The Brain's Sensitivity to Real-world Statistical Regularity Does Not Require Full Attention

Abstract

Predictive coding accounts of perception state that the brain generates perceptual predictions in the service of processing incoming sensory data. These predictions are hypothesized to be afforded by the brain's ability to internalize useful patterns, that is, statistical regularities, from the environment. We have previously argued that the N300 ERP component serves as an index of the brain's use of representations of (real-world) statistical regularities. However, we do not yet know whether overt attention is necessary in order for this process to engage. We addressed this question by presenting stimuli of either high or low real-world statistical regularity in terms of their representativeness (good/bad exemplars of natural scene categories) to participants who either fully attended the stimuli or were distracted by another task (attended/distracted conditions). Replicating past work, N300 responses were larger to bad than to good scene exemplars, and furthermore, we demonstrate minimal impacts of distraction on N300 effects. Thus, it seems that overtly focused attention is not required to maintain the brain's sensitivity to real-world statistical regularity. Furthermore, in an exploratory analysis, we showed that providing additional, artificial regularities, formed by altering the proportions of good and bad exemplars within blocks, further enhanced the N300 effect in both attended and distracted conditions, shedding light on the relationship between statistical regularities learned in the real world and those learned within the context of an experiment.