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Identifying intrinsic connectivity network pattern during propofol-induced loss of consciousness: a multivariate analysis
Li, Huandong1; Liu, Xiaoyuan2; Jie, Nanfeng1; Zhu, Maohu3; Jiang, Tianzi1
2016
Conference NameIET International Conference on Biomedical Image and Signal Processing (ICBISP)
Source PublicationICBISP conference proceedings
Conference Date2015-11-19
Conference Place北京
Funding OrganizationThe Institution of Engineering and Technology (IET)
AbstractDespite 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.
Other Abstract
KeywordPropofol Functional Mri Svm-foba Feature Selection Consciousness
URL查看原文
Indexed ByEI
Language英语
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/10557
Collection脑网络组研究中心
Corresponding AuthorLi, Huandong
Affiliation1.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
Recommended Citation
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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