Evidence map›Paper›PMID 30797099›Full record

ArticleCognition2019

Neural evidence for Bayesian trial-by-trial adaptation on the N400 during semantic priming.

Nathaniel Delaney-Busch, Emily Morgan, Ellen Lau, Gina R Kuperberg

Abstract read
In one paragraph

Article in Cognition, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed.

  1. The Influence of Prior Semantic Knowledge in Noisy Channel Interpretation.Quarterly journal of experimental psychology (2006) · 2026
    Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Understanding the Effects of Constraint and Predictability in ERP.Neurobiology of language (Cambridge, Mass.) · 2023
    Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Nathaniel Delaney-BuschDepartment of Psychology, Tufts University, USA.
Emily MorganDepartment of Psychology, Tufts University, USA; Department of Linguistics, University of California, Davis, USA. Electronic address: eimorgan@ucdavis.edu.
Ellen LauDepartment of Linguistics, University of Maryland, USA.
Gina R KuperbergDepartment of Psychology, Tufts University, USA; Department of Psychiatry and the Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, USA.

Funding

The neural basis of language comprehension: Insights from spatiotemporal imagingR01HD082527 · NICHD · MASSACHUSETTS GENERAL HOSPITAL · PI GINA R KUPERBERG · 2015 to 2026
$5.8M
Spatiotemporal Imaging of Language in SchizophreniaR01MH071635 · NIMH · MASSACHUSETTS GENERAL HOSPITAL · PI KUPERBERG, GINA R · 2005 to 2014
$5.0M
Selection Mechanisms Regulating Contextual Predictions in LanguageF32HD063221 · NICHD · MASSACHUSETTS GENERAL HOSPITAL · PI LAU, ELLEN FRANCES · 2010 to 2011
$99k
NICHD NIH HHS F32 HD063221NICHD NIH HHS R01 HD082527NIMH NIH HHS R01 MH071635
6 · The paper itself

Abstract

When semantic information is activated by a context prior to new bottom-up input (i.e. when a word is predicted), semantic processing of that incoming word is typically facilitated, attenuating the amplitude of the N400 event related potential (ERP) - a direct neural measure of semantic processing. N400 modulation is observed even when the context is a single semantically related "prime" word. This so-called "N400 semantic priming effect" is sensitive to the probability of encountering a related prime-target pair within an experimental block, suggesting that participants may be adapting the strength of their predictions to the predictive validity of their broader experimental environment. We formalize this adaptation using a Bayesian learning model that estimates and updates the probability of encountering a related versus an unrelated prime-target pair on each successive trial. We found that our model's trial-by-trial estimates of target word probability accounted for significant variance in trial-by-trial N400 amplitude. These findings suggest that Bayesian principles contribute to how comprehenders adapt their semantic predictions to the statistical structure of their broader environment, with implications for the functional significance of the N400 component and the predictive nature of language processing.

Indexed as

AssociationUncertaintyAdaptation, PsychologicalAdultBayes TheoremComprehensionElectroencephalographyEvoked PotentialsFemaleHumansMalePsycholinguisticsSemanticsYoung AdultAdaptationExpected uncertaintyLanguage comprehensionN400PrecisionPredictionUnexpected uncertainty

Identifiers

PMID30797099
PMCPMC6552672

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.