Research in Parkinson's disease (PD) has centred around the exploration of beta activity (12-30 Hz) and beta bursts as potential markers for evaluating therapeutic effectiveness, and in the context of closed-loop deep brain stimulation (DBS). Although current clinical trials of closed-loop DBS employ beta power as a physiomarker to adjust the stimulation, uncertainties remain regarding how the beta power and characteristics of beta bursts respond to stimulation and different symptomatic scenarios. High-density surface electromyography (HDsEMG) offers a promising non-invasive neural signal to explore the underlying mechanisms of beta activity and bursts along the corticospinal tract. This technique records muscle activity with high spatial and temporal resolution, allowing for a comprehensive assessment of electrophysiological activity. Recent research findings have demonstrated that beta activity occurs in bursting patterns at both cortical and motor unit levels during isometric contractions of the tibialis anterior muscle [1]. This indicates that peripherally measured beta bursts are a consequence of cortical projections. Expanding on this work, our study replicates these findings using smaller muscles of the upper limb, and in a case-study demonstrated its sensitivity to DBS.  

We recorded from the forearm muscles to track beta burst characteristics (e.g. duration, amplitude, rate) at the peripheral levels. Motor cortex activity was recorded using a 19-electrode electroencephalography (EEG) headset, while forearm muscle activity was monitored using HDsEMG with 256 electrodes, targeting the flexor carpi radialis (FCR) and ulnaris (FCU), and the extensor carpi radialis (ECR) and ulnaris (ECU). We incorporated torque measurements during a trapezoidal force tracking task at varying tasks (isometric wrist flexion and extension), and varying percentages (5%, 10%, 20%, and 30%) of maximum voluntary contraction (MVC). This involved both non-PD (n=6) and PD (n=1) participants, with a particular emphasis on a case study featuring a PD-DBS patient (n=1). In this case study, the participant manipulated their DBS settings using a remote control (decreasing left electrode amplitude by 1.5mA), allowing us to examine the sensitivity of HDsEMG signals in detecting changes induced by alterations in DBS parameters.  

Our analysis involved the decomposition of a substantial number of motor units for each muscle (up to 27 for the ECU), revealing greater decomposition in wrist extension than flexion (p=0.004, Mann-Whitney U test). Furthermore, our exploration into variations in beta burst features showed correlations between HDsEMG and EEG beta bursts (Pearson correlation coefficients 0.54, 0.56 and 0.78 respectively for rate, duration, and amplitude), suggesting a degree of coherence between the beta bursts occurring within the motor cortex and those in the peripheral regions. We validated the multimodal setup’s ability to track beta bursts across the corticospinal tract and showed its generalisability and sensitivity to PD and PD-DBS patients. This integrated approach holds the potential to understand the dynamic changes the brain undergoes during neuromodulation interventions and fluctuations in symptoms.