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This study investigates the abnormal brain structural connectivity in patients with major depressive disorder (MDD) through a modularization approach. Diffusion tensor imaging (DTI) data were collected from 20 MDD patients and 20 age-matched controls. The structural modularity characteristics and their relationships with clinical variables were examined. Results indicated that MDD patients exhibited reorganized modules with widely damaged global inter-module connectivity in limbic system and altered intra-module connectivity in left hemisphere. Furthermore, the module degree in right rolandic operculum, left posterior cingulate gyrus, right cuneus and right fusiform gyrus were negatively correlated with the depression severity. Additionally, a positive relationship was also found between the duration of disease and participant coefficient in left median cingulate. The current findings highlight altered modular organization in MDD patients, which might contribute to the pathogenesis of the disease.

Purposes: To probe abnormality that may lead to anxiety in depressive patients. Procedures: This study investigated the graph theory features ahead of machine learning feature selection procedure. Classification methods were applied afterwards. Methods: Graph theory, statistical analysis and forward sequential feature se lection were combined to find features. SVM classifier was also involved. Results: 1 global and 22 local features were found correlated with clinical anxiety factor. Conclusions: Anxiety is correlated with emotion and cognitive loop and other regions.