Revisiting nonlinear functional brain co-activations: Directed, dynamic, and delayed

Autores
Cifre, Ignacio; Miller Flores, Maria T.; Penalba, Lucia; Ochab, Jeremi K.; Chialvo, Dante Renato
Año de publicación
2021
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The center stage of neuro-imaging is currently occupied by studies of functional correlations between brain regions. These correlations define the brain functional networks, which are the most frequently used framework to represent and interpret a variety of experimental findings. In the previous study, we first demonstrated that the relatively stronger blood oxygenated level dependent (BOLD) activations contain most of the information relevant to understand functional connectivity, and subsequent work confirmed that a large compression of the original signals can be obtained without significant loss of information. In this study, we revisit the correlation properties of these epochs to define a measure of nonlinear dynamic directed functional connectivity (nldFC) across regions of interest. We show that the proposed metric provides at once, without extensive numerical complications, directed information of the functional correlations, as well as a measure of temporal lags across regions, overall offering a different and complementary perspective in the analysis of brain co-activation patterns. In this study, we provide further details for the computations of these measures and for a proof of concept based on replicating existing results from an Autistic Syndrome database, and discuss the main features and advantages of the proposed strategy for the study of brain functional correlations.
Fil: Cifre, Ignacio. Universitat Ramon Llull; España. Universidad Nacional de San Martin. Escuela de Ciencia y Tecnologia. Centro de Estudios Multidisciplinarios En Sistemas Complejos y Ciencias del Cerebro.; Argentina
Fil: Miller Flores, Maria T.. Universidad Nacional de San Martin. Escuela de Ciencia y Tecnologia. Centro de Estudios Multidisciplinarios En Sistemas Complejos y Ciencias del Cerebro.; Argentina
Fil: Penalba, Lucia. Universitat Ramon Llull; España
Fil: Ochab, Jeremi K.. Jagiellonian University; Polonia
Fil: Chialvo, Dante Renato. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de San Martin. Escuela de Ciencia y Tecnologia. Centro de Estudios Multidisciplinarios En Sistemas Complejos y Ciencias del Cerebro.; Argentina
Materia
AUTISM (ASD)
DYNAMIC FUNCTIONAL CONNECTIVITY
FMRI
FUNCTIONAL CONNECTIVITY
RESTING STATE NETWORKS
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:11336/155440
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Revisiting nonlinear functional brain co-activations: Directed, dynamic, and delayedCifre, IgnacioMiller Flores, Maria T.Penalba, LuciaOchab, Jeremi K.Chialvo, Dante RenatoAUTISM (ASD)DYNAMIC FUNCTIONAL CONNECTIVITYFMRIFUNCTIONAL CONNECTIVITYRESTING STATE NETWORKShttps://purl.org/becyt/ford/3.1https://purl.org/becyt/ford/3The center stage of neuro-imaging is currently occupied by studies of functional correlations between brain regions. These correlations define the brain functional networks, which are the most frequently used framework to represent and interpret a variety of experimental findings. In the previous study, we first demonstrated that the relatively stronger blood oxygenated level dependent (BOLD) activations contain most of the information relevant to understand functional connectivity, and subsequent work confirmed that a large compression of the original signals can be obtained without significant loss of information. In this study, we revisit the correlation properties of these epochs to define a measure of nonlinear dynamic directed functional connectivity (nldFC) across regions of interest. We show that the proposed metric provides at once, without extensive numerical complications, directed information of the functional correlations, as well as a measure of temporal lags across regions, overall offering a different and complementary perspective in the analysis of brain co-activation patterns. In this study, we provide further details for the computations of these measures and for a proof of concept based on replicating existing results from an Autistic Syndrome database, and discuss the main features and advantages of the proposed strategy for the study of brain functional correlations.Fil: Cifre, Ignacio. Universitat Ramon Llull; España. Universidad Nacional de San Martin. Escuela de Ciencia y Tecnologia. Centro de Estudios Multidisciplinarios En Sistemas Complejos y Ciencias del Cerebro.; ArgentinaFil: Miller Flores, Maria T.. Universidad Nacional de San Martin. Escuela de Ciencia y Tecnologia. Centro de Estudios Multidisciplinarios En Sistemas Complejos y Ciencias del Cerebro.; ArgentinaFil: Penalba, Lucia. Universitat Ramon Llull; EspañaFil: Ochab, Jeremi K.. Jagiellonian University; PoloniaFil: Chialvo, Dante Renato. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de San Martin. Escuela de Ciencia y Tecnologia. Centro de Estudios Multidisciplinarios En Sistemas Complejos y Ciencias del Cerebro.; ArgentinaFrontiers Media2021-10-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/155440Cifre, Ignacio; Miller Flores, Maria T.; Penalba, Lucia; Ochab, Jeremi K.; Chialvo, Dante Renato; Revisiting nonlinear functional brain co-activations: Directed, dynamic, and delayed; Frontiers Media; Frontiers in Neuroscience; 15; 700171; 12-10-2021; 1-131662-45481662-453XCONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.frontiersin.org/articles/10.3389/fnins.2021.700171/fullinfo:eu-repo/semantics/altIdentifier/doi/10.3389/fnins.2021.700171info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-10T13:20:51Zoai:ri.conicet.gov.ar:11336/155440instacron: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:34982025-09-10 13:20:51.483CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Revisiting nonlinear functional brain co-activations: Directed, dynamic, and delayed
title Revisiting nonlinear functional brain co-activations: Directed, dynamic, and delayed
spellingShingle Revisiting nonlinear functional brain co-activations: Directed, dynamic, and delayed
Cifre, Ignacio
AUTISM (ASD)
DYNAMIC FUNCTIONAL CONNECTIVITY
FMRI
FUNCTIONAL CONNECTIVITY
RESTING STATE NETWORKS
title_short Revisiting nonlinear functional brain co-activations: Directed, dynamic, and delayed
title_full Revisiting nonlinear functional brain co-activations: Directed, dynamic, and delayed
title_fullStr Revisiting nonlinear functional brain co-activations: Directed, dynamic, and delayed
title_full_unstemmed Revisiting nonlinear functional brain co-activations: Directed, dynamic, and delayed
title_sort Revisiting nonlinear functional brain co-activations: Directed, dynamic, and delayed
dc.creator.none.fl_str_mv Cifre, Ignacio
Miller Flores, Maria T.
Penalba, Lucia
Ochab, Jeremi K.
Chialvo, Dante Renato
author Cifre, Ignacio
author_facet Cifre, Ignacio
Miller Flores, Maria T.
Penalba, Lucia
Ochab, Jeremi K.
Chialvo, Dante Renato
author_role author
author2 Miller Flores, Maria T.
Penalba, Lucia
Ochab, Jeremi K.
Chialvo, Dante Renato
author2_role author
author
author
author
dc.subject.none.fl_str_mv AUTISM (ASD)
DYNAMIC FUNCTIONAL CONNECTIVITY
FMRI
FUNCTIONAL CONNECTIVITY
RESTING STATE NETWORKS
topic AUTISM (ASD)
DYNAMIC FUNCTIONAL CONNECTIVITY
FMRI
FUNCTIONAL CONNECTIVITY
RESTING STATE 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 The center stage of neuro-imaging is currently occupied by studies of functional correlations between brain regions. These correlations define the brain functional networks, which are the most frequently used framework to represent and interpret a variety of experimental findings. In the previous study, we first demonstrated that the relatively stronger blood oxygenated level dependent (BOLD) activations contain most of the information relevant to understand functional connectivity, and subsequent work confirmed that a large compression of the original signals can be obtained without significant loss of information. In this study, we revisit the correlation properties of these epochs to define a measure of nonlinear dynamic directed functional connectivity (nldFC) across regions of interest. We show that the proposed metric provides at once, without extensive numerical complications, directed information of the functional correlations, as well as a measure of temporal lags across regions, overall offering a different and complementary perspective in the analysis of brain co-activation patterns. In this study, we provide further details for the computations of these measures and for a proof of concept based on replicating existing results from an Autistic Syndrome database, and discuss the main features and advantages of the proposed strategy for the study of brain functional correlations.
Fil: Cifre, Ignacio. Universitat Ramon Llull; España. Universidad Nacional de San Martin. Escuela de Ciencia y Tecnologia. Centro de Estudios Multidisciplinarios En Sistemas Complejos y Ciencias del Cerebro.; Argentina
Fil: Miller Flores, Maria T.. Universidad Nacional de San Martin. Escuela de Ciencia y Tecnologia. Centro de Estudios Multidisciplinarios En Sistemas Complejos y Ciencias del Cerebro.; Argentina
Fil: Penalba, Lucia. Universitat Ramon Llull; España
Fil: Ochab, Jeremi K.. Jagiellonian University; Polonia
Fil: Chialvo, Dante Renato. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de San Martin. Escuela de Ciencia y Tecnologia. Centro de Estudios Multidisciplinarios En Sistemas Complejos y Ciencias del Cerebro.; Argentina
description The center stage of neuro-imaging is currently occupied by studies of functional correlations between brain regions. These correlations define the brain functional networks, which are the most frequently used framework to represent and interpret a variety of experimental findings. In the previous study, we first demonstrated that the relatively stronger blood oxygenated level dependent (BOLD) activations contain most of the information relevant to understand functional connectivity, and subsequent work confirmed that a large compression of the original signals can be obtained without significant loss of information. In this study, we revisit the correlation properties of these epochs to define a measure of nonlinear dynamic directed functional connectivity (nldFC) across regions of interest. We show that the proposed metric provides at once, without extensive numerical complications, directed information of the functional correlations, as well as a measure of temporal lags across regions, overall offering a different and complementary perspective in the analysis of brain co-activation patterns. In this study, we provide further details for the computations of these measures and for a proof of concept based on replicating existing results from an Autistic Syndrome database, and discuss the main features and advantages of the proposed strategy for the study of brain functional correlations.
publishDate 2021
dc.date.none.fl_str_mv 2021-10-12
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/11336/155440
Cifre, Ignacio; Miller Flores, Maria T.; Penalba, Lucia; Ochab, Jeremi K.; Chialvo, Dante Renato; Revisiting nonlinear functional brain co-activations: Directed, dynamic, and delayed; Frontiers Media; Frontiers in Neuroscience; 15; 700171; 12-10-2021; 1-13
1662-4548
1662-453X
CONICET Digital
CONICET
url http://hdl.handle.net/11336/155440
identifier_str_mv Cifre, Ignacio; Miller Flores, Maria T.; Penalba, Lucia; Ochab, Jeremi K.; Chialvo, Dante Renato; Revisiting nonlinear functional brain co-activations: Directed, dynamic, and delayed; Frontiers Media; Frontiers in Neuroscience; 15; 700171; 12-10-2021; 1-13
1662-4548
1662-453X
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.frontiersin.org/articles/10.3389/fnins.2021.700171/full
info:eu-repo/semantics/altIdentifier/doi/10.3389/fnins.2021.700171
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 Frontiers Media
publisher.none.fl_str_mv Frontiers Media
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 12.48226

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