Cargando…

Meta-Analytically Informed Network Analysis of Resting State fMRI Reveals Hyperconnectivity in an Introspective Socio-Affective Network in Depression

Alterations of social cognition and dysfunctional interpersonal expectations are thought to play an important role in the etiology of depression and have, thus, become a key target of psychotherapeutic interventions. The underlying neurobiology, however, remains elusive. Based upon the idea of a clo...

Descripción completa

Detalles Bibliográficos
Autores principales: Schilbach, Leonhard, Müller, Veronika I., Hoffstaedter, Felix, Clos, Mareike, Goya-Maldonado, Roberto, Gruber, Oliver, Eickhoff, Simon B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3997658/
https://www.ncbi.nlm.nih.gov/pubmed/24759619
http://dx.doi.org/10.1371/journal.pone.0094973
_version_ 1782313211304869888
author Schilbach, Leonhard
Müller, Veronika I.
Hoffstaedter, Felix
Clos, Mareike
Goya-Maldonado, Roberto
Gruber, Oliver
Eickhoff, Simon B.
author_facet Schilbach, Leonhard
Müller, Veronika I.
Hoffstaedter, Felix
Clos, Mareike
Goya-Maldonado, Roberto
Gruber, Oliver
Eickhoff, Simon B.
author_sort Schilbach, Leonhard
collection PubMed
description Alterations of social cognition and dysfunctional interpersonal expectations are thought to play an important role in the etiology of depression and have, thus, become a key target of psychotherapeutic interventions. The underlying neurobiology, however, remains elusive. Based upon the idea of a close link between affective and introspective processes relevant for social interactions and alterations thereof in states of depression, we used a meta-analytically informed network analysis to investigate resting-state functional connectivity in an introspective socio-affective (ISA) network in individuals with and without depression. Results of our analysis demonstrate significant differences between the groups with depressed individuals showing hyperconnectivity of the ISA network. These findings demonstrate that neurofunctional alterations exist in individuals with depression in a neural network relevant for introspection and socio-affective processing, which may contribute to the interpersonal difficulties that are linked to depressive symptomatology.
format Online
Article
Text
id pubmed-3997658
institution National Center for Biotechnology Information
language English
publishDate 2014
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-39976582014-04-29 Meta-Analytically Informed Network Analysis of Resting State fMRI Reveals Hyperconnectivity in an Introspective Socio-Affective Network in Depression Schilbach, Leonhard Müller, Veronika I. Hoffstaedter, Felix Clos, Mareike Goya-Maldonado, Roberto Gruber, Oliver Eickhoff, Simon B. PLoS One Research Article Alterations of social cognition and dysfunctional interpersonal expectations are thought to play an important role in the etiology of depression and have, thus, become a key target of psychotherapeutic interventions. The underlying neurobiology, however, remains elusive. Based upon the idea of a close link between affective and introspective processes relevant for social interactions and alterations thereof in states of depression, we used a meta-analytically informed network analysis to investigate resting-state functional connectivity in an introspective socio-affective (ISA) network in individuals with and without depression. Results of our analysis demonstrate significant differences between the groups with depressed individuals showing hyperconnectivity of the ISA network. These findings demonstrate that neurofunctional alterations exist in individuals with depression in a neural network relevant for introspection and socio-affective processing, which may contribute to the interpersonal difficulties that are linked to depressive symptomatology. Public Library of Science 2014-04-23 /pmc/articles/PMC3997658/ /pubmed/24759619 http://dx.doi.org/10.1371/journal.pone.0094973 Text en © 2014 Schilbach et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Schilbach, Leonhard
Müller, Veronika I.
Hoffstaedter, Felix
Clos, Mareike
Goya-Maldonado, Roberto
Gruber, Oliver
Eickhoff, Simon B.
Meta-Analytically Informed Network Analysis of Resting State fMRI Reveals Hyperconnectivity in an Introspective Socio-Affective Network in Depression
title Meta-Analytically Informed Network Analysis of Resting State fMRI Reveals Hyperconnectivity in an Introspective Socio-Affective Network in Depression
title_full Meta-Analytically Informed Network Analysis of Resting State fMRI Reveals Hyperconnectivity in an Introspective Socio-Affective Network in Depression
title_fullStr Meta-Analytically Informed Network Analysis of Resting State fMRI Reveals Hyperconnectivity in an Introspective Socio-Affective Network in Depression
title_full_unstemmed Meta-Analytically Informed Network Analysis of Resting State fMRI Reveals Hyperconnectivity in an Introspective Socio-Affective Network in Depression
title_short Meta-Analytically Informed Network Analysis of Resting State fMRI Reveals Hyperconnectivity in an Introspective Socio-Affective Network in Depression
title_sort meta-analytically informed network analysis of resting state fmri reveals hyperconnectivity in an introspective socio-affective network in depression
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3997658/
https://www.ncbi.nlm.nih.gov/pubmed/24759619
http://dx.doi.org/10.1371/journal.pone.0094973
work_keys_str_mv AT schilbachleonhard metaanalyticallyinformednetworkanalysisofrestingstatefmrirevealshyperconnectivityinanintrospectivesocioaffectivenetworkindepression
AT mullerveronikai metaanalyticallyinformednetworkanalysisofrestingstatefmrirevealshyperconnectivityinanintrospectivesocioaffectivenetworkindepression
AT hoffstaedterfelix metaanalyticallyinformednetworkanalysisofrestingstatefmrirevealshyperconnectivityinanintrospectivesocioaffectivenetworkindepression
AT closmareike metaanalyticallyinformednetworkanalysisofrestingstatefmrirevealshyperconnectivityinanintrospectivesocioaffectivenetworkindepression
AT goyamaldonadoroberto metaanalyticallyinformednetworkanalysisofrestingstatefmrirevealshyperconnectivityinanintrospectivesocioaffectivenetworkindepression
AT gruberoliver metaanalyticallyinformednetworkanalysisofrestingstatefmrirevealshyperconnectivityinanintrospectivesocioaffectivenetworkindepression
AT eickhoffsimonb metaanalyticallyinformednetworkanalysisofrestingstatefmrirevealshyperconnectivityinanintrospectivesocioaffectivenetworkindepression