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How well does surprisal explain N400 amplitude under different experimental conditions?
October 09, 2020 ยท Declared Dead ยท ๐ Conference on Computational Natural Language Learning
"No code URL or promise found in abstract"
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Authors
James A. Michaelov, Benjamin K. Bergen
arXiv ID
2010.04844
Category
cs.CL: Computation & Language
Cross-listed
cs.AI,
cs.IT,
cs.LG,
q-bio.NC
Citations
44
Venue
Conference on Computational Natural Language Learning
Last Checked
4 months ago
Abstract
We investigate the extent to which word surprisal can be used to predict a neural measure of human language processing difficulty - the N400. To do this, we use recurrent neural networks to calculate the surprisal of stimuli from previously published neurolinguistic studies of the N400. We find that surprisal can predict N400 amplitude in a wide range of cases, and the cases where it cannot do so provide valuable insight into the neurocognitive processes underlying the response.
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