No abstract

Priority maps are winner-take-all neural mechanisms that are thought to guide the allocation of attention. Within these maps, attentional priority is coded as weights on a topographic representation of physical space. Research has shown that these weights are not just influenced by the current stimuli presented but also by selection episodes that occurred in the past – called selection history. The current study demonstrates, for the first time, that these latent, implicitly-learned spatial biases can be visualized by ‘pinging’ the brain (a technique previously used to study activity-silent working memory). By briefly flashing high-contrast, task-irrelevant visual stimuli in the inter-stimulus interval between searches, participants’ current history-trained latent attentional priority could be decoded via scalp encephalography. Our findings not only offer a novel method of visualizing this latent attentional priority map, but also shed light on the underlying mechanisms allowing our past experiences to influence future behaviour.

It has been well established that attention can be sharpened through the process of statistical learning, whereby visual search is optimally adapted to the spatial probabilities of a target in visual fields. Specifically, attentional processing becomes more efficient when targets appear at high relatively to low probability locations. Statistically learned attentional enhancement has been shown to differ behaviorally from the more well studied top-down and bottom-up forms of attention; and while the electrophysiological characteristics of top-down and bottom-up attention have been well explored, relatively little work has been done to characterize the electrophysiological correlates of statistically learned attentional enhancement. In the current study, EEG data was collected while participants performed the additional singleton task with an unbalanced target distribution. Encephalographic data was then analyzed for two well-known correlates of attentional processing; alpha lateralization and the N2pc component. Our results showed that statistically learned attentional enhancement is not characterized by alpha lateralization, thereby differentiating it from top-down enhancement. Yet targets at high probability locations did reliably produce larger N2pc amplitudes, a known marker of increased bottom-up capture due to higher target-distractor contrasts. These results support an interpretation of the probability cuing effects where the improved processing of targets at expected locations is mediated by a saliency-based mechanism; boosting the salience of targets appearing at high-probability locations relative to those at low-probability locations.