Predictive pre-updating and working memory capacity: Evidence from event-related potentials

Tal Ness*, Aya Meltzer-Asscher

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

It was recently proposed that lexical prediction in sentence context encompasses two qualitatively distinct prediction mechanisms: “pre-activation,” namely, activating representations stored in long-term memory, and “pre-updating,” namely, updating the sentence’s representation, built online in working memory (WM), to include the predicted content [Lau, E. F., Holcomb, P. J., & Kuperberg, G. R. Dissociating N400 effects of predi cti on from associ ati on i n si ngl e-word contexts. Journal of Cognitive Neuroscience, 25, 484–502, 2013]. The current study sought to find evidence for pre-updating and test the influence of individual differences in WM capacity on the tendency to engage in this process. Participants read strongly and weakly constraining sentences. ERPs were measured on the predictable noun as well as on the preceding verb, where the prediction is generated. Increased P600 amplitude was observed at the verb in the strongly constraining sentences, reflecting integration of the predicted upcoming argument, thus providing evidence for pre-updating. This effect was greater for participants with higher WM capacity, indicating that the tendency to engage in pre-updating is highly affected by WM capacity. The opposite effect was observed at the noun, that is, for participants with higher WM span, a greater decrease in P600 amplitude in the strongly constraining sentences was observed, indicating that the integration of a pre-updated word was easier. We discuss these results in light of previous literature and propose a plausible architecture to account for the interplay between pre-activation and pre-updating, mediating the influence of factors such as WM capacity.

Original languageEnglish
Pages (from-to)1916-1938
Number of pages23
JournalJournal of Cognitive Neuroscience
Volume30
Issue number12
DOIs
StatePublished - 2018

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