Exploring cognitive predictors of language in children with developmental language disorder: The role of nonverbal IQ, working memory, implicit statistical learning, and speed of automatization
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Updated: Sep 18, 2025

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques
Published on: June 30, 2020
Ashley Blake1, Ewa Dąbrowska2, Nick Riches3
1University of Birmingham, Department of Linguistics and Communication, Edgbaston, Birmingham, B15 2TT, United Kingdom.
Abstract:
Children with developmental language disorder (DLD) have varied strengths and difficulties in both language and cognition but we do not yet have a comprehensive understanding as to how these abilities are interrelated. In this study, we explore performance in language typical children and children with DLD to evaluate how different areas of nonverbal cognition predict linguistic outcomes. We investigate nonverbal intelligence, working memory, implicit statistical learning, and the speed of automatization. 77 children (54 language typical children and 23 children with DLD), aged between 6;9 and 10;8 years, completed a battery of cognitive and language tasks. Our results show between-group differences in both language and cognitive abilities. We propose a cumulative risk model, suggesting that important predictors of language in children with DLD are a combination of nonverbal working memory, nonverbal intelligence, and the speed of automatization.
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