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Visual selective attention is the brain function that modulates ongoing processing of retinal input in order for selected representations to gain privileged access to perceptual awareness and guide behavior. Enhanced analysis of currently relevant or otherwise salient information is often accompanied by suppressed processing of the less relevant or salient input. Recent findings indicate that rewards exert a powerful influence on the deployment of visual selective attention. Such influence takes different forms depending on the specific protocol adopted in the given study. In some cases, the prospect of earning a larger reward in relation to a specific stimulus or location biases attention accordingly in order to maximize overall gain. This is mediated by an effect of reward acting as a type of incentive motivation for the strategic control of attention. In contrast, reward delivery can directly alter the processing of specific stimuli by increasing their attentional priority, and this can be measured even when rewards are no longer involved, reflecting a form of reward-mediated attentional learning. As a further development, recent work demonstrates that rewards can affect attentional learning in dissociable ways depending on whether rewards are perceived as feedback on performance or instead are registered as random-like events occurring during task performance. Specifically, it appears that visual selective attention is shaped by two distinct reward-related learning mechanisms: one requiring active monitoring of performance and outcome, and a second one detecting the sheer association between objects in the environment (whether attended or ignored) and the more-or-less rewarding events that accompany them. Overall this emerging literature demonstrates unequivocally that rewards "teach" visual selective attention so that processing resources will be allocated to objects, features and locations which are likely to optimize the organism's interaction with the surrounding environment and maximize positive outcome.

Every instant of perception depends on a cascade of brain processes calibrated to the history of sensory and decisional events. In the present work, we show that human visual perception is constantly shaped by two contrasting forces exerted by sensory adaptation and past decisions. In a series of experiments, we used multilevel modeling and cross-validation approaches to investigate the impact of previous stimuli and decisions on behavioral reports during adjustment and forced-choice tasks. Our results revealed that each perceptual report is permeated by opposite biases from a hierarchy of serially dependent processes: Low-level adaptation repels perception away from previous stimuli, whereas decisional traces attract perceptual reports toward the recent past. In this hierarchy of serial dependence, “continuity fields” arise from the inertia of decisional templates and not from low-level sensory processes. This finding is consistent with a Two-process model of serial dependence in which the persistence of readout weights in a decision unit compensates for sensory adaptation, leading to attractive biases in sequential perception. We propose a unified account of serial dependence in which functionally distinct mechanisms, operating at different stages, promote the differentiation and integration of visual information over time.

Spatial priority maps are real-time representations of the behavioral salience of locations in the visual field, resulting from the combined influence of stimulus driven activity and top-down signals related to the current goals of the individual. They arbitrate which of a number of (potential) targets in the visual scene will win the competition for attentional resources. As a result, deployment of visual attention to a specific spatial location is determined by the current peak of activation (corresponding to the highest behavioral salience) across the map. Here we report a behavioral study performed on healthy human volunteers, where we demonstrate that spatial priority maps can be shaped via reward-based learning, reflecting long-lasting alterations (biases) in the behavioral salience of specific spatial locations. These biases exert an especially strong influence on performance under conditions where multiple potential targets compete for selection, conferring competitive advantage to targets presented in spatial locations associated with greater reward during learning relative to targets presented in locations associated with lesser reward. Such acquired biases of spatial attention are persistent, are nonstrategic in nature, and generalize across stimuli and task contexts. These results suggest that reward-based attentional learning can induce plastic changes in spatial priority maps, endowing these representations with the "intelligent" capacity to learn from experience.

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