Abstract
The left and right visual hemifields appear to have separate spotlights of attention, as two targets divided between hemifields can be tracked as well as one target within a single hemifield (Alvarez & Cavanagh, 2005). Unresolved, however, is how these separate spotlights are integrated with global feature-based attention, where focusing on a particular feature facilitates processing of that feature throughout the entire visual field (Sàenz, Buraĉasa, & Boynton, 2003). Here we examined tracking of multiple targets across the hemifields when those targets could have different motion features, either rotating around a central point, or translating freely. Although accuracy for tracking two targets with the same motion type (uniform tracking: both rotation or both translation; M=82.6%) was not significantly different than accuracy for tracking a single target (M=85.3%, p=.28), tracking performance decreased significantly when tracking two targets with different motion types (mixed tracking: one rotation + one translation; M=70.3%, p=.001). The cost for mixed tracking was greater for the rotation condition than the translation condition. We hypothesized that attention must alternate between separate global feature templates for translation and rotation, and that the asymmetry in the cost for mixed tracking reflects an asymmetry in the cost incurred when briefly interrupting tracking for the two tasks. In Experiment 2 we quantified each motion type's interruption cost by periodically removing all items from the display (for 0, 50, 100, or 200 ms) while observers tracked a single rotating or translating target. A greater interruption cost was found for rotation than for translation, which mirrored a greater accuracy reduction for rotation than for translation during mixed tracking. These findings suggest the hemifield-specific attentional spotlights are dependent on a global tracking template, which repeatedly switches its tuning when multiple types of motion must be attended.
Meeting abstract presented at VSS 2017