Chen Long, Zhang Lei, Wang Zhongpeng, Gu Bin, Zhang Xin, Ming Dong
Department of Biomedical Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China.
Department of Biomedical Engineering, College of Precision Instruments & Optoelectronics Engineering, Tianjin University, Tianjin, China.
Front Neurosci. 2022 Jun 17;16:909434. doi: 10.3389/fnins.2022.909434. eCollection 2022.
Motor imagery-based brain-computer interface (MI-BCI) has been largely studied to improve motor learning and promote motor recovery. However, the difficulty in performing MI limits the widespread application of MI-BCI. It has been suggested that the usage of sensory threshold somatosensory electrical stimulation (st-SES) is a promising way to guide participants on MI tasks, but it is still unclear whether st-SES is effective for all users. In the present study, we aimed to examine the effects of st-SES on the MI-BCI performance in two BCI groups (High Performers and Low Performers). Twenty healthy participants were recruited to perform MI and resting tasks with EEG recordings. These tasks were modulated with or without st-SES. We demonstrated that st-SES improved the performance of MI-BCI in the Low Performers, but led to a decrease in the accuracy of MI-BCI in the High Performers. Furthermore, for the Low Performers, the combination of st-SES and MI resulted in significantly greater event-related desynchronization (ERD) and sample entropy of sensorimotor rhythm than MI alone. However, the ERD and sample entropy values of MI did not change significantly during the st-SES intervention in the High Performers. Moreover, we found that st-SES had an effect on the functional connectivity of the fronto-parietal network in the alpha band of Low Performers and the beta band of High Performers, respectively. Our results demonstrated that somatosensory input based on st-SES was only beneficial for sensorimotor cortical activation and MI-BCI performance in the Low Performers, but not in the High Performers. These findings help to optimize guidance strategies to adapt to different categories of users in the practical application of MI-BCI.
基于运动想象的脑机接口(MI-BCI)已得到大量研究,以改善运动学习并促进运动恢复。然而,执行运动想象的难度限制了MI-BCI的广泛应用。有人提出,使用感觉阈值体感电刺激(st-SES)是指导参与者进行运动想象任务的一种有前景的方法,但尚不清楚st-SES是否对所有用户都有效。在本研究中,我们旨在研究st-SES对两个脑机接口组(高表现者和低表现者)中MI-BCI性能的影响。招募了20名健康参与者进行带有脑电图记录的运动想象和静息任务。这些任务在有或没有st-SES的情况下进行调制。我们证明,st-SES改善了低表现者中MI-BCI的性能,但导致高表现者中MI-BCI的准确性下降。此外,对于低表现者,st-SES与运动想象的结合导致与单独运动想象相比,感觉运动节律的事件相关去同步化(ERD)和样本熵显著更大。然而,在高表现者的st-SES干预期间,运动想象的ERD和样本熵值没有显著变化。此外,我们发现st-SES分别对低表现者α波段和高表现者β波段的额顶网络功能连接有影响。我们的结果表明,基于st-SES的体感输入仅对低表现者的感觉运动皮层激活和MI-BCI性能有益,而对高表现者则不然。这些发现有助于优化指导策略,以在MI-BCI的实际应用中适应不同类别的用户。