Altered network connectivity during resting state in Parkinson’s disease patients with mild cognitive impairment as a marker for dementia

Full text is free to read at publisher website Cognitive disturbances in Parkinson’s disease (PD) contribute to a high dis- ease burden. Mild cognitive impairment (MCI) is common in PD and is a prodromal state of dementia. This study aimed to investigate brain connectivity associated with PD–MCI during resting-state fMRI. This may extend understanding of the neurobiology of pre-clinical dementia in PD. Forty two PD patients and 22 healthy controls (HC) were scanned (3T Siemens PRISMA). Seed-based functional connectivity analysis was performed to identify altered connectivity between seeds in the default mode networks (DMN), fronto-parietal network, and dorsal attention network (DAN) to other regions between groups. The prevalence of MCI in PD patients was 38% (16 of 42). Medial prefrontal cortex in DMN to left calcarine gyrus and right cuneus showed greater connectivity in HC compared to PD non-MCI (nMCI). When compared to HC, the connectivity between the left intraparietal sulcus (IPS) in DAN and left inferior frontal gyrus; left IPS and left middle frontal gyrus; and right IPS and right middle frontal gyrus was decreased in PD–MCI. Whereas, in PD–nMCI compared to HC, the connectivity between left IPS and right inferior frontal gyrus and right IPS and right temporal gyrus. PD–MCI and PD–nMCI showed altered connectivity in DMN and DAN. Although there was no significant difference between PD–MCI and PD–nMCI, different regions were highlighted when compared to HC. This finding could potentially explain that networks in PD–MCI and PD–nMCI may operate differently. PD–MCI and PD–nMCI showed significantly lower connectivity in bilateral IFG which are part of Broca’s area compared to HC. Use of task-based fMRI will provide in-depth knowledge of altered functional connectivity in cognitively impaired PD. We hope to investigate an accurate approach to identify MCI and explore precise resting- state analysis methods