Visual Implicit Learning Abilities in Infants at Familial Risk for Language and Learning Impairments

The ability of infants to track transitional probabilities (Statistical Learning-SL) and to extract and generalize high-order rules (Rule Learning-RL) from sequences of items have been proposed as being pivotal for the acquisition of language and reading skills. Although there is ample evidence of specific associations between SL and RL abilities and, respectively, vocabulary and grammar skills, research exploring SL and RL as early markers of language and learning (dis)abilities is still scarce. Here we investigated the efficiency of visual SL and RL skills in typically developing (TD) seven-month-old infants and in seven-month-old infants at high risk (HR) for language learning impairment. Infants were tested in two visual-habituation tasks aimed to measure their ability to extract transitional probabilities (SL task) or high-order, repetition-based rules (RL task) from sequences of visual shapes. Post-habituation looking time preferences revealed that both TD and HR infants succeeded in learning the statistical structure (SL task), while only TD infants, but not HR infants, were able to learn and generalize the high-order rule (RL task). These findings suggest that SL and RL may contribute differently to the emergence of language learning impairment and support the hypothesis that a mechanism linked to the extraction of grammar structures may contribute to the disorder.

Medienart:

E-Artikel

Erscheinungsjahr:

2022

Erschienen:

2022

Enthalten in:

Zur Gesamtaufnahme - volume:19

Enthalten in:

International journal of environmental research and public health - 19(2022), 3 vom: 08. Feb.

Sprache:

Englisch

Beteiligte Personen:

Bettoni, Roberta [VerfasserIn]
Cantiani, Chiara [VerfasserIn]
Riva, Valentina [VerfasserIn]
Molteni, Massimo [VerfasserIn]
Macchi Cassia, Viola [VerfasserIn]
Bulf, Hermann [VerfasserIn]

Links:

Volltext

Themen:

Early markers
Infancy
Journal Article
Language learning impairment
Research Support, Non-U.S. Gov't
Rule learning
Statistical learning

Anmerkungen:

Date Completed 28.02.2022

Date Revised 28.02.2022

published: Electronic

Citation Status MEDLINE

doi:

10.3390/ijerph19031877

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM336949979