| Identifying intrinsic connectivity network pattern during propofol-induced loss of consciousness: a multivariate analysis | |
Li, Huandong1 ; Liu, Xiaoyuan2; Jie, Nanfeng1; Zhu, Maohu3; Jiang, Tianzi1
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| 2016 | |
| 会议名称 | IET International Conference on Biomedical Image and Signal Processing (ICBISP) |
| 会议录名称 | ICBISP conference proceedings |
| 会议日期 | 2015-11-19 |
| 会议地点 | 北京 |
| 会议主办者 | The Institution of Engineering and Technology (IET) |
| 摘要 | Despite the routine use of general anesthesia during surgery, no consensus has been reached on the precise mechanisms by which anesthetic agents suppress consciousness. Recent functional magnetic resonance imaging studies have shown that changes in connectivity is generally observed during propofol-induced loss of consciousness, especially in the fronto-parietal association cortex. Here, we developed a novel feature selection approach based on linear support vector machine with a forward-back search strategy to investigate the mostly discriminative connectivity patterns of different consciousness states. The classification accuracy between wakefulness and deep sedation was up to 96.4%. Weight analysis further revealed that consciousness could be linked to functional connectivity within and across the default mode network, executive control network, salience network and cerebellum. Moreover, the angular, supplementary motor cortex, inferior parietal, insula, and cerebellum exhibited significantly larger weight, suggesting important roles in consciousness. In all, our study sheds light on the mechanism of consciousness. |
| 其他摘要 | 无 |
| 关键词 | Propofol Functional Mri Svm-foba Feature Selection Consciousness |
| URL | 查看原文 |
| 收录类别 | EI |
| 语种 | 英语 |
| 文献类型 | 会议论文 |
| 条目标识符 | http://ir.ia.ac.cn/handle/173211/10557 |
| 专题 | 脑图谱与类脑智能实验室_脑网络组研究 |
| 通讯作者 | Li, Huandong |
| 作者单位 | 1.Brainnetome Center, Institute of Automation, Chinese Academy of Sciences 2.Capital University of Medical Sciences Affiliated Tiantan Hospital 3.Elementary Educational College, Jiangxi Normal University |
| 第一作者单位 | 中国科学院自动化研究所 |
| 通讯作者单位 | 中国科学院自动化研究所 |
| 推荐引用方式 GB/T 7714 | Li, Huandong,Liu, Xiaoyuan,Jie, Nanfeng,et al. Identifying intrinsic connectivity network pattern during propofol-induced loss of consciousness: a multivariate analysis[C],2016. |
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| 文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
| ICBISP15_0055_final.（407KB） | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 | ||
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