Considerable individual differences in language ability exist among normally developing children and adults. Whereas past research have attributed such differences to variations in verbal working memory or experience with language, we test the hypothesis that individual differences in statistical learning may be associated with differential language performance. We employ a novel paradigm for studying statistical learning on-line, combining a serial-reaction time task with artificial grammar learning. This task offers insights into both the timecourse of and individual differences in statistical learning. Experiment 1 charts the micro-level trajectory for statistical learning of nonadjacent dependencies and provides an on-line index of individual differences therein. In Experiment 2, these differences are then shown to predict variations in participants’ on-line processing of long-distance dependencies involving center-embedded relative clauses. The findings suggest that individual differences in the ability to learn from experience through statistical learning may contribute to variations in linguistic performance.
On-Line Individual Differences in Statistical Learning Predict Language Processing
Jennifer Misyak,Morten H. Christiansen,J. Tomblin
Published 2010 in Front. Psychology
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- Publication year
2010
- Venue
Front. Psychology
- Publication date
2010-05-03
- Fields of study
Computer Science, Linguistics, Medicine, Psychology
- Identifiers
- External record
- Source metadata
Semantic Scholar, PubMed
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