Further results on why a point process is effective for estimating correlation between brain regions

Autores
Cifre, I.; Zarepour Nasir Abadi, Mahdi; Horovitz, S. G.; Cannas, Sergio Alejandro; Chialvo, Dante Renato
Año de publicación
2020
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Signals from brain functional magnetic resonance imaging (fMRI) can be efficiently represented by a sparse spatiotemporal point process, according to a recently introduced heuristic signal processing scheme. This approach has already been validated for relevant conditions, demonstrating that it preserves and compresses a surprisingly large fraction of the signal information. Here we investigated the conditions necessary for such an approach to succeed, as well as the underlying reasons, using real fMRI data and a simulated dataset. The results show that the key lies in the temporal correlation properties of the time series under consideration. It was found that signals with slowly decaying autocorrelations are particularly suitable for this type of compression, where inflection points contain most of the information.
Fil: Cifre, I.. Universitat Ramon Llull; España
Fil: Zarepour Nasir Abadi, Mahdi. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Física Enrique Gaviola. Universidad Nacional de Córdoba. Instituto de Física Enrique Gaviola; Argentina
Fil: Horovitz, S. G.. National Institutes of Health; Estados Unidos
Fil: Cannas, Sergio Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Física Enrique Gaviola. Universidad Nacional de Córdoba. Instituto de Física Enrique Gaviola; Argentina
Fil: Chialvo, Dante Renato. Universidad Nacional de San Martín. Escuela de Ciencia y Tecnología; Argentina
Materia
TIME SERIES
POINT PROCESSES
FUNCTIONAL CONNECTIVITY
RESTING STATES
DYNAMICS
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:11336/145417
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Further results on why a point process is effective for estimating correlation between brain regionsCifre, I.Zarepour Nasir Abadi, MahdiHorovitz, S. G.Cannas, Sergio AlejandroChialvo, Dante RenatoTIME SERIESPOINT PROCESSESFUNCTIONAL CONNECTIVITYRESTING STATESDYNAMICShttps://purl.org/becyt/ford/1.3https://purl.org/becyt/ford/1Signals from brain functional magnetic resonance imaging (fMRI) can be efficiently represented by a sparse spatiotemporal point process, according to a recently introduced heuristic signal processing scheme. This approach has already been validated for relevant conditions, demonstrating that it preserves and compresses a surprisingly large fraction of the signal information. Here we investigated the conditions necessary for such an approach to succeed, as well as the underlying reasons, using real fMRI data and a simulated dataset. The results show that the key lies in the temporal correlation properties of the time series under consideration. It was found that signals with slowly decaying autocorrelations are particularly suitable for this type of compression, where inflection points contain most of the information.Fil: Cifre, I.. Universitat Ramon Llull; EspañaFil: Zarepour Nasir Abadi, Mahdi. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Física Enrique Gaviola. Universidad Nacional de Córdoba. Instituto de Física Enrique Gaviola; ArgentinaFil: Horovitz, S. G.. National Institutes of Health; Estados UnidosFil: Cannas, Sergio Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Física Enrique Gaviola. Universidad Nacional de Córdoba. Instituto de Física Enrique Gaviola; ArgentinaFil: Chialvo, Dante Renato. Universidad Nacional de San Martín. Escuela de Ciencia y Tecnología; ArgentinaPapers in Physics2020-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/145417Cifre, I.; Zarepour Nasir Abadi, Mahdi; Horovitz, S. G.; Cannas, Sergio Alejandro; Chialvo, Dante Renato; Further results on why a point process is effective for estimating correlation between brain regions; Papers in Physics; Papers in Physics; 12; 6-2020; 1-81852-4249CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.papersinphysics.org/papersinphysics/article/view/515info:eu-repo/semantics/altIdentifier/doi/10.4279/pip.120003info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-22T11:32:02Zoai:ri.conicet.gov.ar:11336/145417instacron: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:34982025-10-22 11:32:02.949CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Further results on why a point process is effective for estimating correlation between brain regions
title Further results on why a point process is effective for estimating correlation between brain regions
spellingShingle Further results on why a point process is effective for estimating correlation between brain regions
Cifre, I.
TIME SERIES
POINT PROCESSES
FUNCTIONAL CONNECTIVITY
RESTING STATES
DYNAMICS
title_short Further results on why a point process is effective for estimating correlation between brain regions
title_full Further results on why a point process is effective for estimating correlation between brain regions
title_fullStr Further results on why a point process is effective for estimating correlation between brain regions
title_full_unstemmed Further results on why a point process is effective for estimating correlation between brain regions
title_sort Further results on why a point process is effective for estimating correlation between brain regions
dc.creator.none.fl_str_mv Cifre, I.
Zarepour Nasir Abadi, Mahdi
Horovitz, S. G.
Cannas, Sergio Alejandro
Chialvo, Dante Renato
author Cifre, I.
author_facet Cifre, I.
Zarepour Nasir Abadi, Mahdi
Horovitz, S. G.
Cannas, Sergio Alejandro
Chialvo, Dante Renato
author_role author
author2 Zarepour Nasir Abadi, Mahdi
Horovitz, S. G.
Cannas, Sergio Alejandro
Chialvo, Dante Renato
author2_role author
author
author
author
dc.subject.none.fl_str_mv TIME SERIES
POINT PROCESSES
FUNCTIONAL CONNECTIVITY
RESTING STATES
DYNAMICS
topic TIME SERIES
POINT PROCESSES
FUNCTIONAL CONNECTIVITY
RESTING STATES
DYNAMICS
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.3
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Signals from brain functional magnetic resonance imaging (fMRI) can be efficiently represented by a sparse spatiotemporal point process, according to a recently introduced heuristic signal processing scheme. This approach has already been validated for relevant conditions, demonstrating that it preserves and compresses a surprisingly large fraction of the signal information. Here we investigated the conditions necessary for such an approach to succeed, as well as the underlying reasons, using real fMRI data and a simulated dataset. The results show that the key lies in the temporal correlation properties of the time series under consideration. It was found that signals with slowly decaying autocorrelations are particularly suitable for this type of compression, where inflection points contain most of the information.
Fil: Cifre, I.. Universitat Ramon Llull; España
Fil: Zarepour Nasir Abadi, Mahdi. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Física Enrique Gaviola. Universidad Nacional de Córdoba. Instituto de Física Enrique Gaviola; Argentina
Fil: Horovitz, S. G.. National Institutes of Health; Estados Unidos
Fil: Cannas, Sergio Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Física Enrique Gaviola. Universidad Nacional de Córdoba. Instituto de Física Enrique Gaviola; Argentina
Fil: Chialvo, Dante Renato. Universidad Nacional de San Martín. Escuela de Ciencia y Tecnología; Argentina
description Signals from brain functional magnetic resonance imaging (fMRI) can be efficiently represented by a sparse spatiotemporal point process, according to a recently introduced heuristic signal processing scheme. This approach has already been validated for relevant conditions, demonstrating that it preserves and compresses a surprisingly large fraction of the signal information. Here we investigated the conditions necessary for such an approach to succeed, as well as the underlying reasons, using real fMRI data and a simulated dataset. The results show that the key lies in the temporal correlation properties of the time series under consideration. It was found that signals with slowly decaying autocorrelations are particularly suitable for this type of compression, where inflection points contain most of the information.
publishDate 2020
dc.date.none.fl_str_mv 2020-06
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/11336/145417
Cifre, I.; Zarepour Nasir Abadi, Mahdi; Horovitz, S. G.; Cannas, Sergio Alejandro; Chialvo, Dante Renato; Further results on why a point process is effective for estimating correlation between brain regions; Papers in Physics; Papers in Physics; 12; 6-2020; 1-8
1852-4249
CONICET Digital
CONICET
url http://hdl.handle.net/11336/145417
identifier_str_mv Cifre, I.; Zarepour Nasir Abadi, Mahdi; Horovitz, S. G.; Cannas, Sergio Alejandro; Chialvo, Dante Renato; Further results on why a point process is effective for estimating correlation between brain regions; Papers in Physics; Papers in Physics; 12; 6-2020; 1-8
1852-4249
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.papersinphysics.org/papersinphysics/article/view/515
info:eu-repo/semantics/altIdentifier/doi/10.4279/pip.120003
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
dc.publisher.none.fl_str_mv Papers in Physics
publisher.none.fl_str_mv Papers in Physics
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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score 12.982451

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