利用偏最小二乘相关性分析确定脑外伤平衡障碍的神经相关性。

Vikram Shenoy Handiru, Easter Selvan Suviseshamuthu, Soha Saleh, Haiyan Su, Guang Yue, Didier Allexandre
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摘要

背景:平衡障碍是创伤性脑损伤(TBI)造成的最严重后果之一。为了研究平衡障碍的神经生理学基础,扰动任务中的大脑功能连接可以提供新的见解。为了更好地描述与任务相关的功能连接与 TBI 平衡障碍程度之间的关联,需要根据平衡障碍对数据进行分层分析。然而,这种分层并不简单,需要采用数据驱动的方法:我们进行了一项研究,使用计算机化的体位测量平台评估 17 名创伤性脑损伤患者和 15 名年龄匹配的健康对照者的平衡控制能力。我们使用在平衡扰动任务中压力中心(COP)位移或伯格平衡量表(BBS)评分作为功能结果测量的 k-means 聚类,将 TBI 参与者分为平衡受损和非受损 TBI 患者。我们使用不同频段不同皮质区域的相干性虚部分析了大脑功能连通性。然后使用均值中心偏最小二乘相关分析(MC-PLSC)对这些连接特征进行研究,该分析是一个多变量统计框架,其优点是处理的特征数量多于样本数量,因此适用于小样本研究:基于使用permutation和bootstrap程序进行的非参数显著性检验,我们注意到,无论分层类型如何,以下相关区域的θ波段连接强度对区分平衡受损和非受损人群有显著作用:左额叶中回、右侧旁中央小叶、楔前区和双侧枕叶中回 意义:确定与平衡障碍有关的神经区域有助于加深我们对创伤性脑损伤相关平衡功能障碍的了解,并为新的治疗策略提供依据。未来的工作将探索平衡平台训练对感觉运动和视觉运动连接的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identifying neural correlates of balance impairment in traumatic brain injury using partial least squares correlation analysis.

Objective.Balance impairment is one of the most debilitating consequences of traumatic brain injury (TBI). To study the neurophysiological underpinnings of balance impairment, the brain functional connectivity during perturbation tasks can provide new insights. To better characterize the association between the task-relevant functional connectivity and the degree of balance deficits in TBI, the analysis needs to be performed on the data stratified based on the balance impairment. However, such stratification is not straightforward, and it warrants a data-driven approach.Approach.We conducted a study to assess the balance control using a computerized posturography platform in 17 individuals with TBI and 15 age-matched healthy controls. We stratified the TBI participants into balance-impaired and non-impaired TBI usingk-means clustering of either center of pressure (COP) displacement during a balance perturbation task or Berg Balance Scale score as a functional outcome measure. We analyzed brain functional connectivity using the imaginary part of coherence across different cortical regions in various frequency bands. These connectivity features are then studied using the mean-centered partial least squares correlation analysis, which is a multivariate statistical framework with the advantage of handling more features than the number of samples, thus making it suitable for a small-sample study.Main results.Based on the nonparametric significance testing using permutation and bootstrap procedure, we noticed that the weakened theta-band connectivity strength in the following regions of interest significantly contributed to distinguishing balance impaired from non-impaired population, regardless of the type of stratification:left middle frontal gyrus, right paracentral lobule, precuneus, andbilateral middle occipital gyri. Significance.Identifying neural regions linked to balance impairment enhances our understanding of TBI-related balance dysfunction and could inform new treatment strategies. Future work will explore the impact of balance platform training on sensorimotor and visuomotor connectivity.

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