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A neural mechanism for conserved value computations integrating information and rewards

View ORCID ProfileEthan S. Bromberg-Martin, View ORCID ProfileYang-Yang Feng, Takaya Ogasawara, J. Kael White, Kaining Zhang, View ORCID ProfileIlya E. Monosov
doi: https://doi.org/10.1101/2022.08.14.503903
Ethan S. Bromberg-Martin
1Department of Neuroscience, Washington University School of Medicine, USA
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Yang-Yang Feng
1Department of Neuroscience, Washington University School of Medicine, USA
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Takaya Ogasawara
1Department of Neuroscience, Washington University School of Medicine, USA
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J. Kael White
1Department of Neuroscience, Washington University School of Medicine, USA
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Kaining Zhang
1Department of Neuroscience, Washington University School of Medicine, USA
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Ilya E. Monosov
1Department of Neuroscience, Washington University School of Medicine, USA
2Department of Neurosurgery, Washington University School of Medicine, USA
3Department of Biomedical Engineering, Washington University, USA
4Department of Electrical Engineering, Washington University, USA
5Pain Center, Washington University School of Medicine, USA
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  • For correspondence: ilya.monosov@gmail.com
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Abstract

Behavioral and economic theory dictates that we decide between options based on their values. However, humans and animals eagerly seek information about uncertain future rewards, even when this information does not provide any objective value. This implies that decisions can be made by endowing information with subjective value and integrating it with the value of extrinsic rewards, but the mechanism is unknown. Using a novel multi-attribute decision making task we found that human and monkey value judgements are regulated by strikingly conserved computational principles, including how they compute the value of information and scale it with information’s timing and ability to resolve a specific form of uncertainty. We then identified a neural substrate in a highly conserved and ancient structure, the lateral habenula (LHb). LHb neurons signal the subjective value of choice options integrating the value of information with extrinsic rewards, and LHb activity both predicts and causally influences online decisions. Key input regions to LHb provide the necessary ingredients for these computations, but do not themselves signal an integrated value signal to guide multi attribute decisions. Our data thus identifies neural mechanisms of the conserved computations underlying multi-attribute, value-based decisions to seek information about the future.

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-NC-ND 4.0 International license.
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Posted August 15, 2022.
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A neural mechanism for conserved value computations integrating information and rewards
Ethan S. Bromberg-Martin, Yang-Yang Feng, Takaya Ogasawara, J. Kael White, Kaining Zhang, Ilya E. Monosov
bioRxiv 2022.08.14.503903; doi: https://doi.org/10.1101/2022.08.14.503903
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A neural mechanism for conserved value computations integrating information and rewards
Ethan S. Bromberg-Martin, Yang-Yang Feng, Takaya Ogasawara, J. Kael White, Kaining Zhang, Ilya E. Monosov
bioRxiv 2022.08.14.503903; doi: https://doi.org/10.1101/2022.08.14.503903

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