兰州大学机构库
Altered Brain Dynamics and Their Ability for Major Depression Detection Using EEG Microstates Analysis
Li, Jianxiu1; Li, Nan1; Shao, Xuexiao1; Chen, Junhao1; Hao, Yanrong1; Li, XW(李小伟)1,2; Hu, B(胡斌)1,3,4,5
2023
Source PublicationIEEE Transactions on Affective Computing   Impact Factor & Quartile
ISSN1949-3045
Volume14Issue:3Pages:2116-2126
page numbers11
AbstractMajor depressive disorder (MDD) may be driven by dysfunction in intrinsic dynamic properties of the brain, and EEG microstate is a promising method for analyzing brain dynamics. However, the alterations in EEG microstate is still not entirely clear, and its ability for MDDs detection is worth probing. Moreover, the mechanism behind the neural networks contributing to microstates remains poorly understood in MDDs. Therefore, we applied microstate analysis and Topographic Electrophysiological State Source-imaging (TESS) on EEG data of 27 MDDs and 28 healthy controls (HCs). Compared to HCs, MDDs had apparent increase in microstate C and decrease in microstate D. Furthermore, TESS results showed that the underlying network of microstate C in MDDs overlapped with the anterior cingulate cortex and left insula gyrus, whereas main source of microstate D was in the orbital part of inferior frontal gyrus. The reduced transition probability from C to D in MDDs may reveal an imbalance between the networks of microstates. The microstate parameters as features reached good performance in identifying MDD (89.09% accuracy, 92.86% sensitivity, 85.19% specificity), indicating their potential as biomarkers of depression pathology. Collectively, these results highlight alteration of brain activity patterns and provide new insights into abnormal EEG dynamics in MDDs.
KeywordBrain network dynamics classification EEG microstates major depressive disorder
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI10.1109/TAFFC.2021.3139104
Indexed BySCIE ; IEEE
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Cybernetics
WOS IDWOS:001075041900031
Original Document TypeArticle
Citation statistics
Cited Times:5[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttps://ir.lzu.edu.cn/handle/262010/568947
Collection兰州大学
信息科学与工程学院
Corresponding AuthorLi, Xiaowei; Hu, Bin
Affiliation
1.Lanzhou Univ, Gansu Prov Key Lab Wearable Comp, Sch Informat Sci & Engn, Lanzhou 730000, Peoples R China;
2.Shandong Acad Intelligent Comp Technol, Qingdao 266590, Shandong, Peoples R China;
3.Chinese Acad Sci, Shanghai Inst Biol Sci, CAS Ctr Excellence Brain Sci & Intelligence Techno, Shanghai 200234, Peoples R China;
4.Chinese Acad Sci, Joint Res Ctr Cognit Neurosensor Technol Lanzhou U, Shanghai 200234, Peoples R China;
5.Lanzhou Univ, Engn Res Ctr Open Source Software & Real Time Syst, Minist Educ, Lanzhou 730000, Gansu, Peoples R China
First Author AffilicationSchool of Information Science and Engineering
Corresponding Author AffilicationSchool of Information Science and Engineering;  Lanzhou University
Recommended Citation
GB/T 7714
Li, Jianxiu,Li, Nan,Shao, Xuexiao,et al. Altered Brain Dynamics and Their Ability for Major Depression Detection Using EEG Microstates Analysis[J]. IEEE Transactions on Affective Computing,2023,14(3):2116-2126.
APA Li, Jianxiu.,Li, Nan.,Shao, Xuexiao.,Chen, Junhao.,Hao, Yanrong.,...&Hu, Bin.(2023).Altered Brain Dynamics and Their Ability for Major Depression Detection Using EEG Microstates Analysis.IEEE Transactions on Affective Computing,14(3),2116-2126.
MLA Li, Jianxiu,et al."Altered Brain Dynamics and Their Ability for Major Depression Detection Using EEG Microstates Analysis".IEEE Transactions on Affective Computing 14.3(2023):2116-2126.
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