Increase in Beta-Band Activity during Preparation for Overt Speech in Patients with Parkinson’s Disease

AbstractParkinson’s disease is characterized by a gradual loss of dopaminergic neurons, which are associated with altered neuronal activity in the beta band (13-30 Hz). Assessing beta band activity typically involves transforming the time-series to get the power of the signal in the frequency-domain. Such transformation assumes that the time-series can be reduced to a combination of steady-state sine-and cosine waves. However, recent studies have suggested that this approach masks relevant biophysical features in the beta band activity—for example, that the beta band exhibits transient bursts of high-amplitude activity.In an exploratory study we used magnetoencephalography (MEG) to record cortical beta band activity to characterize how spontaneous cortical beta bursts manifest in Parkinson’s patients ON and OFF dopaminergic medication, and compare this to matched healthy controls. From three minutes of MEG data, we extracted the time-course of beta band activity from the sensorimotor cortex and characterized high-amplitude epochs in the signal to test if they exhibited burst like properties. We then compared the rate, duration, inter-burst interval, and peak amplitude of the high-amplitude epochs between the Parkinson’s patients and healthy controls.Our results show that Parkinson’s patients OFF medication had a 6-17% lower beta bursts rate compared to healthy controls, while both the duration and the amplitude of the bursts were the same for Parkinson’s patients and healthy controls and medicated state of the Parkinson’s patients. These data thus support the view that beta bursts are fundamental underlying features of beta band activity, and show that changes in cortical beta band power in PD can be explained primarily by changes in the underlying burst rate. Importantly, our results also revealed a relationship between beta bursts rate and motor symptom severity in PD: a lower burst rate scaled with increased in severity of bradykinesia and postural/kinetic tremor. Beta burst rate might thus serve as neuromarker for Parkinson’s disease that can help in the assessment of symptom severity in Parkinson’s disease or evaluate treatment effectiveness.

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Bursts of beta oscillation differentiate postperformance activity in the striatum and motor cortex of monkeys performing movement tasks

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1517629112 ◽

2015 ◽

Vol 112 (44) ◽

pp. 13687-13692 ◽

Cited By ~ 151

Author(s):

Joseph Feingold ◽

Daniel J. Gibson ◽

Brian DePasquale ◽

Ann M. Graybiel

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Motor Cortex ◽

Time Scale ◽

Premotor Cortex ◽

Short Time Scale ◽

Beta Activity ◽

Beta Band ◽

Time Specific ◽

Band Activity

Studies of neural oscillations in the beta band (13–30 Hz) have demonstrated modulations in beta-band power associated with sensory and motor events on time scales of 1 s or more, and have shown that these are exaggerated in Parkinson’s disease. However, even early reports of beta activity noted extremely fleeting episodes of beta-band oscillation lasting <150 ms. Because the interpretation of possible functions for beta-band oscillations depends strongly on the time scale over which they occur, and because of these oscillations’ potential importance in Parkinson’s disease and related disorders, we analyzed in detail the distributions of duration and power for beta-band activity in a large dataset recorded in the striatum and motor-premotor cortex of macaque monkeys performing reaching tasks. Both regions exhibited typical beta-band suppression during movement and postmovement rebounds of up to 3 s as viewed in data averaged across trials, but single-trial analysis showed that most beta oscillations occurred in brief bursts, commonly 90–115 ms long. In the motor cortex, the burst probabilities peaked following the last movement, but in the striatum, the burst probabilities peaked at task end, after reward, and continued through the postperformance period. Thus, what appear to be extended periods of postperformance beta-band synchronization reflect primarily the modulated densities of short bursts of synchrony occurring in region-specific and task-time-specific patterns. We suggest that these short-time-scale events likely underlie the functions of most beta-band activity, so that prolongation of these beta episodes, as observed in Parkinson’s disease, could produce deleterious network-level signaling.

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Reduction of spontaneous cortical beta bursts in Parkinson’s disease is linked to symptom severity

Brain Communications ◽

10.1093/braincomms/fcaa052 ◽

2020 ◽

Vol 2 (1) ◽

Author(s):

Mikkel C Vinding ◽

Panagiota Tsitsi ◽

Josefine Waldthaler ◽

Robert Oostenveld ◽

Martin Ingvar ◽

...

Keyword(s):

Parkinson’S Disease ◽

Time Series ◽

Parkinson's Disease ◽

Sensorimotor Cortex ◽

Symptom Severity ◽

Time Course ◽

Motor Symptom ◽

Healthy Controls ◽

Beta Band ◽

Band Activity

Abstract Parkinson’s disease is characterized by a gradual loss of dopaminergic neurons, which is associated with altered neuronal activity in the beta-band (13–30 Hz). Assessing beta-band activity typically involves transforming the time-series to get the power of the signal in the frequency domain. Such transformation assumes that the time-series can be reduced to a combination of steady-state sine- and cosine waves. However, recent studies have suggested that this approach masks relevant biophysical features in the beta-band—for example, that the beta-band exhibits transient bursts of high-amplitude activity. In an exploratory study, we used magnetoencephalography to record beta-band activity from the sensorimotor cortex, to characterize how spontaneous cortical beta bursts manifest in Parkinson’s patients on and off dopaminergic medication, and compare this to matched healthy controls. We extracted the time-course of beta-band activity from the sensorimotor cortex and characterized bursts in the signal. We then compared the burst rate, duration, inter-burst interval and peak amplitude between the Parkinson’s patients and healthy controls. Our results show that Parkinson’s patients off medication had a 5–17% lower beta bursts rate compared to healthy controls, while both the duration and the amplitude of the bursts were the same for healthy controls and medicated state of the Parkinson’s patients. These data thus support the view that beta bursts are fundamental underlying features of beta-band activity, and show that changes in cortical beta-band power in Parkinson’s disease can be explained—primarily by changes in the underlying burst rate. Importantly, our results also revealed a relationship between beta burst rate and motor symptom severity in Parkinson’s disease: a lower burst rate scaled with increased severity of bradykinesia and postural/kinetic tremor. Beta burst rate might thus serve as a neuromarker for Parkinson’s disease that can help in the assessment of symptom severity in Parkinson’s disease or in the evaluation of treatment effectiveness.

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Reinforcement magnitudes modulate subthalamic beta band activity in patients with Parkinson’s disease

Scientific Reports ◽

10.1038/s41598-018-26887-3 ◽

2018 ◽

Vol 8 (1) ◽

Cited By ~ 1

Author(s):

Henning Schroll ◽

Andreas Horn ◽

Joachim Runge ◽

Axel Lipp ◽

Gerd-Helge Schneider ◽

...

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Beta Band ◽

Band Activity

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Dopamine and beta-band oscillations differentially link to striatal value and motor control

Science Advances ◽

10.1126/sciadv.abb9226 ◽

2020 ◽

Vol 6 (39) ◽

pp. eabb9226

Author(s):

H. N. Schwerdt ◽

K. Amemori ◽

D. J. Gibson ◽

L. L. Stanwicks ◽

T. Yoshida ◽

...

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Oscillatory Activity ◽

Beta Band ◽

Performance History ◽

Multimodal Systems ◽

Long Time ◽

Normative Rule ◽

Time Frames ◽

Band Activity

Parkinson’s disease is characterized by decreased dopamine and increased beta-band oscillatory activity accompanying debilitating motor and mood impairments. Coordinate dopamine-beta opposition is considered a normative rule for basal ganglia function. We report a breakdown of this rule. We developed multimodal systems allowing the first simultaneous, chronic recordings of dopamine release and beta-band activity in the striatum of nonhuman primates during behavioral performance. Dopamine and beta signals were anticorrelated over seconds-long time frames, in agreement with the posited rule, but at finer time scales, we identified conditions in which these signals were modulated with the same polarity. These measurements demonstrated that task-elicited beta suppressions preceded dopamine peaks and that relative dopamine-beta timing and polarity depended on reward value, performance history, movement, and striatal domain. These findings establish a new view of coordinate dopamine and beta signaling operations, critical to guide novel strategies for diagnosing and treating Parkinson’s disease and related neurodegenerative disorders.

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

Frontiers in Neuroscience ◽

10.3389/fnins.2021.750806 ◽

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.

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