Neural specificity of acupuncture stimulation from support vector machine classification analysis
文献类型：期刊论文
| 作者 | Xue, Ting2; Bai, Lijun1; Chen, Shangjie3; Zhong, Chongguang1; Feng, Yuanyuan1; Wang, Hu1; Liu, Zhenyu1 ; You, Youbo1; Cui, Fangyuan4; Ren, Yanshuang5
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| 刊名 | MAGNETIC RESONANCE IMAGING
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| 出版日期 | 2011-09-01 |
| 卷号 | 29期号:7页码:943-950 |
| 关键词 | Acupuncture specificity Functional magnetic resonance imaging (fMRI) Support vector machine analysis (SVM) |
| 英文摘要 | Acupoint specificity, as a crucial issue in acupuncture neuroimaging studies, is still a controversial topic. Previous studies have generally adopted a block-based general linear model (GLM) approach, which predicts the temporal changes in the blood oxygenation level-dependent signal conforming to the "on-off" specifications. However, this method might become impractical since the precise timing and duration of acupuncture actions cannot be specified a priori. In the current study, we applied a data-driven multivariate classification approach, namely, support vector machine (SVM), to explore the neural specificity of acupuncture at gall bladder 40 (GB40) using kidney 3 (KI3) as a control condition (belonging to different meridians but the same nerve segment). In addition, to verify whether the typical GLM approach is sensitive enough in exploring the neural response patterns evoked by acupuncture, we also employed the GLM method to the same data sets. The SVM analysis detected distinct neural response patterns between GB40 and KI3 - positive predominantly for the GB40, while negative following the KI3. By contrast, group analysis from the GLM showed that acupuncture at these different acupoints can both evoke similar widespread signal decreases in multiple brain regions, and most of these regions were spatially overlapped, mainly distributing in the limbic and subcortical structures. Our findings may provide additional evidence to support the specificity of acupuncture, relevant to its clinical efficacy. Moreover, we also proved that GLM analysis is prone to be susceptible to errors and is not appropriate for detecting neural response patterns evoked by acupuncture stimulation. Crown Copyright (C) 2011 Published by Elsevier Inc. All rights reserved. |
| WOS标题词 | Science & Technology ; Life Sciences & Biomedicine |
| 类目[WOS] | Radiology, Nuclear Medicine & Medical Imaging |
| 研究领域[WOS] | Radiology, Nuclear Medicine & Medical Imaging |
| 关键词[WOS] | HUMAN BRAIN ; FMRI ; PAIN ; MODULATION |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000294314200007 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/3961]  |
| 专题 | 自动化研究所_中国科学院分子影像重点实验室 |
| 作者单位 | 1.Chinese Acad Sci, Inst Automat, Med Image Proc Grp, Beijing 100190, Peoples R China 2.Xidian Univ, Life Sci Res Ctr, Sch Life Sci & Technol, Xian 710071, Peoples R China 3.So Med Univ, Baoan Hosp, Shenzhen 518101, Peoples R China 4.Beijing Univ Chinese Med, Dept Neurol, Dongzhimen Hosp Affiliated, Beijing 100700, Peoples R China 5.Guanganmen Hosp, Chinese Acad Tradit, Dept Radiol, Beijing 100053, Peoples R China 6.Univ Florida, McKnight Brain Inst, Dept Psychiat & Neurosci, Gainesville, FL 32611 USA |
| 推荐引用方式 GB/T 7714 | Xue, Ting,Bai, Lijun,Chen, Shangjie,et al. Neural specificity of acupuncture stimulation from support vector machine classification analysis[J]. MAGNETIC RESONANCE IMAGING,2011,29(7):943-950. |
| APA | Xue, Ting.,Bai, Lijun.,Chen, Shangjie.,Zhong, Chongguang.,Feng, Yuanyuan.,...&Liu, Yijun.(2011).Neural specificity of acupuncture stimulation from support vector machine classification analysis.MAGNETIC RESONANCE IMAGING,29(7),943-950. |
| MLA | Xue, Ting,et al."Neural specificity of acupuncture stimulation from support vector machine classification analysis".MAGNETIC RESONANCE IMAGING 29.7(2011):943-950. |
入库方式： OAI收割
来源：自动化研究所
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