A new publication from the project funded by the Yidan Foundation has been published in the Frontiers in Human Neuroscience Journal, in June 2024.
Atypical low-frequency cortical encoding of speech identifies children with developmental dyslexia
Slow cortical oscillations play a crucial role in processing the speech amplitude envelope, which is perceived atypically by children with developmental dyslexia. Here, we have analysed EEG datasets from British and Australian cohorts of dyslexic, DLD and typically-developing children to further understand their differences in oscillatory responses to speech. We found not only significant effects of cross-frequency coupling in deta and theta between dyslexic and DLD populations but most importantly differences in the power relationship of delta and theta rhythms. Using machine learning, we were able to create a dyslexia classifier with around 80% accuracy using the magnitude of low-frequency oscillatory responses to connected speech. Finally, we found that spatial and temporal components of this classifier for connected speech was also useful when building a dyslexia classifier featuring oscillatory responses to a steady-state syllable repetition task.
Find the paper here: https://doi.org/10.3389/fnhum.2024.1403677
Find more about our publications here: https://www.cne.psychol.cam.ac.uk/publications