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Early developing syntactic knowledge influences sequential statistical learning in infancy.

Erik D Thiessen1, Luca Onnis2, Soo-Jong Hong3

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|September 19, 2018
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Summary
This summary is machine-generated.

Infants rapidly adapt their statistical learning to their native language. By 13 months, English-learning infants show a bias for backward-going patterns, mirroring adult language structure.

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Cross-linguistic differencesHeadLinguisticsParameterPhrase structureStatistical learning

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Area of Science:

  • Developmental Psychology
  • Linguistics
  • Cognitive Science

Background:

  • Adults' language background shapes their statistical learning of artificial languages.
  • English speakers prefer backward-going transitional probabilities (head-initial).
  • Korean speakers prefer forward-going transitional probabilities (head-final).

Purpose of the Study:

  • To determine when infants develop directional biases in statistical learning.
  • To investigate if infant statistical learning adapts to native language syntax.

Main Methods:

  • Experimental assessment of sequential statistical learning in infants.
  • Testing 7-month-old and 13-month-old infants on artificial language tasks.
  • Analyzing directional bias in processing forward-going vs. backward-going probabilities.

Main Results:

  • Seven-month-old infants showed no directional bias in statistical learning.
  • Thirteen-month-old infants learning English favored backward-going probabilities.
  • This bias aligns with the head-initial structure of the English language.

Conclusions:

  • Infant statistical learning rapidly adapts to the predominant syntactic structure of their native language.
  • This adaptation may enhance learning by prioritizing relevant linguistic patterns.
  • Directional biases in statistical learning emerge during the first year of life.