scholarly journals Effect of levodopa on electroencephalographic biomarkers of the parkinsonian state

2019 ◽  
Vol 122 (1) ◽  
pp. 290-299 ◽  
Author(s):  
Andrew M. Miller ◽  
Svjetlana Miocinovic ◽  
Nicole C. Swann ◽  
Sheila S. Rajagopalan ◽  
David M. Darevsky ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Voluntary Movement ◽  
Motor Impairment ◽  
Body Part ◽  
Dopaminergic Therapy ◽  
Scalp Eeg ◽  
New Findings ◽  
Phase Amplitude ◽  
Motor Improvement

The objective of this study was to evaluate proposed electroencephalographic (EEG) biomarkers of Parkinson’s disease (PD) and test their correlation with motor impairment in a new, well-characterized cohort of PD patients and controls. Sixty-four-channel EEG was recorded from 14 patients with rigid-akinetic PD with minimal tremor and from 14 age-matched healthy controls at rest and during voluntary movement. Patients were tested off and on medication during a single session. Recordings were analyzed for phase-amplitude coupling over sensorimotor cortex and for pairwise coherence from all electrode pairs in the recording montage (distributed coherence). Phase-amplitude coupling and distributed coherence were found to be elevated Off compared with On levodopa, and their reduction was correlated with motor improvement. In the Off medication state, phase-amplitude coupling was greater in sensorimotor contacts contralateral to the most affected body part and reduced by voluntary movement. We conclude that phase-amplitude coupling and distributed coherence are cortical biomarkers of the parkinsonian state that are detectable noninvasively and may be useful as objective aids for management of dopaminergic therapy. Several analytic methods may be used for noninvasive measurement of abnormal brain synchronization in PD. Calculation of phase-amplitude coupling requires only a single electrode over motor cortex. NEW & NOTEWORTHY Several EEG biomarkers of the parkinsonian state have been proposed that are related to abnormal cortical synchronization. We report several new findings in this study: correlations of EEG markers of synchronization with specific motor signs of Parkinson’s disease (PD), and demonstration that one of the EEG markers, phase-amplitude coupling, is more elevated over the more clinically affected brain hemisphere. These findings underscore the potential utility of scalp EEG for objective, noninvasive monitoring of medication state in PD.

scholarly journals Subthalamic nucleus phase–amplitude coupling correlates with motor impairment in Parkinson’s disease

2016 ◽  
Vol 127 (4) ◽  
pp. 2010-2019 ◽  
Author(s):  
Bernadette C.M. van Wijk ◽  
Martijn Beudel ◽  
Ashwani Jha ◽  
Ashwini Oswal ◽  
Tom Foltynie ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Subthalamic Nucleus ◽  
Motor Impairment ◽  
Phase Amplitude

scholarly journals Characteristics of Beta Waveform Shape in Parkinson’s Disease Detected with Scalp Electroencephalography

2019 ◽  
Author(s):  
Nicko Jackson ◽  
Scott R. Cole ◽  
Bradley Voytek ◽  
Nicole C. Swann
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Beta Phase ◽  
Beta Oscillations ◽  
Non Invasive ◽  
Scalp Eeg ◽  
Phase Amplitude ◽  
Beta Frequency ◽  
Intracranial Recordings ◽  
Beta Oscillation

AbstractNeural activity in the beta frequency range (13-30 Hz) is excessively synchronized in Parkinson’s Disease (PD). Previous work using invasive intracranial recordings and non-invasive scalp electroencephalography (EEG) has shown that correlations between beta phase and broadband gamma amplitude (i.e., phase-amplitude coupling) are elevated in PD, perhaps a reflection of this synchrony. Recently, it has also been shown, in invasive human recordings, that nonsinusoidal features of beta oscillation shape also characterize PD. Here we show that these features of beta waveform shape also distinguish PD patients on and off medication using non-invasive recordings in a dataset of 15 PD patients with resting scalp EEG. Specifically, beta oscillations over sensorimotor electrodes in PD patients off medication had greater sharpness asymmetry and steepness asymmetry than on medication (sign rank, p=0.006, p=0.003 respectively). We also showed that beta oscillations over sensorimotor cortex most often had a canonical shape and that using this prototypical shape as an inclusion criterion increased the effect size of our findings. Together our findings suggest that novel ways of measuring beta synchrony that incorporate waveform shape could improve detection of PD pathophysiology in non-invasive recordings.

Dopaminergic therapy does not affect body weight in Parkinson's disease patients

2006 ◽  
Vol 33 (S 1) ◽  
Author(s):  
C.G. Bachmann ◽  
C. Werner ◽  
E. Brunner ◽  
C. Trenkwalder
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Body Weight ◽  
Dopaminergic Therapy ◽  
Affect Body Weight

scholarly journals Single-Cell RNA Sequencing in Parkinson’s Disease

Biomedicines ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 368
Author(s):  
Shi-Xun Ma ◽  
Su Bin Lim
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Single Cell ◽  
Rna Sequencing ◽  
Rna Degradation ◽  
Postmortem Brain ◽  
Cell Type ◽  
New Findings ◽  
Postmortem Brain Tissue ◽  
Technical Challenges

Single-cell and single-nucleus RNA sequencing (sc/snRNA-seq) technologies have enhanced the understanding of the molecular pathogenesis of neurodegenerative disorders, including Parkinson’s disease (PD). Nonetheless, their application in PD has been limited due mainly to the technical challenges resulting from the scarcity of postmortem brain tissue and low quality associated with RNA degradation. Despite such challenges, recent advances in animals and human in vitro models that recapitulate features of PD along with sequencing assays have fueled studies aiming to obtain an unbiased and global view of cellular composition and phenotype of PD at the single-cell resolution. Here, we reviewed recent sc/snRNA-seq efforts that have successfully characterized diverse cell-type populations and identified cell type-specific disease associations in PD. We also examined how these studies have employed computational and analytical tools to analyze and interpret the rich information derived from sc/snRNA-seq. Finally, we highlighted important limitations and emerging technologies for addressing key technical challenges currently limiting the integration of new findings into clinical practice.

scholarly journals Extradural Motor Cortex Stimulation in Parkinson’s Disease: Long-Term Clinical Outcome

2021 ◽  
Vol 11 (4) ◽  
pp. 416
Author(s):  
Carla Piano ◽  
Francesco Bove ◽  
Delia Mulas ◽  
Enrico Di Stasio ◽  
Alfonso Fasano ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Motor Cortex ◽  
Clinical Outcome ◽  
Motor Cortex Stimulation ◽  
Dopaminergic Therapy

Previous investigations have reported on the motor benefits and safety of chronic extradural motor cortex stimulation (EMCS) for patients with Parkinson’s disease (PD), but studies addressing the long-term clinical outcome are still lacking. In this study, nine consecutive PD patients who underwent EMCS were prospectively recruited, with a mean follow-up time of 5.1 ± 2.5 years. As compared to the preoperatory baseline, the Unified Parkinson’s Disease Rating Scale (UPDRS)-III in the off-medication condition significantly decreased by 13.8% at 12 months, 16.1% at 18 months, 18.4% at 24 months, 21% at 36 months, 15.6% at 60 months, and 8.6% at 72 months. The UPDRS-IV decreased by 30.8% at 12 months, 22.1% at 24 months, 25% at 60 months, and 36.5% at 72 months. Dopaminergic therapy showed a progressive reduction, significant at 60 months (11.8%). Quality of life improved by 18.0% at 12 months, and 22.4% at 60 months. No surgical complication, cognitive or behavioral change occurred. The only adverse event reported was an infection of the implantable pulse generator pocket. Even in the long-term follow-up, EMCS was shown to be a safe and effective treatment option in PD patients, resulting in improvements in motor symptoms and quality of life, and reductions in motor complications and dopaminergic therapy.

scholarly journals Parkinson’s Disease Motor Symptom Progression Slowed with Multisensory Dance Learning over 3-Years: A Preliminary Longitudinal Investigation

2021 ◽  
Vol 11 (7) ◽  
pp. 895
Author(s):  
Karolina A. Bearss ◽  
Joseph F. X. DeSouza
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Daily Living ◽  
Rating Scale ◽  
Motor Impairment ◽  
Motor Dysfunction ◽  
Motor Symptom ◽  
Significant Group ◽  
Rate Of Decline ◽  
Symptom Progression

Parkinson’s disease (PD) is a neurodegenerative disease that has a fast progression of motor dysfunction within the first 5 years of diagnosis, showing an annual motor rate of decline of the Movement Disorder Society Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) between 5.2 and 8.9 points. We aimed to determine both motor and non-motor PD symptom progression while participating in dance classes once per week over a period of three years. Longitudinal data was assessed for a total of 32 people with PD using MDS-UPDRS scores. Daily motor rate of decline was zero (slope = 0.000146) in PD-Dancers, indicating no motor impairment, whereas the PD-Reference group showed the expected motor decline across three years (p < 0.01). Similarly, non-motor aspects of daily living, motor experiences of daily living, and motor complications showed no significant decline. A significant group (PD-Dancers and PD-Reference) by days interaction showed that PD who train once per week have less motor impairment (M = 18.75) than PD-References who do not train (M = 24.61) over time (p < 0.05). Training is effective at slowing both motor and non-motor PD symptoms over three years as shown in decreased scores of the MDS-UPDRS.

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.

scholarly journals Perspective: Phase Amplitude Coupling–Based Phase–Dependent Neuromodulation in Parkinson’s Disease

2020 ◽  
Vol 14 ◽  
Author(s):  
Brian Y. Hwang ◽  
Yousef Salimpour ◽  
Yohannes K. Tsehay ◽  
William S. Anderson ◽  
Kelly A. Mills
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Phase Amplitude
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