Clinical correlates of quantitative EEG in Parkinson disease: A systematic review. (6th November 2018)

• Record Type: Journal Article
• Authors: Geraedts, Victor J.; Boon, Lennard I.; Marinus, Johan; Gouw, Alida A.; van Hilten, Jacobus J.; Stam, Cornelis J.; Tannemaat, Martijn R.; Contarino, Maria Fiorella
• Is Part Of: Neurology. Volume 91:Number 19(2018)
• Publication Date: 2018-11-06
• Subjects: Neurology -- Periodicals; Neurology -- Periodicals; Neurologie -- Périodiques; 616.8
• DOI: 10.1212/WNL.0000000000006473
• Languages: English
• ISSNs: 0028-3878

Abstract

Abstract : Objective: To assess the relevance of quantitative EEG (qEEG) measures as outcomes of disease severity and progression in Parkinson disease (PD). Methods: Main databases were systematically searched (January 2018) for studies of sufficient methodologic quality that examined correlations between clinical symptoms of idiopathic PD and cortical (surface) qEEG metrics. Results: Thirty-six out of 605 identified studied were included. Results were classified into 4 domains: cognition (23 studies), motor function (13 studies), responsiveness to interventions (7 studies), and other (10 studies). In cross-sectional studies, EEG slowing correlated with global cognitive impairment and with diffuse deterioration in other domains. In longitudinal studies, decreased dominant frequency and increased θ power, reflecting EEG slowing, were biomarkers of cognitive deterioration at an individual level. Results on motor dysfunction and treatment yielded contrasting findings. Studies on functional connectivity at an individual level and longitudinal studies on other domains or on connectivity measures were lacking. Conclusion: qEEG measures reflecting EEG slowing, particularly decreased dominant frequency and increased θ power, correlate with cognitive impairment and predict future cognitive deterioration. qEEG could provide reliable and widely available biomarkers for nonmotor disease severity and progression in PD, potentially promoting early diagnosis of nonmotor symptoms and an objective monitoring of progression. More studies are needed to clarify the role of functional connectivity and network analyses.