The babe with the predictive power: a registered report examining the role of prediction in early word encoding

Fazekas, Judit, Vidal, Yamil, Pine, julian and Brusini, Perrine ORCID: 0000-0003-0703-7765 The babe with the predictive power: a registered report examining the role of prediction in early word encoding. . (In Press)

Access the full-text of this item by clicking on the Open Access link.

Abstract

Error-based learning theories suggest that predictions play a key role from the earliest stages of language acquisition; yet existing studies have typically focused only on older age groups. As a result, there is currently limited evidence that prediction is a viable learning mechanism in infancy. This study targets the role of prediction in early word encoding to assess the viability of such a learning mechanism. To achieve this, we have adapted an adult EEG study focusing on syllabic prediction (Vidal et al., 2019) for an infant population. Our study starts with a learning phase, in which 39 nine-month-old infants hear two trisyllabic pseudowords. These words are then used as standard stimuli in an oddball-phase with four new words. Two of these deviant words only share their first syllable with a familiar word while the other two share their first two syllables. We will measure whether infants’ mismatch-response (MMR) differs between standard and deviant words, to address whether 9-month-olds make phonemic-level predictions. We willalso assess the MMR-difference between the two kinds of deviants. An MMR difference after one versus two shared syllables would suggest that cumulative congruent input reinforces prediction. As infants’ MMR can vary, we will also carry out a second task to localize the individual MMR responses of each participant in the form of a tone-change-detection Optimum-1 task. This task will determine the location, latency and polarity of the MMR for each infant separately, and will ensure that the study has sufficient statistical power.

Item Type:	Other
Uncontrolled Keywords:	predictive coding, error-based learning, word learning, EEG, mismatch response, Optimum-1
Divisions:	Faculty of Health and Life Sciences Faculty of Health and Life Sciences > Institute of Population Health
Depositing User:	Symplectic Admin
Date Deposited:	10 Jan 2024 09:39
Last Modified:	10 Jan 2024 09:39
Open Access URL:	https://osf.io/8jcpy/
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3177783