A systematic review of statistical learning in autism spectrum disorder.

Abstract

Statistical learning, the ability to detect and extract statistical regularities from the environment, has been proposed as a key mechanism underlying language, social, and cognitive development. Numerous studies have examined statistical learning abilities in autistic individuals to test the hypothesis that differences contribute to the behavioral presentation of autism spectrum disorder (ASD). Findings have been inconsistent, with variations in methodology, sensory modality, and participant characteristics complicating the interpretation of results. The current study presents a systematic review of statistical, implicit, and procedural learning studies in autism, considering how statistical learning abilities vary across (a) modality (e.g., auditory versus visual), (b) methodology (e.g., behavioral versus neuroimaging), and (c) task design, and considering the influence of language and cognitive abilities. Results across 37 studies in visual and auditory modalities indicate few behavioral differences in statistical learning abilities (with the exception of slowed reaction times in autism), and that learning may benefit from extended exposure and explicit cues. In contrast, neuroimaging findings reveal substantial variability in the neural mechanisms implicated in these tasks, with evidence suggesting compensatory cognitive processing in some autistic samples. Individual differences in language, cognitive abilities, and autism-related traits strongly influence statistical learning outcomes. Significant gaps remain, particularly in the inclusion of minimally verbal individuals and those with intellectual disabilities. Methodological heterogeneity, skewed gender and sociodemographic sample characteristics, and inconsistent neural findings highlight the need for more standardized approaches in future research. Understanding the mechanisms of statistical learning in autism has critical implications for language and cognitive interventions, emphasizing the importance of individualized support strategies.