Gogeascoechea Antonio, Kuck Alexander, van Asseldonk Edwin, Negro Francesco, Buitenweg Jan R, Yavuz Utku S, Sartori Massimo
Department of Biomechanical Engineering, University of Twente, Enschede, Netherlands.
Department of Clinical and Experimental Sciences, Università degli Studi di Brescia, Brescia, Italy.
Front Neurol. 2020 Jun 9;11:493. doi: 10.3389/fneur.2020.00493. eCollection 2020.
Trans-spinal direct current stimulation (tsDCS) provides a non-invasive, clinically viable approach to potentially restore physiological neuromuscular function after neurological impairment, e.g., spinal cord injury (SCI). Use of tsDCS has been hampered by the inability of delivering stimulation patterns based on the activity of neural targets responsible to motor function, i.e., α-motor neurons (α-MNs). State of the art modeling and experimental techniques do not provide information about how individual α-MNs respond to electrical fields. This is a major element hindering the development of neuro-modulative technologies highly tailored to an individual patient. For the first time, we propose the use of a signal-based approach to infer tsDCS effects on large α-MNs pools in four incomplete SCI individuals. We employ leg muscles spatial sampling and deconvolution of high-density fiber electrical activity to decode accurate α-MNs discharges across multiple lumbosacral segments during isometric plantar flexion sub-maximal contractions. This is done before, immediately after and 30 min after sub-threshold cathodal stimulation. We deliver sham tsDCS as a control measure. First, we propose a new algorithm for removing compromised information from decomposed α-MNs spike trains, thereby enabling robust decomposition and frequency-domain analysis. Second, we propose the analysis of α-MNs spike trains coherence (i.e., frequency-domain) as an indicator of spinal response to tsDCS. Results showed that α-MNs spike trains coherence analysis sensibly varied across stimulation phases. Coherence analyses results suggested that the common synaptic input to α-MNs pools decreased immediately after cathodal tsDCS with a persistent effect after 30 min. Our proposed non-invasive decoding of individual α-MNs behavior may open up new avenues for the design of real-time closed-loop control applications including both transcutaneous and epidural spinal electrical stimulation where stimulation parameters are adjusted on-the-fly.
经脊髓直流电刺激（tsDCS）提供了一种非侵入性的、临床上可行的方法，有可能在神经损伤（如脊髓损伤，SCI）后恢复生理神经肌肉功能。tsDCS的应用一直受到阻碍，因为无法根据负责运动功能的神经靶点（即α运动神经元，α-MNs）的活动来传递刺激模式。现有的建模和实验技术无法提供关于单个α-MNs如何对电场做出反应的信息。这是阻碍高度个性化的神经调节技术发展的一个主要因素。我们首次提出使用基于信号的方法来推断tsDCS对四名不完全性SCI个体中大型α-MNs池的影响。我们采用腿部肌肉空间采样和高密度纤维电活动的反卷积，以解码在等长跖屈次最大收缩期间多个腰骶段的准确α-MNs放电。这在阈下阴极刺激之前、之后立即以及之后30分钟进行。我们提供伪tsDCS作为对照措施。首先，我们提出一种新算法，用于从分解的α-MNs尖峰序列中去除受损信息，从而实现稳健的分解和频域分析。其次，我们提出将α-MNs尖峰序列相干性（即频域）分析作为脊髓对tsDCS反应的指标。结果表明，α-MNs尖峰序列相干性分析在刺激阶段有明显变化。相干性分析结果表明，阴极tsDCS后，α-MNs池的共同突触输入立即减少，并在30分钟后持续存在。我们提出的对单个α-MNs行为的非侵入性解码可能为实时闭环控制应用的设计开辟新途径，包括经皮和硬膜外脊髓电刺激，其中刺激参数可实时调整。
