Characterizing High-order Interactions between Eye Movement and Head Motion Variables in Augmented Reality-based Navigation Experience

The coordination of eye and head in visual scanning is a fundamental behavior of humans in everyday sensorimotor activities such as walking and navigation. Deep understanding of the spatiotemporal dynamics of this coordination behavior undoubtedly plays an important role for many fields. However, relatively little is known about the computational and high-order interactions between eye and head in visual scanning during sensorimotor tasks. In this paper, based on the utilization of a recent tool from information theory, Partial Information Decomposition (PID), we quantify high-order components, namely uniqueness, redundancy, and synergy, in spatiotemporal interactions between eye movement and head motion time-series data during augmented reality-based navigation experience. To our knowledge, this is the first data-driven approach that leverages an information-theoretic tool to characterize high-order interactions involved in eye-head coordination during sensorimotor activities.