Multimodal neuromarkers in schizophrenia via cognition-guided MRI fusion
文献类型:期刊论文
作者 | Sui, Jing1,2,3,4,5; Qi, Shile1,2,4; van Erp, Theo G. M.6; Bustillo, Juan7; Jiang, Rongtao1,2,4; Lin, Dongdong3; Turner, Jessica A.3,8; Damaraju, Eswar3; Mayer, Andrew R.3,7; Cui, Yue1,2 |
刊名 | NATURE COMMUNICATIONS |
出版日期 | 2018-08-02 |
卷号 | 9期号:0页码:0 |
DOI | 10.1038/s41467-018-05432-w |
文献子类 | Article |
英文摘要 | Cognitive impairment is a feature of many psychiatric diseases, including schizophrenia. Here we aim to identify multimodal biomarkers for quantifying and predicting cognitive performance in individuals with schizophrenia and healthy controls. A supervised learning strategy is used to guide three-way multimodal magnetic resonance imaging (MRI) fusion in two independent cohorts including both healthy individuals and individuals with schizophrenia using multiple cognitive domain scores. Results highlight the salience network (gray matter, GM), corpus callosum (fractional anisotropy, FA), central executive and default-mode networks (fractional amplitude of low-frequency fluctuation, fALFF) as modality-specific biomarkers of generalized cognition. FALFF features are found to be more sensitive to cognitive domain differences, while the salience network in GM and corpus callosum in FA are highly consistent and predictive of multiple cognitive domains. These modality-specific brain regions define-in three separate cohorts-promising co-varying multimodal signatures that can be used as predictors of multi-domain cognition. |
WOS关键词 | White-matter Abnormalities ; Working-memory ; 1st-episode Schizophrenia ; Brain Networks ; Functional Connectome ; Connectivity Networks ; Negative Symptoms ; Deficits ; Individuals ; Biomarkers |
WOS研究方向 | Science & Technology - Other Topics |
语种 | 英语 |
WOS记录号 | WOS:000440617500004 |
资助机构 | Chinese National Natural Science Foundation(81471367 ; Chinese Academy of Sciences(XDB02060005) ; National High-Tech Development Plan (863 program)(2015AA020513) ; Chinese Academy of Sciences ; NIH(R01EB005846 ; NSF(1539067) ; 61773380 ; 1R01MH094524 ; 61703253) ; P20GM103472) |
源URL | [http://ir.ia.ac.cn/handle/173211/21851] |
专题 | 自动化研究所_脑网络组研究中心 |
作者单位 | 1.Chinese Acad Sci, Inst Automat, Brainnetome Ctr, Beijing 100190, Peoples R China 2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China 3.Mind Res Network, Albuquerque, NM 87106 USA 4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 5.Chinese Acad Sci, Inst Automat, CAS Ctr Excellence Brain Sci & Intelligence Techn, Beijing 100190, Peoples R China 6.Univ Calif Irvine, Dept Psychiat & Human Behav, Irvine, CA 92697 USA 7.Univ New Mexico, Dept Psychiat, Albuquerque, NM 87131 USA 8.Georgia State Univ, Dept Psychol & Neurosci, Atlanta, GA 30302 USA 9.Univ Calif San Francisco, Dept Psychiat, San Francisco, CA 94143 USA 10.San Francisco VA Med Ctr, San Francisco, CA 94143 USA |
推荐引用方式 GB/T 7714 | Sui, Jing,Qi, Shile,van Erp, Theo G. M.,et al. Multimodal neuromarkers in schizophrenia via cognition-guided MRI fusion[J]. NATURE COMMUNICATIONS,2018,9(0):0. |
APA | Sui, Jing.,Qi, Shile.,van Erp, Theo G. M..,Bustillo, Juan.,Jiang, Rongtao.,...&Calhoun, Vince D..(2018).Multimodal neuromarkers in schizophrenia via cognition-guided MRI fusion.NATURE COMMUNICATIONS,9(0),0. |
MLA | Sui, Jing,et al."Multimodal neuromarkers in schizophrenia via cognition-guided MRI fusion".NATURE COMMUNICATIONS 9.0(2018):0. |
入库方式: OAI收割
来源:自动化研究所
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