Modulation of working memory capacity on predictive processing during language comprehension

ABSTRACTABSTRACTAmple evidence has shown facilitations of context-based prediction on language comprehension. However, the influential effect of working memory capacity on this predictive processing remains debated. To investigate this issue with the electroencephalograph technique, high and low working memory capacity participants read strong-, moderate- and weak-constraint sentences which resulted in high-, moderate- and low-predictability for the critical nouns. The strong-constraint (vs. weak-constraint) contexts preceding the nouns elicited a larger positive deflection, which was only observed for the high-span group. Along with the smaller N400s for strong- vs. weak-predictable nouns for both groups, the moderately predictable nouns elicited smaller N400 than the weakly predictable nouns for the high-span group. The ERP effects at both verbs and nouns correlated significantly with the noun's predictability. These findings suggest that predictive processing involves at least partially an effortful-meaning-computation mechanism, and high working memory capacity facilitates the activation and integration of predicted information during language comprehension.KEYWORDS: Working memoryanticipatory processingpredictive integrationlanguage comprehension Disclosure statementNo potential conflict of interest was reported by the author(s).Data availability statementThe dataset containing the raw data and analysed data (cleandata ready for ERP calculation), as well as analysis script are available for public download at the following links:https://data.mendeley.com/datasets/35wnrnzr3k/draft?a = 5a7ea263-3e5b-4a86-b49c-1d236ccfe58bhttps://data.mendeley.com/datasets/r8bgfr8yfc/draft?a = daa91c80-3da5-4270-bf9b-30748d4613cfhttps://data.mendeley.com/datasets/j3nvgbbxvb/draft?a = 67fdea33-3cf2-49b8-bda0-7828defca208Other detailed information about the data and analysis script are available on request.Additional informationFundingThis work was supported by Grants from the National Natural Science Foundation of China (32171057, 31900762).