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Changes in brain functional network connectivity after stroke

机译:脑卒中后大脑功能网络连接的变化

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Studies have shown that functional network connection models can be used to study brain network changes in patients with schizophrenia. In this study, we inferred that these models could also be used to explore functional network connectivity changes in stroke patients. We used independent component analysis to find the motor areas of stroke patients, which is a novel way to determine these areas. In this study, we collected functional magnetic resonance imaging datasets from healthy controls and right-handed stroke patients following their first ever stroke. Using independent component analysis, six spatially independent components highly correlated to the experimental paradigm were extracted. Then, the functional network connectivity of both patients and controls was established to observe the differences between them. The results showed that there were 11 connections in the model in the stroke patients, while there were only four connections in the healthy controls. Further analysis found that some damaged connections may be compensated for by new indirect connections or circuits produced after stroke. These connections may have a direct correlation with the degree of stroke rehabilitation. Our findings suggest that functional network connectivity in stroke patients is more complex than that in hea-lthy controls, and that there is a compensation loop in the functional network following stroke. This implies that functional network reorganization plays a very important role in the process of rehabilitation after stroke.
机译:研究表明,功能性网络连接模型可用于研究精神分裂症患者的大脑网络变化。在这项研究中,我们推断这些模型也可以用于探讨中风患者的功能网络连通性变化。我们使用独立成分分析来查找中风患者的运动区域,这是确定这些区域的一种新颖方法。在这项研究中,我们收集了健康对照者和右手卒中患者首次卒中后的功能磁共振成像数据集。使用独立分量分析,提取了与实验范式高度相关的六个空间独立分量。然后,建立患者和对照组的功能网络连接以观察他们之间的差异。结果显示,中风患者模型中有11种关联,而健康对照组中只有4种关联。进一步的分析发现,某些损坏的连接可以通过新的间接连接或行程后产生的电路来补偿。这些联系可能与中风康复的程度直接相关。我们的研究结果表明,中风患者的功能网络连通性比健康对照者复杂,并且中风后功能网络中存在补偿回路。这意味着功能网络的重组在中风后的康复过程中起着非常重要的作用。

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