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

ABSTRACTBackgroundPathological 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.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.</jats:sec

Quantitative Digitography Solves the Remote Measurement Problem in Parkinson’s disease

AbstractBackgroundAssessment of motor signs in Parkinson’s disease (PD) has required an in-person examination. However, 50% of people with PD do not have access to a neurologist. Wearable sensors can provide remote measures of some motor signs but require continuous data acquisition for several days. A major unmet need is reliable metrics of all cardinal motor signs, including rigidity, from a simple short active task that can be performed remotely or in the clinic.ObjectiveInvestigate whether thirty seconds of repetitive alternating finger tapping (RAFT) on a portable quantitative digitography (QDG) device, which measures amplitude and timing, produces reliable metrics of all cardinal motor signs in PDMethodsNinety-six individuals with PD and forty-two healthy controls performed a thirty-second QDG-RAFT task and clinical motor assessment. Eighteen individuals were followed longitudinally with repeated assessments for an average of three years and up to six years.ResultsQDG-RAFT metrics differentiated individuals with PD from controls and provided validated metrics for total motor disability (MDS-UPDRS III) and for rigidity, bradykinesia, tremor, gait impairment and freezing of gait (FOG). Additionally, QDG-RAFT tracked disease progression over several years off therapy, and differentiated akinetic rigid from tremor dominant phenotypes, as well as people with from those without FOG.ConclusionsQDG is a reliable technology, which will improve access to care, allows complex remote disease management, and accurate monitoring of disease progression over time in PD. QDG-RAFT also provides the comprehensive PD motor metrics needed for therapeutic trials.</jats:sec

Sixty hertz neurostimulation amplifies subthalamic neural synchrony in Parkinson's disease.

High frequency subthalamic nucleus (STN) deep brain stimulation (DBS) improves the cardinal motor signs of Parkinson's disease (PD) and attenuates STN alpha/beta band neural synchrony in a voltage-dependent manner. While there is a growing interest in the behavioral effects of lower frequency (60 Hz) DBS, little is known about its effect on STN neural synchrony. Here we demonstrate for the first time that during intra-operative 60 Hz STN DBS, one or more bands of resting state neural synchrony were amplified in the STN in PD. We recorded intra-operative STN resting state local field potentials (LFPs) from twenty-eight STNs in seventeen PD subjects after placement of the DBS lead (model 3389, Medtronic, Inc.) before and during three randomized neurostimulation sets (130 Hz/1.35V, 130 Hz/2V, 60 Hz/2V). During 130 Hz/2V DBS, baseline (no DBS) STN alpha (8-12 Hz) and beta (13-35 Hz) band power decreased (N=14, P < 0.001 for both), whereas during 60 Hz/2V DBS, alpha band and peak frequency power increased (P = 0.012, P = 0.007, respectively). The effect of 60 Hz/2V DBS opposed that of power-equivalent (130 Hz/1.35V) DBS (alpha: P < 0.001, beta: P = 0.006). These results show that intra-operative 60 Hz STN DBS amplified whereas 130 Hz STN DBS attenuated resting state neural synchrony in PD; the effects were frequency-specific. We demonstrate that neurostimulation may be useful as a tool to selectively modulate resting state resonant bands of neural synchrony and to investigate its influence on motor and non-motor behaviors in PD and other neuropsychiatric diseases

Peak detection for all fourteen sides.

<p><b>A</b>—<b>N</b> are absolute PSDs from all fourteen recordings. Black = baseline; red = 60 Hz/2V; dashed = 130 Hz/2V. Arrows indicate where peaks were detected by the algorithm, and the color of an arrow corresponds to its PSD spectrum. Black asterisks on <b>J</b> (one for 60 Hz/2V) and <b>K</b> (two, one for 60 Hz/2V and one for baseline) indicate peaks chosen visually.</p

Change (Δ) in Mean Power with Respect to Baseline.

<p>The total power delivered during 60 Hz/2V DBS was equivalent to that delivered during 130 Hz/1.35V DBS. However, their effects on baseline spectral power were significantly different from each other in both the alpha (P < 0.001) and beta (P = 0.006) bands.</p><p>Change (Δ) in Mean Power with Respect to Baseline.</p

Example STN during the different stimulation sets.

<p><b>A</b>, <b>B</b>, <b>C</b>, and <b>D</b> are raw waveforms and spectrograms from the baseline epoch, 130 Hz/2V DBS epoch, 60 Hz/2V DBS epoch, and 130 Hz/1.35V DBS epoch, respectively. Spectrograms are displayed with 99% window overlap. <b>E</b>: Relative PSD traces of the four epochs. Black = baseline; red = 130 Hz/2V; blue = 60 Hz/2V; green = 130 Hz/1.35V. Colored dashed lines represent 95% confidence intervals for each spectrum.</p