Motor imagery helps updating internal models during microgravity exposure.

Skilled movements result from a mixture of feedforward and feedback mechanisms conceptualized by internal models. These mechanisms subserve both motor execution and motor imagery. Current research suggests that imagery allows updating feedforward mechanisms, leading to better performance in familiar contexts. Does this still hold in radically new contexts? Here, we test this ability by asking participants to imagine swinging arm movements around shoulder in normal gravity condition and in microgravity in which studies showed that movements slow down. We timed several cycles of actual and imagined arm pendular movements in three groups of subjects during parabolic flight campaign. The first, control, group remained on the ground. The second group was exposed to microgravity but did not imagine movements inflight. The third group was exposed to microgravity and imagined movements inflight. All groups performed and imagined the movements before and after the flight. We predicted that a mere exposure to microgravity would induce changes in imagined movement duration. We found this held true for the group who imagined the movements, suggesting an update of internal representations of gravity. However, we did not find a similar effect in the group exposed to microgravity despite the fact that the participants lived the same gravitational variations as the first group. Overall, these results suggest that motor imagery contributes to update internal representations of the considered movement in unfamiliar environments, while a mere exposure proved to be insufficient. Gravity strongly affects the way movements are performed. How internal models process this information to adapt behavior to novel contexts is still unknown. The microgravity environment itself does not provide enough information to optimally adjust the period of natural arm swinging movements to microgravity. However, motor imagery of the task while immersed in microgravity was sufficient to update internal models. These results show that actually executing a task is not necessary to update graviception.