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吴 杰,赵智勇,唐朝正,宫家玉,王鹤玮,孙莉敏,贾 杰,范明霞.基于独立成分分析的脑卒中感觉运动网络功能连接异常的研究[J].中国康复医学杂志,2017,(6):607~612
基于独立成分分析的脑卒中感觉运动网络功能连接异常的研究    点此下载全文
吴 杰  赵智勇  唐朝正  宫家玉  王鹤玮  孙莉敏  贾 杰  范明霞
华东师范大学物理与材料科学学院 上海市磁共振重点实验室,上海,200062
基金项目:国家自然科学基金面上项目(81471651);国家自然科学基金青年项目(81401859);国家科技部“十二五”支撑计划项目(2013BAI10B03);上海市卫生和计划生育委员会项目(201440634);上海市闸北区卫生局项目(面上2014MS06)资助
DOI:
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摘要:
      摘要 目的:运用独立成分分析(independent component analysis, ICA)探讨脑卒中偏瘫患者感觉运动网络功能连接变化。 方法:收集33例慢性期左侧皮质下脑卒中患者和34例年龄、性别相匹配的健康志愿者的静息态功能磁共振成像(resting-state functional magnetic resonance imaging, rs-fMRI)数据,采用组ICA方法提取出健康对照组与脑卒中患者组的感觉运动网络,并运用双样本t检验(P<0.05,AlphaSim校正)比较其组间差异。 结果:与健康对照组相比,ICA提取出的感觉运动网络(包括背侧、腹侧、左侧和右侧感觉运动网络)在患者组均显示其内功能连接明显下降,具体涉及脑区有:背侧感觉运动网络内的左侧中央前回和右侧中央后回,腹侧感觉运动网络内的左侧中央后回,左侧感觉运动网络内的左侧辅助运动皮质和右侧中央后回,右侧感觉运动网络内的左侧中央前后回。 结论:脑卒中偏瘫患者涉及全身感觉运动功能连接网络损伤,ICA为更加全面了解感觉运动功能损伤机制提供了一种新的有效途径。
关键词:静息态  磁共振成像  卒中  独立成分分析  感觉运动网络
A resting-state fMRI study of sensorimotor network in stroke based on independent component analysis    Download Fulltext
Shanghai Key Laboratory of Magnetic Resonance, East China Normal University,Shanghai,200062
Fund Project:
Abstract:
      Abstract Objective:To investigate the abnormal functional connectivity of sensorimotor network in stroke hemiplegia by using independent component analysis (ICA). Method:Thirty-three chronic stroke patients with left subcortical lesions and thirty-four age- and sex- matched healthy subjects were performed resting-state fMRI examination. Sensorimotor network were identified by conducting a group ICA and compared between the two groups by using two sample t-test(P<0.05,AlphaSim corrected). Result: Four sensorimotor networks demonstrated significantly reduced functional connectivity in stroke patients compared with healthy controls. Specifically, stroke patients showed decreased functional connectivity in the left precentral gyrus and right postcentral gyrus within dorsal sensorimotor network, in the left postcentral gyrus within ventral sensorimotor network, in the left supplementary motor network and right postcentral gyrus within left sensorimotor network, in the left precentral and postcentral gyrus within right sensorimotor network. Conclusion: The stroke hemiplegia displayed multiple sensorimotor networks impairments, and ICA approach can provide new insights in comprehensively understanding the mechanism of stroke motor deficits.
Keywords:resting-state  magnetic resonance imaging  stroke  independent component analysis  sensorimotor network
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