Alternating Modulation of Subthalamic Nucleus Beta Oscillations during Stepping

Abstract

Gait disturbances in Parkinson's disease are commonly refractory to current treatment options and majorly impair patient's quality of life. Auditory cues facilitate gait and prevent motor blocks. We investigated how neural dynamics in the human subthalamic nucleus of Parkinsons's disease patients (14 male, 2 female) vary during stepping and whether rhythmic auditory cues enhance the observed modulation. Oscillations in the beta band were suppressed after ipsilateral heel strikes, when the contralateral foot had to be raised, and reappeared after contralateral heel strikes, when the contralateral foot rested on the floor. The timing of this 20–30 Hz beta modulation was clearly distinct between the left and right subthalamic nucleus, and was alternating within each stepping cycle. This modulation was similar, whether stepping movements were made while sitting, standing, or during gait, confirming the utility of the stepping in place paradigm. During stepping in place, beta modulation increased with auditory cues that assisted patients in timing their steps more regularly. Our results suggest a link between the degree of power modulation within high beta frequency bands and stepping performance. These findings raise the possibility that alternating deep brain stimulation patterns may be superior to constant stimulation for improving parkinsonian gait.SIGNIFICANCE STATEMENT Gait disturbances in Parkinson's disease majorly reduce patients' quality of life and are often refractory to current treatment options. We investigated how neural activity in the subthalamic nucleus of patients who received deep brain stimulation surgery covaries with the stepping cycle. 20–30 Hz beta activity was modulated relative to each step, alternating between the left and right STN. The stepping performance of patients improved when auditory cues were provided, which went along with enhanced beta modulation. This raises the possibility that alternating stimulation patterns may also enhance beta modulation and may be more beneficial for gait control than continuous stimulation, which needs to be tested in future studies.

Corticomuscular control of walking in older people and people with Parkinson’s disease

“…Notably, walking and cycling was found to decrease STN beta power in people with PD (Storzer et al 2017, Hell et al 2018. Moreover, stepping movements have been shown to modulate STN beta power relative to the movement phase (suppressed during contralateral foot lift, Fischer et al 2018). Some disturbances in gait-related brain activity may be due to the dopamine deficit in the basal ganglia-thalamo-cortical circuit in PD, but other pathways, including cortical cholinergic deficits, may also contribute to PD gait disorders (Bohnen & Jahn 2013, Lewis 2015, Peterson & Horak 2016.…”

Toward Electrophysiology-Based Intelligent Adaptive Deep Brain Stimulation for Movement Disorders

“…Nevertheless, it was recently demonstrated that beta activity reflects bradykinesia even during phases of relative desynchronization during continuous movement [63]. Moreover, specific patterns for walking [64][65][66][67] and even riding the bicycle [68] have been reported for beta activity in PD patients. Studies on the spatial distribution of subthalamic beta activity have found a robust overlap between the location of peak beta power with the optimal target location in the dorsolateral STN [69].…”

“…Ideally, intelligent aDBS could evolve from a computational model based on deep learning with hierarchically organized artificial neural networks that are optimized to predict the need to adapt DBS stimulation parameters in real-time. Practically, electrophysiological time series data from LFP and ECoG electrodes of each channel can be transformed to the timefrequency domain to produce feature matrices with high temporal resolution from relevant frequency bands (theta, alpha, low beta, high beta, low gamma, high gamma) in addition to raw data and full spectrum features such as total power and variance that have previously been used to decode behavior from neural fields [64,[208][209][210][211][212]. Recurrent neural network approaches (e.g., long short-term memory networks; LSTM [213,214]) could be used for training on oscillatory neural time series data [215] to simultaneously conduct hierarchical classifications and predictions that can ultimately guide DBS parameter adaptations.…”

“…Importantly, this approach can learn an almost infinite amount of spectral, spatial, and temporal patterns of activity, given that both concurrent and preceding activities are used to inform the model. This strategy may have significant benefit in the detection of rhythmic activity, such as walking [64,67], speaking, tremor, [60,61] or sleep [77], as well as in the prediction of clinical symptom severity [34,35,59], where a continuous increase of pathological activity could predict upcoming symptoms more robustly than single time points. This could also account for symptom-specific differences in the time lag to therapeutic response.…”

Entraining stepping movements of Parkinson’s patients to alternating subthalamic nucleus deep brain stimulation

“…Conventional high-frequency DBS is provided continuously and is thought to attenuate beta activity (Kühn et al, 2008). Several reports describe changes in STN beta activity or its phase locking between hemispheres during gait (Arnulfo et al, 2018;Hell, Plate, Mehrkens, & Bötzel, 2018;Storzer et al, 2017), and our previous work has shown rhythmic modulation of STN activity when patients perform stepping movements (Fischer et al, 2018): Beta (20-30 Hz) activity briefly increased just after the contralateral heel strike during the stance period, resulting in alternating peaks of right and left STN activity. Auditory cueing, which also helps improve gait rhythmicity, further enhanced this alternating pattern (Fischer et al, 2018).…”