Establishment of an Attentional Set via Statistical Learning

The ability to overcome attentional capture and attend goal-relevant information is typically viewed as a volitional, effortful process that relies on the maintenance of current task priorities or attentional sets in working memory. However, the visual system possesses statistical learning mechanisms that can incidentally encode probabilistic associations between goal-relevant objects and the attributes likely to define them. Thus, it is possible that statistical learning may contribute to the establishment of a given attentional set and modulate the effects of attentional capture. Here we provide evidence for such a mechanism, showing that implicitly learned associations between a search target and its likely color directly influence the ability of a salient color precue to capture attention in a classic attentional capture task. This indicates a novel role for statistical learning in the modulation of attentional capture, and emphasizes the role that this learning may play in goal-directed attentional control more generally.