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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 principales: Alonso Martínez, Sonsoles, Deco, Gustavo, Ter Horst, Gert J., Cabral, Joana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7530893/
https://www.ncbi.nlm.nih.gov/pubmed/33071760
http://dx.doi.org/10.3389/fncir.2020.570583
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author Alonso Martínez, Sonsoles
Deco, Gustavo
Ter Horst, Gert J.
Cabral, Joana
author_facet Alonso Martínez, Sonsoles
Deco, Gustavo
Ter Horst, Gert J.
Cabral, Joana
author_sort Alonso Martínez, Sonsoles
collection PubMed
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.
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spelling pubmed-75308932020-10-17 The Dynamics of Functional Brain Networks Associated With Depressive Symptoms in a Nonclinical Sample Alonso Martínez, Sonsoles Deco, Gustavo Ter Horst, Gert J. Cabral, Joana Front Neural Circuits Neuroscience 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. Frontiers Media S.A. 2020-09-18 /pmc/articles/PMC7530893/ /pubmed/33071760 http://dx.doi.org/10.3389/fncir.2020.570583 Text en Copyright © 2020 Alonso Martínez, Deco, Ter Horst and Cabral. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). 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.
spellingShingle Neuroscience
Alonso Martínez, Sonsoles
Deco, Gustavo
Ter Horst, Gert J.
Cabral, Joana
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
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_short The Dynamics of Functional Brain Networks Associated With Depressive Symptoms in a Nonclinical Sample
title_sort dynamics of functional brain networks associated with depressive symptoms in a nonclinical sample
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7530893/
https://www.ncbi.nlm.nih.gov/pubmed/33071760
http://dx.doi.org/10.3389/fncir.2020.570583
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