科研之友
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摘要
Objective: Newly developed techniques for understanding brain connectivity have emerged with the application of graph theoryebased measures to neuroimaging modalities. However, the cognitive correlates of these measures, particularly in the context of clinical diagnoses like major depression, are still poorly understood. The purpose of this study was to compare four measures of network efficiency derived from novel techniques for understanding white matter connectivity on their associations with aging, depression, and cognition. Methods: In a cross-sectional neuroimaging study, we recruited from the general community 43 healthy comparison subjects and 40 subjects with major depressive disorder who volunteered in response to advertisements. Brain network efficiency measures were generated from diffusion tensor imagingederived structural connectivity matrices using the Brain Connectivity Toolbox. Information processing speed and decision making were assessed with the Trail Making Test and the Object Alternation task, respectively. Results: All four network efficiency measures correlated negatively with age. In the depressed group, normalized global efficiency was negatively correlated with depression severity, whereas increasing global efficiency was associated with poorer performance on Object Alternation. Conclusion: Brain network efficiency measures may represent different aspects of underlying network organization depending on the population and behaviors in question.
- 出版日期2014-2
