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Does working memory capacity affect the ability to predict upcoming words in discourse?

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Van Berkum,  Jos J. A.
Neurobiology of Language Group, MPI for Psycholinguistics, Max Planck Society;
Language in Action , MPI for Psycholinguistics, Max Planck Society;
Donders Institute for Brain, Cognition and Behaviour, External Organizations;
Department of Psychology, University of Amsterdam;

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Citation

Otten, M., & Van Berkum, J. J. A. (2009). Does working memory capacity affect the ability to predict upcoming words in discourse? Brain Research, 1291, 92-101. doi:doi:10.1016/j.brainres.2009.07.042.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0013-23F0-8
Abstract
Prior research has indicated that readers and listeners can use information in the prior discourse to rapidly predict specific upcoming words, as the text is unfolding. Here we used event-related potentials to explore whether the ability to make rapid online predictions depends on a reader's working memory capacity (WMC). Readers with low WMC were hypothesized to differ from high WMC readers either in their overall capability to make predictions (because of their lack of cognitive resources). High and low WMC participants read highly constraining stories that supported the prediction of a specific noun, mixed with coherent but essentially unpredictive ‘prime control’ control stories that contained the same content words as the predictive stories. To test whether readers were anticipating upcoming words, critical nouns were preceded by a determiner whose gender agreed or disagreed with the gender of the expected noun. In predictive stories, both high and low WMC readers displayed an early negative deflection (300–600 ms) to unexpected determiners, which was not present in prime control stories. Only the low WMC participants displayed an additional later negativity (900–1500 ms) to unexpected determiners. This pattern of results suggests that WMC does not influence the ability to anticipate upcoming words per se, but does change the way in which readers deal with information that disconfirms the generated prediction.