Examining the influence of cognitive processing orientation on tracking performance using a modified multiple object tracking task

Poster Presentation 43.447: Monday, May 20, 2024, 8:30 am – 12:30 pm, Pavilion
Session: Attention: Tracking, shifting

Mengzhu Fu1, Michael D Dodd2; 1Shippensburg University of Pennsylvania, 2University of Nebraska - Lincoln

Extensive research on multiple-object tracking (MOT) has shown that task performance may be influenced by both object-related and task-irrelevant factors (Meyerhoff, Papenmeier, & Huff, 2017). While some research suggests that certain expertise might be associated with more efficient tracking (Allen, McGeorge, Pearson, & Milne, 2004; Green & Bavelier, 2006), the question of how to consistently improve performance across individuals remains uncertain. The present study explores whether maintaining a wider attentional scope could enhance tracking abilities using a novel dual task paradigm. Participants tracked a number of moving targets (ranging 2-4) while performing a simultaneous secondary probe-detection task. While objects are in motion, a number of probes may appear on any of the moving objects (i.e., targets & distractors). In the global task condition, participants were instructed to respond only when probes appeared simultaneously on all tracking targets. This aims to prompt global processing by requiring participants to attend to the overall structure of the display to detect all probes at once. In the local task condition, participants were instructed to respond whenever a probe appeared on any tracking target. This aims to prompt local processing by directing participants to attend to individual objects within the display. It was observed that while tracking accuracy decreased as number of tracking targets increased, adopting a global processing orientation is associated with more efficient tracking performance than local processing orientation, especially with larger tracking sets. These results suggest that maintaining a broader attentional focus might efficiently improve tracking efficiency in dynamic scenes.