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
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/267539

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network_name_str CONICET Digital (CONICET)
spelling 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
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv 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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