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• W2901491630 abstract "Previous studies have suggested that major depressive disorder was associated with topological properties of impaired white matter. However, most related studies only use one property of nerve fibers to construct whole-brain structural brain network. Considering white matter changes variously, We hypothesized whether the alternations of white matter topological properties could reflect different impairment of white matter integrity. In addition, it is still unknown whether impaired integrity of the white matter fiber tracts has relationship with abnormal topological properties in MDD. This study investigated the impaired white matter by using graph theoretic analyses in a cohort of 37 MDD patients and 38 matched control subjects. In addition, we further investigated fiber tracts differences in three interregional connectivity matrixes of significant different topological regions in MDD. Our graph theoretic analyses demonstrated that 7 different regions were observed for the local measures in patients with MDD compared with control groups. These regions were the central nodes of cortical-limbic network, frontal-cingulate network, default mode network (DMN), cognitive control network(CCN)and affective network (AN). In addition, two impaired white matter pathways which included inferior longitudinal fasciculus (ILF) and cingulum were observed in MDD using fiber tracts analysis. We speculate impaired integrity of ILF is due to the alternations in the number of axons or myelination. The results further demonstrated that the number of fiber tracts of anterior cingulum was associated with the depression scores in MDD." @default.
• W2901491630 created "2018-11-29" @default.
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• W2901491630 date "2019-02-01" @default.
• W2901491630 modified "2023-10-16" @default.
• W2901491630 title "Structural networks analysis for depression combined with graph theory and the properties of fiber tracts via diffusion tensor imaging" @default.
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• W2901491630 doi "https://doi.org/10.1016/j.neulet.2018.11.025" @default.
• W2901491630 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30465819" @default.
• W2901491630 hasPublicationYear "2019" @default.
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