Yi Weibo, Qiu Shuang, Wang Kun, Qi Hongzhi, He Feng, Zhou Peng, Zhang Lixin, Ming Dong
Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China.
Tianjin Key Laboratory of Biomedical Detecting Techniques and Instruments, Tianjin University, Tianjin, China.
J Neuroeng Rehabil. 2016 Jan 28;13:11. doi: 10.1186/s12984-016-0119-8.
A number of studies have been done on movement imagination of motor sequences with a single limb. However, brain oscillatory patterns induced by movement imagination of motor sequences involving multiple limbs have not been reported in recent years. The goal of the present study was to verify the feasibility of application of motor sequences involving multiple limbs to brain-computer interface (BCI) systems based on motor imagery (MI). The changes of EEG patterns and the inter-influence between movements associated with the imagination of motor sequences were also investigated.
The experiment, where 12 healthy subjects participated, involved one motor sequence with a single limb and three kinds of motor sequences with two or three limbs. The activity involved mental simulation, imagining playing drums with two conditions (60 and 30 beats per minute for the first and second conditions, respectively).
Movement imagination of different limbs in the sequence contributed to time-variant event-related desynchronization (ERD) patterns within both mu and beta rhythms, which was more obvious for the second condition compared with the first condition. The ERD values of left/right hand imagery with prior hand imagery were significantly larger than those with prior foot imagery, while the phase locking values (PLVs) between central electrodes and the mesial frontocentral electrode of non-initial movement were significantly larger than those of the initial movement during imagination of motor sequences for both conditions. Classification results showed that the power spectral density (PSD) based method outperformed the multi-class common spatial patterns (multi-CSP) based method: The highest accuracies were 82.86 % and 91.43 %, and the mean values were 65 % and 74.14 % for the first and second conditions, respectively.
This work implies that motor sequences involving multiple limbs can be utilized to build a multimodal classification paradigm in MI-based BCI systems, and that prior movement imagination can result in the changes of neural activities in motor areas during subsequent movement imagination in the process of limb switching.
已经对单肢运动序列的运动想象进行了多项研究。然而，近年来尚未报道涉及多肢的运动序列的运动想象所诱发的脑振荡模式。本研究的目的是验证将涉及多肢的运动序列应用于基于运动想象（MI）的脑机接口（BCI）系统的可行性。还研究了脑电图模式的变化以及与运动序列想象相关的运动之间的相互影响。
12名健康受试者参与了该实验，实验包括一个单肢运动序列和三种两肢或三肢运动序列。活动包括心理模拟，在两种条件下想象打鼓（第一种和第二种条件下分别为每分钟60和30拍）。
序列中不同肢体的运动想象导致μ和β节律内随时间变化的事件相关去同步化（ERD）模式，与第一种条件相比，第二种条件下这种模式更明显。与先前的足部想象相比，先前有手部想象时左/右手想象的ERD值显著更大，而在两种条件下运动序列想象期间，非初始运动的中央电极与额中央内侧电极之间的锁相值（PLV）显著大于初始运动的锁相值。分类结果表明，基于功率谱密度（PSD）的方法优于基于多类共同空间模式（multi-CSP）的方法：第一种和第二种条件下的最高准确率分别为82.86%和91.43%，平均值分别为65%和74.14%。
这项工作表明，涉及多肢的运动序列可用于在基于MI的BCI系统中构建多模态分类范式，并且先前的运动想象可导致肢体切换过程中后续运动想象期间运动区域神经活动的变化。
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