Objective: This study attempts to identify cognitive impairment related networks in the subjects with Parkinson’s disease using functional magnetic resonance imaging (MRI).

Background: Voxelwise analysis has been carried out in fixed networks including default mode network. Although some of these networks significantly correlated with cognitive decline, these networks appear less specific to each domain of cognitive impairment of Parkinson’s disease.

Method: Forty patients with Parkinson’s disease and 15 normal controls were enrolled in this study. All subjects underwent structural and resting state functional MRI. Japanese version of the Montreal Cognitive Assessment (MoCA-J) was used to assess the relationship between domains of cognitive impairment and resting state networks. Before network analysis with GIFT, voxel-based morphometry (VBM) was performed using SPM 12. Independent component analysis (ICA) allowed for functional segmentation to identify cognitive impairment related pattern using multiple regression model.

Results: There was no significant difference in gray matter volume between subjects with Parkinson’s disease and normal controls. Some networks were positively correlated with score of visuospatial executive (R² = 0.54, P < 0.001), naming (R² = 0.39, P < 0.001), attention (R² = 0.86, P < 0.001), language (R² = 0.64, P < 0.001), abstraction (R² = 0.10, P = 0.047) or orientation domains (R² = 0.64, P < 0.001), respectively. The key regions that were implicated in two networks and more included bilateral Brodmann’s area (BA) 10, BA 30, BA37 and right BA 46.

Conclusion: Cognitive impairment related networks in Parkinson’s disease were identified using resting state functional MRI although validation was not performed.

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MDS Abstracts - https://www.mdsabstracts.org/abstract/cognitive-impairment-related-networks-of-functional-mri-in-parkinsons-disease/