Characterizing multiscale modular structures in medication-free obsessive-compulsive disorder patients with no comorbidity

HUMAN BRAIN MAPPING(2022)

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摘要
Brain networks exhibit signatures of modular structure, which maintains a fine trade-off between wiring cost and efficiency of information transmission. Alterations in modular structure have been found in patients with obsessive-compulsive disorder (OCD). However, previous studies were focused on a single scale (i.e., modularity or intra/intermodular connectivity) for investigation. Here, we recruited 92 OCD patients and 90 healthy controls. A comprehensive analysis was performed on modular architecture alterations in the voxelwise functional connectome at the "global" (modularity), "meso" (modular segregation and within- and between-module connections), and "local" (participation coefficients, PC) scales. We also examined the correlation between modular structure metrics and clinical symptoms. The findings revealed that (1) there was no significant group difference in global modularity; (2) both primary modules (visual network, sensorimotor network) and high-order modules (dorsal attention network, frontoparietal network) exhibited lower modular segregation in OCD patients, which was mainly driven by increased numbers of between-module connections; and (3) OCD patients showed higher PC in several connectors including the bilateral middle occipital gyri, left medial orbital frontal gyrus, left superior frontal gyrus, left posterior cingulate gyrus, right superior temporal gyrus and right middle frontal gyrus, and lower PC in the right lingual gyrus. Moreover, these alterations in modular structure were associated with clinical symptoms in patients. Our findings provide further insights into the involvement of different modules in functional network dysfunction in OCD from a connectomic perspective and suggest a synergetic mechanism of module interactions that may be related to the pathophysiology of OCD.
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关键词
graph theory, modularity, obsessive-compulsive disorder, resting-state fMRI
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