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Impulsivity Relates to Multi-Trial Choice Strategy in Probabilistic Reversal Learning
Impulsivity is defined as a trait-like tendency to engage in rash actions that are poorly thought out or expressed in an untimely manner. Previous research has found that impulsivity relates to deficits in decision making, in particular when it necessitates executive control or reward outcomes. Rein...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8964258/ https://www.ncbi.nlm.nih.gov/pubmed/35360119 http://dx.doi.org/10.3389/fpsyt.2022.800290 |
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author | Zou, Amy R. Muñoz Lopez, Daniela E. Johnson, Sheri L. Collins, Anne G. E. |
author_facet | Zou, Amy R. Muñoz Lopez, Daniela E. Johnson, Sheri L. Collins, Anne G. E. |
author_sort | Zou, Amy R. |
collection | PubMed |
description | Impulsivity is defined as a trait-like tendency to engage in rash actions that are poorly thought out or expressed in an untimely manner. Previous research has found that impulsivity relates to deficits in decision making, in particular when it necessitates executive control or reward outcomes. Reinforcement learning (RL) relies on the ability to integrate reward or punishment outcomes to make good decisions, and has recently been shown to often recruit executive function; as such, it is unsurprising that impulsivity has been studied in the context of RL. However, how impulsivity relates to the mechanisms of RL remains unclear. We aimed to investigate the relationship between impulsivity and learning in a reward-driven learning task with probabilistic feedback and reversal known to recruit executive function. Based on prior literature in clinical populations, we predicted that higher impulsivity would be associated with poorer performance on the task, driven by more frequent switching following unrewarded outcomes. Our results did not support this prediction, but more advanced, trial-history dependent analyses revealed specific effects of impulsivity on switching behavior following consecutive unrewarded trials. Computational modeling captured group-level behavior, but not impulsivity results. Our results support previous findings highlighting the importance of sensitivity to negative outcomes in understanding how impulsivity relates to learning, but indicate that this may stem from more complex strategies than usually considered in computational models of learning. This should be an important target for future research. |
format | Online Article Text |
id | pubmed-8964258 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-89642582022-03-30 Impulsivity Relates to Multi-Trial Choice Strategy in Probabilistic Reversal Learning Zou, Amy R. Muñoz Lopez, Daniela E. Johnson, Sheri L. Collins, Anne G. E. Front Psychiatry Psychiatry Impulsivity is defined as a trait-like tendency to engage in rash actions that are poorly thought out or expressed in an untimely manner. Previous research has found that impulsivity relates to deficits in decision making, in particular when it necessitates executive control or reward outcomes. Reinforcement learning (RL) relies on the ability to integrate reward or punishment outcomes to make good decisions, and has recently been shown to often recruit executive function; as such, it is unsurprising that impulsivity has been studied in the context of RL. However, how impulsivity relates to the mechanisms of RL remains unclear. We aimed to investigate the relationship between impulsivity and learning in a reward-driven learning task with probabilistic feedback and reversal known to recruit executive function. Based on prior literature in clinical populations, we predicted that higher impulsivity would be associated with poorer performance on the task, driven by more frequent switching following unrewarded outcomes. Our results did not support this prediction, but more advanced, trial-history dependent analyses revealed specific effects of impulsivity on switching behavior following consecutive unrewarded trials. Computational modeling captured group-level behavior, but not impulsivity results. Our results support previous findings highlighting the importance of sensitivity to negative outcomes in understanding how impulsivity relates to learning, but indicate that this may stem from more complex strategies than usually considered in computational models of learning. This should be an important target for future research. Frontiers Media S.A. 2022-03-14 /pmc/articles/PMC8964258/ /pubmed/35360119 http://dx.doi.org/10.3389/fpsyt.2022.800290 Text en Copyright © 2022 Zou, Muñoz Lopez, Johnson and Collins. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Psychiatry Zou, Amy R. Muñoz Lopez, Daniela E. Johnson, Sheri L. Collins, Anne G. E. Impulsivity Relates to Multi-Trial Choice Strategy in Probabilistic Reversal Learning |
title | Impulsivity Relates to Multi-Trial Choice Strategy in Probabilistic Reversal Learning |
title_full | Impulsivity Relates to Multi-Trial Choice Strategy in Probabilistic Reversal Learning |
title_fullStr | Impulsivity Relates to Multi-Trial Choice Strategy in Probabilistic Reversal Learning |
title_full_unstemmed | Impulsivity Relates to Multi-Trial Choice Strategy in Probabilistic Reversal Learning |
title_short | Impulsivity Relates to Multi-Trial Choice Strategy in Probabilistic Reversal Learning |
title_sort | impulsivity relates to multi-trial choice strategy in probabilistic reversal learning |
topic | Psychiatry |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8964258/ https://www.ncbi.nlm.nih.gov/pubmed/35360119 http://dx.doi.org/10.3389/fpsyt.2022.800290 |
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