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Beta-band oscillations as a biomarker of gait recovery in spinal cord injury patients: A quantitative electroencephalography analysis
Clinical Neurophysiology ( IF 3.7 ) Pub Date : 2020-08-01 , DOI: 10.1016/j.clinph.2020.04.166
Marcel Simis 1 , Elif Uygur-Kucukseymen 2 , Kevin Pacheco-Barrios 3 , Linamara R Battistella 1 , Felipe Fregni 2
Affiliation  

OBJECTIVE The gait recovery in spinal cord injury (SCI) seems to be partially related to the reorganization of cerebral function; however, the neural mechanisms and the respective biomarkers are not well known. This study tested the hypothesis that enhanced beta-band oscillations may be a marker of compensatory neural plasticity during the recovery period in SCI. We tested this hypothesis at baseline in SCI subjects and also in response to cortical stimulation with transcranial direct current stimulation (tDCS) combined with robotic-assisted gait training (RAGT). METHODS In this neurophysiological analysis of a randomized controlled trial, thirty-nine patients with incomplete SCI were included. They received 30 sessions of either active or sham anodal tDCS over the primary motor area for 20 min combined with RAGT. We analyzed the Electroencephalography (EEG) power spectrum and task-related power modulation of EEG oscillations, and their association with gait function indexed by Walk Index for Spinal Cord Injury (WISCI-II). Univariate and multivariate linear/logistic regression analyses were performed to identify the predictors of gait function and recovery. RESULTS Consistent with our hypothesis, we found that in the sensorimotor area: (1) Anodal tDCS combined with RAGT can modulate high-beta EEG oscillations power and enhance gait recovery; (2) higher high-beta EEG oscillations power at baseline can predict baseline gait function; (3) high-beta EEG oscillations power at baseline can predict gait recovery - the higher power at baseline, the better gait recovery; (4) decreases in relative high-beta power and increases in beta power decrease during walking are associated with gait recovery. CONCLUSIONS Enhanced EEG beta oscillations in the sensorimotor area in SCI subjects may be part of a compensatory mechanism to enhance local plasticity. Our results point to the direction that interventions enhancing local plasticity such as tDCS combined with robotic training also lead to an immediate increase in sensorimotor cortex activation, improvement in gait recovery, and subsequent decrease in high-beta power. These findings suggest that beta-band oscillations may be potential biomarkers of gait function and recovery in SCI. SIGNIFICANCE These findings are significant for rehabilitation in SCI patients, and as EEG is a portable, inexpensive, and easy-to-apply system, the clinical translation is feasible to follow better the recovery process and to help to individualize rehabilitation therapies of SCI patients.

中文翻译:

Beta 波段振荡作为脊髓损伤患者步态恢复的生物标志物:定量脑电图分析

目的 脊髓损伤(SCI)的步态恢复似乎与脑功能的重组有关;然而,神经机制和相应的生物标志物尚不清楚。这项研究检验了以下假设:增强的 β 波段振荡可能是 SCI 恢复期补偿性神经可塑性的标志。我们在 SCI 受试者的基线测试了这一假设,并响应了经颅直流电刺激 (tDCS) 与机器人辅助步态训练 (RAGT) 的皮层刺激。方法 在一项随机对照试验的神经生理学分析中,纳入了 39 名不完全 SCI 患者。他们在主要运动区域接受了 30 次主动或假阳极 tDCS,持续 20 分钟,并结合 RAGT。我们分析了脑电图 (EEG) 功率谱和 EEG 振荡的与任务相关的功率调制,以及它们与由脊髓损伤步行指数 (WISCI-II) 索引的步态功能的关联。进行单变量和多变量线性/逻辑回归分析以确定步态功能和恢复的预测因子。结果与我们的假设一致,我们发现在感觉运动区:(1)Anodal tDCS结合RAGT可以调节高βEEG振荡功率并增强步态恢复;(2)基线时较高的高β脑电振荡功率可以预测基线步态功能;(3)基线高β脑电振荡功率可以预测步态恢复——基线功率越高,步态恢复越好;(4) 相对高β功率的降低和行走期间β功率降低的增加与步态恢复有关。结论 SCI 受试者感觉运动区增强的 EEG β 振荡可能是增强局部可塑性的补偿机制的一部分。我们的研究结果表明,增强局部可塑性的干预措施(例如 tDCS 与机器人训练相结合)也会导致感觉运动皮层激活的立即增加、步态恢复的改善以及随后的高β功率降低。这些发现表明,β 波段振荡可能是 SCI 步态功能和恢复的潜在生物标志物。意义这些发现对于 SCI 患者的康复具有重要意义,并且由于 EEG 是一种便携式、廉价且易于应用的系统,
更新日期:2020-08-01
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