Differential Effects of Pathological Beta Burst Dynamics Between Parkinson’s Disease Phenotypes Across Different Movements

Abstract

Background: Resting state beta band (13-30 Hz) oscillations represent pathological neural activity in Parkinson's disease (PD). It is unknown whether the peak frequency or dynamics of beta oscillations change among rest, fine, limb and axial movements. This will be critical for the development and feasibility of closed loop deep brain stimulation (DBS) algorithms during resting and movement states. Methods: Subthalamic (STN) local field potentials (LFPs) were recorded from a sensing neurostimulator (Activa PC+S, Medtronic Inc.,) and synchronized to kinematic recordings in twelve PD participants off medication/off STN DBS during thirty seconds of repetitive alternating finger tapping, wrist-flexion extension, stepping in place, and free walking. Beta power peaks and beta burst dynamics were identified by custom algorithms; beta burst dynamics were compared among rest and movement tasks. Results: Resting state burst durations were longer in a PD beta band, which was elevated above the 1/f physiological spectrum compared to an overlapping band (p < 0.001). Beta power peaks were evident during fine, limb, and axial movements in 98% of movement trials; the peak frequencies were similar during movements and at rest. Burst duration, average and peak power were also similar among the four movement tasks across the group but varied within individuals. Conclusions: Prolonged burst durations were a feature of PD bands elevated above and not of PD bands overlapping the 1/f spectrum. The conservation of rest/movement band peak frequency and burst dynamics during different activity states supports the feasibility of successful closed loop DBS algorithms driven by beta burst dynamics during different activities and at rest.

Perspective: Evolution of Control Variables and Policies for Closed-Loop Deep Brain Stimulation for Parkinson’s Disease Using Bidirectional Deep-Brain-Computer Interfaces

“…The ability to record synchronized neural and kinematic signals in freely moving individuals with PD using the implanted, sensing dBCI (Activa™ PC+S, Medtronic PLC), led to the discovery of neural and kinematic signals that corresponded to abnormal movements such as bradykinesia, gait impairment, and FOG. These recordings have demonstrated that STN beta band power can be tracked during ongoing movement in PD, that the peak frequency of the beta band did not change among rest, or finger, limb and axial movements, and that there was a subject-specific band of elevated beta power that was conserved throughout a variety of gait tasks (Blumenfeld et al, 2017 ; Anidi et al, 2018 ; Neuville et al, 2020 ). These contributions demonstrate that control policy algorithms in closed-loop DBS will be able to track, and do not need to adjust the frequency of, the beta band neural input in freely moving people with PD.…”

Cortical and Subthalamic Nucleus Spectral Changes During Limb Movements in Parkinson's Disease Patients with and Without Dystonia

“…31 Other studies analyzing spontaneous LFPs during resting, sitting, standing, and walking have found mixed results regarding movement-related STN beta desynchronization. [32][33][34][35][36] Greater mechanistic knowledge about changes in STN field potentials during specific limb movements could lead to a better understanding of the pathophysiology and novel strategies for therapy.…”

“…One recent study reported that lower and upper limb movement onset coincides with high and low beta desynchronization, respectively, in both STN and motor cortex 31 . Other studies analyzing spontaneous LFPs during resting, sitting, standing, and walking have found mixed results regarding movement‐related STN beta desynchronization 32‐36 . Greater mechanistic knowledge about changes in STN field potentials during specific limb movements could lead to a better understanding of the pathophysiology and novel strategies for therapy.…”

Diurnal modulation of subthalamic beta oscillatory power in Parkinson’s disease patients during deep brain stimulation

“…Finally, levels of physical activity are also related to the time of day. This may lead to physiological modulation of beta in response to movements (Jenkinson & Brown, 2011; Kühn et al, 2004; Lofredi et al, 2019; Neuville et al, 2021; Quinn et al, 2015), but will also increase potential artifact sources. It is already known that the heartbeat can affect measures of beta power in certain DBS devices (Neumann et al, 2021; Sorkhabi et al, 2020), and movements themselves present another potential source of transient artifacts in LFP recordings (Hammer et al, 2021; Swann, Hemptinne, Miocinovic, et al, 2018).…”