https://doi.org/10.1140/epjs/s11734-025-01776-9
Regular Article
The disturbed functional brain network in major depressive disorder identified by graph theory analysis
1
School of Mathematics and Data Science, Shaanxi University of Science and Technology, 710021, Xi’an, China
2
School of Medicine, Yan’ an University, 716000, Yan’an, China
a
dumm119@sust.edu.cn
b
qxy@yau.edu.cn
Received:
19
March
2025
Accepted:
26
June
2025
Published online:
14
July
2025
The disturbed brain functional connectivity (FC) of major depressive disorder (MDD) has been found, but the underlying pathological mechanisms are not explained clearly. This paper used EEG data of 46 participants (Health Control: HC, 20, MMD: 26) in eyes-closed state to explore the disturbed brain function features based on phase lag index and graph theory analysis. The results showed that MDD patients exhibited lower functional brain network features (global efficiency, local efficiency, the FC strength and FC degree of the left frontal region, and the FC strength of the left hemisphere) in the delta band, and these features were negatively correlated with depression scale scores, and based on those features, this study achieved a classification accuracy of 84.8% with the K-nearest neighbor classifier, suggesting that the network features can serve as reliable indicators to distinguish MDD and HC. Furthermore, the FC strength of the left parietal-occipital region in the gamma band was higher than that in HC, indicating more severely damaged in left hemisphere in MDD patients. This paper illustrates the disruption of the functional brain network features in MDD patients, notably in the left frontal region, and offers the objective biomarkers for the early clinical diagnosis and treatment of depression.
Supplementary Information The online version contains supplementary material available at https://doi.org/10.1140/epjs/s11734-025-01776-9.
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© The Author(s), under exclusive licence to EDP Sciences, Springer-Verlag GmbH Germany, part of Springer Nature 2025
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
