Precise estimation of human corticospinal excitability associated with the levels of motor imagery-related EEG desynchronization extracted by a locked-in amplifier algorithm.
Precise estimation of human corticospinal excitability associated with the levels of motor imagery-related EEG desynchronization extracted by a locked-in amplifier algorithm.
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DOI：
10.1186/s12984-018-0440-5
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发表时间：
2018-11-01
影响因子：
5.1
通讯作者：
Ushiba J
中科院分区：
文献类型：
--
作者：
Takahashi K;Kato K;Mizuguchi N;Ushiba J
在基于脑电图（EEG）的脑机接口（BCI）的辅助下，身体运动锻炼可以改善中风患者的运动恢复。在这样的BCI范例中，经常使用从记录在初级感觉运动区（SM 1）上的EEG中提取的α和β频带中的事件相关去极化（ERD），因为ERD已被认为与皮质脊髓兴奋性的增加相关。最近，我们展示了一种新的在线锁定放大器（LIA）算法来估计电机相关的SM 1 ERD的幅度调制。与传统的快速傅里叶变换（FFT）算法相比，该算法在估计电机相关SM 1 ERD的延迟时间、精度和稳定性方面都有明显改善。提取ERD迹线的这些技术改进意味着在BCI背景下更好地跟踪SM 1的兴奋状态的潜在优势。因此，本研究的目的是评估使用经颅磁刺激（TMS）范例估计皮质脊髓兴奋性的基于LIA的ERD跟踪的精度。由单脉冲TMS在初级运动皮层上诱导的运动诱发电位（MEP）取决于SM 1 ERD的幅度（即，35%和70%）提取的在线LIA或FFT算法进行监测期间的运动想象任务的手腕伸展在17名健康的参与者。然后，MEPs的峰-峰幅度及其变异性进行评估，以调查算法的精度。我们发现更大的MEP幅度诱发的单脉冲TMS触发的运动影像相关的α SM 1 ERD比在休息。这种增强与FFT和LIA算法中的ERD的幅度相关。此外，我们发现，在35%和70%ERD的MEP振幅的变化的新的在线LIA算法计算的峰到峰小于使用传统的FFT算法提取的。本研究表明，使用新的在线LIA算法的运动图像相关的SM 1 ERD的计算导致更精确的估计皮质脊髓兴奋性比当使用普通的基于FFT的算法。本文的在线版本（10.1186/s12984-018-0440-5）包含补充材料，可供授权用户使用。
Physical motor exercise aided by an electroencephalogram (EEG)-based brain-computer interface (BCI) is known to improve motor recovery in patients with stroke. In such a BCI paradigm, event-related desynchronization (ERD) in the alpha and beta bands extracted from EEG recorded over the primary sensorimotor area (SM1) is often used, since ERD has been suggested to be associated with an increase of corticospinal excitability. Recently, we demonstrated a novel online lock-in amplifier (LIA) algorithm to estimate the amplitude modulation of motor-related SM1 ERD. With this algorithm, the delay time, accuracy, and stability to estimate motor-related SM1 ERD were significantly improved compared with the conventional fast Fourier transformation (FFT) algorithm. These technical improvements to extract an ERD trace imply a potential advantage for a better trace of the excitatory status of the SM1 in a BCI context. Therefore, the aim of this study was to assess the precision of LIA-based ERD tracking for estimation of corticospinal excitability using a transcranial magnetic stimulation (TMS) paradigm. The motor evoked potentials (MEPs) induced by single-pulse TMS over the primary motor cortex depending on the magnitudes of SM1 ERD (i.e., 35% and 70%) extracted by the online LIA or FFT algorithm were monitored during a motor imagery task of wrist extension in 17 healthy participants. Then, the peak-to-peak amplitudes of MEPs and their variabilities were assessed to investigate the precision of the algorithms. We found greater MEP amplitude evoked by single-pulse TMS triggered by motor imagery-related alpha SM1 ERD than at rest. This enhancement was associated with the magnitude of ERD in both FFT and LIA algorithms. Moreover, we found that the variabilities of peak-to-peak MEP amplitudes at 35% and 70% ERDs calculated by the novel online LIA algorithm were smaller than those extracted using the conventional FFT algorithm. The present study demonstrated that the calculation of motor imagery-related SM1 ERDs using the novel online LIA algorithm led to a more precise estimation of corticospinal excitability than when the ordinary FFT-based algorithm was used. The online version of this article (10.1186/s12984-018-0440-5) contains supplementary material, which is available to authorized users.
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