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 (Elsevier, 2024)
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.
Keywords: Dislexia; Procesamiento de señales; Mixture models; Cross-Frequency Coupling; EEG; Signal processing; Explainable machine learning; Dyslexia