A Novel Method for Calculating Beta Band Burst Durations in Parkinson’s Disease Using a Physiological Baseline

Abstract

Parkinson's disease, Deep Brain Stimulation HighlightsA novel method for measuring variability in subthalamic local field potential oscillations in Parkinson's disease using a physiological baseline of power.Modeling normal brain activity using a physiological 1/f spectrum.Burst durations depend on choice of bandwidth and center frequency.Defining an inert frequency band whose mean burst duration overlap the physiological 1/f spectrum, from which the baseline was determined.Burst durations progressively shortened during increasing intensities of deep brain stimulation. ABSTRACT BackgroundPathological bursts of neural activity in Parkinson's disease present as exaggerated subthalamic neuronal oscillations in the 8-30 Hz frequency range and are related to motor impairment. New MethodThis study introduces a novel method for determining burst dynamics using a baseline that matches physiological 1/f spectrum activity. We used resting state local field potentials from people with Parkinson's disease and a simulated 1/f signal to measure beta burst durations, to demonstrate how tuning parameters (i.e., bandwidth and center frequency) affect burst durations, to compare this with high power threshold methods, and to study the effect of increasing neurostimulation intensities on burst duration. ResultsBurst durations calculated using the Anderson method captured the longest and broadest distribution of burst durations in a pathological beta band compared to previous methods. Mean beta band burst durations were significantly shorter on compared to off neurostimulation (p = 0.011), and their distribution was shifted towards that of the physiological 1/f spectrum during increasing intensities of stimulation. Comparison with Existing MethodExisting methods of measuring local field potential power either lack temporal specificity to detect bursts (power spectral density diagrams and spectrograms) or include only higher power bursts and portions of the neural signal. ConclusionsWe suggest that this novel method is well suited to quantify the full range of fluctuations in beta band neural activity in the Parkinsonian brain. This method may reveal more relevant feedback biomarkers than averaged beta band power for future closed loop algorithms.

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

“…The temporal dynamics of beta band power (termed beta bursts) have been associated with clinical assessments of disease severity and with kinematic measures of bradykinesia, gait impairment, and FOG (Tinkhauser et al, 2017b ; Anidi et al, 2018 ). There is a similar dose dependency between DBS intensity and beta burst duration both during rest and movement: increasing intensities of STN DBS were associated with shorter mean beta band durations and improved bradykinesia (Anderson et al, 2020 ). This dose-dependency of beta bursts suggests that a similar dual-threshold control policy in bidirectional DBCIs that monitors prolonged beta burst durations, as opposed to beta power specifically, could keep the DBS intensity within a therapeutic window.…”

“…The benchtop system played back previously recorded neural data and recorded output stimulation from the developed system. We used STN beta burst durations as the neural inputs and developed a novel faster time scale single threshold control policy algorithm that only increased stimulation intensity after the burst duration exceeded the inferred normal duration from simulated 1/f data, red bars in the left-hand panel in Figure 2 (Anderson et al, 2020 ). The benchtop system successfully adjusted stimulation in real-time in response to prolonged beta burst durations and demonstrated the feasibility of the algorithm by responding to pre-recorded STN data from an individual with PD (Petrucci et al, 2020a ).…”

Lack of progression of beta dynamics after long‐term subthalamic neurostimulation

“…Parkinson's disease is a progressive neurological disease, whose severity worsens even on optimal doses of medication. [1][2][3] Recordings of local field potentials (LFPs) in the subthalamic nucleus (STN) have revealed exaggerated neuronal oscillations and synchrony in the beta frequency band (13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30), known as the beta oscillopathy, which is a marker of the pathophysiology of Parkinson's disease. [4][5][6][7] Beta power has been linked to motor impairment and longer duration of fluctuations of beta power (bursts) are associated with increased motor and gait disablity.…”

The Sequence Effect Worsens over Time in Parkinson’s disease and Responds to Open and Closed-Loop Subthalamic Nucleus Deep Brain Stimulation

“…Recently, Lofredi et al demonstrated that the duration of low beta (13-20 Hz) bursts in the pathological range predicted the degree of the sequence effect in limb movement [33]. We demonstrated that STN DBS shortened resting state beta band burst durations in a dose-dependent manner [48] and that both 60 Hz and 140 Hz DBS shortened prolonged beta burst durations in people with PD and FOG, while improving their FOG [49]. This suggests that one mechanism for the therapeutic effect of DBS on the sequence effect may be in its ability to attenuate pathological beta burst durations.…”