Beta Burst Waveform Motifs Link Cortico-Subcortical Connectivity and Clinical Improvement in Parkinson’s Disease

Beta bursts are increasingly being studied as biomarkers of Parkinson’s disease (PD) symptoms and therapeutic response. While most prior work has focused on time-frequency burst features such as duration or amplitude, recent evidence suggests that the temporal waveform of individual bursts carries additional functional significance. Here, we investigated whether distinct beta burst waveform motifs in the subthalamic nucleus (STN) and sensorimotor cortex are modulated by levodopa and whether these modulations relate to cortico-subcortical connectivity and clinical improvement. We analyzed resting-state activity from 11 PD patients recorded from deep contacts in the STN and EEG electrodes over the motor cortex, both before and after levodopa administration. Using a novel adaptive burst detection algorithm, we extracted individual beta bursts and characterized their waveform variability using principal component analysis. While levodopa had inconsistent effects on conventional time-frequency burst features, it selectively modulated the rate of specific burst waveform motifs in the sensorimotor cortex, consistently across patients. Furthermore, we found that levodopa increased functional connectivity between the STN and cortex specifically during bursts with certain waveform motifs, and these connectivity changes predicted individual clinical improvement. Our findings suggest that beta bursts are not uniform events but comprise a set of functionally distinct motifs whose rates and network involvement are modulated by dopaminergic therapy. This waveform-based approach refines our understanding of pathological beta activity in PD and offers novel targets for personalized, adaptive neuromodulation strategies.