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Abstract #4411

Functional Network-Based Statistics Reveal Abnormal Resting-State Functional Connectivity in Parkinson’s Disease with Apathy

Haikun Xu1, Sha Sa1, Yueluan Jiang2, Mengchao Zhang1, and Lin Liu1
1The Department of Radiology, China-Japan Union Hospital of Jilin University, Changchun, China, 2MR Research Collaboration, Siemens Healthineers, Beijing, China

Synopsis

Keywords: Functional Connectivity, fMRI (resting state), Parkinson’s disease, apathy, network-based statistics

Motivation: Apathy is a common and disabling symptom of Parkinson’s disease (PD), yet brain networks involved in Patients with PD with apathy (PD-A) remain underexplored.

Goal(s): The aim of our study was to identify brain networks of PD-A using network-based statistics (NBS).

Approach: Resting-state fMRI data was obtained from twenty-eight patients with PD-A, 19 PD patients without apathy (PD-NA), and 32 healthy controls (HCs). A network-based statistic analysis was used to isolate networks of interconnected nodes that differ among the three groups.

Results: PD-A showed decreased connectivities in control network, default network, attention network, somatomotor network, temporoparietal network, and visual network.

Impact: We performed NBS analysis to identify brain networks related to PD-A at the whole-brain functional connectome level for the first time. NBS is a validated nonparametrical statistical approach for understanding the neural mechanisms of PD-A.

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