Abstract
Most experimental paradigms used to study attention require brief unitary shifts to single objects or locations, whereas everyday experience requires sustained attention to multiple dynamic objects and events. Such dynamic attention has often been studied using multiple object tracking (MOT): observers track several featurally identical targets that move haphazardly and unpredictably among identical moving distractors. But how and where is attention allocated during MOT? Here we present a deeply counterintuitive answer to this question: though targets are prioritized over distractors, as expected, attention prioritizes static stimuli over moving stimuli — including moving targets. In addition to tracking, observers had to detect small probes that appeared sporadically on targets, distractors, or various regions of empty space. There were no visual differences between these conditions, since all objects were patches of random visual noise moving on a background of random visual noise — such that the objects were invisible on any given static frame. We used probe detection as a measure of attention, and consistently observed several surprising effects. First, probe detection in static empty space was always better than on moving targets. Second, probe detection was worse for moving targets compared to targets that were momentarily stopped. Third, the attentional deficit for moving objects relative to the background disappeared when the entire noise-defined background was itself constantly translating. We will describe and demonstrate these and several other results which all fuel the same conclusion: attention treats dynamic and static information differently, and there appears to be a severe cost involved in attending to dynamic information. This could reflect the depletion of attentional resources on moving objects due to motion processing itself. These results are also consistent with the idea that moving objects are represented on a visual map — the ‘motion map’ — that is independent of global salience maps.