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Intrinsic Network Brain Dysfunction Correlates With Temporal Complexity in Generalized Anxiety Disorder and Panic Disorder

Background: Generalized anxiety disorder (GAD) and panic disorder (PD) are the two severe subtypes of anxiety disorders (ADs), which are similar in clinical manifestation, pathogenesis, and treatment. Earlier studies have taken a whole-brain perspective on GAD and PD in the assumption that intrinsic...

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Autores principales: Xu, Li, Xu, Huazhen, Ding, Huachen, Li, Jinyang, Wang, Chun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8319536/
https://www.ncbi.nlm.nih.gov/pubmed/34335204
http://dx.doi.org/10.3389/fnhum.2021.647518
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author Xu, Li
Xu, Huazhen
Ding, Huachen
Li, Jinyang
Wang, Chun
author_facet Xu, Li
Xu, Huazhen
Ding, Huachen
Li, Jinyang
Wang, Chun
author_sort Xu, Li
collection PubMed
description Background: Generalized anxiety disorder (GAD) and panic disorder (PD) are the two severe subtypes of anxiety disorders (ADs), which are similar in clinical manifestation, pathogenesis, and treatment. Earlier studies have taken a whole-brain perspective on GAD and PD in the assumption that intrinsic fluctuations are static throughout the entire scan. However, it has recently been suggested that the dynamic alternations in functional connectivity (FC) may reflect the changes in macroscopic neural activity patterns underlying the critical aspects of cognition and behavior, and thus may act as biomarkers of disease. Methods: In this study, the resting-state functional MRI (fMRI) data were collected from 26 patients with GAD, 22 patients with PD, and 26 healthy controls (HCs). We investigated dynamic functional connectivity (DFC) by using the group spatial independent component analysis, a sliding window approach, and the k-means clustering methods. For group comparisons, the temporal properties of DFC states were analyzed statistically. Results: The dynamic analysis demonstrated two discrete connectivity “States” across the entire group, namely, a more segregated State I and a strongly integrated State II. Compared with HCs, patients with both GAD and PD spent more time in the weakly within-network State I, while performing fewer transitions and dwelling shorter in the integrated State II. Additionally, the analysis of DFC strength showed that connections associated with ADs were identified including the regions that belonged to default mode (DM), executive control (EC), and salience (SA) networks, especially the connections between SA and DM networks. However, no significant difference was found between the GAD and PD groups in temporal features and connection strength. Conclusions: More common but less specific alterations were detected in the GAD and PD groups, which implied that they might have similar state-dependent neurophysiological mechanisms and, in addition, could hopefully help us better understand their abnormal affective and cognitive performances in the clinic.
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spelling pubmed-83195362021-07-30 Intrinsic Network Brain Dysfunction Correlates With Temporal Complexity in Generalized Anxiety Disorder and Panic Disorder Xu, Li Xu, Huazhen Ding, Huachen Li, Jinyang Wang, Chun Front Hum Neurosci Human Neuroscience Background: Generalized anxiety disorder (GAD) and panic disorder (PD) are the two severe subtypes of anxiety disorders (ADs), which are similar in clinical manifestation, pathogenesis, and treatment. Earlier studies have taken a whole-brain perspective on GAD and PD in the assumption that intrinsic fluctuations are static throughout the entire scan. However, it has recently been suggested that the dynamic alternations in functional connectivity (FC) may reflect the changes in macroscopic neural activity patterns underlying the critical aspects of cognition and behavior, and thus may act as biomarkers of disease. Methods: In this study, the resting-state functional MRI (fMRI) data were collected from 26 patients with GAD, 22 patients with PD, and 26 healthy controls (HCs). We investigated dynamic functional connectivity (DFC) by using the group spatial independent component analysis, a sliding window approach, and the k-means clustering methods. For group comparisons, the temporal properties of DFC states were analyzed statistically. Results: The dynamic analysis demonstrated two discrete connectivity “States” across the entire group, namely, a more segregated State I and a strongly integrated State II. Compared with HCs, patients with both GAD and PD spent more time in the weakly within-network State I, while performing fewer transitions and dwelling shorter in the integrated State II. Additionally, the analysis of DFC strength showed that connections associated with ADs were identified including the regions that belonged to default mode (DM), executive control (EC), and salience (SA) networks, especially the connections between SA and DM networks. However, no significant difference was found between the GAD and PD groups in temporal features and connection strength. Conclusions: More common but less specific alterations were detected in the GAD and PD groups, which implied that they might have similar state-dependent neurophysiological mechanisms and, in addition, could hopefully help us better understand their abnormal affective and cognitive performances in the clinic. Frontiers Media S.A. 2021-07-15 /pmc/articles/PMC8319536/ /pubmed/34335204 http://dx.doi.org/10.3389/fnhum.2021.647518 Text en Copyright © 2021 Xu, Xu, Ding, Li and Wang. https://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 Human Neuroscience
Xu, Li
Xu, Huazhen
Ding, Huachen
Li, Jinyang
Wang, Chun
Intrinsic Network Brain Dysfunction Correlates With Temporal Complexity in Generalized Anxiety Disorder and Panic Disorder
title Intrinsic Network Brain Dysfunction Correlates With Temporal Complexity in Generalized Anxiety Disorder and Panic Disorder
title_full Intrinsic Network Brain Dysfunction Correlates With Temporal Complexity in Generalized Anxiety Disorder and Panic Disorder
title_fullStr Intrinsic Network Brain Dysfunction Correlates With Temporal Complexity in Generalized Anxiety Disorder and Panic Disorder
title_full_unstemmed Intrinsic Network Brain Dysfunction Correlates With Temporal Complexity in Generalized Anxiety Disorder and Panic Disorder
title_short Intrinsic Network Brain Dysfunction Correlates With Temporal Complexity in Generalized Anxiety Disorder and Panic Disorder
title_sort intrinsic network brain dysfunction correlates with temporal complexity in generalized anxiety disorder and panic disorder
topic Human Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8319536/
https://www.ncbi.nlm.nih.gov/pubmed/34335204
http://dx.doi.org/10.3389/fnhum.2021.647518
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