Brain-wide representations of prior information in mouse decision-making

Charles Findling (), Félix Hubert, Luigi Acerbi, Brandon Benson, Julius Benson, Daniel Birman, Niccolò Bonacchi, E. Kelly Buchanan, Sebastian Bruijns, Matteo Carandini, Joana A. Catarino, Gaelle A. Chapuis, Anne K. Churchland, Yang Dan, Felicia Davatolhagh, Eric E. J. DeWitt, Tatiana A. Engel, Michele Fabbri, Mayo A. Faulkner, Ila Rani Fiete, Laura Freitas-Silva, Berk Gerçek, Kenneth D. Harris, Michael Häusser, Sonja B. Hofer, Fei Hu, Julia M. Huntenburg, Anup Khanal, Chris Krasniak, Christopher Langdon, Christopher A. Langfield, Peter E. Latham, Petrina Y. P. Lau, Zach Mainen, Guido T. Meijer, Nathaniel J. Miska, Thomas D. Mrsic-Flogel, Jean-Paul Noel, Kai Nylund, Alejandro Pan-Vazquez, Liam Paninski, Jonathan Pillow, Cyrille Rossant, Noam Roth, Rylan Schaeffer, Michael Schartner, Yanliang Shi, Karolina Z. Socha, Nicholas A. Steinmetz, Karel Svoboda, Charline Tessereau, Anne E. Urai, Miles J. Wells, Steven Jon West, Matthew R. Whiteway, Olivier Winter, Ilana B. Witten, Anthony Zador, Yizi Zhang, Peter Dayan and Alexandre Pouget
Additional contact information
Charles Findling: University of Geneva
Félix Hubert: University of Geneva
Luigi Acerbi: University of Helsinki
Brandon Benson: Stanford University
Julius Benson: New York University
Daniel Birman: University of Washington
Niccolò Bonacchi: Instituto Universitário
E. Kelly Buchanan: Stanford University
Sebastian Bruijns: University of Tübingen
Matteo Carandini: University College London
Joana A. Catarino: Champalimaud Foundation
Gaelle A. Chapuis: University of Geneva
Anne K. Churchland: University of California Los Angeles
Yang Dan: University of California Berkeley
Felicia Davatolhagh: University of California Los Angeles
Eric E. J. DeWitt: Champalimaud Foundation
Tatiana A. Engel: Princeton University
Michele Fabbri: Champalimaud Foundation
Mayo A. Faulkner: University College London
Ila Rani Fiete: Massachusetts Institute of Technology
Laura Freitas-Silva: Champalimaud Foundation
Berk Gerçek: University of Geneva
Kenneth D. Harris: University College London
Michael Häusser: University College London
Sonja B. Hofer: University College London
Fei Hu: University of California Berkeley
Julia M. Huntenburg: University of Tübingen
Anup Khanal: University of California Los Angeles
Chris Krasniak: Cold Spring Harbor Laboratory
Christopher Langdon: Princeton University
Christopher A. Langfield: Columbia University
Peter E. Latham: University College London
Petrina Y. P. Lau: University College London
Zach Mainen: Champalimaud Foundation
Guido T. Meijer: Champalimaud Foundation
Nathaniel J. Miska: University College London
Thomas D. Mrsic-Flogel: University College London
Jean-Paul Noel: University of Minnesota
Kai Nylund: University of Washington
Alejandro Pan-Vazquez: Princeton University
Liam Paninski: Columbia University
Jonathan Pillow: Princeton University
Cyrille Rossant: University College London
Noam Roth: University of Washington
Rylan Schaeffer: Massachusetts Institute of Technology
Michael Schartner: Champalimaud Foundation
Yanliang Shi: Princeton University
Karolina Z. Socha: University College London
Nicholas A. Steinmetz: University of Washington
Karel Svoboda: Seattle
Charline Tessereau: University of Tübingen
Anne E. Urai: Leiden University
Miles J. Wells: University College London
Steven Jon West: University College London
Matthew R. Whiteway: Columbia University
Olivier Winter: Champalimaud Foundation
Ilana B. Witten: Princeton University
Anthony Zador: Cold Spring Harbor Laboratory
Yizi Zhang: Columbia University
Peter Dayan: University of Tübingen
Alexandre Pouget: University of Geneva

Nature, 2025, vol. 645, issue 8079, 192-200

Abstract: Abstract The neural representations of prior information about the state of the world are poorly understood1. Here, to investigate them, we examined brain-wide Neuropixels recordings and widefield calcium imaging collected by the International Brain Laboratory. Mice were trained to indicate the location of a visual grating stimulus, which appeared on the left or right with a prior probability alternating between 0.2 and 0.8 in blocks of variable length. We found that mice estimate this prior probability and thereby improve their decision accuracy. Furthermore, we report that this subjective prior is encoded in at least 20% to 30% of brain regions that, notably, span all levels of processing, from early sensory areas (the lateral geniculate nucleus and primary visual cortex) to motor regions (secondary and primary motor cortex and gigantocellular reticular nucleus) and high-level cortical regions (the dorsal anterior cingulate area and ventrolateral orbitofrontal cortex). This widespread representation of the prior is consistent with a neural model of Bayesian inference involving loops between areas, as opposed to a model in which the prior is incorporated only in decision-making areas. This study offers a brain-wide perspective on prior encoding at cellular resolution, underscoring the importance of using large-scale recordings on a single standardized task.

Date: 2025
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DOI: 10.1038/s41586-025-09226-1

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