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Disrupted effective connectivity of the default, salience and dorsal attention networks in major depressive disorder: a study using spectral dynamic causal modelling of resting-state fMRI

BACKGROUND: Understanding the neural basis for major depressive disorder (MDD) is essential for its diagnosis and treatment. Aberrant activation and functional connectivity of the default mode network (DMN), salience network (SN) and dorsal attention network (DAN) have been found consistently in pat...

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Autores principales: Wang, Yun, Chen, Xiongying, Liu, Rui, Zhang, Zhifang, Zhou, Jingjing, Feng, Yuan, Zeidman, Peter, Wang, Gang, Zhou, Yuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: CMA Impact Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9744200/
http://dx.doi.org/10.1503/jpn.220038
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author Wang, Yun
Chen, Xiongying
Liu, Rui
Zhang, Zhifang
Zhou, Jingjing
Feng, Yuan
Zeidman, Peter
Wang, Gang
Zhou, Yuan
author_facet Wang, Yun
Chen, Xiongying
Liu, Rui
Zhang, Zhifang
Zhou, Jingjing
Feng, Yuan
Zeidman, Peter
Wang, Gang
Zhou, Yuan
author_sort Wang, Yun
collection PubMed
description BACKGROUND: Understanding the neural basis for major depressive disorder (MDD) is essential for its diagnosis and treatment. Aberrant activation and functional connectivity of the default mode network (DMN), salience network (SN) and dorsal attention network (DAN) have been found consistently in patients with MDD. However, whether effective connectivity within and between these networks is altered in MDD remains unknown. The primary objective of this study was to investigate the effective connectivity of the 3 networks in patients with MDD at rest. METHODS: We included 63 patients with MDD (35 first-episode and 28 recurrent) and 74 healthy controls, and collected resting-state functional MRI data for all participants. We defined 15 regions of interest from the 3 functional brain networks of interest using group independent component analysis. We estimated the coupling parameters that reflected the causal interactions among these regions using spectral dynamic causal modelling. We used parametric empirical Bayes to determine commonalities across groups, differences between patients with MDD and healthy controls, and differences between patients with recurrent and first-episode MDD. RESULTS: We found positive (excitatory) connections within each network, negative (inhibitory) connections from the SN and DAN to the DMN, and positive connections from the DAN to the SN across groups. Compared to healthy controls, patients with MDD showed increased positive connections within the DMN, a decreased absolute value of negative connectivity from the SN to the DMN, and increased positive connections from the SN to the DAN. We also found that patients with recurrent MDD showed remarkably different effective connections compared to patients with first-episode MDD, especially related to the DAN. LIMITATIONS: Because of the relatively small sample size and the unclear medication history of the MDD sample, the present findings are in need of replication. CONCLUSION: These findings suggest that effective connectivity among high-order brain functional networks during rest was disrupted in patients with MDD. Moreover, patients with recurrent MDD exhibited different effective connections compared to patients with first-episode MDD. These differences in effective connectivity might provide new insights into the neural substrates of MDD.
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spelling pubmed-97442002022-12-16 Disrupted effective connectivity of the default, salience and dorsal attention networks in major depressive disorder: a study using spectral dynamic causal modelling of resting-state fMRI Wang, Yun Chen, Xiongying Liu, Rui Zhang, Zhifang Zhou, Jingjing Feng, Yuan Zeidman, Peter Wang, Gang Zhou, Yuan J Psychiatry Neurosci Research Paper BACKGROUND: Understanding the neural basis for major depressive disorder (MDD) is essential for its diagnosis and treatment. Aberrant activation and functional connectivity of the default mode network (DMN), salience network (SN) and dorsal attention network (DAN) have been found consistently in patients with MDD. However, whether effective connectivity within and between these networks is altered in MDD remains unknown. The primary objective of this study was to investigate the effective connectivity of the 3 networks in patients with MDD at rest. METHODS: We included 63 patients with MDD (35 first-episode and 28 recurrent) and 74 healthy controls, and collected resting-state functional MRI data for all participants. We defined 15 regions of interest from the 3 functional brain networks of interest using group independent component analysis. We estimated the coupling parameters that reflected the causal interactions among these regions using spectral dynamic causal modelling. We used parametric empirical Bayes to determine commonalities across groups, differences between patients with MDD and healthy controls, and differences between patients with recurrent and first-episode MDD. RESULTS: We found positive (excitatory) connections within each network, negative (inhibitory) connections from the SN and DAN to the DMN, and positive connections from the DAN to the SN across groups. Compared to healthy controls, patients with MDD showed increased positive connections within the DMN, a decreased absolute value of negative connectivity from the SN to the DMN, and increased positive connections from the SN to the DAN. We also found that patients with recurrent MDD showed remarkably different effective connections compared to patients with first-episode MDD, especially related to the DAN. LIMITATIONS: Because of the relatively small sample size and the unclear medication history of the MDD sample, the present findings are in need of replication. CONCLUSION: These findings suggest that effective connectivity among high-order brain functional networks during rest was disrupted in patients with MDD. Moreover, patients with recurrent MDD exhibited different effective connections compared to patients with first-episode MDD. These differences in effective connectivity might provide new insights into the neural substrates of MDD. CMA Impact Inc. 2022-12-06 /pmc/articles/PMC9744200/ http://dx.doi.org/10.1503/jpn.220038 Text en © 2022 CMA Impact Inc. or its licensors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY-NC-ND 4.0) licence, which permits use, distribution and reproduction in any medium, provided that the original publication is properly cited, the use is noncommercial (i.e., research or educational use), and no modifications or adaptations are made. See: https://creativecommons.org/licenses/by-nc-nd/4.0/
spellingShingle Research Paper
Wang, Yun
Chen, Xiongying
Liu, Rui
Zhang, Zhifang
Zhou, Jingjing
Feng, Yuan
Zeidman, Peter
Wang, Gang
Zhou, Yuan
Disrupted effective connectivity of the default, salience and dorsal attention networks in major depressive disorder: a study using spectral dynamic causal modelling of resting-state fMRI
title Disrupted effective connectivity of the default, salience and dorsal attention networks in major depressive disorder: a study using spectral dynamic causal modelling of resting-state fMRI
title_full Disrupted effective connectivity of the default, salience and dorsal attention networks in major depressive disorder: a study using spectral dynamic causal modelling of resting-state fMRI
title_fullStr Disrupted effective connectivity of the default, salience and dorsal attention networks in major depressive disorder: a study using spectral dynamic causal modelling of resting-state fMRI
title_full_unstemmed Disrupted effective connectivity of the default, salience and dorsal attention networks in major depressive disorder: a study using spectral dynamic causal modelling of resting-state fMRI
title_short Disrupted effective connectivity of the default, salience and dorsal attention networks in major depressive disorder: a study using spectral dynamic causal modelling of resting-state fMRI
title_sort disrupted effective connectivity of the default, salience and dorsal attention networks in major depressive disorder: a study using spectral dynamic causal modelling of resting-state fmri
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9744200/
http://dx.doi.org/10.1503/jpn.220038
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