1. Differentiating neurodegenerative diseases based on EEG complexity.
- Author
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Mostile G, Terranova R, Carlentini G, Contrafatto F, Terravecchia C, Donzuso G, Sciacca G, Cicero CE, Luca A, Nicoletti A, and Zappia M
- Subjects
- Humans, Female, Male, Aged, Diagnosis, Differential, Middle Aged, Tauopathies diagnosis, Tauopathies physiopathology, Synucleinopathies diagnosis, Synucleinopathies physiopathology, Aged, 80 and over, Electroencephalography methods, Neurodegenerative Diseases diagnosis, Neurodegenerative Diseases physiopathology
- Abstract
Neurodegenerative diseases are common causes of impaired mobility and cognition in the elderly. Among them, tauopathies and α-synucleinopathies were considered. The neurodegenerative processes and relative differential diagnosis were addressed through a qEEG non-linear analytic method. Study aims were to test accuracy of the power law exponent β applied to EEG in differentiating neurodegenerative diseases and to explore differences in neuronal connectivity among different neurodegenerative processes based on β. N = 230 patients with a diagnosis of tauopathy or α-synucleinopathy and at least one artifact-free EEG recording were selected. Periodogram was applied to EEG signal epochs from continuous recordings. Power law exponent β was determined by the slope of the signal power spectrum versus frequency in logarithmic scale. A data-driven clustering based on β values was performed to identify independent subgroups. Data-driven clustering based on β differentiated tauopathies (overall lower β values) from α-synucleinopathies (higher β values) with high sensitivity and specificity. Tauopathies also presented lower values in the correlation coefficients matrix among frontal sites of recording. In conclusion, significant differences in β values were found between tauopathies and α-synucleinopathies. Hence, β is proposed as a possible biomarker of differential diagnosis and neuronal connectivity., (© 2024. The Author(s).)
- Published
- 2024
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