Group information guided ICA for fMRI data analysis
文献类型：期刊论文
| 作者 | Du, Yuhui1,2; Fan, Yong1 |
| 刊名 | NEUROIMAGE
 |
| 出版日期 | 2013-04-01 |
| 卷号 | 69页码:157-197 |
| 关键词 | fMRI Independent component analysis Group information Enhanced independence Multi-objective optimization Subject specific ICs reconstruction |
| 英文摘要 | Group independent component analysis (ICA) has been widely applied to studies of multi-subject fMRI data for computing subject specific independent components with correspondence across subjects. However, the independence of subject specific independent components (ICs) derived from group ICA has not been explicitly optimized in existing group ICA methods. In order to preserve independence of ICs at the subject level and simultaneously establish correspondence of ICs across subjects, we present a new framework for obtaining subject specific ICs, which we coined group-information guided ICA (GIG-ICA). In this framework, group information captured by standard ICA on the group level is exploited as guidance to compute individual subject specific ICs using a multi-objective optimization strategy. Specifically, we propose a framework with two stages: at first, group ICs (GICs) are obtained using standard group ICA tools, and then the GICs are used as references in a new one-unit ICA with spatial reference (ICA-R) using a multi-objective optimization solver. Comparison experiments with back-reconstruction (GICA1 and GICA3) and dual regression on simulated and real fMRI data have demonstrated that GIG-ICA is able to obtain subject specific ICs with stronger independence and better spatial correspondence across different subjects in addition to higher spatial and temporal accuracy. (C) 2012 Elsevier Inc. All rights reserved. |
| WOS标题词 | Science & Technology ; Life Sciences & Biomedicine |
| 类目[WOS] | Neurosciences ; Neuroimaging ; Radiology, Nuclear Medicine & Medical Imaging |
| 研究领域[WOS] | Neurosciences & Neurology ; Radiology, Nuclear Medicine & Medical Imaging |
| 关键词[WOS] | INDEPENDENT COMPONENT ANALYSIS ; RESONANCE-IMAGING DATA ; FUNCTIONAL MRI DATA ; MULTIOBJECTIVE OPTIMIZATION ; BLIND SEPARATION ; CONSTRAINED ICA ; SPATIAL ICA ; CONNECTIVITY ; BRAIN ; ALGORITHMS |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000314627800017 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/3162]  |
| 专题 | 自动化研究所_脑网络组研究中心 |
| 作者单位 | 1.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100190, Peoples R China 2.N Univ China, Sch Informat & Commun Engn, Taiyuan 030051, Peoples R China |
| 推荐引用方式 GB/T 7714 | Du, Yuhui,Fan, Yong. Group information guided ICA for fMRI data analysis[J]. NEUROIMAGE,2013,69:157-197. |
| APA | Du, Yuhui,&Fan, Yong.(2013).Group information guided ICA for fMRI data analysis.NEUROIMAGE,69,157-197. |
| MLA | Du, Yuhui,et al."Group information guided ICA for fMRI data analysis".NEUROIMAGE 69(2013):157-197. |
入库方式： OAI收割
来源：自动化研究所
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