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Infants Segment Continuous Events Using Transitional Probabilities
Author(s) -
Stahl Aimee E.,
Romberg Alexa R.,
Roseberry Sarah,
Golinkoff Roberta Michnick,
HirshPasek Kathryn
Publication year - 2014
Publication title -
child development
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.103
H-Index - 257
eISSN - 1467-8624
pISSN - 0009-3920
DOI - 10.1111/cdev.12247
Subject(s) - statistical learning , psychology , event (particle physics) , sequence (biology) , statistical hypothesis testing , segmentation , cognitive psychology , developmental psychology , statistical analysis , sequence learning , communication , artificial intelligence , computer science , statistics , mathematics , physics , quantum mechanics , biology , genetics
Throughout their 1st year, infants adeptly detect statistical structure in their environment. However, little is known about whether statistical learning is a primary mechanism for event segmentation. This study directly tests whether statistical learning alone is sufficient to segment continuous events. Twenty‐eight 7‐ to 9‐month‐old infants viewed a sequence of continuous actions performed by a novel agent in which there were no transitional movements that could have constrained the possible upcoming actions. At test, infants distinguished statistically intact units from less predictable ones. The ability to segment events using statistical structure may help infants discover other cues to event boundaries, such as intentions, and carve up the world of continuous motion in meaningful ways.