Continuous motor skills as flexible control policies: a video game study

Abstract

Many motor skills consist of continuous sequential actions, such as a tennis serve. It is currently unclear how these surprisingly understudied behaviors are learned, with the leading hypothesis being that sequences of single actions become "chunked" into larger single executable units. Under this hypothesis, continuous sequential actions should become more task-specific and less generalizable with practice. To test this, we developed a video game that requires participants to hold a tablet with both hands and steer a virtual car (the "ant car") along a curving track. We tested participants ability to generalize their skill to a probe track that required a different sequence of turns. Across days of practice, task success increased, and movement variability decreased. On the probe track, movement quality at the level of kinematics fully generalized but performance at the level of task success showed a consistent decrement. To address this apparent paradox, we empirically derived the control policy participants used at their maximal skill level on the training track. Notably, this policy was fully transferred to the probe track, but there were more instances of momentary deviations from it (lapses), which explains the worse performance despite equivalent skill. We conclude that continuous motor skills are acquired through learning of a flexible control policy that maps states onto actions and not through chunking or automatizing of a specific sequence of actions.