We developed a brain–computer interface (BCI) able to continuously monitor working memory (WM) load in real-time (considering the last 2.5 s of brain activity). The BCI is based on biomarkers derived from spectral properties of non-invasive electroencephalography (EEG), subsequently classified by a linear discriminant analysis classifier. The BCI was trained on a visual WM task, tested in a real-time visual WM task, and further validated in a real-time cross task (mental arithmetic). Throughout each trial of the cross task, subjects were given real or sham feedback about their WM load. At the end of the trial, subjects were asked whether the feedback provided was real or sham. The high rate of correct answers provided by the subjects validated not only the global behaviour of the WM-load feedback, but also its real-time dynamics. On average, subjects were able to provide a correct answer 82% of the time, with one subject having 100% accuracy. Possible cognitive and motor confounding factors were disentangled to support the claim that our EEG-based markers correspond indeed to WM.

中文翻译：

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脑机接口，用于连续实时监控现实环境中的工作记忆负载。


我们开发了一种脑机接口 (BCI)，能够实时连续监测工作记忆 (WM) 负载（考虑最后 2.5 秒的大脑活动）。 BCI 基于源自非侵入性脑电图 (EEG) 光谱特性的生物标志物，随后通过线性判别分析分类器进行分类。 BCI 在视觉 WM 任务上进行训练，在实时视觉 WM 任务中进行测试，并在实时交叉任务（心算）中进一步验证。在交叉任务的每次试验中，受试者都会获得有关其 WM 负荷的真实或虚假反馈。试验结束时，受试者被询问所提供的反馈是真实的还是虚假的。受试者提供的高正确率不仅验证了 WM 负载反馈的全局行为，还验证了其实时动态。平均而言，受试者能够在 82% 的时间内提供正确答案，其中一名受试者的准确率达到 100%。可能的认知和运动混杂因素被理清，以支持我们基于脑电图的标记确实与 WM 相对应的说法。