2026-05-29T23:29:11Zhttps://riuma.uma.es/rest/oai/request

oai:riuma.uma.es:10630/348962026-02-03T11:34:46Zcom_10630_2254col_10630_37953

Probabilistic and explainable modeling of Phase–Phase Cross-Frequency Coupling patterns in EEG. Application to dyslexia diagnosis Castillo-Barnes, Diego Gallego-Molina, Nicolás J. Formoso, Marco A. Ortiz-García, Andrés Figueiredo, Patrícia Luque-Vilaseca, Juan Luis Dislexia Procesamiento de señales This work explores the intricate neural dynamics associated with dyslexia through the lens of Cross-Frequency Coupling (CFC) analysis applied to electroencephalography (EEG) signals evaluated from 48 seven-year-old Spanish readers from the LEEDUCA research platform. The analysis focuses on CFS (Cross-Frequency phase Synchronization) maps, capturing the interaction between different frequency bands during low-level auditory processing stimuli. Then, making use of Gaussian Mixture Models (GMMs), CFS activations are quantified and classified, offering a compressed representation of EEG activation maps. The study unveils promising results specially at the Theta-Gamma coupling (Area Under the Curve = 0.821), demonstrating the method’s sensitivity to dyslexia-related neural patterns and highlighting potential applications in the early identification of dyslexic individuals. 2024-10-24T11:25:03Z 2024-10-24T11:25:03Z 2024-10-24T11:25:03Z 2024 journal article Diego Castillo-Barnes, Nicolás J. Gallego-Molina, Marco A. Formoso, Andrés Ortiz, Patrícia Figueiredo, Juan L. Luque, Probabilistic and explainable modeling of Phase–Phase Cross-Frequency Coupling patterns in EEG. Application to dyslexia diagnosis, Biocybernetics and Biomedical Engineering, Volume 44, Issue 4, 2024, Pages 814-823, ISSN 0208-5216, https://doi.org/10.1016/j.bbe.2024.09.003. (https://www.sciencedirect.com/science/article/pii/S0208521624000688) https://hdl.handle.net/10630/34896 https://doi.org/10.1016/j.bbe.2024.09.003 eng http://creativecommons.org/licenses/by-nc-nd/4.0/ open access Attribution-NonCommercial-NoDerivatives 4.0 Internacional Elsevier