Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, 16132, Genoa, Italy.
Movement Control and Neuroplasticity Research Group, KU Leuven, 3001, Leuven, Belgium.
Sci Rep. 2022 Mar 12;12(1):4314. doi: 10.1038/s41598-022-07511-x.
The aim of this study was to investigate differences between usual and complex gait motor imagery (MI) task in healthy subjects using high-density electroencephalography (hdEEG) with a MI protocol. We characterized the spatial distribution of α- and β-bands oscillations extracted from hdEEG signals recorded during MI of usual walking (UW) and walking by avoiding an obstacle (Dual-Task, DT). We applied a source localization algorithm to brain regions selected from a large cortical-subcortical network, and then we analyzed α and β bands Event-Related Desynchronizations (ERDs). Nineteen healthy subjects visually imagined walking on a path with (DT) and without (UW) obstacles. Results showed in both gait MI tasks, α- and β-band ERDs in a large cortical-subcortical network encompassing mostly frontal and parietal regions. In most of the regions, we found α- and β-band ERDs in the DT compared with the UW condition. Finally, in the β band, significant correlations emerged between ERDs and scores in imagery ability tests. Overall we detected MI gait-related α- and β-band oscillations in cortical and subcortical areas and significant differences between UW and DT MI conditions. A better understanding of gait neural correlates may lead to a better knowledge of pathophysiology of gait disturbances in neurological diseases.
本研究旨在使用高空间分辨率脑电图 (hdEEG) 与运动想象 (MI) 协议,探究健康个体在进行常规步态和复杂步态 MI 任务时的差异。我们对 MI 常规行走 (UW) 和避开障碍物行走 (双重任务,DT) 时从 hdEEG 信号中提取的 α 和 β 波段振荡的空间分布进行了特征描述。我们应用了一种源定位算法,对从大脑皮质-皮质下大网络中选择的脑区进行分析,并对 α 和 β 波段事件相关去同步化 (ERD) 进行了分析。19 名健康个体进行了想象路径行走 (DT) 和无障碍物行走 (UW) 的视觉想象。结果表明,在两种步态 MI 任务中,在包含额部和顶叶区域的大部分皮质-皮质下网络中均出现了 α 和 β 波段 ERD。在大多数区域中,与 UW 条件相比,在 DT 中发现了 α 和 β 波段 ERD。最后,在 β 波段,ERD 与想象能力测试评分之间出现了显著相关性。总体而言,我们在皮质和皮质下区域检测到了 MI 步态相关的 α 和 β 波段振荡,以及 UW 和 DT MI 条件之间的显著差异。对步态神经相关的更好理解可能会更好地了解神经疾病中步态障碍的病理生理学。