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Multimodal Fusion With Reference: Searching for Joint Neuromarkers of Working Memory Deficits in Schizophrenia
Qi, Shile1,2,3,4; Calhoun, Vince D.5,6; van Erp, Theo G. M.7; Bustillo, Juan8; Damaraju, Eswar5; Turner, Jessica A.5; Du, Yuhui5; Yang, Jian9; Chen, Jiayu5; Yu, Qingbao5; Mathalon, Daniel H.10,11; Ford, Judith M.10,11; Voyvodic, James12; Mueller, Bryon A.13; Belger, Aysenil14; McEwen, Sarah15; Potkin, Steven G.7; Preda, Adrian7; Jiang, Tianzi1,2,3,4; Sui, Jing1,2,3,4,5
2018
发表期刊IEEE TRANSACTIONS ON MEDICAL IMAGING
卷号37期号:1页码:93-105
文章类型Article
摘要By exploiting cross-information among multiple imaging data, multimodal fusion has often been used to better understand brain diseases. However, most current fusion approaches are blind, without adopting any prior information. There is increasing interest to uncover the neurocognitive mapping of specific clinical measurements on enriched brain imaging data; hence, a supervised, goal-directed model that employs prior information as a reference to guide multimodal data fusion is much needed and becomes a natural option. Here, we proposed a fusion with reference model called "multi-site canonical correlation analysis with reference + joint-independent component analysis" (MCCAR+jICA), which can precisely identify co-varying multimodal imaging patterns closely related to the reference, such as cognitive scores. In a three-way fusion simulation, the proposed method was compared with its alternatives on multiple facets; MCCAR+jICA outperforms others with higher estimation precision and high accuracy on identifying a target component with the right correspondence. In human imaging data, working memory performance was utilized as a reference to investigate the co-varying working memory-associated brain patterns among three modalities and how they are impaired in schizophrenia. Two independent cohorts (294 and 83 subjects respectively) were used. Similar brain maps were identified between the two cohorts along with substantial overlaps in the central executive network in fMRI, salience network in sMRI, and major white matter tracts in dMRI. These regions have been linked with working memory deficits in schizophrenia in multiple reports and MCCAR+jICA further verified them in a repeatable, joint manner, demonstrating the ability of the proposed method to identify potential neuromarkersfor mental disorders.
关键词Multimodal Fusion With Reference Mccar Supervised Learning Schizophrenia Working Memory Ica Mccb Cminds
WOS标题词Science & Technology ; Technology ; Life Sciences & Biomedicine
DOI10.1109/TMI.2017.2725306
关键词[WOS]GRAY-MATTER ABNORMALITIES ; BLIND SOURCE SEPARATION ; RESTING-STATE FMRI ; BRAIN IMAGING DATA ; 1ST-EPISODE SCHIZOPHRENIA ; CONNECTIVITY NETWORKS ; EXECUTIVE CONTROL ; TREATMENT-NAIVE ; METAANALYSIS ; ACTIVATION
收录类别SCI ; SSCI
语种英语
项目资助者National High-Tech Development Plan (863 plan)(2015AA020513) ; Chinese National Science Foundation(81471367) ; Strategic Priority Research Program of the Chinese Academy of Sciences (CAS)(XDB02060005) ; 100 Talents Plan of CAS ; NIH(P20GM103472 ; R01EB005846 ; 1R01EB006841)
WOS研究方向Computer Science ; Engineering ; Imaging Science & Photographic Technology ; Radiology, Nuclear Medicine & Medical Imaging
WOS类目Computer Science, Interdisciplinary Applications ; Engineering, Biomedical ; Engineering, Electrical & Electronic ; Imaging Science & Photographic Technology ; Radiology, Nuclear Medicine & Medical Imaging
WOS记录号WOS:000419346900009
引用统计
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/20801
专题脑网络组研究中心
作者单位1.Chinese Acad Sci, Brainnetome Ctr, Inst Automat, Beijing 100190, Peoples R China
2.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100190, Peoples R China
3.Univ Chinese Acad Sci, Beijing 100190, Peoples R China
4.CAS Ctr Excellence Brain Sci & Intelligence Techno, Beijing 100190, Peoples R China
5.Mind Res Network LBERI, Albuquerque, NM 87106 USA
6.Univ New Mexico, Dept ECE, Albuquerque, NM 87106 USA
7.Univ Calif Irvine, Dept Psychiat & Human Behav, Irvine, CA 92697 USA
8.Univ New Mexico, Dept Psychiat, Albuquerque, NM 87131 USA
9.Beijing Inst Technol, Sch Opt & Elect, Beijing Engn Res Ctr Mixed Real & Adv Display, Beijing 100081, Peoples R China
10.san Francisco VA Med Ctr, San Francisco, CA 94143 USA
11.Univ Calif San Francisco, Dept Psychiat, San Francisco, CA 94143 USA
12.Duke Univ, Brain Imaging & Anal Ctr, Dept Radiol, Durham, NC 27710 USA
13.Univ Minnesota, Dept Psychiat, Minneapolis, MN 55454 USA
14.Univ N Carolina, Dept Psychiat, Sch Med, Chapel Hill, NC 27599 USA
15.Univ Calif Los Angeles, Dept Psychiat & Biobehav Sci, Los Angeles, CA 90095 USA
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Qi, Shile,Calhoun, Vince D.,van Erp, Theo G. M.,et al. Multimodal Fusion With Reference: Searching for Joint Neuromarkers of Working Memory Deficits in Schizophrenia[J]. IEEE TRANSACTIONS ON MEDICAL IMAGING,2018,37(1):93-105.
APA Qi, Shile.,Calhoun, Vince D..,van Erp, Theo G. M..,Bustillo, Juan.,Damaraju, Eswar.,...&Sui, Jing.(2018).Multimodal Fusion With Reference: Searching for Joint Neuromarkers of Working Memory Deficits in Schizophrenia.IEEE TRANSACTIONS ON MEDICAL IMAGING,37(1),93-105.
MLA Qi, Shile,et al."Multimodal Fusion With Reference: Searching for Joint Neuromarkers of Working Memory Deficits in Schizophrenia".IEEE TRANSACTIONS ON MEDICAL IMAGING 37.1(2018):93-105.
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