《中国康复理论与实践》

《中国康复理论与实践》 ›› 2007, Vol. 13 ›› Issue (10): 957-959.

• 中医康复 • 上一篇    下一篇

采用独立分量分析观察经皮穴位电针刺激对脑功能的影响(英文)

魏鹏绪; 卢虎英; 徐基民   

  1. 中国康复研究中心北京博爱医院中医康复科, 首都医科大学康复医学院,北京市 100068,中国
  • 收稿日期:2007-05-08 出版日期:2007-10-01 发布日期:2007-10-01

Effects of Transcutaneous Electrical Acupoint Sti mulation on Brain Function Explored with Independent Component Analysis

WEI Peng-xu, LUHu-ying, XUJi-min   

  1. Chinese Rehabilitation Medicine Department, China Rehabilitation Research Center, Capital Medical University School of Rehabilitation Medicine, Beijing 100068, China.
  • Received:2007-05-08 Published:2007-10-01 Online:2007-10-01

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摘要： 目的使用独立分量分析方法探索督脉穴位经皮电刺激对脑功能的影响。方法使用1.5T GE Signa Excite核磁成像仪对一位女性脑外伤患者进行BOLD成像。采用组块设计,静息期与刺激期交替,组块长度均为30 s。数据处理采用GIFT、SPM5和MRIcro软件进行,并将独立分量分析与SPM软件处理的结果进行比较。结果采用GIFT中的扩展Infomax算法进行独立分量分析,显示有13个独立成分,每一独立成分包含一空间图和相应的时间变化曲线。任务相关性独立成分的空间激活图与SPM5的分析结果类似,但并不完全相同。此外,这些任务相关性独立成分的时间曲线与SPM所用的经典血流动力相应函数模型的形状并不一致。结论在使用模型依赖的数据分析方法如SPM之前,可以使用独立分量分析探索fMRI数据并获得先验知识。

关键词: 独立分量分析, 经皮穴位电刺激, 功能性磁共振, 统计参数图软件

Abstract: ObjectiveTo explore fMRI data with independent component analysis (ICA) in order toinvestigate effects of transcu-taneous electrical acupoint sti mulation (TEAS) on brain function.MethodsThe experi ment was performed on a whole-body 1 .5 TGE Signa Excite MRI scanner with which the brain oxygenation level dependent (BOLD)/EPI i mages were acquired froma femaletraumatic braininjury patient . A block designed protocol was used . Both durations of rest and TEAS were 30 seconds . The dataprocessing was performed with GIFT,Statistical Parametric Mapping 5 (SPM5) and MRIcro .Results fromICAand SPMwere com-pared .Results Extended Infomax algorithmprovided by GIFT found thirteen independent components (ICs) ,each of which containeda spatial map and a corresponding ti me course . The spatial maps associated with task-related ICs resembled the activation maps from SPM5 but were not totally identical .In addition,the ti me courses of these ICs differed from the shape of canonical HRF model usedby SPM.Conclusion ICA is a good choice to investigate data and obtain prior knowledge before using model-based methods such as SPM.

Key words: independent component analysis (ICA), transcutaneous electrical acupoint stimulation (TEAS), functional magnetic resonance imaging (fMRI), statistical parametric mapping (SPM)