Controlling posture to see the world: The integration of visual task demands and postural sway in sitting and standing infants

Our ability to integrate posture with visually demanding tasks is a critical aspect of motor behavior flexibility. When looking at a small object, excessive body movements impair an individual's ability to visually attend to the object. To overcome this problem, we adjust our postural sway to successfully focus on the object. The goal of the current study was to assess whether infants also adjust postural sway when engaged in a challenging visual task. The participants, 19 independently sitting infants (Sitters) and 21 newly independently standing infants (Standers), sat or stood on a force plate while viewing differently sized images displayed on a monitor (smaller images: 8 × 6.5 cm or 3 × 3 cm; larger images: 13 × 16 cm or 13 × 13 cm). Regardless of image size, Standers were less stable than Sitters with larger sway areas and faster sway velocities. Both Sitters and Standers adjusted sway area but not sway velocity, based on image size. Sitters and Standers differed in how they controlled sway dynamics. Standers but not Sitters altered sway dynamics based on image size. Overall, infants used posture-specific adaptive control strategies to make fine-grained adjustments based on image size. The development of the ability to integrate posture with a visually demanding task further emphasizes the capability of advanced complex motor behaviors during infancy, enabling infants to flexibly attend to important aspects of their environment at different postural positions.

Do concurrent task demands impact the benefit of automation transparency?

Automated decision aids typically improve decision-making, but incorrect advice risks automation misuse or disuse. We examined the novel question of whether increased automation transparency improves the accuracy of automation use under conditions with/without concurrent (non-automated assisted) task demands. Participants completed an uninhabited vehicle (UV) management task whereby they assigned the best UV to complete missions. Automation advised the best UV but was not always correct. Concurrent non-automated task demands decreased the accuracy of automation use, and increased decision time and perceived workload. With no concurrent task demands, increased transparency which provided more information on how the automation made decisions, improved the accuracy of automation use. With concurrent task demands, increased transparency led to higher trust ratings, faster decisions, and a bias towards agreeing with automation. These outcomes indicate increased reliance on highly transparent automation under conditions with concurrent task demands and have potential implications for human-automation teaming design.