Auditory Neural Tracking in Pediatric Epilepsy

Investigated speech comprehension in children with SeLECTS (a self-limited childhood epilepsy) compared to typically-developing peers, using high-density 128-channel EEG recorded during naturalistic story listening. Applied multivariate temporal response function (mTRF) modeling to build both encoding and decoding models linking EEG activity to speech acoustics, and used permutation-based null models and cluster-based statistics to test for group differences in neural speech tracking. Found that reliable, above-chance decoding of speech content from EEG was achievable from just a few minutes of pediatric data, which is gives implications for clinical EEG-based auditory assessment.

Currently in the process of writing the paper for publication.