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Changes in brain functional network connectivity after stroke

Neural Regeneration Research 2014年第1期9卷 51-60页

作者： Wei Li Yapeng Li Wenzhen Zhu Xi Chen Key Laboratory of Image Processing and Intelligent Control Ministry of Education Department of Control Science and Engineering Huazhong University of Science and Technology Department of Radiology Tongji HospitalTongji Medical CollegeHuazhong University of Science and Technology

Studies have shown that functional network connection models can be used to study brain net- work 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 correlat- ed 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.

关键词： nerve regeneration brain injury stroke motor areas functional magnetic resonanceimaging brain network independent component analysis functional network connectivity neuralplasticity NSFC grant neural regeneration

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