A resting-state brain functional network study in MDD based on minimum spanning tree analysis and the hierarchical clustering
Summary: A large number of studies demonstrated that major depressive disorder (MDD) is characterized by the alterations in brain functional connections which is also identifiable during the brain's ``resting-state.'' But, in the present study, the approach of constructing functional connectivity is often biased by the choice of the threshold. Besides, more attention was paid to the number and length of links in brain networks, and the clustering partitioning of nodes was unclear. Therefore, minimum spanning tree (MST) analysis and the hierarchical clustering are first used for the depression disease in this study. Resting-state electroencephalogram (EEG) sources were assessed from 15 healthy and 23 major depressive subjects. Then, the coherence, MST, and the hierarchical clustering are obtained. In the theta band, coherence analysis showed that the EEG coherence of the MDD patients is significantly higher than that of the healthy controls especially in the left temporal region. The MST results indicate the higher leaf fraction in the depressed group. Compared with the normal group, the major depressive patients lose clustering in frontal regions. Our findings suggest that there is a stronger brain interaction in the MDD group and a left-right functional imbalance in the frontal regions for MDD controls.
resting-state electroencephalogram (EEG)
scientific article; zbMATH DE number 6798514