Extracting the fingerprints of sequences of random rhythmic auditory stimuli from electrophysiological data

Autores
Najman, Fernando A.; Galves, Antonio; Svarc, Marcela; Vargas, Claudia D.
Año de publicación
2025
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
It has been classically conjectured that the brain assigns probabilistic models to sequences of stimuli. An important issue associated with this conjecture is the identification of the classes of models used by the brain to perform this task. We address this issue by using a new clustering procedure for sets of electroencephalographic (EEG) data recorded from participants exposed to a sequence of auditory stimuli generated by a stochastic chain. This clustering procedure indicates that the brain uses the recurrent occurrences of a regular auditory stimulus in order to build a model.
Fil: Najman, Fernando A.. Universidade Estadual de Campinas; Brasil
Fil: Galves, Antonio. Universidade de Sao Paulo; Brasil
Fil: Svarc, Marcela. Universidad de San Andrés. Departamento de Matemáticas y Ciencias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Vargas, Claudia D.. Universidade Federal do Estado do Rio de Janeiro; Brasil
Materia
Concesus clustering
statistical regularities in the brain
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/261422
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/261422
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Extracting the fingerprints of sequences of random rhythmic auditory stimuli from electrophysiological dataNajman, Fernando A.Galves, AntonioSvarc, MarcelaVargas, Claudia D.Concesus clusteringstatistical regularities in the brainhttps://purl.org/becyt/ford/1.1https://purl.org/becyt/ford/1It has been classically conjectured that the brain assigns probabilistic models to sequences of stimuli. An important issue associated with this conjecture is the identification of the classes of models used by the brain to perform this task. We address this issue by using a new clustering procedure for sets of electroencephalographic (EEG) data recorded from participants exposed to a sequence of auditory stimuli generated by a stochastic chain. This clustering procedure indicates that the brain uses the recurrent occurrences of a regular auditory stimulus in order to build a model.Fil: Najman, Fernando A.. Universidade Estadual de Campinas; BrasilFil: Galves, Antonio. Universidade de Sao Paulo; BrasilFil: Svarc, Marcela. Universidad de San Andrés. Departamento de Matemáticas y Ciencias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Vargas, Claudia D.. Universidade Federal do Estado do Rio de Janeiro; BrasilPublic Library of Science2025-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/261422Najman, Fernando A.; Galves, Antonio; Svarc, Marcela; Vargas, Claudia D.; Extracting the fingerprints of sequences of random rhythmic auditory stimuli from electrophysiological data; Public Library of Science; PLOS Computational Biology; 21; 1; 1-2025; 1-181553-7358CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://dx.plos.org/10.1371/journal.pcbi.1012765info:eu-repo/semantics/altIdentifier/doi/10.1371/journal.pcbi.1012765info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:58:27Zoai:ri.conicet.gov.ar:11336/261422instacron: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 09:58:27.88CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Extracting the fingerprints of sequences of random rhythmic auditory stimuli from electrophysiological data
title Extracting the fingerprints of sequences of random rhythmic auditory stimuli from electrophysiological data
spellingShingle Extracting the fingerprints of sequences of random rhythmic auditory stimuli from electrophysiological data
Najman, Fernando A.
Concesus clustering
statistical regularities in the brain
title_short Extracting the fingerprints of sequences of random rhythmic auditory stimuli from electrophysiological data
title_full Extracting the fingerprints of sequences of random rhythmic auditory stimuli from electrophysiological data
title_fullStr Extracting the fingerprints of sequences of random rhythmic auditory stimuli from electrophysiological data
title_full_unstemmed Extracting the fingerprints of sequences of random rhythmic auditory stimuli from electrophysiological data
title_sort Extracting the fingerprints of sequences of random rhythmic auditory stimuli from electrophysiological data
dc.creator.none.fl_str_mv Najman, Fernando A.
Galves, Antonio
Svarc, Marcela
Vargas, Claudia D.
author Najman, Fernando A.
author_facet Najman, Fernando A.
Galves, Antonio
Svarc, Marcela
Vargas, Claudia D.
author_role author
author2 Galves, Antonio
Svarc, Marcela
Vargas, Claudia D.
author2_role author
author
author
dc.subject.none.fl_str_mv Concesus clustering
statistical regularities in the brain
topic Concesus clustering
statistical regularities in the brain
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.1
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv It has been classically conjectured that the brain assigns probabilistic models to sequences of stimuli. An important issue associated with this conjecture is the identification of the classes of models used by the brain to perform this task. We address this issue by using a new clustering procedure for sets of electroencephalographic (EEG) data recorded from participants exposed to a sequence of auditory stimuli generated by a stochastic chain. This clustering procedure indicates that the brain uses the recurrent occurrences of a regular auditory stimulus in order to build a model.
Fil: Najman, Fernando A.. Universidade Estadual de Campinas; Brasil
Fil: Galves, Antonio. Universidade de Sao Paulo; Brasil
Fil: Svarc, Marcela. Universidad de San Andrés. Departamento de Matemáticas y Ciencias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Vargas, Claudia D.. Universidade Federal do Estado do Rio de Janeiro; Brasil
description It has been classically conjectured that the brain assigns probabilistic models to sequences of stimuli. An important issue associated with this conjecture is the identification of the classes of models used by the brain to perform this task. We address this issue by using a new clustering procedure for sets of electroencephalographic (EEG) data recorded from participants exposed to a sequence of auditory stimuli generated by a stochastic chain. This clustering procedure indicates that the brain uses the recurrent occurrences of a regular auditory stimulus in order to build a model.
publishDate 2025
dc.date.none.fl_str_mv 2025-01
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/11336/261422
Najman, Fernando A.; Galves, Antonio; Svarc, Marcela; Vargas, Claudia D.; Extracting the fingerprints of sequences of random rhythmic auditory stimuli from electrophysiological data; Public Library of Science; PLOS Computational Biology; 21; 1; 1-2025; 1-18
1553-7358
CONICET Digital
CONICET
url http://hdl.handle.net/11336/261422
identifier_str_mv Najman, Fernando A.; Galves, Antonio; Svarc, Marcela; Vargas, Claudia D.; Extracting the fingerprints of sequences of random rhythmic auditory stimuli from electrophysiological data; Public Library of Science; PLOS Computational Biology; 21; 1; 1-2025; 1-18
1553-7358
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://dx.plos.org/10.1371/journal.pcbi.1012765
info:eu-repo/semantics/altIdentifier/doi/10.1371/journal.pcbi.1012765
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Public Library of Science
publisher.none.fl_str_mv Public Library of 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
_version_ 1844613742029963264
score 13.070432

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