Brain oscillatory patterns in mild cognitive impairment due to Alzheimer's and Parkinson's disease: An exploratory high-density EEG study. (June 2022) - Polverino, Paola; Ajčević, Miloš; Catalan, Mauro; Mazzon, Giulia; Bertolotti, Claudio; Manganotti, Paolo
Highlights: Different brain oscillatory patterns characterize mild cognitive impairment due to Parkinson' s and Alzheimer's disease. Quantitative spectral EEG parameters can represent a surrogate biomarker of cognitive decline since its early stage. Quantitative spectral analysis of EEG signals could provide support in monitoring disease progression. Abstract: Objective: We investigated brain cortical activity alterations, using a resting-state 256-channel high-density EEG (hd-EEG), in Alzheimer's (AD) and Parkinson's (PD) disease subjects with mild cognitive impairment (MCI) and correlations between quantitative spectral EEG parameters and the global cognitive status assessed by Montreal Cognitive Assessment (MoCA) score. Methods: Fifteen AD-MCI, eleven PD-MCI and ten age-matched healthy-controls (HC) underwent hd-EEG recordings and neuropsychological assessment. Cerebrospinal fluid biomarker analysis was performed to obtain well-characterized groups. EEG spectral features were extracted and the differences between the three groups, as well as correlations with MoCA, were investigated. Results: The results showed significantly lower alpha2 power and alpha2/alpha1 ratio in both AD-MCI and PD-MCI compared to controls. The significantly higher theta and lower beta power and alpha/theta ratio were observed in PD-MCI compared to AD-MCI and HC. MoCA score correlated inversely with theta power and directly with alpha2 and beta powers, as well as with alpha2/alpha1 and alpha/theta ratios. Conclusions: This study highlighted significant differences in EEG patterns in AD-MCI and PD-MCI patients and remarked the role of EEG parameters as possible surrogate markers of cognitive status in both neurodegenerative diseases. Significance: In addition to well-established biomarkers, our findings could support early detection of cognitive dysfunction in neurodegenerative disorders and could help to monitor disease progression and therapeutic responses.