While the visual environment contains massive amounts of information, we should not and
cannot pay attention to all events. Instead, we need to direct attention to those events that …

Through statistical learning, humans can learn to suppress visual areas that often contain
distractors. Recent findings suggest that this form of learned suppression is insensitive to …

Research has recently shown that efficient selection relies on the implicit extraction of
environmental regularities, known as statistical learning. Although this has been …

Cronbach (1957) famously noted the divergence between the experimental and
psychometric traditions in psychology and called for a unification, but many domains of …

Attention has been usefully thought of as organized in priority maps–putative maps of space
where attentional priority is weighted across spatial regions in a winner-take-all competition …

People can learn and use both static and dynamic (cross-trial) regularities in the positioning
of target items during parallel,'pop-out'visual search. Static target-location learning also …

Attentional habits acquired by visual statistical learning cause enduring biases toward
specific locations. These habits, driven by recent search history, are thought to be …

Selection history effects in visual attention are typically considered implicit memory effects. In
three experiments, we investigated if a key selection history effect, intertrial priming, could be …

Static statistical regularities in the placement of targets and salient distractors within the
search display can be learned and used to optimize attentional guidance. Whether statistical …

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 …