Covert attention allows for continuous control of brain-computer interfaces

被引:49
|
作者
Bahramisharif, Ali [1 ,2 ]
van Gerven, Marcel [1 ,2 ]
Heskes, Tom [1 ,2 ]
Jensen, Ole [2 ]
机构
[1] Radboud Univ Nijmegen, Inst Comp & Informat Sci, NL-6525 ED Nijmegen, Netherlands
[2] Radboud Univ Nijmegen, Donders Inst Brain Cognit & Behav, NL-6525 ED Nijmegen, Netherlands
关键词
BCI; circular regression; magnetoencephalography; peripheral sensory stimulus; posterior alpha activity; VISUAL-SPATIAL ATTENTION; COMMUNICATION; POWER; OSCILLATIONS; SUPPRESSION; INHIBITION; INCREASES; DEVICES; BCI; MEG;
D O I
10.1111/j.1460-9568.2010.07174.x
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
While brain-computer interfaces (BCIs) can be used for controlling external devices, they also hold the promise of providing a new tool for studying the working brain. In this study we investigated whether modulations of brain activity by changes in covert attention can be used as a continuous control signal for BCI. Covert attention is the act of mentally focusing on a peripheral sensory stimulus without changing gaze direction. The ongoing brain activity was recorded using magnetoencephalography in subjects as they covertly attended to a moving cue while maintaining fixation. Based on posterior alpha power alone, the direction to which subjects were attending could be recovered using circular regression. Results show that the angle of attention could be predicted with a mean absolute deviation of 51 degrees in our best subject. Averaged over subjects, the mean deviation was similar to 70 degrees. In terms of information transfer rate, the optimal data length used for recovering the direction of attention was found to be 1700 ms; this resulted in a mean absolute deviation of 60 degrees for the best subject. The results were obtained without any subject-specific feature selection and did not require prior subject training. Our findings demonstrate that modulations of posterior alpha activity due to the direction of covert attention has potential as a control signal for continuous control in a BCI setting. Our approach will have several applications, including a brain-controlled computer mouse and improved methods for neuro-feedback that allow direct training of subjects' ability to modulate posterior alpha activity.
引用
收藏
页码:1501 / 1508
页数:8
相关论文
共 50 条
  • [41] Decoding covert speech for intuitive control of brain-computer interfaces based on single-trial EEG: a feasibility study
    Tottrup, L.
    Leerskov, K.
    Hadsund, J. T.
    Kamavuako, E. N.
    Kaeseter, R. L.
    Jochumsen, M.
    2019 IEEE 16TH INTERNATIONAL CONFERENCE ON REHABILITATION ROBOTICS (ICORR), 2019, : 689 - 693
  • [42] Editorial: Brain-Computer Interfaces for Perception, Learning, and Motor Control
    Bhattacharyya, Saugat
    Konar, Amit
    Raza, Haider
    Khasnobish, Anwesha
    FRONTIERS IN NEUROSCIENCE, 2021, 15
  • [43] Using Motor Imagery to Control Brain-Computer Interfaces for Communication
    Brumberg, Jonathan S.
    Burnison, Jeremy D.
    Pitt, Kevin M.
    FOUNDATIONS OF AUGMENTED COGNITION: NEUROERGONOMICS AND OPERATIONAL NEUROSCIENCE, AC 2016, PT I, 2016, 9743 : 14 - 25
  • [44] Volitional control of neural activity: implications for brain-computer interfaces
    Fetz, Eberhard E.
    JOURNAL OF PHYSIOLOGY-LONDON, 2007, 579 (03): : 571 - 579
  • [45] Brain-machine and brain-computer interfaces
    Friehs, GM
    Zerris, VA
    Ojakangas, CL
    Fellows, MR
    Donoghue, JP
    STROKE, 2004, 35 (11) : 2702 - 2705
  • [46] Adaptive and Warning Displays with Brain-Computer Interfaces : Enhanced Visuospatial Attention Performance
    Trachel, Romain
    Brochier, Thomas
    Clerc, Maureen
    2013 6TH INTERNATIONAL IEEE/EMBS CONFERENCE ON NEURAL ENGINEERING (NER), 2013, : 367 - 370
  • [47] Use of Kohonen maps as feature selector for selective attention brain-computer interfaces
    Lopez, Miguel Angel
    Pomares, Hector
    Damas, Miguel
    Prieto, Alberto
    Hernandez, Eva Maria de la Plaza
    BIO-INSPIRED MODELING OF COGNITIVE TASKS, PT 1, PROCEEDINGS, 2007, 4527 : 407 - +
  • [48] Brain-Computer Interfaces in Disorders of Consciousness
    He, Qiheng
    He, Jianghong
    Yang, Yi
    Zhao, Jizong
    NEUROSCIENCE BULLETIN, 2023, 39 (02) : 348 - 352
  • [49] Optimizing the Usability of Brain-Computer Interfaces
    Zhang, Yin
    Chase, Steve M.
    NEURAL COMPUTATION, 2018, 30 (05) : 1323 - 1358
  • [50] Recent advances in brain-computer interfaces
    Ebrahimi, Touradj
    2007 IEEE NINTH WORKSHOP ON MULTIMEDIA SIGNAL PROCESSING, 2007, : 17 - 17