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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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2014
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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 |
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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 |
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