title: Infants segment continuous events using transitional probabilities.
abstract: 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.
authors.affiliation: Johns Hopkins University.
authors.forename: Aimee E
authors.initials: AE
authors.lastname: Stahl
authors.forename: Alexa R
authors.initials: AR
authors.lastname: Romberg
authors.forename: Sarah
authors.initials: S
authors.lastname: Roseberry
authors.forename: Roberta Michnick
authors.initials: RM
authors.lastname: Golinkoff
authors.forename: Kathryn
authors.initials: K
authors.lastname: Hirsh-Pasek
mesh_terms: D001288:Attention / Q000502:physiology*; D002657:Child Development / Q000502:physiology*; D005260:Female; D006801:Humans; D007223:Infant; D008297:Male; D009039:Motion Perception / Q000502:physiology*; D010364:Pattern Recognition, Visual / Q000502:physiology*; D011336:Probability
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