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人类平衡控制的神经影像学:一项系统综述。

Neuroimaging of Human Balance Control: A Systematic Review.

作者信息

Wittenberg Ellen, Thompson Jessica, Nam Chang S, Franz Jason R

机构信息

Edward P. Fitts Department of Industrial and Systems Engineering, North Carolina State UniversityRaleigh, NC, USA.

Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill and North Carolina State UniversityChapel Hill, NC, USA.

出版信息

Front Hum Neurosci. 2017 Apr 10;11:170. doi: 10.3389/fnhum.2017.00170. eCollection 2017.

Abstract

This review examined 83 articles using neuroimaging modalities to investigate the neural correlates underlying static and dynamic human balance control, with aims to support future mobile neuroimaging research in the balance control domain. Furthermore, this review analyzed the mobility of the neuroimaging hardware and research paradigms as well as the analytical methodology to identify and remove movement artifact in the acquired brain signal. We found that the majority of static balance control tasks utilized mechanical perturbations to invoke feet-in-place responses (27 out of 38 studies), while cognitive dual-task conditions were commonly used to challenge balance in dynamic balance control tasks (20 out of 32 studies). While frequency analysis and event related potential characteristics supported enhanced brain activation during static balance control, that in dynamic balance control studies was supported by spatial and frequency analysis. Twenty-three of the 50 studies utilizing EEG utilized independent component analysis to remove movement artifacts from the acquired brain signals. Lastly, only eight studies used truly mobile neuroimaging hardware systems. This review provides evidence to support an increase in brain activation in balance control tasks, regardless of mechanical, cognitive, or sensory challenges. Furthermore, the current body of literature demonstrates the use of advanced signal processing methodologies to analyze brain activity during movement. However, the static nature of neuroimaging hardware and conventional balance control paradigms prevent full mobility and limit our knowledge of neural mechanisms underlying balance control.

摘要

本综述研究了83篇使用神经成像模态来探究人类静态和动态平衡控制背后神经关联的文章,旨在支持未来在平衡控制领域的移动神经成像研究。此外,本综述分析了神经成像硬件和研究范式的可移动性以及用于识别和去除采集到的脑信号中运动伪影的分析方法。我们发现,大多数静态平衡控制任务利用机械扰动来引发原地脚部反应(38项研究中的27项),而认知双任务条件常用于动态平衡控制任务中挑战平衡(32项研究中的20项)。虽然频率分析和事件相关电位特征支持在静态平衡控制期间增强脑激活,但在动态平衡控制研究中,这是由空间和频率分析支持的。在利用脑电图的50项研究中,有23项使用独立成分分析从采集到的脑信号中去除运动伪影。最后,只有8项研究使用了真正的移动神经成像硬件系统。本综述提供了证据,支持在平衡控制任务中脑激活增加,无论机械、认知或感觉挑战如何。此外,当前的文献表明使用先进的信号处理方法来分析运动期间的脑活动。然而,神经成像硬件的静态性质和传统的平衡控制范式阻碍了完全的可移动性,并限制了我们对平衡控制背后神经机制的了解。

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