Neurofeedback learning for mental practice rather than repetitive practice improves neural pattern consistency and...

Area of Science:

• Neuroscience
• Cognitive Science
• Motor Control

Background:

• Mental motor practice effectiveness hinges on consistent neural activity, often requiring feedback for performance adjustment.
• Achieving stable neural states during mental tasks is crucial for efficient motor learning.

Purpose of the Study:

• To investigate if brief neurofeedback learning enhances neural pattern consistency during mental motor execution.
• To examine changes in functional connectivity within motor imagery and default mode networks after neurofeedback.

Main Methods:

• Two groups (experimental with neurofeedback, control without) performed mental motor tasks before and after a neurofeedback training session.
• Real-time fMRI neurofeedback was provided to the experimental group during a virtual navigation game.
• Neural pattern consistency and functional connectivity were analyzed using fMRI data.

Main Results:

• The neurofeedback group demonstrated significantly higher trial-by-trial neural pattern consistency and classification accuracy compared to the control group.
• Motor imagery network strength and efficiency increased, while the default mode network's decreased, exclusively in the neurofeedback group.
• Neurofeedback learning led to increased neural pattern consistency and task-dependent functional connectivity.

Conclusions:

• Even brief neurofeedback experience is more effective for mental motor learning than unguided practice.
• Neurofeedback enhances neural pattern consistency and modulates functional connectivity in relevant brain networks.
• This study highlights the benefits of feedback in optimizing brain modulation for motor imagery.