Frontolimbic alpha activity tracks intentional rest BCI control improvement through mindfulness meditation

Haiteng Jiang, James Stieger, Mary Jo Kreitzer, Stephen Engel, Bin He

Research output: Contribution to journalArticlepeer-review

Abstract

Brain–computer interfaces (BCIs) are capable of translating human intentions into signals controlling an external device to assist patients with severe neuromuscular disorders. Prior work has demonstrated that participants with mindfulness meditation experience evince improved BCI performance, but the underlying neural mechanisms remain unclear. Here, we conducted a large-scale longitudinal intervention study by training participants in mindfulness-based stress reduction (MBSR; a standardized mind–body awareness training intervention), and investigated whether and how short-term MBSR affected sensorimotor rhythm (SMR)-based BCI performance. We hypothesize that MBSR training improves BCI performance by reducing mind wandering and enhancing self-awareness during the intentional rest BCI control, which would mainly be reflected by modulations of default-mode network and limbic network activity. We found that MBSR training significantly improved BCI performance compared to controls and these behavioral enhancements were accompanied by increased frontolimbic alpha activity (9–15 Hz) and decreased alpha connectivity among limbic network, frontoparietal network, and default-mode network. Furthermore, the modulations of frontolimbic alpha activity were positively correlated with the duration of meditation experience and the extent of BCI performance improvement. Overall, these data suggest that mindfulness allows participant to reach a state where they can modulate frontolimbic alpha power and improve BCI performance for SMR-based BCI control.

Original languageEnglish (US)
Article number6818
JournalScientific reports
Volume11
Issue number1
DOIs
StatePublished - Dec 2021

Bibliographical note

Funding Information:
This work was supported in part by NIH AT009263, EB008389, EB029354, MH114233, and NS096761.

Publisher Copyright:
© 2021, The Author(s).

PubMed: MeSH publication types

  • Journal Article

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