High Theta and Low Alpha Powers May Be Indicative of BCI-Illiteracy in Motor Imagery

被引:151
作者
Ahn, Minkyu [1 ]
Cho, Hohyun [1 ]
Ahn, Sangtae [1 ]
Jun, Sung Chan [1 ,2 ]
机构
[1] Gwangju Inst Sci & Technol, Sch Informat & Commun, Kwangju, South Korea
[2] New York State Hlth Dept, Wadsworth Ctr, Albany, NY USA
基金
新加坡国家研究基金会;
关键词
DEFAULT MODE; BRAIN; ATTENTION; OSCILLATIONS; CORTEX; DESYNCHRONIZATION; SYNCHRONIZATION; INFORMATION; BIOFEEDBACK; DYNAMICS;
D O I
10.1371/journal.pone.0080886
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
In most brain computer interface (BCI) systems, some target users have significant difficulty in using BCI systems. Such target users are called 'BCI-illiterate'. This phenomenon has been poorly investigated, and a clear understanding of the BCI-illiteracy mechanism or a solution to this problem has not been reported to date. In this study, we sought to demonstrate the neurophysiological differences between two groups (literate, illiterate) with a total of 52 subjects. We investigated recordings under non-task related state (NTS) which is collected during subject is relaxed with eyes open. We found that high theta and low alpha waves were noticeable in the BCI-illiterate relative to the BCI-literate people. Furthermore, these high theta and low alpha wave patterns were preserved across different mental states, such as NTS, resting before motor imagery (MI), and MI states, even though the spatial distribution of both BCI-illiterate and BCI-literate groups did not differ. From these findings, an effective strategy for pre-screening subjects for BCI illiteracy has been determined, and a performance factor that reflects potential user performance has been proposed using a simple combination of band powers. Our proposed performance factor gave an r = 0.59 (r(2) = 0.34) in a correlation analysis with BCI performance and yielded as much as r = 0.70 (r(2) = 0.50) when seven outliers were rejected during the evaluation of whole data (N = 61), including BCI competition datasets (N = 9). These findings may be directly applicable to online BCI systems.
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页数:11
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