Li Mengfan, Qi Enming, Xu Guizhi, Jin Jing, Zhao Qi, Guo Miaomiao, Liao Wenzhe
State Key Laboratory of Reliability and Intelligence of Electrical Equipment, School of Health Sciences and Biomedical Engineering, Hebei University of Technology, Tianjin, 300132 China.
Hebei Key Laboratory of Bioelectromagnetics and Neuroengineering, Tianjin, 300132 China.
Cogn Neurodyn. 2024 Aug;18(4):1593-1607. doi: 10.1007/s11571-023-10030-8. Epub 2023 Nov 9.
The way people imagine greatly affects performance of brain-computer interface (BCI) based on motion imagery (MI). Action sequence is a basic unit of imitation, learning, and memory for motor behavior. Whether it influences the MI-BCI is unknown, and how to manifest this influence is difficult since the MI is a spontaneous brain activity. To investigate the influence of the action sequence, this study proposes a novel paradigm named action sequences observing and delayed matching task to use images and videos to guide people to observe, match and reinforce the memory of sequence. Seven subjects' ERPs and MI performance are analyzed under four different levels of complexities or orders of the sequence. Results demonstrated that the action sequence in terms of complexity and sequence order significantly affects the MI. The complex action in positive order obtains stronger ERD/ERS and more pronounced MI feature distributions, and yields an MI classification accuracy that is 12.3% higher than complex action in negative order ( < 0.05). In addition, the ERP amplitudes derived from the supplementary motor area show a positive correlation to the MI. This study demonstrates a new perspective of improving imagery in the MI-BCI by considering the complexity and order of the action sequences, and provides a novel index for manifesting the MI performance by ERP.
人们的想象方式对基于运动想象（MI）的脑机接口（BCI）的性能有很大影响。动作序列是运动行为模仿、学习和记忆的基本单元。它是否会影响MI-BCI尚不清楚，而且由于MI是一种自发的大脑活动，很难体现这种影响。为了研究动作序列的影响，本研究提出了一种名为动作序列观察与延迟匹配任务的新范式，利用图像和视频引导人们观察、匹配并强化序列记忆。在序列的四种不同复杂程度或顺序水平下，分析了七名受试者的事件相关电位（ERP）和MI性能。结果表明，动作序列在复杂性和序列顺序方面对MI有显著影响。正序的复杂动作获得更强的事件相关去同步化/事件相关同步化（ERD/ERS）和更明显的MI特征分布，其MI分类准确率比负序的复杂动作高12.3%（<0.05）。此外，从辅助运动区得出的ERP波幅与MI呈正相关。本研究通过考虑动作序列的复杂性和顺序，展示了改善MI-BCI中想象的新视角，并提供了一种通过ERP体现MI性能的新指标。
