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Implicit reward-based motor learning
Binary feedback, providing information solely about task success or failure, can be sufficient to drive motor learning. While binary feedback can induce explicit adjustments in movement strategy, it remains unclear if this type of feedback also induces implicit learning. We examined this question in...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10471724/ https://www.ncbi.nlm.nih.gov/pubmed/37580611 http://dx.doi.org/10.1007/s00221-023-06683-w |
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author | van Mastrigt, Nina M. Tsay, Jonathan S. Wang, Tianhe Avraham, Guy Abram, Sabrina J. van der Kooij, Katinka Smeets, Jeroen B. J. Ivry, Richard B. |
author_facet | van Mastrigt, Nina M. Tsay, Jonathan S. Wang, Tianhe Avraham, Guy Abram, Sabrina J. van der Kooij, Katinka Smeets, Jeroen B. J. Ivry, Richard B. |
author_sort | van Mastrigt, Nina M. |
collection | PubMed |
description | Binary feedback, providing information solely about task success or failure, can be sufficient to drive motor learning. While binary feedback can induce explicit adjustments in movement strategy, it remains unclear if this type of feedback also induces implicit learning. We examined this question in a center-out reaching task by gradually moving an invisible reward zone away from a visual target to a final rotation of 7.5° or 25° in a between-group design. Participants received binary feedback, indicating if the movement intersected the reward zone. By the end of the training, both groups modified their reach angle by about 95% of the rotation. We quantified implicit learning by measuring performance in a subsequent no-feedback aftereffect phase, in which participants were told to forgo any adopted movement strategies and reach directly to the visual target. The results showed a small, but robust (2–3°) aftereffect in both groups, highlighting that binary feedback elicits implicit learning. Notably, for both groups, reaches to two flanking generalization targets were biased in the same direction as the aftereffect. This pattern is at odds with the hypothesis that implicit learning is a form of use-dependent learning. Rather, the results suggest that binary feedback can be sufficient to recalibrate a sensorimotor map. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00221-023-06683-w. |
format | Online Article Text |
id | pubmed-10471724 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-104717242023-09-02 Implicit reward-based motor learning van Mastrigt, Nina M. Tsay, Jonathan S. Wang, Tianhe Avraham, Guy Abram, Sabrina J. van der Kooij, Katinka Smeets, Jeroen B. J. Ivry, Richard B. Exp Brain Res Research Article Binary feedback, providing information solely about task success or failure, can be sufficient to drive motor learning. While binary feedback can induce explicit adjustments in movement strategy, it remains unclear if this type of feedback also induces implicit learning. We examined this question in a center-out reaching task by gradually moving an invisible reward zone away from a visual target to a final rotation of 7.5° or 25° in a between-group design. Participants received binary feedback, indicating if the movement intersected the reward zone. By the end of the training, both groups modified their reach angle by about 95% of the rotation. We quantified implicit learning by measuring performance in a subsequent no-feedback aftereffect phase, in which participants were told to forgo any adopted movement strategies and reach directly to the visual target. The results showed a small, but robust (2–3°) aftereffect in both groups, highlighting that binary feedback elicits implicit learning. Notably, for both groups, reaches to two flanking generalization targets were biased in the same direction as the aftereffect. This pattern is at odds with the hypothesis that implicit learning is a form of use-dependent learning. Rather, the results suggest that binary feedback can be sufficient to recalibrate a sensorimotor map. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00221-023-06683-w. Springer Berlin Heidelberg 2023-08-14 2023 /pmc/articles/PMC10471724/ /pubmed/37580611 http://dx.doi.org/10.1007/s00221-023-06683-w Text en © The Author(s) 2023 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 | Research Article van Mastrigt, Nina M. Tsay, Jonathan S. Wang, Tianhe Avraham, Guy Abram, Sabrina J. van der Kooij, Katinka Smeets, Jeroen B. J. Ivry, Richard B. Implicit reward-based motor learning |
title | Implicit reward-based motor learning |
title_full | Implicit reward-based motor learning |
title_fullStr | Implicit reward-based motor learning |
title_full_unstemmed | Implicit reward-based motor learning |
title_short | Implicit reward-based motor learning |
title_sort | implicit reward-based motor learning |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10471724/ https://www.ncbi.nlm.nih.gov/pubmed/37580611 http://dx.doi.org/10.1007/s00221-023-06683-w |
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