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Fidelity of the representation of value in decision-making
The ability to make optimal decisions depends on evaluating the expected rewards associated with different potential actions. This process is critically dependent on the fidelity with which reward value information can be maintained in the nervous system. Here we directly probe the fidelity of value...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5352141/ https://www.ncbi.nlm.nih.gov/pubmed/28248958 http://dx.doi.org/10.1371/journal.pcbi.1005405 |
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author | Bays, Paul M. Dowding, Ben A. |
author_facet | Bays, Paul M. Dowding, Ben A. |
author_sort | Bays, Paul M. |
collection | PubMed |
description | The ability to make optimal decisions depends on evaluating the expected rewards associated with different potential actions. This process is critically dependent on the fidelity with which reward value information can be maintained in the nervous system. Here we directly probe the fidelity of value representation following a standard reinforcement learning task. The results demonstrate a previously-unrecognized bias in the representation of value: extreme reward values, both low and high, are stored significantly more accurately and precisely than intermediate rewards. The symmetry between low and high rewards pertained despite substantially higher frequency of exposure to high rewards, resulting from preferential exploitation of more rewarding options. The observed variation in fidelity of value representation retrospectively predicted performance on the reinforcement learning task, demonstrating that the bias in representation has an impact on decision-making. A second experiment in which one or other extreme-valued option was omitted from the learning sequence showed that representational fidelity is primarily determined by the relative position of an encoded value on the scale of rewards experienced during learning. Both variability and guessing decreased with the reduction in the number of options, consistent with allocation of a limited representational resource. These findings have implications for existing models of reward-based learning, which typically assume defectless representation of reward value. |
format | Online Article Text |
id | pubmed-5352141 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-53521412017-04-06 Fidelity of the representation of value in decision-making Bays, Paul M. Dowding, Ben A. PLoS Comput Biol Research Article The ability to make optimal decisions depends on evaluating the expected rewards associated with different potential actions. This process is critically dependent on the fidelity with which reward value information can be maintained in the nervous system. Here we directly probe the fidelity of value representation following a standard reinforcement learning task. The results demonstrate a previously-unrecognized bias in the representation of value: extreme reward values, both low and high, are stored significantly more accurately and precisely than intermediate rewards. The symmetry between low and high rewards pertained despite substantially higher frequency of exposure to high rewards, resulting from preferential exploitation of more rewarding options. The observed variation in fidelity of value representation retrospectively predicted performance on the reinforcement learning task, demonstrating that the bias in representation has an impact on decision-making. A second experiment in which one or other extreme-valued option was omitted from the learning sequence showed that representational fidelity is primarily determined by the relative position of an encoded value on the scale of rewards experienced during learning. Both variability and guessing decreased with the reduction in the number of options, consistent with allocation of a limited representational resource. These findings have implications for existing models of reward-based learning, which typically assume defectless representation of reward value. Public Library of Science 2017-03-01 /pmc/articles/PMC5352141/ /pubmed/28248958 http://dx.doi.org/10.1371/journal.pcbi.1005405 Text en © 2017 Bays, Dowding http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Bays, Paul M. Dowding, Ben A. Fidelity of the representation of value in decision-making |
title | Fidelity of the representation of value in decision-making |
title_full | Fidelity of the representation of value in decision-making |
title_fullStr | Fidelity of the representation of value in decision-making |
title_full_unstemmed | Fidelity of the representation of value in decision-making |
title_short | Fidelity of the representation of value in decision-making |
title_sort | fidelity of the representation of value in decision-making |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5352141/ https://www.ncbi.nlm.nih.gov/pubmed/28248958 http://dx.doi.org/10.1371/journal.pcbi.1005405 |
work_keys_str_mv | AT bayspaulm fidelityoftherepresentationofvalueindecisionmaking AT dowdingbena fidelityoftherepresentationofvalueindecisionmaking |