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

Target Detection as an Online Measure of Adapting to Changing Statistical Regularities

Brent Vernaillen¹, Louisa Bogaerts; ¹Universiteit Gent

Presenter: Brent Vernaillen

Our environments are inherently structured, with certain stimuli or events having a higher probability of co-occurring. Statistical learning (SL), the ability to extract such regularities, is a powerful cognitive mechanism. The majority of SL studies to date, however, have treated our sensory environments as stable, assuming only a single set of to-be-learned regularities. In doing so, they overlooked the flexibility humans need to process and represent changes in the statistical patterns that make up our environments. In the current study, we exposed participants to visual and auditory sequences containing statistical regularities that changed throughout exposure. Our online learning measure, based on the reaction-time benefit in detecting predictable stimuli, showed that participants successfully learned both the initial and updated structure in the visual modality. Our offline test, by contrast, only provided evidence for learning of the first structure in the auditory modality.

Topic Area: Visual Processing & Computational Vision

Extended Abstract: Full Text PDF