Influences of active control and task difficulty on attention allocation in MOT

We investigated the influence of active involvement on the way visual attention is distributed during multiple-object tracking (MOT), specifically when objects bounce, using two experiments modeled after the videogame Pong. In both experiments, participants were either assigned to an active group or a passive group. The active groups were instructed to move a virtual paddle in order to bounce targets as often as possible. Participants in the passive groups viewed recordings of trials from the active groups. In Experiment 1, passive participants were asked to indicate whether targets approached the paddle from the left or from the right. In Experiment 2, passive participants merely had to indicate whether a target was about to hit the paddle. Using probe detection, we explored the distribution of attentional resources over the linear and bounce trajectories of tracked objects. We found that active involvement can enhance probe detection along the future post-bounce trajectory, but it depends on the difficulty of the task. This collection contains the python scripts used to present stimuli to participants and collect their responses, as well as intermediate versions of the published paper.