| 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
|
| Publication: |
2018 Conference on Cognitive Computational Neuroscience, 5-8 September 2018, Philadelphia, Pennsylvania |
| Paper Title: |
Inferences about Uniqueness in Statistical Learning |
| Manuscript: |
Click here to view manuscript |
| DOI: |
https://doi.org/10.32470/CCN.2018.1115-0 |
| 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. |
