Contributed Talk Sessions | Poster Sessions | All Posters | Search Papers

Poster Session C: Friday, August 15, 2:00 – 5:00 pm, de Brug & E‑Hall

A Multiple Trace Theory of Statistical Learning

Dock H Duncan¹, Jan Theeuwes, Sander A Los; ¹Vrije Universiteit Amsterdam

Presenter: Dock H Duncan

The attentional effects of statistical learning and intertrial priming have long been treated as separate selection history effects. This is despite their many similarities, improving performance in the same direction. There is thus motivation to either formally dissociate these two effects, or unify them under a single theoretical framework. We suggest that multiple trace theory is the framework to unify these two cognitive effects. We used a Kalman filter approach to model reaction times while participants performed the additional singleton task with biased distractor presentations - a paradigm known to engender both statistical learning and intertrial effects. Initial results suggest this by-trial modelling approach aptly captures learning effects and their effect on reaction times. Subsequent steps will now compare unified versus divided models of intertrial priming and statistical learning to provide evidence for their dissociation or union.

Topic Area: Object Recognition & Visual Attention

Extended Abstract: Full Text PDF