Poster B64, Sunday, March 26, 8:00 – 10:00 am, Pacific Concourse
Violating linguistic prediction in musicians and non-musicians
Allison R. Fogel1, Edward W. Wlotko1, Gina R. Kuperberg1,2,3, Aniruddh D. Patel1; 1Tufts University, 2MGH/HST Athinoula A. Martinos Center for Biomedical Imaging, 3Massachusetts General Hospital
Prediction is thought to play an important role in the processing of both music and language, leading to recent interest in the possible relationship between neurocognitive mechanisms of prediction across the two domains. While there is evidence that individuals with musical training show enhancements in some aspects of language processing (such as prosody and affect), the impact of musical training on predictive tendencies in language has not been well explored. Here we asked whether musicians are more sensitive than non-musicians to words that violate strong linguistic predictions. Because prediction is vital for successful music processing, it is possible that musical training may be associated with stronger prediction of upcoming information in general, or with changes in other aspects of cognition (such as working memory) that in turn impact predictive tendencies in language. Previous studies have reported individual differences in the neural effects of violating very strong lexical predictions, as indexed by a late ERP component that follows the N400, known as the frontal positivity. We investigated whether this late frontal positivity would differ between individuals with and without musical training. Contrary to our hypothesis, no relationship was observed between the amplitude of the frontal positivity and musical training. However, cognitive testing of a subset of these participants revealed a relationship between musical training and visual statistical learning performance. These results suggest that, while musical training does not impact the strength of an individual’s lexical predictions in language, it may enhance an individual’s ability to learn statistical regularities from the environment.
Topic Area: LANGUAGE: Other