska Brändle: University of Oxford
Fred Callaway: New York University
Julian Coda-Forno: Helmholtz Center
Peter Dayan: University of Tübingen
Can Demircan: Helmholtz Center
Maria K. Eckstein: Google DeepMind
Noémi Éltető: Max Planck Institute for Biological Cybernetics
Thomas L. Griffiths: Princeton University
Susanne Haridi: Helmholtz Center
Akshay K. Jagadish: Helmholtz Center
Li Ji-An: University of California, San Diego
Alexander Kipnis: Helmholtz Center
Sreejan Kumar: Princeton University
Tobias Ludwig: University of Tübingen
Marvin Mathony: Helmholtz Center
Marcelo Mattar: New York University
Alireza Modirshanechi: Helmholtz Center
Surabhi S. Nath: University of Tübingen
Joshua C. Peterson: Boston University
Milena Rmus: Helmholtz Center
Evan M. Russek: Princeton University
Tankred Saanum: Helmholtz Center
Johannes A. Schubert: Max Planck Institute for Biological Cybernetics
Luca M. Schulze Buschoff: Helmholtz Center
Nishad Singhi: TU Darmstadt
Xin Sui: University of Tübingen
Mirko Thalmann: Helmholtz Center
Fabian J. Theis: Helmholtz Center
Vuong Truong: Max Planck Institute for Biological Cybernetics
Vishaal Udandarao: University of Tübingen
Konstantinos Voudouris: Helmholtz Center
Robert Wilson: Georgia Institute of Technology
Kristin Witte: Helmholtz Center
Shuchen Wu: Helmholtz Center
Dirk U. Wulff: University of Basel
Huadong Xiong: Georgia Institute of Technology
Eric Schulz: Helmholtz Center

Nature, 2025, vol. 644, issue 8078, 1002-1009

Abstract: Abstract Establishing a unified theory of cognition has been an important goal in psychology1,2. A first step towards such a theory is to create a computational model that can predict human behaviour in a wide range of settings. Here we introduce Centaur, a computational model that can predict and simulate human behaviour in any experiment expressible in natural language. We derived Centaur by fine-tuning a state-of-the-art language model on a large-scale dataset called Psych-101. Psych-101 has an unprecedented scale, covering trial-by-trial data from more than 60,000 participants performing in excess of 10,000,000 choices in 160 experiments. Centaur not only captures the behaviour of held-out participants better than existing cognitive models, but it also generalizes to previously unseen cover stories, structural task modifications and entirely new domains. Furthermore, the model’s internal representations become more aligned with human neural activity after fine-tuning. Taken together, our results demonstrate that it is possible to discover computational models that capture human behaviour across a wide range of domains. We believe that such models provide tremendous potential for guiding the development of cognitive theories, and we present a case study to demonstrate this.

Date: 2025
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DOI: 10.1038/s41586-025-09215-4

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