Quantification of Beta Activity in Routine EEG Recordings in Parkinson's Disease Patients

Study Overview
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Brief Summary
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The investigators are studying the relationship between a certain oscillatory brain rhythm (13-30 cycles/sec) that emerges prominently in patients with Parkinson's disease and symptoms of slowness of movement. The investigators are recruiting patients with a range of severity of Parkinson's disease symptoms to perform electroencephalography (EEG), in which the study team records brain waves using electrodes placed on the scalp, while patients sit at rest or perform certain hand tasks. The investigators will analyze the recorded brain waves to extract the brain rhythm of interest and relate it to motor symptom severity as well as study its behavior during rest and hand movement.

Detailed Description
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Parkinson's disease (PD) is a devastating, progressive neurodegenerative disease. The hallmark of PD is loss of dopaminergic neurons in the substantia nigra pars compacta (SNc), which disrupts motor circuit processing in the basal ganglia and results in motor dysfunction including tremor, rigidity, and bradykinesia. This disruption of motor circuit processing is reflected in abnormal oscillatory neural activity. For example, recordings of local field potentials with electrodes implanted in the basal ganglia reveal a substantial elevation of beta frequency (15-35 Hz) oscillatory activity in persons with PD, and this increased beta frequency activity is suppressed following levodopa treatment and deep brain stimulation. However, the link between the frequency and amplitude of abnormal oscillations and the degree of Parkinsonian symptoms is unclear. For example, magneto-encephalography revealed that beta-frequency oscillatory activity is elevated over the motor cortices even in persons with early-stage PD, and there were not any clear differences in beta frequency oscillations between newly diagnosed and under treatment PD. However, this study did not address any changes in the frequency of oscillations or distribution of power across frequencies. For example, a recent study has suggested that variability of ongoing beta-frequency oscillatory activity, in this case recorded from the STN, may be more strongly correlated with symptoms than the amplitude of beta frequency oscillations. Therefore, the objective of the investigator's proposed study is to determine whether there are changes in the characteristics of beta frequency oscillatory activity in the EEG over the motor cortex across differing degrees of Parkinson's disease. Such information is critical to understanding the (possible) link between abnormal oscillatory brain activity and symptom severity, as these signals could be used as potential biomarkers of therapeutic efficacy and to inform the design of new methods of intervention This is an observational, prospective evaluation of the beta content in routine 20-40 minute EEG recordings from patients with PD for varied periods of time. The investigators anticipate running data collection for 4-6 months in an outpatient movement disorders clinic. Subjects will be identified by their physician and then referred to the study team. Patients that agree to participate will be screened and have all questions answered at the time of their routine appointment. If the patient decides to participate and informed consent is obtained, a clinic appointment will be made for study data collection at a later date. Patient will be instructed not to take their normal dopamine replacement medications for 12 hours prior to the EEG study visit as this can interfere with the brain wave activity being studied. At the study clinic encounter, routine recordings will be made from a total of 33 PD patients; 11 with <3 years of PD diagnosis, 11 with >5 but <10 years of PD diagnosis, and 11 with advanced >10 years of PD diagnosis. EEG will be recorded using an FDA template system to facilitate EEG lead placement by research coordinators. Clinical description of PD severity and duration will be collected from each subject through questionnaire and from review of clinical evaluation. A UPDRS score may be determined for each participant. Following the data collection period, the EEG recordings will be indexed, de-identified, and randomly ordered to blind the subsequent analyses. These indexed EEG segments will be quantitatively analyzed to determine the relative contribution of beta frequency to the recordings, and comparison between the duration and severity of PD symptoms and beta content will also be made.

Official Title
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Quantification of Beta Activity in Routine EEG Recordings in Parkinson's

Conditions
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Parkinson Disease

Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Age 18 or older who have had PD diagnosis for the following periods of time: Cohort A have had PD diagnosis for <3 year, Cohort B have had PD diagnosis for between 5 and 10 years, and Cohort C have had PD diagnosis for >10 years. Exclusion Criteria: Patients who have a deep brain stimulator or other surgical treatment to control symptoms of PD patients with a history of stroke or prior brain injury Patients with familial PD or rapidly progressive disease will also be excluded.

Ages Eligible for Study
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Minimum Age: 18 Years
Maximum Age: 100 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Correlation between Beta Oscillation and Parkinson's Disease Severity | The study team recorded 19 channels of brain surface activity using electroencephalography. The 19 channels were distributed over the scalp. The data streams were analyzed in the frequency domain to determine the extent of beta frequency (13-30Hz) oscillatory content. Prior to the recording, each patient's off-medication motor severity score using Part III of the Unified Parkinson's disease Rating Scale (UPDRS) was assessed. | 40 minutes | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Parkinson Disease, EEG, Beta Oscillations