A P300-Based BCI System Using Stereoelectroencephalography and Its Application in a Brain Mechanistic Study
A P300-Based BCI System Using Stereoelectroencephalography and Its Application in a Brain Mechanistic Study
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基于 P300 的立体脑电图 BCI 系统及其在脑机制研究中的应用
DOI：
10.1109/tbme.2020.3047812
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发表时间：
2021-08-01
影响因子：
4.6
通讯作者：
Li, Yuanqing
中科院分区：
文献类型：
--
作者：
Huang, Weichen;Zhang, Peiqi;Li, Yuanqing
立体脑电图（SEEG）信号可通过植入颅内深部电极获得。SEEG深部电极能够记录浅皮层和大脑深部结构的脑活动，这是其他记录技术无法实现的。此外，SEEG具有高信噪比（SNR）的优势。因此，它为建立高效的脑机接口（BCI）以及帮助理解人脑活动提供了一种潜在的途径。在这项研究中，我们利用SEEG信号实现了一种基于P300的脑机接口。采用单字符的奇异球范式来诱发P300。为了预测目标字符，我们将从5个SEEG触点收集的信号中提取的特征向量输入到贝叶斯线性判别分析（BLDA）分类器中。13名植入了SEEG电极的癫痫患者参与了实验，平均在线拼写准确率达到93.85%。此外，通过单触点解码分析和模拟在线分析，我们发现基于SEEG的脑机接口系统即使使用单个信号通道也能取得高性能。进一步地，解码准确率高的触点主要分布在视觉腹侧通路，尤其是梭状回（FG）和舌回（LG），它们在构建基于P300的SEEG脑机接口中起着重要作用。这些结果可能为P300机制研究和相应的脑机接口提供新的见解。
Stereoelectroencephalography (SEEG) signals can be obtained by implanting deep intracranial electrodes. SEEG depth electrodes can record brain activity from the shallow cortical layer and deep brain structures, which is not achievable through other recording techniques. Moreover, SEEG has the advantage of a high signal-to-noise ratio (SNR). Therefore, it provides a potential way to establish a highly efficient brain-computer interface (BCI) and aid in understanding human brain activity. In this study, we implemented a P300-based BCI using SEEG signals. A single-character oddball paradigm was applied to elicit P300. To predict target characters, we fed the feature vectors extracted from the signals collected by five SEEG contacts into a Bayesian linear discriminant analysis (BLDA) classifier. Thirteen epileptic patients implanted with SEEG electrodes participated in the experiment and achieved an average online spelling accuracy of 93.85%. Moreover, through single-contact decoding analysis and simulated online analysis, we found that the SEEG-based BCI system achieved a high performance even when using a single signal channel. Furthermore, contacts with high decoding accuracies were mainly distributed in the visual ventral pathway, especially the fusiform gyrus (FG) and lingual gyrus (LG), which played an important role in building P300-based SEEG BCIs. These results might provide new insights into P300 mechanistic studies and the corresponding BCIs.