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Agency rescues competition for credit assignment among predictive cues from adverse learning conditions

A fundamental assumption of learning theories is that the credit assigned to predictive cues is not simply determined by their probability of reinforcement, but by their ability to compete with other cues present during learning. This assumption has guided behavioral and neural science research for...

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Autores principales: Kang, Mihwa, Reverte, Ingrid, Volz, Stephen, Kaufman, Keith, Fevola, Salvatore, Matarazzo, Anna, Alhazmi, Fahd H., Marquez, Inmaculada, Iordanova, Mihaela D., Esber, Guillem R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8355250/
https://www.ncbi.nlm.nih.gov/pubmed/34376741
http://dx.doi.org/10.1038/s41598-021-95541-2
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author Kang, Mihwa
Reverte, Ingrid
Volz, Stephen
Kaufman, Keith
Fevola, Salvatore
Matarazzo, Anna
Alhazmi, Fahd H.
Marquez, Inmaculada
Iordanova, Mihaela D.
Esber, Guillem R.
author_facet Kang, Mihwa
Reverte, Ingrid
Volz, Stephen
Kaufman, Keith
Fevola, Salvatore
Matarazzo, Anna
Alhazmi, Fahd H.
Marquez, Inmaculada
Iordanova, Mihaela D.
Esber, Guillem R.
author_sort Kang, Mihwa
collection PubMed
description A fundamental assumption of learning theories is that the credit assigned to predictive cues is not simply determined by their probability of reinforcement, but by their ability to compete with other cues present during learning. This assumption has guided behavioral and neural science research for decades, and tremendous empirical and theoretical advances have been made identifying the mechanisms of cue competition. However, when learning conditions are not optimal (e.g., when training is massed), cue competition is attenuated. This failure of the learning system exposes the individual’s vulnerability to form spurious associations in the real world. Here, we uncover that cue competition in rats can be rescued when conditions are suboptimal provided that the individual has agency over the learning experience. Our findings reveal a new effect of agency over learning on credit assignment among predictive cues, and open new avenues of investigation into the underlying mechanisms.
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spelling pubmed-83552502021-08-11 Agency rescues competition for credit assignment among predictive cues from adverse learning conditions Kang, Mihwa Reverte, Ingrid Volz, Stephen Kaufman, Keith Fevola, Salvatore Matarazzo, Anna Alhazmi, Fahd H. Marquez, Inmaculada Iordanova, Mihaela D. Esber, Guillem R. Sci Rep Article A fundamental assumption of learning theories is that the credit assigned to predictive cues is not simply determined by their probability of reinforcement, but by their ability to compete with other cues present during learning. This assumption has guided behavioral and neural science research for decades, and tremendous empirical and theoretical advances have been made identifying the mechanisms of cue competition. However, when learning conditions are not optimal (e.g., when training is massed), cue competition is attenuated. This failure of the learning system exposes the individual’s vulnerability to form spurious associations in the real world. Here, we uncover that cue competition in rats can be rescued when conditions are suboptimal provided that the individual has agency over the learning experience. Our findings reveal a new effect of agency over learning on credit assignment among predictive cues, and open new avenues of investigation into the underlying mechanisms. Nature Publishing Group UK 2021-08-10 /pmc/articles/PMC8355250/ /pubmed/34376741 http://dx.doi.org/10.1038/s41598-021-95541-2 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Kang, Mihwa
Reverte, Ingrid
Volz, Stephen
Kaufman, Keith
Fevola, Salvatore
Matarazzo, Anna
Alhazmi, Fahd H.
Marquez, Inmaculada
Iordanova, Mihaela D.
Esber, Guillem R.
Agency rescues competition for credit assignment among predictive cues from adverse learning conditions
title Agency rescues competition for credit assignment among predictive cues from adverse learning conditions
title_full Agency rescues competition for credit assignment among predictive cues from adverse learning conditions
title_fullStr Agency rescues competition for credit assignment among predictive cues from adverse learning conditions
title_full_unstemmed Agency rescues competition for credit assignment among predictive cues from adverse learning conditions
title_short Agency rescues competition for credit assignment among predictive cues from adverse learning conditions
title_sort agency rescues competition for credit assignment among predictive cues from adverse learning conditions
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8355250/
https://www.ncbi.nlm.nih.gov/pubmed/34376741
http://dx.doi.org/10.1038/s41598-021-95541-2
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