Intuitive sensorimotor decisions under risk take Newtonian physics into account
The success of our interactions with objects in natural tasks depends on generating motor actions, which are subject to sensorimotor variability, the objects' physical properties, which are governed by the laws of kinematics, and the costs and benefits associated with the actions' outcomes. Therefore, such interactions jointly involve sensorimotor control, intuitive physics, and decision-making under risk. Here, we devised a mixed reality experiment, which allows investigating human behavior involving the interaction of all three of these cognitive faculties. Participants slid pucks to target areas associated with monetary rewards and losses within an immersive, naturalistic virtual environment. In this task, signal-dependent variability inherent in motor control interacts non-linearly with the physical relationships governing objects' motion under friction. By systematically testing generative models of behavior incorporating different assumptions about how participants may generate the slides, we find decisive evidence that participants' decision under risk readily took their individual motor variability and Newtonian physics into account to gain monetary rewards without relying on trial by trial learning.