Neural correlates of motor learning and performance in a virtual ball putting task

Learning to move skillfully requires that the motor system adjusts motor commands based on ongoing performance, until the task is executed satisfactorily. Robots can be used to emulate motor tasks that involve haptic interaction with objects. These studies may provide useful insights on how humans acquire a novel motor skill. Here we address motor skill learning in a 2D ball putting task, by looking at both kinematic and EEG correlates of learning and performance. Participants grasped the handle of a manipulandum and had to hit a virtual ball in order to put it into a target region (hole). The robot was used to render the contact force with the ball during impact. At every trial, with respect to the initial ball position, the hole appeared in one of three different directions and two distances, selected randomly. The experimental protocol included a total of 300 movements. In movement kinematics we looked at the effects of learning and target distance. In EEG signals, we looked at the effect of learning and the effect of success/failure on the ongoing brain activity. Subjects managed to improve their performance through practice, in all directions and at both target distances. Direction did not affect the performance much, but greater target distance induced greater errors. With regards to the EEG activity, we found that (i) practice led to an increased theta synchronization in the frontal areas; (ii) successful trials were preceded by higher theta synchronization, and alpha and beta desynchronization. These results suggest that EEG signals can be used to monitor the learning process and to predict the outcome (success/failure) of individual trials. These findings open possibilities to develop new schemes to promote and facilitate learning, which integrate EEG and robots.