Predictive language processing in young autistic children.

Recent theories propose that domain-general deficits in prediction (i.e., the ability to anticipate upcoming information) underlie the behavioral characteristics associated with autism spectrum disorder (ASD). If these theories are correct, autistic children might be expected to demonstrate difficulties on linguistic tasks that rely on predictive processing. Previous research has largely focused on older autistic children and adolescents with average language and cognition. The present study used an eye-gaze task to evaluate predictive language processing among 3- to 4-year-old autistic children (n = 34) and 1.5- to 3-year-old, language-matched neurotypical (NT) children (n = 34). Children viewed images (e.g., a cake and a ball) and heard sentences with informative verbs (e.g., Eat the cake) or neutral verbs (e.g., Find the cake). Analyses of children's looking behaviors indicated that young autistic children, like their language-matched NT peers, engaged in predictive language processing. Regression results revealed a significant effect of diagnostic group, when statistically controlling for age differences. The NT group displayed larger difference scores between the informative and neutral verb conditions (in looks to target nouns) compared to the ASD group. Receptive language measures were predictive of looking behavior across time for both groups, such that children with stronger language skills were more efficient in making use of informative verbs to process upcoming information. Taken together, these results suggest that young autistic children can engage in predictive processing though further research is warranted to explore the developmental trajectory relative to NT development. LAY SUMMARY: This study found that 3- to 4-year-old autistic children and younger, language-matched neurotypical (NT) children both used verbs to predict upcoming nouns in sentences like "Eat the cake." For both autistic and NT children, those with stronger language skills were able to predict upcoming nouns more quickly.