Proceedings of the Annual Meeting of the Cognitive Science Society

Statistical learning (SL) refers to the ability to extract statistical regularities from the environment. Many researchersbelieve that SL arises as a consequence of the way that information is stored and accessed in memory (Thiessen, Kronstein,& Hufnagle, 2013). Accordingly, manipulations that influence memory should have similar effects in SL experiments. In thecurrent study, participants were presented with artificial languages that varied along two dimensions known to impact memory:number of distractors in the input and timing of presentation (e.g., spaced vs. massed). Participants’ performance was clearlyinfluenced by these manipulations; for example, the ability to segment a word (e.g., ”dupona”) differed as a function of whetherthere was one frequent competitor (e.g., ”dugalo”) or several less frequent competitors (e.g., ”dugalo,” ”dufalu,” ”dumiso”).Experimental results were compared to two memory-based computational models of SL (PARSER and TRACX). Implicationsof the experimental results and model comparisons will be discussed.