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Competition between parallel sensorimotor learning systems
Sensorimotor learning is supported by at least two parallel systems: a strategic process that benefits from explicit knowledge and an implicit process that adapts subconsciously. How do these systems interact? Does one system’s contributions suppress the other, or do they operate independently? Here...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9068222/ https://www.ncbi.nlm.nih.gov/pubmed/35225229 http://dx.doi.org/10.7554/eLife.65361 |
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author | Albert, Scott T Jang, Jihoon Modchalingam, Shanaathanan 't Hart, Bernard Marius Henriques, Denise Lerner, Gonzalo Della-Maggiore, Valeria Haith, Adrian M Krakauer, John W Shadmehr, Reza |
author_facet | Albert, Scott T Jang, Jihoon Modchalingam, Shanaathanan 't Hart, Bernard Marius Henriques, Denise Lerner, Gonzalo Della-Maggiore, Valeria Haith, Adrian M Krakauer, John W Shadmehr, Reza |
author_sort | Albert, Scott T |
collection | PubMed |
description | Sensorimotor learning is supported by at least two parallel systems: a strategic process that benefits from explicit knowledge and an implicit process that adapts subconsciously. How do these systems interact? Does one system’s contributions suppress the other, or do they operate independently? Here, we illustrate that during reaching, implicit and explicit systems both learn from visual target errors. This shared error leads to competition such that an increase in the explicit system’s response siphons away resources that are needed for implicit adaptation, thus reducing its learning. As a result, steady-state implicit learning can vary across experimental conditions, due to changes in strategy. Furthermore, strategies can mask changes in implicit learning properties, such as its error sensitivity. These ideas, however, become more complex in conditions where subjects adapt using multiple visual landmarks, a situation which introduces learning from sensory prediction errors in addition to target errors. These two types of implicit errors can oppose each other, leading to another type of competition. Thus, during sensorimotor adaptation, implicit and explicit learning systems compete for a common resource: error. |
format | Online Article Text |
id | pubmed-9068222 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-90682222022-05-05 Competition between parallel sensorimotor learning systems Albert, Scott T Jang, Jihoon Modchalingam, Shanaathanan 't Hart, Bernard Marius Henriques, Denise Lerner, Gonzalo Della-Maggiore, Valeria Haith, Adrian M Krakauer, John W Shadmehr, Reza eLife Neuroscience Sensorimotor learning is supported by at least two parallel systems: a strategic process that benefits from explicit knowledge and an implicit process that adapts subconsciously. How do these systems interact? Does one system’s contributions suppress the other, or do they operate independently? Here, we illustrate that during reaching, implicit and explicit systems both learn from visual target errors. This shared error leads to competition such that an increase in the explicit system’s response siphons away resources that are needed for implicit adaptation, thus reducing its learning. As a result, steady-state implicit learning can vary across experimental conditions, due to changes in strategy. Furthermore, strategies can mask changes in implicit learning properties, such as its error sensitivity. These ideas, however, become more complex in conditions where subjects adapt using multiple visual landmarks, a situation which introduces learning from sensory prediction errors in addition to target errors. These two types of implicit errors can oppose each other, leading to another type of competition. Thus, during sensorimotor adaptation, implicit and explicit learning systems compete for a common resource: error. eLife Sciences Publications, Ltd 2022-02-28 /pmc/articles/PMC9068222/ /pubmed/35225229 http://dx.doi.org/10.7554/eLife.65361 Text en © 2022, Albert et al https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Neuroscience Albert, Scott T Jang, Jihoon Modchalingam, Shanaathanan 't Hart, Bernard Marius Henriques, Denise Lerner, Gonzalo Della-Maggiore, Valeria Haith, Adrian M Krakauer, John W Shadmehr, Reza Competition between parallel sensorimotor learning systems |
title | Competition between parallel sensorimotor learning systems |
title_full | Competition between parallel sensorimotor learning systems |
title_fullStr | Competition between parallel sensorimotor learning systems |
title_full_unstemmed | Competition between parallel sensorimotor learning systems |
title_short | Competition between parallel sensorimotor learning systems |
title_sort | competition between parallel sensorimotor learning systems |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9068222/ https://www.ncbi.nlm.nih.gov/pubmed/35225229 http://dx.doi.org/10.7554/eLife.65361 |
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