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事件相关电位 p300 拼写范式的组成结构。

The component structure of event-related potentials in the p300 speller paradigm.

出版信息

IEEE Trans Neural Syst Rehabil Eng. 2013 Nov;21(6):897-907. doi: 10.1109/TNSRE.2013.2285398.

Abstract

We investigated the componential structure of event-related potentials elicited while participants use the P300 BCI. Six healthy participants "typed" all characters in a 6 × 6 matrix twice in a random sequence. A principal component analysis indicated that in addition to the P300, target flashes elicited an earlier frontal positivity, possibly a Novelty P3. The amplitudes of both P300 and the Novelty P3 varied with the matrix row in which the target character was located. However, the P300 elicited by row flashes was largest for targets in the lower part of the matrix, whereas the Novelty P3 elicited by column flashes was largest in the top part. Classification accuracy using stepwise linear discriminant analysis mirrored the pattern in the Novelty P3 (an accuracy difference of 0.1 between rows 1 and 6). When separate classifiers were generated to rely solely on the P300 or solely on the Novelty P3, the latter function led to higher accuracy (a mean accuracy difference of about 0.2 between classifiers). A possible explanation is that some nontarget flashes elicit a P300, leading to lower selection accuracy of the respective classifier. In an additional set of data from six different participants we replicated the ERP structure of the initial analyses and characterized the spatial distributions more closely by using a dense electrode array. Overall, our findings provide new insights in the componential structure of ERPs elicited in the P300 speller paradigm and have important implications for optimizing the speller's selection accuracy.

摘要

我们研究了参与者使用 P300 BCI 时诱发的事件相关电位的成分结构。六名健康参与者以随机顺序两次“键入”6x6 矩阵中的所有字符。主成分分析表明,除了 P300 之外,目标闪烁还诱发出更早的额部正性波,可能是新颖 P3。P300 和新颖 P3 的振幅都随目标字符所在的矩阵行而变化。然而,行闪烁诱发的 P300 对于矩阵下部的目标最大,而列闪烁诱发的新颖 P3 对于矩阵上部最大。使用逐步线性判别分析的分类准确性反映了新颖 P3 的模式(行 1 和 6 之间的准确性差异为 0.1)。当单独的分类器仅依赖 P300 或新颖 P3 生成时,后者的功能导致更高的准确性(分类器之间的平均准确性差异约为 0.2)。一种可能的解释是,一些非目标闪烁会诱发出 P300,从而导致各自分类器的选择准确性降低。在另外六名不同参与者的一组数据中,我们复制了初始分析的 ERP 结构,并通过使用密集电极阵列更紧密地描述了空间分布。总体而言,我们的发现为 P300 拼写器范式中诱发的 ERP 的成分结构提供了新的见解,并对优化拼写器的选择准确性具有重要意义。

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