Neural processing of natural speech by children with developmental language disorder (DLD): EEG speech decoding, power and classifier investigations

The sensory/neural Temporal Sampling (TS) theory of developmental language disorder (DLD) is based on the sensory and linguistic impairments in rhythm processing that are found in children with both developmental dyslexia (DD) and DLD. These sensory/linguistic impairments include decreased sensitivity to amplitude rise times (ARTs), syllable stress patterns and speech rhythm. They are explained via a neural oscillatory speech processing framework drawn from the adult literature. Notably, at the neural level TS theory predicts impairments in the cortical tracking of different rates of amplitude modulation (AM) in the speech signal <10Hz. To date, the accuracy of low-frequency cortical tracking in natural continuous speech has not been measured in children with DLD. Here, EEG was recorded during story listening from children with and without DLD aged around 9 years, and decoding analyses in the delta, theta and alpha (control) bands were carried out. EEG power was computed in the delta, theta and gamma bands, as was phase-amplitude versus phase-phase coupling (PAC, PPC) between bands. The expectation that the accuracy of low-frequency decoding (delta, theta) of the speech signal would be impaired in DLD was not supported. Further, theta-delta and theta-gamma PAC were not atypical, contrary to prediction. EEG power in all bands was elevated for the DLD group, however. Receiving-operator-characteristic (ROC) curves estimated using support vector machine and logistic regression showed that these simple band power measures provided classifier models with the highest areas under the curves (AUC). The data are discussed using TS theory.