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Adaptive tuning of human learning and choice variability to unexpected uncertainty
Human value–based decisions are notably variable under uncertainty. This variability is known to arise from two distinct sources: variable choices aimed at exploring available options and imprecise learning of option values due to limited cognitive resources. However, whether these two sources of de...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Association for the Advancement of Science
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10058239/ https://www.ncbi.nlm.nih.gov/pubmed/36989365 http://dx.doi.org/10.1126/sciadv.add0501 |
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author | Lee, Junseok K. Rouault, Marion Wyart, Valentin |
author_facet | Lee, Junseok K. Rouault, Marion Wyart, Valentin |
author_sort | Lee, Junseok K. |
collection | PubMed |
description | Human value–based decisions are notably variable under uncertainty. This variability is known to arise from two distinct sources: variable choices aimed at exploring available options and imprecise learning of option values due to limited cognitive resources. However, whether these two sources of decision variability are tuned to their specific costs and benefits remains unclear. To address this question, we compared the effects of expected and unexpected uncertainty on decision-making in the same reinforcement learning task. Across two large behavioral datasets, we found that humans choose more variably between options but simultaneously learn less imprecisely their values in response to unexpected uncertainty. Using simulations of learning agents, we demonstrate that these opposite adjustments reflect adaptive tuning of exploration and learning precision to the structure of uncertainty. Together, these findings indicate that humans regulate not only how much they explore uncertain options but also how precisely they learn the values of these options. |
format | Online Article Text |
id | pubmed-10058239 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Association for the Advancement of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-100582392023-03-30 Adaptive tuning of human learning and choice variability to unexpected uncertainty Lee, Junseok K. Rouault, Marion Wyart, Valentin Sci Adv Neuroscience Human value–based decisions are notably variable under uncertainty. This variability is known to arise from two distinct sources: variable choices aimed at exploring available options and imprecise learning of option values due to limited cognitive resources. However, whether these two sources of decision variability are tuned to their specific costs and benefits remains unclear. To address this question, we compared the effects of expected and unexpected uncertainty on decision-making in the same reinforcement learning task. Across two large behavioral datasets, we found that humans choose more variably between options but simultaneously learn less imprecisely their values in response to unexpected uncertainty. Using simulations of learning agents, we demonstrate that these opposite adjustments reflect adaptive tuning of exploration and learning precision to the structure of uncertainty. Together, these findings indicate that humans regulate not only how much they explore uncertain options but also how precisely they learn the values of these options. American Association for the Advancement of Science 2023-03-29 /pmc/articles/PMC10058239/ /pubmed/36989365 http://dx.doi.org/10.1126/sciadv.add0501 Text en Copyright © 2023 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY). https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution license (https://creativecommons.org/licenses/by/4.0/) , which permits which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Neuroscience Lee, Junseok K. Rouault, Marion Wyart, Valentin Adaptive tuning of human learning and choice variability to unexpected uncertainty |
title | Adaptive tuning of human learning and choice variability to unexpected uncertainty |
title_full | Adaptive tuning of human learning and choice variability to unexpected uncertainty |
title_fullStr | Adaptive tuning of human learning and choice variability to unexpected uncertainty |
title_full_unstemmed | Adaptive tuning of human learning and choice variability to unexpected uncertainty |
title_short | Adaptive tuning of human learning and choice variability to unexpected uncertainty |
title_sort | adaptive tuning of human learning and choice variability to unexpected uncertainty |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10058239/ https://www.ncbi.nlm.nih.gov/pubmed/36989365 http://dx.doi.org/10.1126/sciadv.add0501 |
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