Modulation of Predictive Coding in Auditory Paradigms of Varying Complexity in Children With Developmental Language Disorder.

Developmental language disorder (DLD) is a persistent difficulty in the acquisition and use of expressive and/or receptive language, which negatively impacts academic and social development. The present study evaluated the validity of the statistical learning model proposed to account for language difficulties in children with DLD. To this end, two auditory paradigms of varying complexity, framed within predictive coding theory, were passively presented to children diagnosed with DLD and to typically developing children without neurological impairments. The paradigms consisted of stimulus sequences with decreasing or increasing frequencies, interspersed with the sporadic occurrence of unexpected tone endings. The psychophysiological response was recorded using EEG, focusing on the P1, mismatch negativity (MMN), postimperative negative variation (PINV), and contingent negative variation (CNV) components. Results showed an absent MMN and a higher P1 response to deviant tones in children with DLD, suggesting an impaired development of frontal MMN generators, potentially compensated by activity in the primary auditory cortex. DLD participants also showed increased PINV and CNV responses during the most complex paradigm, which could imply greater cognitive effort and resource allocation for reassessment of stimulus patterns. Finally, incomplete maturation of frontal areas in children within this age range (3-11 years) was proposed as a possible explanation for the absence of differences between groups in P1 and N1/MMN responses elicited by simple and complex conditions. These findings support statistical learning as a valid model for understanding the possible neural basis of DLD and highlight this predictive EEG design as a potential protocol for early detection.