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Optimism and pessimism in optimised replay

The replay of task-relevant trajectories is known to contribute to memory consolidation and improved task performance. A wide variety of experimental data show that the content of replayed sequences is highly specific and can be modulated by reward as well as other prominent task variables. However,...

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Detalles Bibliográficos
Autores principales: Antonov, Georgy, Gagne, Christopher, Eldar, Eran, Dayan, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8809607/
https://www.ncbi.nlm.nih.gov/pubmed/35020718
http://dx.doi.org/10.1371/journal.pcbi.1009634
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author Antonov, Georgy
Gagne, Christopher
Eldar, Eran
Dayan, Peter
author_facet Antonov, Georgy
Gagne, Christopher
Eldar, Eran
Dayan, Peter
author_sort Antonov, Georgy
collection PubMed
description The replay of task-relevant trajectories is known to contribute to memory consolidation and improved task performance. A wide variety of experimental data show that the content of replayed sequences is highly specific and can be modulated by reward as well as other prominent task variables. However, the rules governing the choice of sequences to be replayed still remain poorly understood. One recent theoretical suggestion is that the prioritization of replay experiences in decision-making problems is based on their effect on the choice of action. We show that this implies that subjects should replay sub-optimal actions that they dysfunctionally choose rather than optimal ones, when, by being forgetful, they experience large amounts of uncertainty in their internal models of the world. We use this to account for recent experimental data demonstrating exactly pessimal replay, fitting model parameters to the individual subjects’ choices.
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spelling pubmed-88096072022-02-03 Optimism and pessimism in optimised replay Antonov, Georgy Gagne, Christopher Eldar, Eran Dayan, Peter PLoS Comput Biol Research Article The replay of task-relevant trajectories is known to contribute to memory consolidation and improved task performance. A wide variety of experimental data show that the content of replayed sequences is highly specific and can be modulated by reward as well as other prominent task variables. However, the rules governing the choice of sequences to be replayed still remain poorly understood. One recent theoretical suggestion is that the prioritization of replay experiences in decision-making problems is based on their effect on the choice of action. We show that this implies that subjects should replay sub-optimal actions that they dysfunctionally choose rather than optimal ones, when, by being forgetful, they experience large amounts of uncertainty in their internal models of the world. We use this to account for recent experimental data demonstrating exactly pessimal replay, fitting model parameters to the individual subjects’ choices. Public Library of Science 2022-01-12 /pmc/articles/PMC8809607/ /pubmed/35020718 http://dx.doi.org/10.1371/journal.pcbi.1009634 Text en © 2022 Antonov et al 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 unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Antonov, Georgy
Gagne, Christopher
Eldar, Eran
Dayan, Peter
Optimism and pessimism in optimised replay
title Optimism and pessimism in optimised replay
title_full Optimism and pessimism in optimised replay
title_fullStr Optimism and pessimism in optimised replay
title_full_unstemmed Optimism and pessimism in optimised replay
title_short Optimism and pessimism in optimised replay
title_sort optimism and pessimism in optimised replay
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8809607/
https://www.ncbi.nlm.nih.gov/pubmed/35020718
http://dx.doi.org/10.1371/journal.pcbi.1009634
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