Qingjie Sun¹, Zinong Li², Michael S. Landy^1,3; ¹Department of Psychology, New York University, ²New York University Abu Dhabi, ³Center for Neural Science, New York University

Accurate goal-directed reaching requires humans to coordinate movement speed, distance, and duration while maintaining endpoint precision. We have found that movement plans are near-optimal for reaches under risk with incentives and penalties for reach outcome and a short duration limit (e.g., Trommershäuser et al., Spatial Vision, 2003). But, to determine whether optimality holds for reach planning in general requires a model of reach uncertainty across target locations and reach durations. Here, we measured endpoint variability as a function of movement duration and distance. Twelve right-handed participants performed unseen-hand reaches on a digitizing tablet. At trial onset, participants remained at the start point for 0.5 s until a green target circle appeared and began shrinking at a constant rate. Participants were instructed to reach the target before it disappeared. Endpoint feedback and a score that decreased linearly with endpoint error were displayed after each trial. The experiment consisted of three blocks defined by different target-disappearance durations (0.6, 0.79, 1.04 s). Each block included three target distances (overall range: 57–172 mm), scaled to keep movement speeds relatively consistent. Target direction was chosen uniformly (±15°) relative to leftward or rightward. Reach uncertainty (SD) was fit reasonably well as a linear function of reach distance and duration, with moderate positive slopes for each. Fitts’ Law predicts the movement time a human will use as a function of reach distance and target size. One hypothesis is that Fitts’ Law derives from the amount of uncertainty as a function of reach distance and duration, i.e., from an attempt to maintain a fixed percentage of target hits. Our data are inconsistent with that hypothesis.

Acknowledgements: NIH EY08266, NYUAD Center for Brain and Health, funded by Tamkeen under NYU Abu Dhabi Research Institute award CG012