Being able to track dependencies between syntactic elements separated by other constituents is crucial for language acquisition and processing (e.g., in subject-noun/verb agreement). Although long assumed to require language-specific machinery, research on statistical learning has suggested that domain-general mechanisms may support the acquisition of non-adjacent dependencies. In this study, we investigated whether individuals with specific language impairment (SLI)-who have problems with long-distance dependencies in language-also have problems with statistical learning of non-adjacent relations. The results confirmed this hypothesis, indicating that statistical learning may subserve the acquisition and processing of long-distance dependencies in natural language.
Keywords: non-adjacent dependencies; specific language impairment; statistical learning.