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

James R. Stieger, Stephen Engel, Haiteng Jiang, Christopher C. Cline, Mary Jo Kreitzer, Bin He

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Brain-computer interfaces (BCIs) are promising tools for assisting patients with paralysis, but suffer from long training times and variable user proficiency. Mind-body awareness training (MBAT) can improve BCI learning, but how it does so remains unknown. Here, we show that MBAT allows participants to learn to volitionally increase alpha band neural activity during BCI tasks that incorporate intentional rest. We trained individuals in mindfulness-based stress reduction (MBSR; a standardized MBAT intervention) and compared performance and brain activity before and after training between randomly assigned trained and untrained control groups. The MBAT group showed reliably faster learning of BCI than the control group throughout training. Alpha-band activity in electroencephalogram signals, recorded in the volitional resting state during task performance, showed a parallel increase over sessions, and predicted final BCI performance. The level of alpha-band activity during the intentional resting state correlated reliably with individuals' mindfulness practice as well as performance on a breath counting task. Collectively, these results show that MBAT modifies a specific neural signal used by BCI. MBAT, by increasing patients' control over their brain activity during rest, may increase the effectiveness of BCI in the large population who could benefit from alternatives to direct motor control.

Original languageEnglish (US)
Pages (from-to)426-438
Number of pages13
JournalCerebral Cortex
Volume31
Issue number1
DOIs
StatePublished - Jan 1 2021

Keywords

  • alpha rhythm
  • brain-computer interface
  • learning
  • mindfulness meditation
  • rehabilitation

PubMed: MeSH publication types

  • Journal Article

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