An object-tracking model that combines position and speed explains spatial and temporal responses in a timing task

Many tasks require synchronizing our actions withparticular moments along the path of moving targets.However, it is controversial whether we base theseactions on spatial or temporal information, and whetherusing either can enhance our performance. Weaddressed these questions with a coincidence timingtask. A target varying in speed and motion durationapproached a goal. Participants stopped the target andwere rewarded according to its proximity to the goal.Results showed larger reward for responses temporally(rather than spatially) equidistant to the goal acrossspeeds, and this pattern was promoted by longer motiondurations. We used a Kalman filter to simulate time andspace-based responses, where modeled speeduncertainty depended on motion duration and positionaluncertainty on target speed. The comparison betweensimulated and observed responses revealed that a singleposition-tracking mechanism could account for bothspatial and temporal patterns, providing a unifiedcomputational explanation