ABSTRACT Parkinson disease (PD) is a progressive neurodegenerative disease characterized by motor, cognitive, and psychiatric manifestations resulting from abnormal protein deposition and neurotransmitter deficits. The variability in clinical presentation and progression in PD likely reflects underlying variability in brain pathology. Although current treatments provide dramatic motor benefit in PD, they fail to fully alleviate gait impairment and non-motor symptoms and may exacerbate cognitive and psychiatric features. These more complex symptoms are linked to the function of large-scale brain networks, which can be measured with resting-state functional connectivity MRI (RSFC). In our past work, we demonstrated that PD participants, as a group, show differences in RSFC relative to healthy controls. However, development of clinical applications requires reliable individual- level biomarkers that capture the widespread neuropathology and respects the clinical heterogeneity of PD, opening the avenue to “personalized medicine” in PD. Recently developed precision-mapping RSFC approaches now permit identification of individual-level differences in brain network organization with high reliability and may provide a non-invasive biomarker for PD. Therefore, we propose to identify individual-level RSFC markers of PD, examine the relationship of these precision RSFC markers with the clinical manifestations and neuropathology of PD, and determine if precision RSFC markers predict cognitive decline and dementia in PD.