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A new theoretical framework jointly explains behavioral and neural variability across subjects performing flexible decision-making

View ORCID ProfileMarino Pagan, Vincent D Tang, View ORCID ProfileMikio C. Aoi, View ORCID ProfileJonathan W. Pillow, View ORCID ProfileValerio Mante, View ORCID ProfileDavid Sussillo, View ORCID ProfileCarlos D. Brody
doi: https://doi.org/10.1101/2022.11.28.518207
Marino Pagan
1Princeton Neuroscience Institute, Stanford University, Stanford, CA, USA
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  • For correspondence: mpagan@princeton.edu brody@princeton.edu
Vincent D Tang
1Princeton Neuroscience Institute, Stanford University, Stanford, CA, USA
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Mikio C. Aoi
1Princeton Neuroscience Institute, Stanford University, Stanford, CA, USA
2Department of Neurobiology & Halıcıoğlu Data Science Institute, University of California, San Diego, Stanford University, Stanford, CA, USA
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Jonathan W. Pillow
1Princeton Neuroscience Institute, Stanford University, Stanford, CA, USA
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Valerio Mante
3University of Zurich, Stanford University, Stanford, CA, USA
4ETH Zurich, Stanford University, Stanford, CA, USA
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David Sussillo
5Department of Electrical Engineering, Stanford University, Stanford, CA, USA
6Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
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Carlos D. Brody
1Princeton Neuroscience Institute, Stanford University, Stanford, CA, USA
7HHMI
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  • ORCID record for Carlos D. Brody
  • For correspondence: mpagan@princeton.edu brody@princeton.edu
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Abstract

The ability to flexibly select and accumulate relevant information to form decisions, while ignoring irrelevant information, is a fundamental component of higher cognition. Yet its neural mechanisms remain unclear. Here we demonstrate that, under assumptions supported by both monkey and rat data, the space of possible network mechanisms to implement this ability is spanned by the combination of three different components, each with specific behavioral and anatomical implications. We further show that existing electrophysiological and modeling data are compatible with the full variety of possible combinations of these components, suggesting that different individuals could use different component combinations. To study variations across subjects, we developed a rat task requiring context-dependent evidence accumulation, and trained many subjects on it. Our task delivers sensory evidence through pulses that have random but precisely known timing, providing high statistical power to characterize each individual’s neural and behavioral responses. Consistent with theoretical predictions, neural and behavioral analysis revealed remarkable heterogeneity across rats, despite uniformly good task performance. The theory further predicts a specific link between behavioral and neural signatures, which was robustly supported in the data. Our results provide a new experimentally-supported theoretical framework to analyze biological and artificial systems performing flexible decision-making tasks, and open the door to the study of individual variability in neural computations underlying higher cognition.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
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Posted November 28, 2022.
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A new theoretical framework jointly explains behavioral and neural variability across subjects performing flexible decision-making
Marino Pagan, Vincent D Tang, Mikio C. Aoi, Jonathan W. Pillow, Valerio Mante, David Sussillo, Carlos D. Brody
bioRxiv 2022.11.28.518207; doi: https://doi.org/10.1101/2022.11.28.518207
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A new theoretical framework jointly explains behavioral and neural variability across subjects performing flexible decision-making
Marino Pagan, Vincent D Tang, Mikio C. Aoi, Jonathan W. Pillow, Valerio Mante, David Sussillo, Carlos D. Brody
bioRxiv 2022.11.28.518207; doi: https://doi.org/10.1101/2022.11.28.518207

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