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James Stieger

3 papers in the library · 2 citations · publishing 2020-2021

Papers

Effects of Long-Term Meditation Practices on Sensorimotor Rhythm Based BCI Learning

bioRxiv Preprint Server September 9, 2020 Xiyuan Jiang, Emily Lopez, James Stieger et al. 2 citations preprint

Meditators outperformed non-meditators in brain-computer interface (BCI) cursor control tasks using motor imagery. Experienced meditators showed better performance in both 1-dimensional and 2-dimensional tasks, and fewer meditators were unable to generate decodable EEG signals. Meditators also had higher sensorimotor rhythm (SMR) predictor values and were better able to produce decodable EEG signals for SMR-based BCI control, suggesting meditation training may improve BCI performance.

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

Scientific Reports March 25, 2021 Haiteng Jiang, James Stieger, Mary Jo Kreitzer et al.

Training in mindfulness-based stress reduction (MBSR) improves brain-computer interface (BCI) performance by reducing mind wandering and enhancing self-awareness. In a longitudinal intervention study, participants who completed MBSR showed significantly better BCI control compared to controls. This improvement was accompanied by increased frontolimbic alpha activity (9-15 Hz) and decreased alpha connectivity among the limbic network, frontoparietal network, and default-mode network. The changes in frontolimbic alpha activity correlated positively with meditation experience duration and the extent of BCI performance improvement. The findings suggest that mindfulness enables participants to modulate frontolimbic alpha power, thereby improving sensorimotor rhythm-based BCI control.

Effects of Long-Term Meditation Practices on Sensorimotor Rhythm-Based Brain-Computer Interface Learning

Frontiers in Neuroscience January 21, 2021 Xiyuan Jiang, Emily Lopez, James Stieger et al.

Experienced meditators outperformed meditation-naïve subjects in one-dimensional and two-dimensional cursor control tasks using a sensorimotor rhythm-based brain–computer interface. Fewer meditators were classified as BCI inefficient. Meditators also showed a higher resting SMR predictor, more stable resting mu rhythm, and larger control signal contrast during the task, suggesting that meditation training may enhance BCI performance.