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The importance of nonmotor symptoms in understanding the pathogenesis of the heterogeneity of Parkinson's disease has been highlighted. However, the validation of specific brain network biomarkers in nonmotor symptom subtypes is currently lacking. By performing a new approach to compute functional connectivity with structural prior using magnetic resonance imaging, the present study computed both functional connectivity and fusional connectivity features in the nonmotor symptom subtypes of Parkinson's disease, one characterized by cognitive impairment with late onset and the other depression with early onset.

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