Competition between parallel sensorimotor learning systems
- Autores
- Albert, Scott T.; Jang, Jihoon; Modchalingam, Shanaathanan; 't Hart, Bernard Marius; Henriques, Denise; Lerner, Gonzalo Martin; Della Maggiore, Valeria Monica; Haith, Adrian M.; Krakauer, John W.; Shadmehr, Reza
- Año de publicación
- 2022
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- 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.
Fil: Albert, Scott T.. University Johns Hopkins; Estados Unidos. University of North Carolina; Estados Unidos
Fil: Jang, Jihoon. University Johns Hopkins; Estados Unidos. Vanderbilt University School of Medicine; Estados Unidos
Fil: Modchalingam, Shanaathanan. York University; Canadá
Fil: 't Hart, Bernard Marius. York University; Canadá
Fil: Henriques, Denise. York University; Canadá
Fil: Lerner, Gonzalo Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Fisiología y Biofísica Bernardo Houssay. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Fisiología y Biofísica Bernardo Houssay; Argentina
Fil: Della Maggiore, Valeria Monica. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Fisiología y Biofísica Bernardo Houssay. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Fisiología y Biofísica Bernardo Houssay; Argentina
Fil: Haith, Adrian M.. University Johns Hopkins; Estados Unidos
Fil: Krakauer, John W.. University Johns Hopkins; Estados Unidos
Fil: Shadmehr, Reza. University Johns Hopkins; Estados Unidos - Materia
-
motor
learning
competition
explicit/implicit - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by/2.5/ar/
- Repositorio
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/267539
Ver los metadatos del registro completo
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Competition between parallel sensorimotor learning systemsAlbert, Scott T.Jang, JihoonModchalingam, Shanaathanan't Hart, Bernard MariusHenriques, DeniseLerner, Gonzalo MartinDella Maggiore, Valeria MonicaHaith, Adrian M.Krakauer, John W.Shadmehr, Rezamotorlearningcompetitionexplicit/implicithttps://purl.org/becyt/ford/3.1https://purl.org/becyt/ford/3Sensorimotor 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.Fil: Albert, Scott T.. University Johns Hopkins; Estados Unidos. University of North Carolina; Estados UnidosFil: Jang, Jihoon. University Johns Hopkins; Estados Unidos. Vanderbilt University School of Medicine; Estados UnidosFil: Modchalingam, Shanaathanan. York University; CanadáFil: 't Hart, Bernard Marius. York University; CanadáFil: Henriques, Denise. York University; CanadáFil: Lerner, Gonzalo Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Fisiología y Biofísica Bernardo Houssay. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Fisiología y Biofísica Bernardo Houssay; ArgentinaFil: Della Maggiore, Valeria Monica. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Fisiología y Biofísica Bernardo Houssay. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Fisiología y Biofísica Bernardo Houssay; ArgentinaFil: Haith, Adrian M.. University Johns Hopkins; Estados UnidosFil: Krakauer, John W.. University Johns Hopkins; Estados UnidosFil: Shadmehr, Reza. University Johns Hopkins; Estados UnidoseLife Sciences Publications Ltd.2022-02info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/267539Albert, Scott T.; Jang, Jihoon; Modchalingam, Shanaathanan; 't Hart, Bernard Marius; Henriques, Denise; et al.; Competition between parallel sensorimotor learning systems; eLife Sciences Publications Ltd.; eLife; 11; 2-2022; 1-812050-084XCONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://elifesciences.org/articles/65361info:eu-repo/semantics/altIdentifier/doi/10.7554/eLife.65361info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:37:00Zoai:ri.conicet.gov.ar:11336/267539instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:37:00.776CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
Competition between parallel sensorimotor learning systems |
title |
Competition between parallel sensorimotor learning systems |
spellingShingle |
Competition between parallel sensorimotor learning systems Albert, Scott T. motor learning competition explicit/implicit |
title_short |
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_sort |
Competition between parallel sensorimotor learning systems |
dc.creator.none.fl_str_mv |
Albert, Scott T. Jang, Jihoon Modchalingam, Shanaathanan 't Hart, Bernard Marius Henriques, Denise Lerner, Gonzalo Martin Della Maggiore, Valeria Monica Haith, Adrian M. Krakauer, John W. Shadmehr, Reza |
author |
Albert, Scott T. |
author_facet |
Albert, Scott T. Jang, Jihoon Modchalingam, Shanaathanan 't Hart, Bernard Marius Henriques, Denise Lerner, Gonzalo Martin Della Maggiore, Valeria Monica Haith, Adrian M. Krakauer, John W. Shadmehr, Reza |
author_role |
author |
author2 |
Jang, Jihoon Modchalingam, Shanaathanan 't Hart, Bernard Marius Henriques, Denise Lerner, Gonzalo Martin Della Maggiore, Valeria Monica Haith, Adrian M. Krakauer, John W. Shadmehr, Reza |
author2_role |
author author author author author author author author author |
dc.subject.none.fl_str_mv |
motor learning competition explicit/implicit |
topic |
motor learning competition explicit/implicit |
purl_subject.fl_str_mv |
https://purl.org/becyt/ford/3.1 https://purl.org/becyt/ford/3 |
dc.description.none.fl_txt_mv |
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. Fil: Albert, Scott T.. University Johns Hopkins; Estados Unidos. University of North Carolina; Estados Unidos Fil: Jang, Jihoon. University Johns Hopkins; Estados Unidos. Vanderbilt University School of Medicine; Estados Unidos Fil: Modchalingam, Shanaathanan. York University; Canadá Fil: 't Hart, Bernard Marius. York University; Canadá Fil: Henriques, Denise. York University; Canadá Fil: Lerner, Gonzalo Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Fisiología y Biofísica Bernardo Houssay. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Fisiología y Biofísica Bernardo Houssay; Argentina Fil: Della Maggiore, Valeria Monica. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Fisiología y Biofísica Bernardo Houssay. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Fisiología y Biofísica Bernardo Houssay; Argentina Fil: Haith, Adrian M.. University Johns Hopkins; Estados Unidos Fil: Krakauer, John W.. University Johns Hopkins; Estados Unidos Fil: Shadmehr, Reza. University Johns Hopkins; Estados Unidos |
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. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-02 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
format |
article |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://hdl.handle.net/11336/267539 Albert, Scott T.; Jang, Jihoon; Modchalingam, Shanaathanan; 't Hart, Bernard Marius; Henriques, Denise; et al.; Competition between parallel sensorimotor learning systems; eLife Sciences Publications Ltd.; eLife; 11; 2-2022; 1-81 2050-084X CONICET Digital CONICET |
url |
http://hdl.handle.net/11336/267539 |
identifier_str_mv |
Albert, Scott T.; Jang, Jihoon; Modchalingam, Shanaathanan; 't Hart, Bernard Marius; Henriques, Denise; et al.; Competition between parallel sensorimotor learning systems; eLife Sciences Publications Ltd.; eLife; 11; 2-2022; 1-81 2050-084X CONICET Digital CONICET |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/url/https://elifesciences.org/articles/65361 info:eu-repo/semantics/altIdentifier/doi/10.7554/eLife.65361 |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/2.5/ar/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by/2.5/ar/ |
dc.format.none.fl_str_mv |
application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
eLife Sciences Publications Ltd. |
publisher.none.fl_str_mv |
eLife Sciences Publications Ltd. |
dc.source.none.fl_str_mv |
reponame:CONICET Digital (CONICET) instname:Consejo Nacional de Investigaciones Científicas y Técnicas |
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CONICET Digital (CONICET) |
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CONICET Digital (CONICET) |
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Consejo Nacional de Investigaciones Científicas y Técnicas |
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CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.mail.fl_str_mv |
dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar |
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13.069144 |