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

被引:12
作者
Jiang, Haiteng [1 ]
Stieger, James [1 ,2 ]
Kreitzer, Mary Jo [2 ]
Engel, Stephen [2 ]
He, Bin [1 ]
机构
[1] Carnegie Mellon Univ, Dept Biomed Engn, Pittsburgh, PA 15213 USA
[2] Univ Minnesota, Minneapolis, MN USA
关键词
D O I
10.1038/s41598-021-86215-0
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
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页数:8
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共 48 条
  • [41] The neuroscience of mindfulness meditation
    Tang, Yi-Yuan
    Hoelzel, Britta K.
    Posner, Michael I.
    [J]. NATURE REVIEWS NEUROSCIENCE, 2015, 16 (04) : 213 - U80
  • [42] Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain
    Tzourio-Mazoyer, N
    Landeau, B
    Papathanassiou, D
    Crivello, F
    Etard, O
    Delcroix, N
    Mazoyer, B
    Joliot, M
    [J]. NEUROIMAGE, 2002, 15 (01) : 273 - 289
  • [43] MAXIMUM ENTROPY SPECTRAL ANALYSIS AND AUTOREGRESSIVE DECOMPOSITION
    ULRYCH, TJ
    BISHOP, TN
    [J]. REVIEWS OF GEOPHYSICS, 1975, 13 (01) : 183 - 200
  • [44] Distributed cortical adaptation during learning of a brain-computer interface task
    Wander, Jeremiah D.
    Blakely, Timothy
    Miller, Kai J.
    Weaver, Kurt E.
    Johnson, Lise A.
    Olson, Jared D.
    Fetz, Eberhard E.
    Rao, Rajesh P. N.
    Ojemann, Jeffrey G.
    [J]. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2013, 110 (26) : 10818 - 10823
  • [45] Control of a two-dimensional movement signal by a noninvasive brain-computer interface in humans
    Wolpaw, JR
    McFarland, DJ
    [J]. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2004, 101 (51) : 17849 - 17854
  • [46] Worden MS, 2000, J NEUROSCI, V20
  • [47] The organization of the human cerebral cortex estimated by intrinsic functional connectivity
    Yeo, B. T. Thomas
    Krienen, Fenna M.
    Sepulcre, Jorge
    Sabuncu, Mert R.
    Lashkari, Danial
    Hollinshead, Marisa
    Roffman, Joshua L.
    Smoller, Jordan W.
    Zoeller, Lilla
    Polimeni, Jonathan R.
    Fischl, Bruce
    Liu, Hesheng
    Buckner, Randy L.
    [J]. JOURNAL OF NEUROPHYSIOLOGY, 2011, 106 (03) : 1125 - 1165
  • [48] Network-based statistic: Identifying differences in brain networks
    Zalesky, Andrew
    Fornito, Alex
    Bullmore, Edward T.
    [J]. NEUROIMAGE, 2010, 53 (04) : 1197 - 1207