Just-in-time: gaze guidance behavior while action planning and execution in VR

Abstract

Natural eye movements have primarily been studied for over-learned activities such as tea-making, sandwich-making, and hand-washing, which have a fixed sequence of associated actions. These studies indicate a sequential activation of low-level cognitive schemas facilitating task completion. However, it is unclear if these action schemas are activated in the same pattern when a task is novel and a sequence of actions must be planned in the moment. Here, we recorded gaze and body movements in a naturalistic task to study action-oriented gaze behavior. In a virtual environment, subjects moved objects on a life-size shelf to achieve a given order. In order to compel cognitive planning, we added complexity to the sorting tasks. Fixations aligned with the action onset showed gaze as tightly coupled with the action sequence, and task complexity moderately affected the proportion of fixations on the task-relevant regions. Our analysis further revealed that the gaze was allocated to action-relevant targets just in time. Planning behavior predominantly corresponded to a greater visual search for task-relevant objects before the action onset. The results support the idea that natural behavior relies very little on working memory, and humans refrain from encoding objects in the environment to plan long-term actions. Instead, they prefer just-in-time planning by searching for action-relevant items in the moment, directing their body and hand to it, monitoring the action until it is terminated, and moving on to the next action. Author SummaryEye movements in the natural environment have primarily been studied for over-learned and habitual everyday activities (tea-making, sandwich-making, hand-washing) with a fixed sequence of associated actions. These studies show eye movements correspond to a specific order of actions learned over time. In this study, we were interested in how humans plan and execute actions for tasks that do not have an inherent action sequence. To that end, we asked subjects to sort objects based on object features on a life-size shelf in a virtual environment as we recorded their eye and body movements. We investigated the general characteristics of gaze behavior while acting under natural conditions. Our paper provides a comprehensive approach to preprocess naturalistic gaze data in virtual reality. Furthermore, we provide a data-driven method of analyzing the different action-oriented functions of gaze. The results show that bereft of a predefined action sequence, humans prefer to plan only their immediate actions where eye movements are used to search for the target object to immediately act on, then to guide the hand towards it, and to monitor the action until it is terminated. Such a simplistic approach ensures that humans choose sub-optimal behavior over planning under sustained cognitive load.