通过特定动作的大脑连接模式增强运动意象的神经表征。

IF 5.2 2区 医学 Q2 ENGINEERING, BIOMEDICAL
Guangying Wang;Lin Jiang;Xipeng Song;Yulin Zhang;Dezhong Yao;Jing Lu;Peng Xu;Fali Li;Yi Liang
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引用次数: 0

摘要

运动意象(MI)是一种认知过程,它允许个体在没有身体执行的情况下在心理上模拟运动。然而,对不同MI行为下功能连接(FC)和侧化机制的探索仍然不够充分。在这项工作中,采用公共正交基提取(COBE)算法,通过从MI过程的原始FC中去除共享背景组件来分离特定于动作的组件。我们证明,行动特异性FC有效地捕获了左右脑MI之间的半球统计差异,优于传统的FC和时间变异性测量。通过对三个不同层次的网络特性的综合分析,包括全脑网络特性、半脑网络特性和单个节点强度,成功地识别了与不同类型MI过程相关的复杂侧化模式。进一步计算脑侧化指数,定量反映脑侧化程度。值得注意的是,来自动作特异性FC的侧化表现(LP)显示出对心肌梗死表现的显著预测能力,从而表明其评估个体心肌梗死能力的潜力。总的来说,这些发现验证了动作特异性FC模式表征MI过程的神经机制,并表明LP可能是预测基于MI的脑机推理(BCI)的MI表现的有用工具,从而从新的角度为临床康复的个性化治疗策略的制定做出贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhancing Neural Representations of Motor Imagery Through Action-Specific Brain Connectivity Patterns
Motor imagery (MI) is a cognitive process that allows individuals to mentally simulate movements without physical executio n. However, the exploration of functional connectivity (FC) and lateralization mechanisms under different MI actions remains insufficiently understood. In this work, the common orthogonal basis extraction (COBE) algorithm was employed to isolate action-specific components by removing shared background components from the raw FC of the MI process. We demonstrate that action-specific FC effectively captures the hemispheric statistical differences between left- and right-hand MI, outperforming traditional FC and temporal variability measures. And through a comprehensive analysis of network properties at three distinct levels, encompassing the whole-brain network properties, hemispherical properties, and individual nodal strength, complex lateralization patterns associated with diverse types of MI processes were successfully discerned. Furthermore, lateralization indices were further calculated to quantitatively reveal the degree of brain lateralization. Notably, the lateralization performance (LP) derived from action-specific FC exhibited a significant predictive capacity for MI performance, thereby suggesting its potential to evaluate individual MI capability. Collectively, these findings validate the action-specific FC patterns in characterizing neural mechanisms of MI processes and indicate that the LP could potentially be a useful tool to predict the MI performance of MI-based brain-computer inference (BCI), thereby contributing to the formulation of personalized therapeutic strategies for clinical rehabilitation from a new perspective.
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来源期刊
CiteScore
8.60
自引率
8.20%
发文量
479
审稿时长
6-12 weeks
期刊介绍: Rehabilitative and neural aspects of biomedical engineering, including functional electrical stimulation, acoustic dynamics, human performance measurement and analysis, nerve stimulation, electromyography, motor control and stimulation; and hardware and software applications for rehabilitation engineering and assistive devices.
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