4.5 Review

Neuroimaging of Human Balance Control: A Systematic Review

期刊

FRONTIERS IN HUMAN NEUROSCIENCE
卷 11, 期 -, 页码 -

出版社

FRONTIERS MEDIA SA
DOI: 10.3389/fnhum.2017.00170

关键词

static and dynamic balance control; temporal and spatial dynamics of brain activation; mechanical perturbation; sensory degradation; susceptibility to cognitive dual tasks; movement artifacts

资金

  1. National Science Foundation (NSF) [IIS-1421948, BCS-1551688]
  2. University of Carolina at Chapel Hill
  3. National Institutes of Health (NIH) [UL1TR001111]
  4. University of Carolina at North Carolina State Rehabilitation Engineering Core (REC)
  5. Direct For Computer & Info Scie & Enginr
  6. Div Of Information & Intelligent Systems [1421948] Funding Source: National Science Foundation

向作者/读者索取更多资源

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.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.5
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据