Abstract

Recent studies have discovered that functional connections are impaired in patients with Parkinson's disease (PD) accompanied by hallucinations (PD-H), even at the preclinical stage. The cerebellum has been implicated in playing a role in cognitive processes. However, the functional connectivity (FC) between the cognitive sub-regions of the cerebellum in PD patients with hallucinations needs further clarification. Resting-state functional magnetic resonance imaging (rs-fMRI) data were collected from three groups (17 PD-H patients, 13 patients with Parkinson's disease not accompanied by hallucinations (PD-NH), and 26 healthy controls (HC)). The data were collected in this study to investigate the impact of cerebellar FC changes on cognitive performance. Additionally, we define cerebellar FC as a training feature for classifying all subjects using Support Vector Machines (SVMs). We found that in the PD-H patients, there was an increase in FC within the left side of the precuneus (PCUN) compared to the HC. Additionally, there was an increase in FC within the bilateral opercular part of the inferior frontal gyrus (IFGoprec) and triangular part of the inferior frontal gyrus (IFCtriang), as well as the left side of the postcentral gyrus (PoCG), inferior parietal lobe (IPL), and PCUN compared to the PD-NH patients. In the machine learning training results, cerebellar FC has also been proven to be an effective biomarker feature, achieving a recognition rate of over 90% for PD-H. These findings indicate that the cortico-cerebellar FC in PD-H and PD-NH patients was significantly disrupted, with different patterns of distribution. The proposed pipeline offers a promising, low-cost alternative for diagnosing preclinical PD-H and may also be beneficial for other degenerative brain disorders.

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