Abstract
Elevated β (13-30 Hz) synchronization within the subthalamic nucleus (STN) characterizes bradykinesia in Parkinson's disease (PD). β oscillations may serve as biomarkers for off-period motor symptoms and control signals for adaptive, closed-loop deep brain stimulation (DBS) in PD. However, their relation to striatal dopaminergic denervation and PD progression remains uncertain. Research on β oscillations is limited to advanced PD stages undergoing DBS, prohibiting insights into early-stage progression and compensatory mechanisms. We therefore investigated β dynamics, correlation with motor performance, and nigrostriatal neurodegeneration in a progressive PD rat model overexpressing AAV1/2-A53T α-synuclein, mimicking PD pathology. Over 8 weeks, we longitudinally conducted behavioural assessments using the cylinder test and recorded local field potentials (LFP) from the STN and motor cortex (MCx) in the AAV-A53T-αSyn PD rat model. Increased β power and burst parameters accompanied early motor deficits in the AAV-A53T-αSyn PD rat model. Changes were observed in the STN and MCx versus empty vector controls; alterations intensified with pathology progression. Increased high β power and burst parameters (e.g. long burst probability in the STN but not MCx) were associated with motor impairment and nigrostriatal dopaminergic neurodegeneration. Multivariate analyses from these rat-derived data demonstrated that combined β parameters in the cortico-subthalamic pathway and striatal dopaminergic fibre density predicted motor performance and neurodegeneration. Additional multivariate analyses confirmed the translational relevance of the A53T PD model, linking β activity and dopamine uptake to motor impairment (UPDRS III Med-OFF) in human PD patients. Our data support the pathophysiological significance of β oscillations as a progression marker of PD for motor symptoms and neurodegeneration. Our predictive models carry translational relevance, with the prospect of monitoring disease progression and neuroprotective outcomes in PD based on LFP recordings.