Technical Program

Paper Detail

Paper: GS-2.1
Session: Contributed Talks II
Location: Ormandy
Session Time: Thursday, September 6, 13:00 - 13:40
Presentation Time:Thursday, September 6, 13:00 - 13:20
Presentation: Oral
Paper Title: Inferences about Uniqueness in Statistical Learning
Manuscript:  Click here to view manuscript
Authors: Anna Leshinskaya, Sharon L Thompson-Schill, University of Pennsylvania, United States
Abstract: The mind adeptly registers statistical regularities in experience, often incidentally. We used a visual statistical learning paradigm to study incidental learning of predictive relations among animated events. We asked what kinds of statistics participants automatically compute, even when tracking such statistics is task-irrelevant and largely implicit. We find that participants are sensitive to a quantity governing associative learning, P, rather than conditional probabilities or chunk frequencies as previously thought. P specifically reflects the uniqueness, as well as strength, of conditional probabilities. This finding opens the possibility of common, sophisticated inferential mechanisms shared between statistical learning, associative learning, and causal inference scenarios.