The effects of cognitive parallel task with varying memory load on motor imagery BCI

Bin Gu, Long Chen, Yufeng Ke, Shuang Liu, Jiabei Tang, Zhongpeng Wang, Yijie Zhou, Haiqing Yu, Dong Ming
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Abstract

As one of the most practical EEG-based paradigms, motor imagery brain computer interface(MI-BCI) is not only used to control external devices, but also to help patients with hemiparesis to reconstruct impaired motor function. However, due to event-related (de)synchronization(ERD/ERS) during motor imagery are not stable enough, the performance of classification of MI-BCI is relatively poor. It has become a focus of study that how to achieve the feature enhancement of motor imagery. Since motor imagery is a cognitive processing that engages parts of the motor resources, we try to improve suppression and enhancement of amplitude (ERD/ERS) in a novel way by changing cognitive state. In this study, we designed a cognitive parallel n-back task with varying memory load to carry out with motor imagery task synchronously. The result of 13 subjects who volunteered in this experiment was shown that increased memory load could activate much stronger power decrease of ERD pattern at alpha rhythms in both sides of sensorimotor cortex, especially in contralateral area. Furthermore, we calculated the accuracy of classification between motor imaginary and motor idle status in different conditions by two classifiers, respectively. Through the paired t-test, we obtained that the accuracy of high memory load condition was significantly higher than the low load condition(SVM: (76.3±13.3)% and (83.4±10.5)%, p<0.01; LDA: (78.0±13.5)% and (84.6±12.4)%, p<0.05). A conclusion can be drawn that memory load have a positive impact on ERD pattern, even it is not caused by motor imagery itself. Besides, it may imply a new approach to modulate brain oscillations related to motor imagery by changing cognitive state.
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不同记忆负荷的认知并行任务对运动意象脑机接口的影响
运动图像脑机接口(MI-BCI)是目前最实用的基于脑电图的模式之一,它不仅用于控制外部设备,还可以帮助偏瘫患者重建受损的运动功能。然而,由于运动想象过程中的事件相关(de)同步(ERD/ERS)不够稳定,MI-BCI的分类性能相对较差。如何实现运动图像的特征增强已成为研究的热点。由于运动意象是一种涉及部分运动资源的认知加工,我们试图通过改变认知状态,以一种新颖的方式改善幅度抑制和增强(ERD/ERS)。在本研究中,我们设计了一种不同记忆负荷的认知并行n-back任务,与运动意象任务同步执行。13名志愿者的实验结果表明,记忆负荷的增加可激活双侧感觉运动皮层(尤其是对侧区域)α节律ERD模式更强的能量下降。在此基础上,分别计算了两种分类器在不同工况下对电机虚状态和空闲状态的分类精度。通过配对t检验,我们得到高记忆负荷条件的准确率显著高于低记忆负荷条件(支持向量机:(76.3±13.3)%和(83.4±10.5)%,p<0.01;LDA分别为(78.0±13.5)%和(84.6±12.4)%,p<0.05)。结果表明,记忆负荷对ERD模式有积极的影响,即使它不是由运动意象本身引起的。此外,这可能暗示了一种通过改变认知状态来调节与运动意象相关的脑振荡的新途径。
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