2020
DOI: 10.3389/fpsyg.2020.00281
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Infants’ Learning of Rule-Based Visual Sequences Predicts Language Outcome at 2 Years

Abstract: The ability to learn and generalize abstract rules from sensory input-i.e., Rule Learning (RL)-is seen as pivotal to language development, and specifically to the acquisition of the grammatical structure of language. Although many studies have shown that RL in infancy is operating across different perceptual domains, including vision, no studies have directly investigated the link between infants' visual RL and later language acquisition. Here, we conducted a longitudinal study to investigate whether 7-monthol… Show more

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Cited by 7 publications
(10 citation statements)
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References 67 publications
(77 reference statements)
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“…Our results in newborns are in line with those of Ylinen et al (2017) who looked at correlation between prediction error responses and language skills cross-sectionally at 12 months and found a strong correlation between prediction error and receptive vocabulary. (Note, however, that in the current study, the neonatal word-level prediction errors correlated with MLU, rather than vocabulary; for similar results, see Bettoni et al, 2020 ; Mittag et al, 2021 .) The current results support Ylinen et al (2017) earlier findings by demonstrating link between prediction error responses and language outcome in a larger number of participants.…”
Section: Discussionsupporting
confidence: 61%
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“…Our results in newborns are in line with those of Ylinen et al (2017) who looked at correlation between prediction error responses and language skills cross-sectionally at 12 months and found a strong correlation between prediction error and receptive vocabulary. (Note, however, that in the current study, the neonatal word-level prediction errors correlated with MLU, rather than vocabulary; for similar results, see Bettoni et al, 2020 ; Mittag et al, 2021 .) The current results support Ylinen et al (2017) earlier findings by demonstrating link between prediction error responses and language outcome in a larger number of participants.…”
Section: Discussionsupporting
confidence: 61%
“…MLU is a widely used index of expressive language ability, tapping both lexical and morphosyntactic proficiency (see Scarborough, 1990 ; DeThorne et al, 2005 , Rice et al, 2006 ; Kunnari et al, 2012 ; Jalilevand and Ebrahimipour, 2014 ). We used this measure in line with both Bettoni et al (2020) , who found infants’ rule-based learning ability to predict MLU outcome, and Mittag et al (2021) , who measured infants’ neural activity and assessed their linguistic and non-linguistic communication skills. Among different measures, they found MLU/M3L to correlate most consistently with neural activity patterns, suggesting that it may be a particularly useful measure for the current neurocognitive setup.…”
Section: Methodsmentioning
confidence: 99%
“…Our results suggests that SL and RL mechanisms play a distinct role in the development of language learning impairment. As previously discussed, it is known that the ability to extract transitional probability is involved in the acquisition of lexical skills (e.g., [13,14]), and the ability to extract and generalize high-order rules are related to the acquisition of grammar skills (e.g., [20,22,73]). Our results revealed that infants at high risk for language learning impairment succeeded in detecting transitional probability between visual items, while they failed in learning and/or generalizing abstract rules.…”
Section: Discussionmentioning
confidence: 97%
“…RL refers to the ability to extract high-order, repetition-based rules from item sequences, and to generalize them to novel items [18,19]. This ability is recognized as critical in tuning early infants' learning to the grammatical structure of language and to the emergence of syntactic skills [20][21][22][23]. Indeed, beyond syllable-level statistics, any natural language also includes word-level statistics, as words are sequentially combined in highly predictable ways defined by grammar.…”
Section: Introductionmentioning
confidence: 99%
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