个人信息Personal Information
教授
博士生导师
硕士生导师
主要任职:信息与通信工程学院副院长
其他任职:电子技术教研室主任
性别:男
毕业院校:北京理工大学
学位:博士
所在单位:信息与通信工程学院
学科:通信与信息系统. 信号与信息处理
办公地点:海山楼B511
联系方式:QQ:51574683
电子邮箱:xfgong@dlut.edu.cn
Model order effects on ICA of resting-state complex-valued fMRI data: Application to schizophrenia.
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论文类型:期刊论文
第一作者:Kuang, Li-Dan
通讯作者:Lin, QH (reprint author), Dalian Univ Technol, Fac Elect Informat & Elect Engn, Sch Informat & Commun Engn, Dalian 116024, Peoples R China.
合写作者:Lin, Qiu-Hua,Gong, Xiao-Feng,Cong, Fengyu,Sui, Jing,Calhoun, Vince D.
发表时间:2018-01-01
发表刊物:Journal of neuroscience methods
收录刊物:PubMed、SCIE
卷号:304
页面范围:24-38
ISSN号:1872-678X
关键字:Independent component analysis (ICA); Complex-valued fMRI data; Model order; Component splitting; Phase data; Schizophrenia
摘要:BACKGROUND: Component splitting at higher model orders is a widely accepted finding for independent component analysis (ICA) of functional magnetic resonance imaging (fMRI) data. However, our recent study found that intact components occurred with subcomponents at higher model orders.; NEW METHOD: This study investigated model order effects on ICA of resting-state complex-valued fMRI data from 82 subjects, which included 40 healthy controls (HCs) and 42 schizophrenia patients. In addition, we explored underlying causes for distinct component splitting between complex-valued data and magnitude-only data by examining model order effects on ICA of phase fMRI data. A best run selection method was proposed to combine subject averaging and a one-sample t-test. We selected the default mode network (DMN)-, visual-, and sensorimotor-related components from the best run of ICA at varying model orders from 10 to 140.; RESULTS: Results show that component integration occurred in complex-valued and phase analyses, whereas component splitting emerged in magnitude-only analysis with increasing model order. Incorporation of phase data appears to play a complementary role in preserving integrity of brain networks.; COMPARISON WITH EXISTING METHOD(S): When compared with magnitude-only analysis, the intact DMN component obtained in complex-valued analysis at higher model orders exhibited highly significant subject-level differences between HCs and patients with schizophrenia. We detected significantly higher activity and variation in anterior areas for HCs and in posterior areas for patients with schizophrenia.; CONCLUSIONS: These results demonstrate the potential of complex-valued fMRI data to contribute generally and specifically to brain network analysis in identification of schizophrenia-related changes. Copyright © 2018 Elsevier B.V. All rights reserved.