Learning a Locomotor Task: With or without Errors?

In this study, the impact of robotic motor learning strategies that amplify or reduce errors on movement performance and muscle activation was investigated in 22 healthy subjects. The MAgnetic Resonance COmpatible Stepper (MARCOS) was used to execute the experiment where the robot moved the dominant leg passively and the subject was requested to actively synchronize the non-dominant leg to achieve an alternating stepping like movement. It was found that error amplification is the most difficult strategy for the subjects, arouses the highest muscle activation, brings an after effect and also seems to provoke the best motor learning in the less skilled subjects. Skilled subjects could not improve their performance, probably because the task was too easy. The impacts of these strategies on patients and brain activation need further investigations