Researchers in neuroscience computing experience difficulties when they try to carry out neuroanalysis in practice or when they need to design an explainable brain-computer interface (BCI) with quick setup and minimal training phase. There is a need of interpretable computational intelligence techniques and new brain states decoding for more understandable interpretation of the sensory, cognitive, and motor brain processing. We propose a general-purpose fuzzy software system shell for developing a custom EEG BCI system. It relies on the bursts of the ongoing EEG frequency power synchronization/desynchronization at scalp level and supports quick BCI setup by linguistic features, ad hoc fuzzy membership construction, explainable IF-THEN rules, and the concept of the Internet of Things (IoT), which makes the BCI system device and service independent. It has a potential for designing both passive and event-related BCIs with options for visual representation at scalp-source level in response to time. The feasibility of the proposed system has been proven by real experiments and bursts for and frequency power have been detected in real time in response to evoked visuospatial selective attention. The presence of the proposed new brain state decoding can be used as a feasible metric for interpretation of the spatiotemporal dynamics of the passive or evoked neural oscillations.

中文翻译：

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基于诱发振荡的时空动力学的可解释BCI的模糊壳

神经科学计算领域的研究人员在尝试进行实践中的神经分析时，或者需要以快速的设置和最少的培训阶段来设计可解释的脑机接口（BCI）时，会遇到困难。需要可解释的计算智能技术和新的大脑状态解码，以对感觉，认知和运动脑处理进行更易理解的解释。我们提出了一种通用的模糊软件系统外壳，用于开发定制的EEG BCI系统。它依靠头皮级持续进行的EEG频率功率同步/去同步的脉冲，并通过语言功能，临时模糊成员构造，可解释的IF-THEN规则和物联网（IoT）的概念来支持快速BCI设置，这使得BCI系统的设备和服务独立。它具有设计被动和事件相关BCI的潜力，并具有响应时间在头皮来源级别进行视觉表示的选项。所提出系统的可行性已经通过实际实验和突发性的验证得到了证实。响应视觉空间选择性注意力，可以实时检测到频率和频率功率。所提出的新的大脑状态解码的存在可以用作解释被动或诱发的神经振荡的时空动力学的可行度量。