The Dynamics of functional brain networks associated with depressive symptoms in a nonclinical sample

Brain function depends on the flexible and dynamic coordination of functional subsystems within distributed neural networks operating on multiple scales. Recent progress has been made in the characterization of functional connectivity (FC) at the whole-brain scale from a dynamic, rather than static,...

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Autores: Alonso Martínez, Sonsoles, Deco, Gustavo, ter Horst, Gert J., Cabral, Joana
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2020
País:España
Recursos:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10230/46188
Acesso em linha:http://hdl.handle.net/10230/46188
http://dx.doi.org/10.3389/fncir.2020.570583
Access Level:acceso abierto
Palavra-chave:Depressive symptoms
Dynamic FC
Functional brain networks
Nonclinical sample
Resting-state fMRI
Static FC
Whole-brain
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dc.title.none.fl_str_mv The Dynamics of functional brain networks associated with depressive symptoms in a nonclinical sample
title The Dynamics of functional brain networks associated with depressive symptoms in a nonclinical sample
spellingShingle The Dynamics of functional brain networks associated with depressive symptoms in a nonclinical sample
Alonso Martínez, Sonsoles
Depressive symptoms
Dynamic FC
Functional brain networks
Nonclinical sample
Resting-state fMRI
Static FC
Whole-brain
title_short The Dynamics of functional brain networks associated with depressive symptoms in a nonclinical sample
title_full The Dynamics of functional brain networks associated with depressive symptoms in a nonclinical sample
title_fullStr The Dynamics of functional brain networks associated with depressive symptoms in a nonclinical sample
title_full_unstemmed The Dynamics of functional brain networks associated with depressive symptoms in a nonclinical sample
title_sort The Dynamics of functional brain networks associated with depressive symptoms in a nonclinical sample
dc.creator.none.fl_str_mv Alonso Martínez, Sonsoles
Deco, Gustavo
ter Horst, Gert J.
Cabral, Joana
author Alonso Martínez, Sonsoles
author_facet Alonso Martínez, Sonsoles
Deco, Gustavo
ter Horst, Gert J.
Cabral, Joana
author_role author
author2 Deco, Gustavo
ter Horst, Gert J.
Cabral, Joana
author2_role author
author
author
dc.subject.none.fl_str_mv Depressive symptoms
Dynamic FC
Functional brain networks
Nonclinical sample
Resting-state fMRI
Static FC
Whole-brain
topic Depressive symptoms
Dynamic FC
Functional brain networks
Nonclinical sample
Resting-state fMRI
Static FC
Whole-brain
description Brain function depends on the flexible and dynamic coordination of functional subsystems within distributed neural networks operating on multiple scales. Recent progress has been made in the characterization of functional connectivity (FC) at the whole-brain scale from a dynamic, rather than static, perspective, but its validity for cognitive sciences remains under debate. Here, we analyzed brain activity recorded with functional Magnetic Resonance Imaging from 71 healthy participants evaluated for depressive symptoms after a relationship breakup based on the conventional Major Depression Inventory (MDI). We compared both static and dynamic FC patterns between participants reporting high and low depressive symptoms. Between-group differences in static FC were estimated using a standard pipeline for network-based statistic (NBS). Additionally, FC was analyzed from a dynamic perspective by characterizing the occupancy, lifetime, and transition profiles of recurrent FC patterns. Recurrent FC patterns were defined by clustering the BOLD phase-locking patterns obtained using leading eigenvector dynamics analysis (LEiDA). NBS analysis revealed a brain subsystem exhibiting significantly lower within-subsystem correlation values in more depressed participants (high MDI). This subsystem predominantly comprised connections between regions of the default mode network (i.e., precuneus) and regions outside this network. On the other hand, LEiDA results showed that high MDI participants engaged more in a state connecting regions of the default mode, memory retrieval, and frontoparietal network (p-FDR = 0.012); and less in a state connecting mostly the visual and dorsal attention systems (p-FDR = 0.004). Although both our analyses on static and dynamic FC implicate the role of the precuneus in depressive symptoms, only including the temporal evolution of BOLD FC helped to disentangle over time the distinct configurations in which this region plays a role. This finding further indicates that a holistic understanding of brain function can only be gleaned if the temporal dynamics of FC is included.
publishDate 2020
dc.date.none.fl_str_mv 2020
2021
2021
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
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dc.identifier.none.fl_str_mv http://hdl.handle.net/10230/46188
http://dx.doi.org/10.3389/fncir.2020.570583
url http://hdl.handle.net/10230/46188
http://dx.doi.org/10.3389/fncir.2020.570583
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Frontiers in Neural Circuits. 2020 Sep 18;14:570583
info:eu-repo/grantAgreement/ES/2PE/PID2019-105772GB-I00
info:eu-repo/grantAgreement/H2020/945539/
dc.rights.none.fl_str_mv https://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
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dc.publisher.none.fl_str_mv Frontiers
publisher.none.fl_str_mv Frontiers
dc.source.none.fl_str_mv reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
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spelling The Dynamics of functional brain networks associated with depressive symptoms in a nonclinical sampleAlonso Martínez, SonsolesDeco, Gustavoter Horst, Gert J.Cabral, JoanaDepressive symptomsDynamic FCFunctional brain networksNonclinical sampleResting-state fMRIStatic FCWhole-brainBrain function depends on the flexible and dynamic coordination of functional subsystems within distributed neural networks operating on multiple scales. Recent progress has been made in the characterization of functional connectivity (FC) at the whole-brain scale from a dynamic, rather than static, perspective, but its validity for cognitive sciences remains under debate. Here, we analyzed brain activity recorded with functional Magnetic Resonance Imaging from 71 healthy participants evaluated for depressive symptoms after a relationship breakup based on the conventional Major Depression Inventory (MDI). We compared both static and dynamic FC patterns between participants reporting high and low depressive symptoms. Between-group differences in static FC were estimated using a standard pipeline for network-based statistic (NBS). Additionally, FC was analyzed from a dynamic perspective by characterizing the occupancy, lifetime, and transition profiles of recurrent FC patterns. Recurrent FC patterns were defined by clustering the BOLD phase-locking patterns obtained using leading eigenvector dynamics analysis (LEiDA). NBS analysis revealed a brain subsystem exhibiting significantly lower within-subsystem correlation values in more depressed participants (high MDI). This subsystem predominantly comprised connections between regions of the default mode network (i.e., precuneus) and regions outside this network. On the other hand, LEiDA results showed that high MDI participants engaged more in a state connecting regions of the default mode, memory retrieval, and frontoparietal network (p-FDR = 0.012); and less in a state connecting mostly the visual and dorsal attention systems (p-FDR = 0.004). Although both our analyses on static and dynamic FC implicate the role of the precuneus in depressive symptoms, only including the temporal evolution of BOLD FC helped to disentangle over time the distinct configurations in which this region plays a role. This finding further indicates that a holistic understanding of brain function can only be gleaned if the temporal dynamics of FC is included.This research was supported by a donation of Mr. Hazewinkel to GH and the Research School of Behavioural and Cognitive Neurosciences, University of Groningen, Netherlands. GD acknowledged AWAKENING Using whole-brain models perturbational approaches for predicting external stimulation to force transitions between different brain states (ref. PID2019-105772GB-I00, AEI FEDER EU), funded by the Spanish Ministry of Science, Innovation and Universities (MCIU), State Research Agency (AEI) and European Regional Development Funds (FEDER); HBP SGA3 Human Brain Project Specific Grant Agreement 3 (Grant Agreement No. 945539) funded by the EU H2020 FET Flagship program; and SGR Research Support Group support (ref. 2017 SGR 1545), funded by the Catalan Agency for Management of University and Research Grants (AGAUR). JC was funded by the Portuguese Foundation for Science and Technology (FCT) CEECIND/03325/2017, by the European Regional Development Fund (FEDER) through the Competitiveness Factors Operational Program (COMPETE), by FCT project UID/Multi/50026, by projects NORTE-01-0145-FEDER-000013, and NORTE-01-0145-FEDER-000023 supported by the NORTE 2020 Programme under the Portugal 2020 Partnership Agreement through FEDER.Frontiers202120212020info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttp://hdl.handle.net/10230/46188http://dx.doi.org/10.3389/fncir.2020.570583reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésFrontiers in Neural Circuits. 2020 Sep 18;14:570583info:eu-repo/grantAgreement/ES/2PE/PID2019-105772GB-I00info:eu-repo/grantAgreement/H2020/945539/© 2020 Alonso Martínez, Deco, Ter Horst and Cabral. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (https://creativecommons.org/licenses/by/4.0/). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.https://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:recercat.cat:10230/461882026-05-29T05:05:01Z
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