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

机译:认知并行任务对电动机图像的不同内存负荷的影响

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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.
机译:作为最实用的eEG的范式之一,电机图像脑电脑界面(MI-BCI)不仅用于控制外部设备,而且还用于帮助偏瘫患者重建运动功能受损。然而,由于在电动机图像期间的事件相关(DE)同步(ERD / ERS)不够稳定,MI-BCI分类的性能相对较差。它已成为研究如何实现电机图像的功能增强的焦点。由于电动机图像是一种接合电动机资源的认知处理,因此我们尝试通过改变认知状态以新颖的方式提高幅度(ERD / ERS)的抑制和增强。在这项研究中,我们设计了一种认知并联N背部任务,其具有不同的内存负载,以同步地执行电动机图像任务。在该实验中志愿参与的13项受试者的结果表明,在感觉电机皮质皮层两侧的α节奏中,增加的内存负荷可能会激活ERD模式的更强的功率降低,特别是在对侧区域。此外,我们分别计算了两个分类器在不同条件下的电机虚构和电动机空闲状态之间分类的准确性。通过配对的T检验,我们获得了高记忆负荷条件的精度明显高于低负荷条件(SVM:(76.3±13.3)%和(83.4±10.5)%,P <0.01; LDA :(78.0±13.5)%和(84.6±12.4)%,p <0.05)。可以绘制结论,即内存负荷对ERD图案产生正影响,即使它不是由电动机图像本身引起的。此外,通过改变认知状态,它可能意味着一种调制与电动机图像相关的脑振荡的新方法。

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