Neural evidence for Bayesian trial-by-trial adaptation on the N400 during semantic priming.
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.
['Delaney-Busch|Nathaniel|N|', 'Morgan|Emily|E|', 'Lau|Ellen|E|', 'Kuperberg|Gina R|GR|']
D000223:Adaptation, Psychological D000328:Adult D001244:Association D001499:Bayes Theorem D032882:Comprehension D004569:Electroencephalography D005071:Evoked Potentials D005260:Female D006801:Humans D008297:Male D011578:Psycholinguistics D012660:Semantics D035501:Uncertainty D055815:Young Adult
Adaptation N400 Prediction Expected uncertainty Language comprehension Precision Unexpected uncertainty