Effect of pattern awareness on the behavioral and neurophysiological correlates of visual statistical learning

Abstract

Statistical learning is the ability to extract predictive patterns from structured input. A common assumption is that statisti-cal learning is a type of implicit learning that does not result in explicit awareness of learned patterns. However, there is also some evidence that statistical learning may involve explicit processing to some extent. The purpose of this study was to examine the effect of pattern awareness on behavioral and neurophysiological correlates of visual statistical learning. Participants completed a visual learning task while behavioral responses and event-related potentials were recorded. Following the completion of the task, awareness of statistical patterns was assessed through a questionnaire scored by three independent raters. Behavioral findings indicated learning only for participants exhibiting high pattern awareness levels. Neurophysiological data indicated that only the high-pattern awareness group showed expected P300 event-related potential learning effects, although there was also some indication that the low awareness groups showed a sustained mid-to late-latency negativity. Linear mixed-model analyses confirmed that only the high awareness group showed neurophysi-ological indications of learning. Finally, source estimation results revealed left hemispheric activation was associated with statistical learning extending from frontal to occipital and parietal regions. Further analyses suggested that left insula, left parahippocampal, and right precentral regions showed different levels of activation based on pattern awareness. To con-clude, we found that pattern awareness, a dimension associated with explicit processing, strongly influences the behavioral and neurophysiological correlates of visual statistical learning.