Stroke is a leading cause of motor disability worldwide, and robot-assisted therapies have been increasingly applied to facilitate the recovery process. However, the underlying mechanism and induced neuroplasticity change remain partially understood, and few studies have investigated this from a multimodality neuroimaging perspective. The current study adopted BCI-guided robot hand therapy as the training intervention and combined multiple neuroimaging modalities to comprehensively understand the potential association between motor function alteration and various neural correlates. We adopted EEG-informed fMRI technique to understand the functional regions sensitive to training intervention. Additionally, correlation analysis among training effects, nonlinear property change quantified by fractal dimension (FD), and integrity of M1-M1 (M1: primary motor cortex) anatomical connection were performed. EEG-informed fMRI analysis indicated that for iM1 (iM1: ipsilesional M1) regressors, regions with significantly increased partial correlation were mainly located in contralesional parietal, prefrontal, and sensorimotor areas and regions with significantly decreased partial correlation were mainly observed in the ipsilesional supramarginal gyrus and superior temporal gyrus. Pearson’s correlations revealed that the interhemispheric asymmetry change significantly correlated with the training effect as well as the integrity of M1-M1 anatomical connection. In summary, our study suggested that multiple functional brain regions not limited to motor areas were involved during the recovery process from multimodality perspective. The correlation analyses suggested the essential role of interhemispheric interaction in motor rehabilitation. Besides, the underlying structural substrate of the bilateral M1-M1 connection might relate to the interhemispheric change. This study might give some insights in understanding the neuroplasticity induced by the integrated BCI-guided robot hand training intervention and further facilitate the design of therapies for chronic stroke patients.

中文翻译：

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慢性中风机器人辅助训练后运动恢复的神经相关性：一项多模式神经影像学研究

中风是全球运动障碍的主要原因，机器人辅助疗法已越来越多地应用于促进康复过程。然而，潜在的机制和诱导的神经可塑性变化仍然部分理解，很少有研究从多模态神经影像学的角度对此进行研究。目前的研究采用 BCI 引导的机器人手部治疗作为训练干预，并结合多种神经影像学方式，全面了解运动功能改变与各种神经相关因素之间的潜在关联。我们采用基于脑电图的 fMRI 技术来了解对训练干预敏感的功能区域。此外，训练效果、分形维数 (FD) 量化的非线性属性变化和 M1-M1 (M1: 进行了初级运动皮层）的解剖连接。EEG-informed fMRI 分析表明，对于 iM1（iM1：同侧 M1）回归器，偏相关显着增加的区域主要位于对侧顶叶、前额叶和感觉运动区域，偏相关显着降低的区域主要位于同侧缘上回。和颞上回。Pearson 的相关性表明，大脑半球间不对称变化与训练效果以及 M1-M1 解剖连接的完整性显着相关。总之，我们的研究表明，从多模态的角度来看，在恢复过程中涉及的多个功能性大脑区域不仅限于运动区域。相关性分析表明大脑半球间相互作用在运动康复中的重要作用。此外，双边 M1-M1 连接的底层结构可能与大脑半球间的变化有关。这项研究可能会为理解由集成 BCI 引导的机器人手部训练干预引起的神经可塑性提供一些见解，并进一步促进慢性中风患者的治疗设计。