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

2021 ◽  
Vol 15 ◽  
Author(s):  
Raumin S. Neuville ◽  
Matthew N. Petrucci ◽  
Kevin B. Wilkins ◽  
Ross W. Anderson ◽  
Shannon L. Hoffman ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Closed Loop ◽  
Peak Frequency ◽  
Patient Specific ◽  
Beta Band ◽  
Disease Phenotypes ◽  
Beta Power ◽  
Flexion Extension ◽  
High Beta

Background: Resting state beta band (13–30 Hz) oscillations represent pathological neural activity in Parkinson’s disease (PD). It is unknown how the peak frequency or dynamics of beta oscillations may change among fine, limb, and axial movements and different disease phenotypes. This will be critical for the development of personalized closed loop deep brain stimulation (DBS) algorithms during different activity states.Methods: Subthalamic (STN) and local field potentials (LFPs) were recorded from a sensing neurostimulator (Activa® PC + S, Medtronic PLC.) in fourteen PD participants (six tremor-dominant and eight akinetic-rigid) off medication/off STN DBS during 30 s 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 and were compared among movement tasks and between tremor-dominant and akinetic-rigid groups.Results: Beta power peaks were evident during fine, limb, and axial movements in 98% of movement trials; the peak frequencies were similar during each type of movement. Burst power and duration were significantly larger in the high beta band, but not in the low beta band, in the akinetic-rigid group compared to the tremor-dominant group.Conclusion: The conservation of beta peak frequency during different activity states supports the feasibility of patient-specific closed loop DBS algorithms driven by the dynamics of the same beta band during different activities. Akinetic-rigid participants had greater power and longer burst durations in the high beta band than tremor-dominant participants during movement, which may relate to the difference in underlying pathophysiology between phenotypes.

scholarly journals Pathological Beta Burst Dynamics are Conserved Across Different Movements in Parkinson’s Disease

2020 ◽  
Author(s):  
Raumin S. Neuville ◽  
Ross. W. Anderson ◽  
Matthew N. Petrucci ◽  
Jordan E. Parker ◽  
Kevin B. Wilkins ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Deep Brain Stimulation ◽  
Neural Activity ◽  
Resting State ◽  
Closed Loop ◽  
Peak Frequency ◽  
Beta Band ◽  
Beta Power ◽  
Deep Brain

AbstractBackgroundResting 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.MethodsSubthalamic (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.ResultsResting 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.ConclusionsProlonged 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.HighlightsProlonged beta burst durations represent pathological neural activity in Parkinson’s diseaseBeta band peak frequencies are similar across rest, fine, limb and axial movementsBeta burst dynamics are similar among rest and different movement statesConservation of Parkinsonian neural characteristics across different activity states supports the feasibility of closed loop deep brain stimulation systems in daily life

scholarly journals Rapid Motor Fluctuations Reveal Short-Timescale Neurophysiological Biomarkers of Parkinson’s Disease

2020 ◽  
Author(s):  
Minkyu Ahn ◽  
Shane Lee ◽  
Peter M. Lauro ◽  
Erin L. Schaeffer ◽  
Umer Akbar ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Neural Activity ◽  
Motor Performance ◽  
Closed Loop ◽  
Oscillatory Activity ◽  
Patient Specific ◽  
Significant Information ◽  
Informative Signal ◽  
Wide Range

ABSTRACTIdentifying neural activity biomarkers of brain disease is essential to provide objective estimates of disease burden, obtain reliable feedback regarding therapeutic efficacy, and potentially to serve as a source of control for closed-loop neuromodulation. In Parkinson’s Disease (PD), microelectrode recordings (MER) are routinely performed in the basal ganglia to guide electrode implantation for deep brain stimulation (DBS). While pathologically-excessive oscillatory activity has been observed and linked to PD motor dysfunction broadly, the extent to which these signals provide quantitative information about disease expression and fluctuations, particularly at short timescales, is unknown. Furthermore, the degree to which informative signal features are similar or different across patients has not been rigorously investigated. Here, we recorded neural activity from the subthalamic nucleus (STN) of patients with PD undergoing awake DBS surgery while they performed an objective, continuous behavioral assessment. This approach leveraged natural motor performance variations as a basis to identify corresponding neurophysiological biomarkers. Using machine learning techniques, we show it was possible to use neural signals from the STN to decode the level of motor impairment at short timescales (as short as one second). Spectral power across a wide range of frequencies, beyond the classic “β” oscillations, contributed to this decoding. While signals providing significant information about the quality of motor performance were found throughout the STN, the most informative signals tended to arise from locations in or near the dorsolateral, sensorimotor portion. Importantly, the informative patterns of neural oscillations were not fully generalizable across subjects, suggesting a patient-specific approach will be critical for optimal disease tracking and closed-loop neuromodulation.

scholarly journals Motion Characteristics of Subclinical Tremors in Parkinson’s Disease and Healthy Subjects

2021 ◽  
Author(s):  
PING YI CHAN ◽  
ZAIDI MOHD RIPIN ◽  
Sanihah Abdul Halim ◽  
Wan Nor Arifin ◽  
Ahmad Shukri Yahya ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Inertial Sensors ◽  
Frequency Dispersion ◽  
Normal Subjects ◽  
Peak Frequency ◽  
Distal Segment ◽  
Full Spectrum ◽  
Flexion Extension ◽  
Motion Characteristics

Abstract The Parkinson’s disease tremor characteristics reported previously are not applicable to the full spectrum of severity. The characteristics of high- and low-amplitude tremors differ in signal regularity and frequency dispersion, which indicates that characterization should be studied in separate severity. The subclinical tremor of Parkinson’s disease is close to physiological tremor, yet their distinctive features are still undetermined. This study aims to determine joint motion characteristics that are unique to subclinical Parkinson’s disease tremors. The tremors were characterized by four hand–arm motions based on displacement and peak frequencies. The rest and postural tremors of 63 patients and 62 normal subjects were measured with inertial sensors. The baseline was established from normal tremors, and the joint motions were compared within and between the two subject groups. Displacement analysis shows that pronation–supination and wrist abduction–adduction are the most and least predominant tremor motions respectively, for both Parkinson’s disease and normal tremors. However, the subclinical Parkinson’s disease has significant greater in amplitude and peak frequency in specific predominant motions as compared to normal tremor. The flexion-extension of normal postural tremor increases in frequency from proximal to distal segment, which is explainable by mechanical oscillation. This characteristic is also observed in patients but with amplification in wrist and elbow joints. The contributed distinctive characteristics of subclinical tremors provide clues on the physiological manifestation that is a result of the neuromuscular mechanism of Parkinson’s disease.

scholarly journals Dopaminergic Modulation of Spectral and Spatial Characteristics of Parkinsonian Subthalamic Nucleus Beta Bursts

2021 ◽  
Vol 15 ◽  
Author(s):  
Matthias Sure ◽  
Jan Vesper ◽  
Alfons Schnitzler ◽  
Esther Florin
Keyword(s):  
Subthalamic Nucleus ◽  
Closed Loop ◽  
Peak Frequency ◽  
Burst Duration ◽  
Beta Band ◽  
Promising Target ◽  
Dopaminergic Modulation ◽  
The Individual ◽  
High Beta ◽  
Closed Loop Stimulation

In Parkinson’s disease (PD), subthalamic nucleus (STN) beta burst activity is pathologically elevated. These bursts are reduced by dopamine and deep brain stimulation (DBS). Therefore, these bursts have been tested as a trigger for closed-loop DBS. To provide better targeted parameters for closed-loop stimulation, we investigate the spatial distribution of beta bursts within the STN and if they are specific to a beta sub-band. Local field potentials (LFP) were acquired in the STN of 27 PD patients while resting. Based on the orientation of segmented DBS electrodes, the LFPs were classified as anterior, postero-medial, and postero-lateral. Each recording lasted 30 min with (ON) and without (OFF) dopamine. Bursts were detected in three frequency bands: ±3 Hz around the individual beta peak frequency, low beta band (lBB), and high beta band (hBB). Medication reduced the duration and the number of bursts per minute but not the amplitude of the beta bursts. The burst amplitude was spatially modulated, while the burst duration and rate were frequency dependent. Furthermore, the hBB burst duration was positively correlated with the akinetic-rigid UPDRS III subscore. Overall, these findings on differential dopaminergic modulation of beta burst parameters suggest that hBB burst duration is a promising target for closed-loop stimulation and that burst parameters could guide DBS programming.

scholarly journals Coordinated Reset Vibrotactile Stimulation Induces Sustained Cumulative Benefits in Parkinson’s Disease

2021 ◽  
Vol 12 ◽  
Author(s):  
Kristina J. Pfeifer ◽  
Justus A. Kromer ◽  
Alexander J. Cook ◽  
Traci Hornbeck ◽  
Erika A. Lim ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Sensorimotor Cortex ◽  
Feasibility Studies ◽  
Motor Ability ◽  
Beta Band ◽  
Band Power ◽  
Beta Power ◽  
Eeg Recordings ◽  
High Beta ◽  
Coordinated Reset

BackgroundAbnormal synchronization of neuronal activity in dopaminergic circuits is related to motor impairment in Parkinson’s disease (PD). Vibrotactile coordinated reset (vCR) fingertip stimulation aims to counteract excessive synchronization and induce sustained unlearning of pathologic synaptic connectivity and neuronal synchrony. Here, we report two clinical feasibility studies that examine the effect of regular and noisy vCR stimulation on PD motor symptoms. Additionally, in one clinical study (study 1), we examine cortical beta band power changes in the sensorimotor cortex. Lastly, we compare these clinical results in relation to our computational findings.MethodsStudy 1 examines six PD patients receiving noisy vCR stimulation and their cortical beta power changes after 3 months of daily therapy. Motor evaluations and at-rest electroencephalographic (EEG) recordings were assessed off medication pre- and post-noisy vCR. Study 2 follows three patients for 6+ months, two of whom received daily regular vCR and one patient from study 1 who received daily noisy vCR. Motor evaluations were taken at baseline, and follow-up visits were done approximately every 3 months. Computationally, in a network of leaky integrate-and-fire (LIF) neurons with spike timing-dependent plasticity, we study the differences between regular and noisy vCR by using a stimulus model that reproduces experimentally observed central neuronal phase locking.ResultsClinically, in both studies, we observed significantly improved motor ability. EEG recordings observed from study 1 indicated a significant decrease in off-medication cortical sensorimotor high beta power (21—30 Hz) at rest after 3 months of daily noisy vCR therapy. Computationally, vCR and noisy vCR cause comparable parameter-robust long-lasting synaptic decoupling and neuronal desynchronization.ConclusionIn these feasibility studies of eight PD patients, regular vCR and noisy vCR were well tolerated, produced no side effects, and delivered sustained cumulative improvement of motor performance, which is congruent with our computational findings. In study 1, reduction of high beta band power over the sensorimotor cortex may suggest noisy vCR is effectively modulating the beta band at the cortical level, which may play a role in improved motor ability. These encouraging therapeutic results enable us to properly plan a proof-of-concept study.

scholarly journals Adaptive Parameter Modulation of Deep Brain Stimulation Based on Improved Supervisory Algorithm

2021 ◽  
Vol 15 ◽  
Author(s):  
Yulin Zhu ◽  
Jiang Wang ◽  
Huiyan Li ◽  
Chen Liu ◽  
Warren M. Grill
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Supervisory Control ◽  
Control Algorithm ◽  
Beta Band ◽  
Rbf Network ◽  
Stimulation Parameters ◽  
Beta Power ◽  
Band Activity ◽  
Deep Brain

Clinically deployed deep brain stimulation (DBS) for the treatment of Parkinson’s disease operates in an open loop with fixed stimulation parameters, and this may result in high energy consumption and suboptimal therapy. The objective of this manuscript is to establish, through simulation in a computational model, a closed-loop control system that can automatically adjust the stimulation parameters to recover normal activity in model neurons. Exaggerated beta band activity is recognized as a hallmark of Parkinson’s disease and beta band activity in model neurons of the globus pallidus internus (GPi) was used as the feedback signal to control DBS of the GPi. Traditional proportional controller and proportional-integral controller were not effective in eliminating the error between the target level of beta power and the beta power under Parkinsonian conditions. To overcome the difficulties in tuning the controller parameters and improve tracking performance in the case of changes in the plant, a supervisory control algorithm was implemented by introducing a Radial Basis Function (RBF) network to build the inverse model of the plant. Simulation results show the successful tracking of target beta power in the presence of changes in Parkinsonian state as well as during dynamic changes in the target level of beta power. Our computational study suggests the feasibility of the RBF network-driven supervisory control algorithm for real-time modulation of DBS parameters for the treatment of Parkinson’s disease.

scholarly journals Electrode Location in a Microelectrode Recording-Based Model of the Subthalamic Nucleus Can Predict Motor Improvement After Deep Brain Stimulation for Parkinson’s Disease

2019 ◽  
Vol 9 (3) ◽  
pp. 51 ◽  
Author(s):  
Rens Verhagen ◽  
Lo Bour ◽  
Vincent Odekerken ◽  
Pepijn van den Munckhof ◽  
P. Schuurman ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Deep Brain Stimulation ◽  
Subthalamic Nucleus ◽  
Brain Stimulation ◽  
Anatomical Variation ◽  
Patient Specific ◽  
One Year ◽  
Motor Improvement ◽  
Deep Brain

Motor improvement after deep brain stimulation (DBS) in the subthalamic nucleus (STN) may vary substantially between Parkinson’s disease (PD) patients. Research into the relation between improvement and active contact location requires a correction for anatomical variation. We studied the relation between active contact location relative to the neurophysiological STN, estimated by the intraoperative microelectrode recordings (MER-based STN), and contralateral motor improvement after one year. A generic STN shape was transformed to fit onto the stereotactically defined MER sites. The location of 43 electrodes (26 patients), derived from MRI-fused CT images, was expressed relative to this patient-specific MER-based STN. Using regression analyses, the relation between contact location and motor improvement was studied. The regression model that predicts motor improvement based on levodopa effect alone was significantly improved by adding the one-year active contact coordinates (R2 change = 0.176, p = 0.014). In the combined prediction model (adjusted R2 = 0.389, p < 0.001), the largest contribution was made by the mediolateral location of the active contact (standardized beta = 0.490, p = 0.002). With the MER-based STN as a reference, we were able to find a significant relation between active contact location and motor improvement. MER-based STN modeling can be used to complement imaging-based STN models in the application of DBS.

Closed-loop programming using external responses for deep brain stimulation in Parkinson's disease

2021 ◽  
Vol 84 ◽  
pp. 47-51
Author(s):  
Fuyuko Sasaki ◽  
Genko Oyama ◽  
Satoko Sekimoto ◽  
Maierdanjiang Nuermaimaiti ◽  
Hirokazu Iwamuro ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Deep Brain Stimulation ◽  
Brain Stimulation ◽  
Closed Loop ◽  
Deep Brain

scholarly journals Association between Objectively Measured Physical Activity and Gait Patterns in People with Parkinson’s Disease: Results from a 3-Month Monitoring

2018 ◽  
Vol 2018 ◽  
pp. 1-10
Author(s):  
Micaela Porta ◽  
Giuseppina Pilloni ◽  
Roberta Pili ◽  
Carlo Casula ◽  
Mauro Murgia ◽  
...  
Keyword(s):  
Physical Activity ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Gait Analysis ◽  
Time Slot ◽  
Moderate Intensity ◽  
Kinematic Parameters ◽  
Gait Patterns ◽  
Flexion Extension ◽  
Vigorous Intensity

Background. Although physical activity (PA) is known to be beneficial in improving motor symptoms of people with Parkinson’s disease (pwPD), little is known about the relationship between gait patterns and features of PA performed during daily life. Objective. To verify the existence of possible relationships between spatiotemporal and kinematic parameters of gait and amount/intensity of PA, both instrumentally assessed. Methods. Eighteen individuals affected by PD (10F and 8M, age 68.0 ± 10.8 years, 1.5 ≤ Hoehn and Yahr (H&Y) < 3) were required to wear a triaxial accelerometer 24 h/day for 3 consecutive months. They also underwent a 3D computerized gait analysis at the beginning and end of the PA assessment period. The number of daily steps and PA intensity were calculated on the whole day, and the period from 6:00 to 24:00 was grouped into 3 time slots, using 3 different cut-point sets previously validated in the case of both pwPD and healthy older adults. 3D gait analysis provided spatiotemporal and kinematic parameters of gait, including summary indexes of quality (Gait Profile Score (GPS) and Gait Variable Score (GVS)). Results. The analysis of hourly trends of PA revealed the existence of two peaks located in the morning (approximately at 10) and in the early evening (between 18 and 19). However, during the morning time slot (06:00–12:00), pwPD performed significantly higher amounts of steps (4313 vs. 3437 in the 12:00–18:00 time slot, p<0.001, and vs. 2889 in the 18:00–24:00 time slot, p=0.021) and of moderate-to-vigorous PA (43.2% vs. 36.3% in the 12:00–18:00 time slot, p=0.002, and vs. 31.4% in the 18:00–24:00 time slot, p=0.049). The correlation analysis shows that several PA intensity parameters are significantly associated with swing-phase duration (rho = −0.675 for sedentary intensity, rho = 0.717 for moderate-to-vigorous intensity, p<0.001), cadence (rho = 0.509 for sedentary intensity, rho = −0.575 for moderate-to-vigorous intensity, p<0.05), and overall gait pattern quality as expressed by GPS (rho = −0.498 to −0.606 for moderate intensity, p<0.05) and GVS of knee flexion-extension (rho = −0.536 for moderate intensity, p<0.05). Conclusions. Long-term monitoring of PA integrated by the quantitative assessment of spatiotemporal and kinematic parameters of gait may represent a useful tool in supporting a better-targeted prescription of PA and rehabilitative treatments in pwPD.

Sign in / Sign up

Export Citation Format

Share Document