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Mindfulness Improves Brain-Computer Interface Performance by Increasing Control Over Neural Activity in the Alpha

James R Stieger^1,2, Stephen Engel³, Haiteng Jiang¹

¹Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA.

Cerebral Cortex (New York, N.Y. : 1991)

|September 23, 2020

Summary

Mind-body awareness training (MBAT) significantly speeds up brain-computer interface (BCI) learning by enhancing users' control over alpha brainwaves during rest. This approach may improve BCI effectiveness for individuals with paralysis.

Keywords:

alpha rhythm brain–computer interface learning mindfulness meditation rehabilitation

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Area of Science:

Neuroscience
Biomedical Engineering
Rehabilitation Technology

Background:

Brain-computer interfaces (BCIs) offer potential for individuals with paralysis but face challenges in training duration and user consistency.
Mind-body awareness training (MBAT) is known to improve BCI learning, yet the underlying mechanisms are not fully understood.

Purpose of the Study:

To investigate how MBAT influences neural activity and learning in BCI tasks.
To determine if MBAT enhances control over specific brain signals relevant to BCI operation.

Main Methods:

Participants underwent mindfulness-based stress reduction (MBSR) training, a form of MBAT.
BCI performance and electroencephalogram (EEG) signals, particularly alpha-band activity during intentional rest, were measured before and after training.
A control group received no MBAT for comparison.

Main Results:

The MBAT group demonstrated significantly faster BCI learning compared to the control group.
Alpha-band activity during volitional rest increased over training sessions in the MBAT group and predicted BCI performance.
Increased alpha-band activity correlated with mindfulness practice and performance on a breath counting task.

Conclusions:

MBAT enhances BCI effectiveness by improving volitional control over alpha-band neural activity during rest.
This neural modulation by MBAT offers a promising avenue for improving BCI applications for individuals with paralysis.
MBAT may provide an alternative to direct motor control for BCI users, broadening accessibility.