Nonlinear Neural Dynamics of Language Processing: A Recurrence Quantification Analysis of EEG in Dyslexia.

Abstract

This study investigates the application of chaos theory and Recurrence Quantification Analysis (RQA) to EEG signals in skilled and dyslexic readers. By quantifying the nonlinear dynamics of brain activity, we aim to identify differences in the complexity and predictability of neural oscillations associated with language processing. Our results demonstrate that the recurrence plot of individuals with dyslexia exhibits higher recurrence rate, determinism, and entropy compared to control subjects. These findings suggest that brain activity around T7 (AUC 0.726), crucial for phonological processing in the dorsal route of language processing, is more repetitive, predictable, and less flexible in dyslexia. The observed patterns align with the Hickok and Poeppel’s dual-route model of language processing and support the hypothesis that dyslexia involves disruptions in the neural mechanisms underlying phonological processing and auditory-motor integration.