Neurofeedback learning for mental practice rather than repetitive practice improves neural pattern consistency and functional network efficiency in the subsequent mental motor execution

Abstract

During brain modulation, repeated mental practice may not always result in efficient learning. Particularly, the effectiveness of mental motor practice depends on how well one induces neural activity in a desired state consistently across mental trials, which calls for feedbacks to adjust one's performance. We hypothesized that even a brief experience of neurofeedback learning enhances trial-by-trial neural pattern consistency during subsequent mental motor execution and that this experience would change recruitment of functional connectivity in the motor imagery and default mode networks. To test this hypothesis, we conducted an experiment with two sessions of mental motor practice before and after a neurofeedback training session, in which participants conducted four types of first-person mental motor execution tasks (walking forward, turning left, turning right, and touching a tree). During the neurofeedback training session, in which participants conducted a virtual navigation game, 10 experimental participants received real-time fMRI neuro-feedbacks, while 10 control participants simply repeated the same mental task according to given cues without feedbacks. The experimental group showed significantly higher effects of neuro-feedback training on trial-by-trial consistencies and classification accuracies of activated neural patterns than the control group. Task-performing global node strength and network efficiency were increased in the motor imagery network but decreased in the default mode network only in the experimental group. These results demonstrate that even a brief experience of feedback learning is more effective than simple practice repetitions without evaluation, which was reflected in increased neural pattern consistency and task-dependent functional connectivity during a mental motor execution task.