现有研究和BCI应用实践中发现，在复杂作业环境下，同步认知活动产生的认知负荷造成基于事件相关电位的脑-机接口（ERP-BCI）识别正确率降低、稳定性难以满足要求，但其深层规律与机制仍不明确，现有研究中仍缺乏有效应对方法。因此，围绕认知负荷“如何影响”ERP-BCI和“如何解决”认知负荷对ERP-BCI的影响，本项目拟通过在视觉ERP-BCI实验中调制认知负荷，研究认知负荷对ERP-BCI的影响规律，探明ERP和ERP-BCI性能在认知负荷作用下的变化模式，构建多源特征融合的认知负荷预测模型，探索基于动态建模、刺激参数调节和闭环视听反馈构建ERP-BCI可适应用户认知负荷变化、用户可适应ERP-BCI认知需求的脑机互适应系统的原理和方法。本项目有望揭示ERP及ERP-BCI在认知负荷作用下的变化模式，为应对ERP-BCI面临同步认知活动的认知负荷影响提供新的科学依据和方法。

It has been found in the existing studies and BCI application practice that, in a complex operating environment, the cognitive load generated by synchronous cognitive activities causes a decrease in the recognition rate of ERP based brain-machine interface (ERP-BCI), and the stability is difficult to meet the requirements. However, its underlying laws and mechanisms are still unclear, and there is still a lack of effective solution in existing research. Therefore, in terms of how the cognitive load affects ERP-BCI and how to resolve the impact of cognitive load on ERP-BCI, this project intends to study the effect of cognitive load on ERP-BCI by modulating cognitive load in visual ERP-BCI experiments, ascertain the changing patterns of ERP and ERP-BCI performance under cognitive load, and construct a multi-source feature-based cognitive load prediction model. Based on dynamic modelling, stimulation parameter adjustment, and closed-loop audiovisual feedback, this project will explore the principles and methods to construct brain-computer coadaptation system, in which ERP-BCI can adapt to the change of user cognitive load and users can adapt to the ERP-BCI cognitive needs. This project is expected to reveal the changing patterns of ERP and ERP-BCI under the influence of cognitive load, and provide new scientific basis and method for dealing with the impact of cognitive load of synchronous cognitive activity in ERP-BCI.