CASIA OpenIR  > 脑网络组研究中心
Multimodal Fusion With Reference: Searching for Joint Neuromarkers of Working Memory Deficits in Schizophrenia.
Shile Qi1; Vince D. Calhoun2; Theo G. M. van Erp2; Juan Bustillo2; Eswar Damaraju2; Jessica A. Turner2; Yuhui Du2; Jiayu Chen2; Qingbao Yu2; Daniel H. Mathalon3; Judith M. Ford3; James Voyvodic4; Bryon A. Mueller4; Aysenil Belger5; Sarah Mc Ewen6; Steven G. Potkin7; Steven G. Potkin7; Tianzi Jiang1; Sui Jing(隋婧)1
2018
发表期刊IEEE Trans Med Imaging.
卷号37(1)期号:201801页码:93-105
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, goaldirected 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 neuromarkers for mental disorders.

关键词Multimodal Fusion With Reference Mccar Supervised Learning Schizophrenia Working Memory Ica Mccb Cminds
关键词[WOS]Multimodal fusion with reference, MCCAR, supervised learning, schizophrenia, working memory, ICA, MCCB, CMINDS.
收录类别SSCi
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/20285
专题脑网络组研究中心
通讯作者Sui Jing(隋婧)
作者单位1.中国科学院自动化研究所
2.the Mind Research Network
3.San Francisco VA Medical Center
4.Department of Radiology, Brain Imaging and Analysis Center, Duke University
5.Department of Psychiatry, University of Minnesota, Minneapolis
6.Department of Psychiatry, University of North Carolina School of Medicine,
7.Department of Psychiatry and Human Behavior, University of California at Irvine
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
Shile Qi,Vince D. Calhoun,Theo G. M. van Erp,et al. Multimodal Fusion With Reference: Searching for Joint Neuromarkers of Working Memory Deficits in Schizophrenia.[J]. IEEE Trans Med Imaging.,2018,37(1)(201801):93-105.
APA Shile Qi.,Vince D. Calhoun.,Theo G. M. van Erp.,Juan Bustillo.,Eswar Damaraju.,...&Sui Jing.(2018).Multimodal Fusion With Reference: Searching for Joint Neuromarkers of Working Memory Deficits in Schizophrenia..IEEE Trans Med Imaging.,37(1)(201801),93-105.
MLA Shile Qi,et al."Multimodal Fusion With Reference: Searching for Joint Neuromarkers of Working Memory Deficits in Schizophrenia.".IEEE Trans Med Imaging. 37(1).201801(2018):93-105.
条目包含的文件 下载所有文件
文件名称/大小 文献类型 版本类型 开放类型 使用许可
Multimodal Fusion wi(1484KB)期刊论文作者接受稿开放获取CC BY-NC-SA浏览 下载
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Shile Qi]的文章
[Vince D. Calhoun]的文章
[Theo G. M. van Erp]的文章
百度学术
百度学术中相似的文章
[Shile Qi]的文章
[Vince D. Calhoun]的文章
[Theo G. M. van Erp]的文章
必应学术
必应学术中相似的文章
[Shile Qi]的文章
[Vince D. Calhoun]的文章
[Theo G. M. van Erp]的文章
相关权益政策
暂无数据
收藏/分享
文件名: Multimodal Fusion with Reference.pdf
格式: Adobe PDF
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。