Variability in functional brain networks predicts expertise during action observation

Autores
Amoruso, Lucía; Ibáñez Barassi, Agustín Mariano; Fonseca, Bruno; Gadea, Sebastián; Sedeño, Lucas; Sigman, Mariano; García, Adolfo Martín; Fraiman, Jacob Ricardo; Fraiman Borrazás, Daniel Edmundo
Año de publicación
2016
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Observing an action performed by another individual activates, in the observer, similar circuits as those involved in the actual execution of that action. This activation is modulated by prior experience; indeed, sustained training in a particular motor domain leads to structural and functional changes in critical brain areas. Here, we capitalized on a novel graph-theory approach to electroencephalographic data (Fraiman et al., 2016) to test whether variability in functional brain networks implicated in Tango observation can discriminate between groups differing in their level of expertise. We found that experts and beginners significantly differed in the functional organization of task-relevant networks. Specifically, networks in expert Tango dancers exhibited less variability and a more robust functional architecture. Notably, these expertise-dependent effects were captured within networks derived from electrophysiological brain activity recorded in a very short time window (2 s). In brief, variability in the organization of task-related networks seems to be a highly sensitive indicator of long-lasting training effects. This finding opens new methodological and theoretical windows to explore the impact of domain-specific expertise on brain plasticity, while highlighting variability as a fruitful measure in neuroimaging research.
Fil: Amoruso, Lucía. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina. Università degli Studi di Udine; Italia
Fil: Ibáñez Barassi, Agustín Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina. Universidad Autónoma del Caribe; Colombia. Universidad Adolfo Ibañez; Chile. Australian Research Council; Australia
Fil: Fonseca, Bruno. Universidad de la República; Uruguay
Fil: Gadea, Sebastián. Universidad de la República; Uruguay
Fil: Sedeño, Lucas. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina
Fil: Sigman, Mariano. Universidad Torcuato di Tella; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: García, Adolfo Martín. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina. Universidad Nacional de Cuyo. Facultad de Educación Elemental y Especial; Argentina
Fil: Fraiman, Jacob Ricardo. Universidad de la República; Uruguay
Fil: Fraiman Borrazás, Daniel Edmundo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de San Andrés; Argentina
Materia
Functional Networks
Predicting Expertise
Statistics on Networks
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/39586
Acceder
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repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Variability in functional brain networks predicts expertise during action observationAmoruso, LucíaIbáñez Barassi, Agustín MarianoFonseca, BrunoGadea, SebastiánSedeño, LucasSigman, MarianoGarcía, Adolfo MartínFraiman, Jacob RicardoFraiman Borrazás, Daniel EdmundoFunctional NetworksPredicting ExpertiseStatistics on Networkshttps://purl.org/becyt/ford/3.1https://purl.org/becyt/ford/3Observing an action performed by another individual activates, in the observer, similar circuits as those involved in the actual execution of that action. This activation is modulated by prior experience; indeed, sustained training in a particular motor domain leads to structural and functional changes in critical brain areas. Here, we capitalized on a novel graph-theory approach to electroencephalographic data (Fraiman et al., 2016) to test whether variability in functional brain networks implicated in Tango observation can discriminate between groups differing in their level of expertise. We found that experts and beginners significantly differed in the functional organization of task-relevant networks. Specifically, networks in expert Tango dancers exhibited less variability and a more robust functional architecture. Notably, these expertise-dependent effects were captured within networks derived from electrophysiological brain activity recorded in a very short time window (2 s). In brief, variability in the organization of task-related networks seems to be a highly sensitive indicator of long-lasting training effects. This finding opens new methodological and theoretical windows to explore the impact of domain-specific expertise on brain plasticity, while highlighting variability as a fruitful measure in neuroimaging research.Fil: Amoruso, Lucía. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina. Università degli Studi di Udine; ItaliaFil: Ibáñez Barassi, Agustín Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina. Universidad Autónoma del Caribe; Colombia. Universidad Adolfo Ibañez; Chile. Australian Research Council; AustraliaFil: Fonseca, Bruno. Universidad de la República; UruguayFil: Gadea, Sebastián. Universidad de la República; UruguayFil: Sedeño, Lucas. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; ArgentinaFil: Sigman, Mariano. Universidad Torcuato di Tella; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: García, Adolfo Martín. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina. Universidad Nacional de Cuyo. Facultad de Educación Elemental y Especial; ArgentinaFil: Fraiman, Jacob Ricardo. Universidad de la República; UruguayFil: Fraiman Borrazás, Daniel Edmundo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de San Andrés; ArgentinaAcademic Press Inc Elsevier Science2016-09info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/39586Amoruso, Lucía; Ibáñez Barassi, Agustín Mariano; Fonseca, Bruno; Gadea, Sebastián; Sedeño, Lucas; et al.; Variability in functional brain networks predicts expertise during action observation; Academic Press Inc Elsevier Science; Neuroimage; 146; 9-2016; 690-7001053-8119CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S105381191630516Xinfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.neuroimage.2016.09.041info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:43:54Zoai:ri.conicet.gov.ar:11336/39586instacron: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:34982025-09-03 09:43:55.159CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Variability in functional brain networks predicts expertise during action observation
title Variability in functional brain networks predicts expertise during action observation
spellingShingle Variability in functional brain networks predicts expertise during action observation
Amoruso, Lucía
Functional Networks
Predicting Expertise
Statistics on Networks
title_short Variability in functional brain networks predicts expertise during action observation
title_full Variability in functional brain networks predicts expertise during action observation
title_fullStr Variability in functional brain networks predicts expertise during action observation
title_full_unstemmed Variability in functional brain networks predicts expertise during action observation
title_sort Variability in functional brain networks predicts expertise during action observation
dc.creator.none.fl_str_mv Amoruso, Lucía
Ibáñez Barassi, Agustín Mariano
Fonseca, Bruno
Gadea, Sebastián
Sedeño, Lucas
Sigman, Mariano
García, Adolfo Martín
Fraiman, Jacob Ricardo
Fraiman Borrazás, Daniel Edmundo
author Amoruso, Lucía
author_facet Amoruso, Lucía
Ibáñez Barassi, Agustín Mariano
Fonseca, Bruno
Gadea, Sebastián
Sedeño, Lucas
Sigman, Mariano
García, Adolfo Martín
Fraiman, Jacob Ricardo
Fraiman Borrazás, Daniel Edmundo
author_role author
author2 Ibáñez Barassi, Agustín Mariano
Fonseca, Bruno
Gadea, Sebastián
Sedeño, Lucas
Sigman, Mariano
García, Adolfo Martín
Fraiman, Jacob Ricardo
Fraiman Borrazás, Daniel Edmundo
author2_role author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Functional Networks
Predicting Expertise
Statistics on Networks
topic Functional Networks
Predicting Expertise
Statistics on Networks
purl_subject.fl_str_mv https://purl.org/becyt/ford/3.1
https://purl.org/becyt/ford/3
dc.description.none.fl_txt_mv Observing an action performed by another individual activates, in the observer, similar circuits as those involved in the actual execution of that action. This activation is modulated by prior experience; indeed, sustained training in a particular motor domain leads to structural and functional changes in critical brain areas. Here, we capitalized on a novel graph-theory approach to electroencephalographic data (Fraiman et al., 2016) to test whether variability in functional brain networks implicated in Tango observation can discriminate between groups differing in their level of expertise. We found that experts and beginners significantly differed in the functional organization of task-relevant networks. Specifically, networks in expert Tango dancers exhibited less variability and a more robust functional architecture. Notably, these expertise-dependent effects were captured within networks derived from electrophysiological brain activity recorded in a very short time window (2 s). In brief, variability in the organization of task-related networks seems to be a highly sensitive indicator of long-lasting training effects. This finding opens new methodological and theoretical windows to explore the impact of domain-specific expertise on brain plasticity, while highlighting variability as a fruitful measure in neuroimaging research.
Fil: Amoruso, Lucía. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina. Università degli Studi di Udine; Italia
Fil: Ibáñez Barassi, Agustín Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina. Universidad Autónoma del Caribe; Colombia. Universidad Adolfo Ibañez; Chile. Australian Research Council; Australia
Fil: Fonseca, Bruno. Universidad de la República; Uruguay
Fil: Gadea, Sebastián. Universidad de la República; Uruguay
Fil: Sedeño, Lucas. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina
Fil: Sigman, Mariano. Universidad Torcuato di Tella; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: García, Adolfo Martín. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina. Universidad Nacional de Cuyo. Facultad de Educación Elemental y Especial; Argentina
Fil: Fraiman, Jacob Ricardo. Universidad de la República; Uruguay
Fil: Fraiman Borrazás, Daniel Edmundo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de San Andrés; Argentina
description Observing an action performed by another individual activates, in the observer, similar circuits as those involved in the actual execution of that action. This activation is modulated by prior experience; indeed, sustained training in a particular motor domain leads to structural and functional changes in critical brain areas. Here, we capitalized on a novel graph-theory approach to electroencephalographic data (Fraiman et al., 2016) to test whether variability in functional brain networks implicated in Tango observation can discriminate between groups differing in their level of expertise. We found that experts and beginners significantly differed in the functional organization of task-relevant networks. Specifically, networks in expert Tango dancers exhibited less variability and a more robust functional architecture. Notably, these expertise-dependent effects were captured within networks derived from electrophysiological brain activity recorded in a very short time window (2 s). In brief, variability in the organization of task-related networks seems to be a highly sensitive indicator of long-lasting training effects. This finding opens new methodological and theoretical windows to explore the impact of domain-specific expertise on brain plasticity, while highlighting variability as a fruitful measure in neuroimaging research.
publishDate 2016
dc.date.none.fl_str_mv 2016-09
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/11336/39586
Amoruso, Lucía; Ibáñez Barassi, Agustín Mariano; Fonseca, Bruno; Gadea, Sebastián; Sedeño, Lucas; et al.; Variability in functional brain networks predicts expertise during action observation; Academic Press Inc Elsevier Science; Neuroimage; 146; 9-2016; 690-700
1053-8119
CONICET Digital
CONICET
url http://hdl.handle.net/11336/39586
identifier_str_mv Amoruso, Lucía; Ibáñez Barassi, Agustín Mariano; Fonseca, Bruno; Gadea, Sebastián; Sedeño, Lucas; et al.; Variability in functional brain networks predicts expertise during action observation; Academic Press Inc Elsevier Science; Neuroimage; 146; 9-2016; 690-700
1053-8119
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://www.sciencedirect.com/science/article/pii/S105381191630516X
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.neuroimage.2016.09.041
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Academic Press Inc Elsevier Science
publisher.none.fl_str_mv Academic Press Inc Elsevier Science
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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