Detection of motor-evoked potentials below the noise floor: rethinking the motor stimulation threshold.
Detection of motor-evoked potentials below the noise floor: rethinking the motor stimulation threshold.
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DOI：
10.1088/1741-2552/ac7dfc
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发表时间：
2022-10-21
影响因子：
4
通讯作者：
Goetz, Stefan M.
中科院分区：
文献类型：
--
作者：
Li, Zhongxi;Peterchev, Angel, V;Rothwell, John C.;Goetz, Stefan M.
关键词：
运动诱发电位（MEP）是对脑刺激（如阈上经颅磁刺激（TMS）和电刺激）最显著的反应之一。理解神经生理学和确定引起响应的最低刺激强度需要检测甚至更小的响应，例如，从单一的运动单位。然而，可用的检测和量化方法遭受大的噪声基底。本文提出了一种检测方法，提取隐藏在本底噪声之下的MEP。用这种方法，我们的目标是估计兴奋性激活的皮质脊髓通路远低于传统的检测水平。所提出的MEP检测方法提出了一种自学习匹配滤波器方法，以提高对噪声的鲁棒性。该滤波器是通过迭代学习自适应地产生每个主题。对于通过传统检测可靠检测的响应，新方法与已建立的峰峰值读数完全兼容，并提供相同的结果，但将动态范围扩展到传统噪声基底以下。与传统的峰-峰测量相比，所提出的方法将信噪比提高了5倍以上。第一个可检测的响应似乎大大低于50 μV中值峰-峰幅度的传统阈值定义。所提出的方法表明，远低于传统的50 μV阈值定义的刺激可以持续和重复地引起肌肉反应，从而激活大脑中的可兴奋神经元群。结果，IO曲线在下端延伸，并且噪声截止偏移。重要的是，IO曲线延伸到50 μV点更接近对数S形曲线的中心，而不是接近第一个可检测的响应。基本方法适用于广泛的诱发电位和其他生物信号，如脑电图。
Motor-evoked potentials (MEP) are one of the most prominent responses to brain stimulation, such as supra-threshold transcranial magnetic stimulation (TMS) and electrical stimulation. Understanding of the neurophysiology and the determination of the lowest stimulation strength that evokes responses requires the detection of even smaller responses, e.g., from single motor units. However, available detection and quantization methods suffer from a large noise floor. This paper develops a detection method that extracts MEPs hidden below the noise floor. With this method, we aim to estimate excitatory activations of the corticospinal pathways well below the conventional detection level. The presented MEP detection method presents a self-learning matched-filter approach for improved robustness against noise. The filter is adaptively generated per subject through iterative learning. For responses that are reliably detected by conventional detection, the new approach is fully compatible with established peak-to-peak readings and provides the same results but extends the dynamic range below the conventional noise floor. In contrast to the conventional peak-to-peak measure, the proposed method increases the signal-to-noise ratio by more than a factor of 5. The first detectable responses appear to be substantially lower than the conventional threshold definition of 50 μV median peak-to-peak amplitude. The proposed method shows that stimuli well below the conventional 50 μV threshold definition can consistently and repeatably evoke muscular responses and thus activate excitable neuron populations in the brain. As a consequence, the IO curve is extended at the lower end, and the noise cut-off is shifted. Importantly, the IO curve extends so far that the 50 μV point turns out to be closer to the center of the logarithmic sigmoid curve rather than close to the first detectable responses. The underlying method is applicable to a wide range of evoked potentials and other biosignals, such as in electroencephalography.
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DOI：
10.1080/09540261.2017.1305949
发表时间：
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期刊：
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影响因子：
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