Comparative analysis of default mode networks in major psychiatric disorders using resting-state EEG

Abstract Default mode network (DMN) is a set of functional brain structures coherently activated when individuals are in resting-state. In this study, we constructed multi-frequency band resting-state EEG-based DMN functional network models for major psychiatric disorders to easily compare their pat...

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Autores principales:	Kang-Min Choi, Jeong-Youn Kim, Yong-Wook Kim, Jung-Won Han, Chang-Hwan Im, Seung-Hwan Lee
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/f97cc7ca4af646d5b1894152f2898301
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spelling	oai:doaj.org-article:f97cc7ca4af646d5b1894152f28983012021-11-14T12:24:17ZComparative analysis of default mode networks in major psychiatric disorders using resting-state EEG10.1038/s41598-021-00975-32045-2322https://doaj.org/article/f97cc7ca4af646d5b1894152f28983012021-11-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-00975-3https://doaj.org/toc/2045-2322Abstract Default mode network (DMN) is a set of functional brain structures coherently activated when individuals are in resting-state. In this study, we constructed multi-frequency band resting-state EEG-based DMN functional network models for major psychiatric disorders to easily compare their pathophysiological characteristics. Phase-locking values (PLVs) were evaluated to quantify functional connectivity; global and nodal clustering coefficients (CCs) were evaluated to quantify global and local connectivity patterns of DMN nodes, respectively. DMNs of patients with post-traumatic stress disorder (PTSD), obsessive compulsive disorder (OCD), panic disorder, major depressive disorder (MDD), bipolar disorder, schizophrenia (SZ), mild cognitive impairment (MCI), and Alzheimer’s disease (AD) were constructed relative to their demographically-matched healthy control groups. Overall DMN patterns were then visualized and compared with each other. In global CCs, SZ and AD showed hyper-clustering in the theta band; OCD, MCI, and AD showed hypo-clustering in the low-alpha band; OCD and MDD showed hypo-clustering and hyper-clustering in low-beta, and high-beta bands, respectively. In local CCs, disease-specific patterns were observed. In the PLVs, lowered theta-band functional connectivity between the left lingual gyrus and the left hippocampus was frequently observed. Our comprehensive comparisons suggest EEG-based DMN as a useful vehicle for understanding altered brain networks of major psychiatric disorders.Kang-Min ChoiJeong-Youn KimYong-Wook KimJung-Won HanChang-Hwan ImSeung-Hwan LeeNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Kang-Min Choi Jeong-Youn Kim Yong-Wook Kim Jung-Won Han Chang-Hwan Im Seung-Hwan Lee Comparative analysis of default mode networks in major psychiatric disorders using resting-state EEG
description	Abstract Default mode network (DMN) is a set of functional brain structures coherently activated when individuals are in resting-state. In this study, we constructed multi-frequency band resting-state EEG-based DMN functional network models for major psychiatric disorders to easily compare their pathophysiological characteristics. Phase-locking values (PLVs) were evaluated to quantify functional connectivity; global and nodal clustering coefficients (CCs) were evaluated to quantify global and local connectivity patterns of DMN nodes, respectively. DMNs of patients with post-traumatic stress disorder (PTSD), obsessive compulsive disorder (OCD), panic disorder, major depressive disorder (MDD), bipolar disorder, schizophrenia (SZ), mild cognitive impairment (MCI), and Alzheimer’s disease (AD) were constructed relative to their demographically-matched healthy control groups. Overall DMN patterns were then visualized and compared with each other. In global CCs, SZ and AD showed hyper-clustering in the theta band; OCD, MCI, and AD showed hypo-clustering in the low-alpha band; OCD and MDD showed hypo-clustering and hyper-clustering in low-beta, and high-beta bands, respectively. In local CCs, disease-specific patterns were observed. In the PLVs, lowered theta-band functional connectivity between the left lingual gyrus and the left hippocampus was frequently observed. Our comprehensive comparisons suggest EEG-based DMN as a useful vehicle for understanding altered brain networks of major psychiatric disorders.
format	article
author	Kang-Min Choi Jeong-Youn Kim Yong-Wook Kim Jung-Won Han Chang-Hwan Im Seung-Hwan Lee
author_facet	Kang-Min Choi Jeong-Youn Kim Yong-Wook Kim Jung-Won Han Chang-Hwan Im Seung-Hwan Lee
author_sort	Kang-Min Choi
title	Comparative analysis of default mode networks in major psychiatric disorders using resting-state EEG
title_short	Comparative analysis of default mode networks in major psychiatric disorders using resting-state EEG
title_full	Comparative analysis of default mode networks in major psychiatric disorders using resting-state EEG
title_fullStr	Comparative analysis of default mode networks in major psychiatric disorders using resting-state EEG
title_full_unstemmed	Comparative analysis of default mode networks in major psychiatric disorders using resting-state EEG
title_sort	comparative analysis of default mode networks in major psychiatric disorders using resting-state eeg
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/f97cc7ca4af646d5b1894152f2898301
work_keys_str_mv	AT kangminchoi comparativeanalysisofdefaultmodenetworksinmajorpsychiatricdisordersusingrestingstateeeg AT jeongyounkim comparativeanalysisofdefaultmodenetworksinmajorpsychiatricdisordersusingrestingstateeeg AT yongwookkim comparativeanalysisofdefaultmodenetworksinmajorpsychiatricdisordersusingrestingstateeeg AT jungwonhan comparativeanalysisofdefaultmodenetworksinmajorpsychiatricdisordersusingrestingstateeeg AT changhwanim comparativeanalysisofdefaultmodenetworksinmajorpsychiatricdisordersusingrestingstateeeg AT seunghwanlee comparativeanalysisofdefaultmodenetworksinmajorpsychiatricdisordersusingrestingstateeeg
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Comparative analysis of default mode networks in major psychiatric disorders using resting-state EEG

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