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Aberrant topographical organization in default-mode network in first-episode remitted geriatric depression: a graph-theoretical analysis

  • Yan Zhu (a1), Dongqing Wang (a1), Zhe Liu (a2) and Yuefeng Li (a1)

Abstract

Background:

Neuroimaging studies have shown that major depressive disorder is associated with altered activity patterns of the default-mode network (DMN). In this study, we sought to investigate the topological organization of the DMN in patients with remitted geriatric depression (RGD) and whether RGD patients would be more likely to show disrupted topological configuration of the DMN during the resting-state.

Methods:

Thirty-three RGD patients and thirty-one healthy control participants underwent clinical and cognitive evaluations as well as resting-state functional magnetic resonance imaging scans. The functional connectivity (FC) networks were constructed by thresholding Pearson correlation metrics of the DMN regions defined by group independent component analysis, and their topological properties (e.g. small-world and network efficiency) were analyzed using graph theory-based approaches.

Results:

Relative to the healthy controls, the RGD patients showed decreased FC in the posterior regions of the DMN (i.e. the posterior cingulate cortex/precuneus, angular gyrus, and middle temporal gyrus). Furthermore, the RGD patients showed abnormal global topology of the DMN (i.e. increased characteristic path length and reduced global efficiency) when compared with healthy controls. Importantly, significant correlations between these network measures and cognitive performance indicated their potential use as biomarkers of cognitive dysfunction in RGD.

Conclusions:

The present study indicated disrupted FC and topological organization of the DMN in the context of RGD, and further implied their contribution to cognitive deficits in RGD patients.

Copyright

Corresponding author

Correspondence should be addressed to: Yuefeng Li, Radiology Department, Affiliated Hospital of Jiangsu University, Zhenjiang, Jiangsu 210001, China. Phone: +86 13626267668; Email: lyf20172017@126.com.

References

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