Computational markers of rhythmic timing in Parkinson's disease

Abstract

Sensorimotor synchronization requires the nervous system to predict upcoming events while continuously correcting the timing of ongoing actions. Parkinson's disease (PD) is associated with impaired temporal processing, but it remains unclear which cognitive-computational mechanisms underlie rhythmic timing deficits. Here, we applied the Adaptation and Anticipation Model (ADAM) to synchronized finger-tapping data from participants with PD and controls across four steady tempi. After data screening, analyzes included 35 participants with PD and 28 controls. PD was associated with reduced synchronization accuracy and stability, reflected in larger absolute asynchronies and higher variability of asynchronies. ADAM parameter estimates indicated lower phase correction (coupling strength) and higher central timekeeper noise in the PD group, whereas period correction (tempo matching) and peripheral motor noise showed no robust group differences. Across participants, timekeeper noise predicted synchronization accuracy. Phase correction, timekeeper noise, and motor noise predicted synchronization stability, but their associations differed between groups: phase correction was more closely associated with stability in PD, whereas timekeeper and motor noise were more closely associated with stability in controls. These findings suggest that sensorimotor synchronization deficits in PD reflect reduced use of recent timing errors to guide upcoming movements and less precise internal timekeeping. Error correction and timekeeper noise thus emerge as candidate computational markers of altered rhythmic timing in PD, with potential relevance for understanding individual differences in responses to rhythmic auditory cueing.