SMR脑机接口性能的可靠预测因素——它们存在吗?

L. Botrel, A. Kübler
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引用次数: 5

摘要

脑机接口性能的可靠预测对于脑机接口的基础研究和临床应用都是可取的。在基础研究中,预测因子有助于阐明大脑如何实例化BCI控制。对于患者最终用户使用的脑机接口控制应用程序,预测器可以支持最佳脑信号的选择。对预测变量的训练可以支持以后的脑机接口控制。其中,生理和心理变量被认为是这样的预测因素。例如,静息状态的μ-节律峰、运动想象时背外侧前额叶皮层的激活以及视觉和运动信息的协调能力与不同运动想象脑机接口模式的表现有关。预测能力从低到中等,少数甚至高,其中生理预测能力最强。为了识别预测因子,那些和相关的标准变量必须被明确地定义。同样,在BCI领域中必须指定可靠性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Reliable predictors of SMR BCI performance — Do they exist?
Reliable predictors of BCI performance would be desirable for basic research and application of BCI in a clinical context alike. In basic research, predictors help to elucidate how the brain instantiates BCI control. With respect to BCI controlled applications to be used by patient end-users with disease, predictors could support the choice of the optimal brain signal. Training of the predicting variable may support later BCI control. Among others, physiologic and psychologic variables have been suggested as such predictors. For example, the resting state μ-rhythm peak, the activation of dorsolateral prefrontal cortex during motor imagery, and the ability to coordinate visual and motor information were related to performance in different motor imagery BCI paradigms. The predictive power was low to medium, few even high, where the physiologic predictor was most powerful. To identify predictors, those and the related criterion variable have to be unambiguously defined. Likewise, reliability and validity have to be specified in the realm of BCI.
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