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Overlapping dual ERP responses to low cloze probability sentence continuations

Authors

  • Katherine A. Delong,

    1. Department of Cognitive Science, University of California, San Diego, La Jolla, California, USA
    2. Center for Research in Language, University of California, San Diego, La Jolla, California, USA
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  • Thomas P. Urbach,

    1. Department of Cognitive Science, University of California, San Diego, La Jolla, California, USA
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  • David M. Groppe,

    1. Department of Cognitive Science, University of California, San Diego, La Jolla, California, USA
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  • Marta Kutas

    1. Department of Cognitive Science, University of California, San Diego, La Jolla, California, USA
    2. Center for Research in Language, University of California, San Diego, La Jolla, California, USA
    3. Department of Neurosciences, University of California, San Diego, La Jolla, California, USA
    4. Kavli Institute for Brain and Mind, University of California, San Diego, La Jolla, California, USA
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  • This research was supported by NICHD grant HD22614 and NIA grant AG08313 to M.K., and by Center for Research in Language and Institute for Neural Computation Training predoctoral fellowships to K.A.D.

Address correspondence to: Katherine A. DeLong, Department of Cognitive Science, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0515, USA. E-mail: kadelong@cogsci.ucsd.edu

Abstract

In 2005, DeLong, Urbach, and Kutas took advantage of the a/an English indefinite article phonological alternation and the sensitivities of the N400 ERP component to show that readers can neurally preactivate individual words of a sentence (including nouns and their prenominal indefinite articles) in a graded fashion with a likelihood estimated from the words' offline probabilities as sentence continuations. Here we report an additional finding from that study: a prolonged ERP frontal positivity to less probable noun continuations. We suggest that this positivity is consistent with hypotheses that additional neural processing may be invoked when highly expected continuations are not encountered in the input and speculate briefly on possible functional correlates.

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