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Surrogate Modelling to Study E/I Imbalances in Children with Developmental Dyslexia

Authors:
Alejandro Orozco Valero
Nicolás Jesús Gallego Molina
Juan Luis Luque Vilaseca
Francisco Pelayo
Jesús González
Christian Morillas
Andrés Ortíz
Pablo Martínez-Cañada

Keywords: Developmental Dyslexia; EEG; E/I ratio; Neural Noise Hypothesis; Temporal Sampling Framework; Machine Learning; Mechanistic modelling; Surrogate model; Feature extraction.

Abstract:
Effective language processing relies on the brain’s capacity to decode rhythmic cues in speech, a function primarily supported by activity in the theta frequency band. According to the Temporal Sampling Framework, impairments in this process may contribute to the phonological deficits observed in individuals with Developmental Dyslexia (DD). These challenges cascade into higher-frequency bands, affecting the integration of phonemes, words, and phrases, ultimately compromising reading and writing fluency. Early diagnosis and treatment are crucial for ensuring proper personal and academic development in children. In this study, we propose a non-invasive methodology that combines electroencephalography (EEG) data with a surrogate modelling framework to detect early imbalances in excitation/inhibition (E/I) mechanisms. We applied this methodology to a cohort of children, divided into controls and DD groups, and compared the inferred E/I mechanisms with patterns predicted by the neural noise hypothesis.

Pages: 29 to 32

Copyright: Copyright (c) IARIA, 2025

Publication date: March 9, 2025

Published in: conference

ISSN: 2519-8653

ISBN: 978-1-68558-239-5

Location: Lisbon, Portugal

Dates: from March 9, 2025 to March 13, 2025