Abstract Details

Title Quantitative Electroencephalography as a Biomarker for Cognitive Dysfunction in Parkinson’s Disease

Topic Movement Disorders

Presentation(s) S16 - Movement Disorders: PD Biomarkers and Clinical Trials (4:18 PM-4:30 PM)

Poster/Presentation
Number 005

Objective Evaluate whether a wavelet-based time-frequency quantitative electroencephalography (qEEG) algorithm can discriminate between Parkinson’s disease (PD) and control subjects and between cognitively normal and impaired PD subjects.

Background qEEG has been proposed as a biomarker of cognitive impairment in PD.

Design/Methods We assessed the relative time spent in primary instantaneous frequency (RTF) in the Delta, Theta, Alpha and Beta bands of twenty PD and twenty age- and sex-matched controls. In PD subjects, cognitive (MoCA 26-30=PDN, n=6; ≤25=PDD, n=14) and motor status (UPDRS-III and H&Y stage) were assessed. Resting occipital rhythm (ROR) was assessed by power spectral analysis. Descriptive statistics, logistic regression, and principal component analysis (PCA) were used to identify variables distinguishing PD from controls, and between PDN from PDD.

Results

PD subjects had lower mean ROR, lower mean RTF-Beta, greater mean RTF-Theta, similar mean RTF-Delta and RTF-Alpha. Arithmetic RTF combinations at occipital and parietal regions distinguished PD from controls. PC2 of a PCA of RTF values in all subjects was associated with PD (p=0.004; coefficient=0.31; ROC=0.780). PC2 had contributions from RTF-Theta at all locations, and RTF-Beta at occipital, parietal, central and temporal regions.

Median RTF-Alpha and RTF-Beta were lower in PDD subjects, greater for RTF-Theta and similar for RTF-Delta. PC2 from a PCA of RTF values in PD subjects was associated with cognitive status (p=0.002, coefficient=0.922, ROC=0.89). PC2 had contributions from RTF-Theta at all locations, RTF-Beta at central regions, and RTF-Delta at central, frontal and temporal regions. None of the PCs were associated with motor scores.

Conclusions A wavelet-based time-frequency qEEG algorithm distinguishes PD from controls and PDN from PDD. Arithmetic combinations of RTF values [e.g., (Alpha+Beta)/(Delta+Theta)] could serve as a biomarker for disease and predict cognitive impairment in PD. The decrease in RTF-Beta in PDD raises the possibility of impaired synchrony in cortex-basal ganglia circuits. Prospective studies are needed to validate these findings.

Authors/Disclosures
Katerina Markopoulou, MD, PhD (NorthShore University Health System) PRESENTER	Dr. Markopoulou has nothing to disclose.
	No disclosure on file
Bruce A. Chase, PhD (NorthShore University HealthSystem)	Dr. Chase has received personal compensation in the range of $500-$4,999 for serving as an Editor, Associate Editor, or Editorial Advisory Board Member for Nebraska Academy of Sciences.
Jaishree T. Narayanan, MD, PhD	Dr. Narayanan has nothing to disclose.
	No disclosure on file

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