论文标题
直观的脑计算机界面的视觉图像的时空动力学
Spatio-Temporal Dynamics of Visual Imagery for Intuitive Brain-Computer Interface
论文作者
论文摘要
视觉图像是直观的脑部计算机界面范式，指的是视觉场景的出现。尽管有方便，但对其内在特征的分析仍然有限。在这项研究中，我们证明了时间间隔和通道选择的效果，从而影响多级视觉图像的解码性能。我们将时期分为0-1 s和1-2 s的时间间隔，并在三个不同的大脑区域进行了六类分类：整个大脑，视觉皮层和额叶皮层。在时间间隔中，0-1 s组显示出平均分类精度的24.2％，这显着高于前额叶皮层中的1-2个组。在三个不同的区域中，前额叶皮层的分类精度显示出比0-1 s间隔组的视觉皮层明显高得多，这意味着在视觉成像过程中的认知唤醒。这一发现将为改善解码性能提供至关重要的信息。
Visual imagery is an intuitive brain-computer interface paradigm, referring to the emergence of the visual scene. Despite its convenience, analysis of its intrinsic characteristics is limited. In this study, we demonstrate the effect of time interval and channel selection that affects the decoding performance of the multi-class visual imagery. We divided the epoch into time intervals of 0-1 s and 1-2 s and performed six-class classification in three different brain regions: whole brain, visual cortex, and prefrontal cortex. In the time interval, 0-1 s group showed 24.2 % of average classification accuracy, which was significantly higher than the 1-2 s group in the prefrontal cortex. In the three different regions, the classification accuracy of the prefrontal cortex showed significantly higher performance than the visual cortex in 0-1 s interval group, implying the cognitive arousal during the visual imagery. This finding would provide crucial information in improving the decoding performance.
