Objective: This study aims to evaluate whether the total power of the main qEEG bands (Delta, Theta, Alpha, and Beta) has predictive power over symptomatic fatigue in Parkinson’s disease (PD), measured the Fatigue Severity Scale (FSS) score.

Background: Fatigue is one of the most disabling and prevalent non-motor symptoms (NMSs) in PD. It is closely related to other NMSs (depression, apathy…) and diagnosed via subjective questionnaires, complicating clinical management. Quantitative electroencephalography (qEEG) has been used to characterize fatigue in other neurodegenerative diseases, such as multiple sclerosis, but its use in PD remains limited. qEEG band power could serve as an objective measure of fatigue.

Method: Brain activity was recorded from 14 non-demented PD patients, with FSS scores ranging from 15 to 63 (mean: 45.14, SD: 15.40). 12 minutes of resting-state activity were collected (6 minutes with eyes open (EO), 6 minutes with eyes closed (EC)) using a 64-electrode qEEG system. The signal was segmented into 2-second epochs and filtered between 0.5 and 60 Hz (with a 50 Hz notch filter). Independent Component Analysis was performed to remove noise and artifacts. An average of 165 clean segments was used to compute the mean power of the bands.

Results: A logit-link, beta logistic regression was performed. Beta power in EO condition significantly predicted FSS scores. The relationship was negative with a large effect size: a decrease in Beta power was associated with an increase in FSS scores (slope = -0.6, CI: [-0.877, -0.324], p < 0.001). Although Delta was also a significant predictor in the EC condition (slope = 0.121, CI: [0.034, 0.209], p = 0.051), its small effect size did not survive multiple comparison correction.

Conclusion: A decrease in Beta power strongly correlates with increased fatigue scores. This finding contrasts with previous literature, both in healthy controls, chronic fatigue and multiple sclerosis, although at least one study has identified similar changes in fibromyalgia. Beta activity is relevant in information processing, reward-seeking, and motivational processes, and is reduced in depressive and apathetic states in PD. Depression, apathy, and fatigue may share, at least partially, a common physiological substrate in PD, explaining their intricate relationship. These results could be highly relevant for characterizing fatigue in PD using qEEG.

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MDS Abstracts - https://www.mdsabstracts.org/abstract/beta-band-power-predicts-fatigue-scores-in-parkinsons-disease-a-qeeg-study/