Atypical low-frequency cortical encoding of speech identifies children with developmental dyslexia
Date
2024Author
Araújo, João
Simons, Benjamin D.
Peter, Varghese
Mandke, Kanad
Kalashnikova, Marina
Macfarlane, Annabel
Gabrielczyk, Fiona
Wilson, Angela
Di Liberto, Giovanni M.
Burnham, Denis
Goswani, Usha
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Araújo, J., Simons, B.D., Peter, V., Mandke, K., Kalashnikova, M., Macfarlane, A,, Gabrielczyk, F,, Wilson, A,, Di Liberto, G,M,, Burnham, D., & Goswami, U. (2024). Atypical low-frequency cortical encoding of speech identifies children with developmental dyslexia. Frontiers in Human Neuroscience, 18:1403677. Doi:10.3389/fnhum.2024.1403677
Frontiers in Human Neuroscience
Frontiers in Human Neuroscience
Abstract
Slow cortical oscillations play a crucial role in processing the speech amplitude envelope, which is perceived atypically by children with developmental dyslexia. Here we use electroencephalography (EEG) recorded during natural speech listening to identify neural processing patterns involving slow oscillations that may characterize children with dyslexia. In a story listening paradigm, we find that atypical power dynamics and phase-amplitude coupling between delta and theta oscillations characterize dyslexic versus other child control groups (typically-developing controls, other language disorder controls). We further isolate EEG common spatial patterns (CSP) during speech listening across delta and theta oscillations that identify dyslexic children. A linear classifier using four delta-band CSP variables predicted dyslexia status (0.77 AUC). Crucially, these spatial patterns also identified children with dyslexia when applied to EEG measured during a rhythmic syllable processing task. This transfer effect (i.e., the ability to use neural features derived from a story listening task as input features to a classifier based on a rhythmic syllable task) is consistent with a core developmental deficit in neural processing of speech rhythm. The findings are suggestive of distinct atypical neurocognitive speech encoding mechanisms underlying dyslexia, which could be targeted by novel interventions.