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. 2013 Dec 6:7:848.
doi: 10.3389/fnhum.2013.00848. eCollection 2013.

Gamma band activity associated with BCI performance: simultaneous MEG/EEG study

Minkyu Ahn  1 , Sangtae Ahn  1 , Jun H Hong  1 , Hohyun Cho  1 , Kiwoong Kim  2 , Bong S Kim  3 , Jin W Chang  3 , Sung C Jun  4
Affiliations

Gamma band activity associated with BCI performance: simultaneous MEG/EEG study

Minkyu Ahn et al. Front Hum Neurosci. .

Abstract

While brain computer interface (BCI) can be employed with patients and healthy subjects, there are problems that must be resolved before BCI can be useful to the public. In the most popular motor imagery (MI) BCI system, a significant number of target users (called "BCI-Illiterates") cannot modulate their neuronal signals sufficiently to use the BCI system. This causes performance variability among subjects and even among sessions within a subject. The mechanism of such BCI-Illiteracy and possible solutions still remain to be determined. Gamma oscillation is known to be involved in various fundamental brain functions, and may play a role in MI. In this study, we investigated the association of gamma activity with MI performance among subjects. Ten simultaneous MEG/EEG experiments were conducted; MI performance for each was estimated by EEG data, and the gamma activity associated with BCI performance was investigated with MEG data. Our results showed that gamma activity had a high positive correlation with MI performance in the prefrontal area. This trend was also found across sessions within one subject. In conclusion, gamma rhythms generated in the prefrontal area appear to play a critical role in BCI performance.

Keywords: BCI-illiteracy; EEG; MEG; gamma activity; motor imagery BCI; performance prediction.

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Figures

FIGURE 1
FIGURE 1
One trial of MI task.
FIGURE 2
FIGURE 2
Classification accuracy in EEG. Accuracy of each subject is presented with its standard deviation.
FIGURE 3
FIGURE 3
Topographic images for MEG gamma. Images are sorted in descending order of MI performance with EEG.
FIGURE 4
FIGURE 4
Regional analysis of MEG gamma. The selected channels in each region are marked as shaded round squares and their mean gamma RPL is plotted against MI accuracy. The direction of the fitted line and the correlation coefficient changed from the prefrontal to occipital areas.
FIGURE 5
FIGURE 5
Topographical plot of correlation distribution between MI performance with EEG and MEG band power. MEG Gamma p-value is shown in the right-bottom; other bands were not statistically significant with FDR-correction threshold (q = 0.1). The significant threshold for p-values is shown with an arrow in the p-value color bar.
FIGURE 6
FIGURE 6
Classification accuracy in MEG. MEG accuracy of each subject is presented as a mean with a standard deviation, and for comparison, EEG accuracy is plotted as a small filled square (r = 0.91, p < 0.0005).
FIGURE 7
FIGURE 7
Topographic images for resting state gamma in EEG. Images are sorted in descending order of MI performance with EEG.
FIGURE 8
FIGURE 8
Prefrontal MEG gamma and accuracy variation in two sessions.
See this image and copyright information in PMC

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