Spectral features of resting-state EEG in Parkinson’s Disease: A multicenter study using functional data analysis

Objective: This study aims 1) To analyse differences in resting-state electroencephalogram (rs-EEG) spectral features of Parkinson’s Disease (PD) and healthy subjects (non-PD) using Functional Data Analysis (FDA) and 2) To explore, in four independent cohorts, the external validity and reproducibility of the findings using both epoch-to-epoch FDA and averaged-epochs approach. Methods: We included 169 subjects (85 non-PD; 84 PD) from four centres. Rs-EEG signals were preprocessed with a combination of automated pipelines. Sensor-level relative power spectral density (PSD), dominant frequency (DF), and DF variability (DFV) features were extracted. Differences in each feature were compared between PD and non-PD on averaged epochs and using FDA to model the epoch-toepoch change of each feature. Results: For averaged epochs, significantly higher theta relative PSD in PD was found across all datasets. Also, higher pre-alpha relative PSD was observed in three of four datasets in PD patients. For FDA, similar

• Autores: Jaramillo-Jiménez, Alberto; Tovar-Rios, Diego Alejandro; Ospina Galindez, Johann Alexis; Mantilla-Ramos, Yorguin José; Loaiza-López, Daniel; Henao Isaza, Verónica; Zapata Saldarriaga, Luisa María; Valeria Cadavid Castro; Suárez-Revelo, Jazmin Ximena; Bocanegra, Yamilé; Lopera, Francisco; Pineda-Salazar, David Antonio; Tobón Quintero, Carlos Andrés; Ochoa-Gómez, John Fredy; Borda, Miguel Germán; Aarsland, Dag; Laura Bonanni
• Tipo de recurso: Article of investigation
• Fecha de publicación: 2023
• Institución: Universidad Autónoma de Occidente
• Repositorio: RED: Repositorio Educativo Digital UAO
• Idioma: eng
• OAI Identifier: oai:red.uao.edu.co:10614/15852
• Acceso en línea: https://hdl.handle.net/10614/15852; https://doi.org/10.1016/j.clinph.2023.03.363; https://red.uao.edu.co/
• Palabra clave: Functional data analysis; Electroencephalography; Parkinson’s disease; Alpha rhythm; Theta rhythm
• Rights: openAccess
• License: Derechos reservados - Elsevier, 2023