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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 approximately 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.

Original publication

DOI

10.1111/j.1460-9568.2010.07174.x

Type

Journal article

Journal

Eur J Neurosci

Publication Date

04/2010

Volume

31

Pages

1501 - 1508

Keywords

Algorithms, Alpha Rhythm, Attention, Brain, Cues, Fixation, Ocular, Humans, Magnetoencephalography, Motion Perception, Neuropsychological Tests, Photic Stimulation, Regression Analysis, Signal Processing, Computer-Assisted, Time Factors, User-Computer Interface