Visual statistical learning requires attention

This is the authors' abstract. We don't add key points for this paper.

Statistical learning is a person’s ability to automatically learn environmental regularities through passive exposure. Since the earliest studies of statistical learning in infants, it has been debated exactly how ‘passive’ this learning can be – i.e. whether attention is needed for learning to occur. In Experiment 1 of the current study, participants performed a serial feature search task where they looked for a target shape among heterogenous nontarget shapes. Unbeknownst to the participants, one of these nontarget shapes was presented much more often in location. Even though the regularity concerned a non-salient nontarget item that did not receive any attentional priority during search, participants still learned its regularity (responding faster when it was presented at this high-probability location). While this may suggest that not much, if any, attention is needed for learning to occur, a follow-up experiment showed that if, during search, no attention is directed to this regularity, incidental learning is no longer seen; suggesting that at least some attention to the critical regularity is needed for learning to occur. We conclude that some degree of attention to a regularity is needed for visual statistical learning to occur.