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Great expectations: Specific lexical anticipation influences the processing of spoken language

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons189

Van Berkum,  Jos J. A.
Neurobiology of Language Group, MPI for Psycholinguistics, Max Planck Society;
The Neurobiology of Language, MPI for Psycholinguistics, Max Planck Society;
Language in Action , MPI for Psycholinguistics, Max Planck Society;

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Otten_2007_great.pdf
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Zitation

Otten, M., Nieuwland, M. S., & Van Berkum, J. J. A. (2007). Great expectations: Specific lexical anticipation influences the processing of spoken language. BMC Neuroscience, 8: 89. doi:10.1186/1471-2202-8-89.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0013-1C95-F
Zusammenfassung
Background Recently several studies have shown that people use contextual information to make predictions about the rest of the sentence or story as the text unfolds. Using event related potentials (ERPs) we tested whether these on-line predictions are based on a message-based representation of the discourse or on simple automatic activation by individual words. Subjects heard short stories that were highly constraining for one specific noun, or stories that were not specifically predictive but contained the same prime words as the predictive stories. To test whether listeners make specific predictions critical nouns were preceded by an adjective that was inflected according to, or in contrast with, the gender of the expected noun. Results When the message of the preceding discourse was predictive, adjectives with an unexpected gender-inflection evoked a negative deflection over right-frontal electrodes between 300 and 600 ms. This effect was not present in the prime control context, indicating that the prediction mismatch does not hinge on word-based priming but is based on the actual message of the discourse. Conclusions When listening to a constraining discourse people rapidly make very specific predictions about the remainder of the story, as the story unfolds. These predictions are not simply based on word-based automatic activation, but take into account the actual message of the discourse.