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  Choosers Adapt Value Coding to the Environment, But Do Not Attain Efficiency

Kurtz-David, V., Alladi, V., Bucher, S., Brandenburger, A., Louie, K., Glimcher, P., et al. (2023). Choosers Adapt Value Coding to the Environment, But Do Not Attain Efficiency. Proceedings of the Annual Meeting of the Cognitive Science Society, 45, 2237-2244.

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 Creators:
Kurtz-David, V, Author
Alladi, V, Author
Bucher, S1, Author                 
Brandenburger, A, Author
Louie, K, Author
Glimcher, P, Author
Tymula, A, Author
Affiliations:
1Department of Computational Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_3017468              

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 Abstract: We investigate how human choosers adapt their value encoding strategy to the statistics of the choice environment. Specifically, we ask whether the human value encoding mechanism exhibits divisive normalization only in the Pareto-distributed environments in which it is information-maximizing. To test this theory, we conduct a risky choice experiment in which subjects are presented with blocks of choice stimuli drawn from either a Pareto-distributed environment or a uniform-distributed environment. Our results show that subjects exhibit some degree of normalization regardless of whether it is efficient or not, but do adapt the curvature of their encoding function to the environment. These findings suggest that human value coding mechanisms are flexible but biologically constrained to be perfectly efficient only in specific environments. This study provides new insights into the neural mechanism of human decision-making and the role of environmental statistics in shaping it.

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 Dates: 2023-07
 Publication Status: Issued
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Title: 45th Annual Meeting of the Cognitive Science Society (CogSci 2023)
Place of Event: Sydney, Australia
Start-/End Date: 2023-07-26 - 2023-07-29

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Title: Proceedings of the Annual Meeting of the Cognitive Science Society
Source Genre: Journal
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Pages: - Volume / Issue: 45 Sequence Number: - Start / End Page: 2237 - 2244 Identifier: ISSN: 1069-7977