Background: The underlying mechanism of Parkinson's disease (PD) is associated with the neurodegeneration of the dopaminergic neurons, and the cerebellum plays a significant role together in non-motor and motor functions in PD progression. Morphological changes in the cerebellum can greatly impact patients' clinical symptoms, especially motor control symptoms, and may also help distinguish patients from healthy subjects. This study aimed to explore the potential of cerebellar gray matter volume, related to motor control function, as a neuroimaging biomarker to classify patients with PD and healthy controls (HC) by using voxel-based morphometric (VBM) measurements and support vector machine (SVM) methods based on independent component analysis (ICA).
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