Jie Z. Wang¹ (), Paul Jolly¹, Michele A. Cox¹, Y. Howard Li¹, Ruitao Lin¹, Alina Neverodska¹, T. Scott Murdison², Michele Rucci¹; ¹University of Rochester, NY, USA, ²Meta Reality Labs, Redmond, WA, USA

Real-world objects often move in depth following complex trajectories. However, laboratory studies on human oculomotor tracking commonly use 2-D targets with uniform motions and predictable trajectories. Moreover, to reliably measure eye movements, the observer’s head is typically immobilized, thus preventing examination of head-eye coordination, a crucial aspect of natural tracking behavior. Here we studied natural head-eye tracking of a real object moving in 3-D space. Precise measurements of eye and head movements were obtained by means of a custom apparatus that combines a specifically-designed magnetic induction coil-based eye-tracker with a motion-capture system. Subjects (N=8) were seated within a cubic cage while wearing scleral coils on both eyes and a tightly-fitting helmet equipped with coils and markers. Observers participated in a Plinko-inspired task: they were instructed to track a small disc dropped from the top of a slanted Galton board and report when the disc reached the bottom. The target disc traveled down approaching the observer and bounced between the obstacles on the board, resulting in a complex path. Our results show that observers tracked the target via a combination of eye saccades and head pursuits. In between saccades, head movements, but not eye movements, were effective in attenuating retinal motion. A subgroup of observers was also tested in a control condition in which the disc fell at slower speed along a track on the board, a condition more similar to standard oculomotor studies with predictable, slow motions. Here subjects relied on binocular smooth pursuit with occasional saccades, so that, on the retina, both the eye and head contributed to reducing the target’s speed, with eye rotations playing the dominant role. These results show that natural 3-D tracking relies on distinct head/eye strategies depending on the target speed and the predictability of motion.

Acknowledgements: Supported by Reality Labs and NIH EY018363 and P30 EY001319