Meta-Modal Information Flow: A Method for Capturing Multimodal Modular Disconnectivity in Schizophrenia
文献类型：期刊论文
| 作者 | Falakshahi, Haleh1,2; Vergara, Victor M.1; Liu, Jingyu1,10 ; Mathalon, Daniel H.9; Ford, Judith M.9; Voyvodic, James8; Mueller, Bryon A.7; Belger, Aysenil6; McEwen, Sarah9; Potkin, Steven G.
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| 刊名 | IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
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| 出版日期 | 2020-09-01 |
| 卷号 | 67期号:9页码:2572-2584 |
| ISSN号 | 0018-9294 |
| 关键词 | Functional magnetic resonance imaging Diseases Graphical models Psychiatry Correlation Translational research Connectivity covariance matrix data fusion default mode network dMRI fMRI GGM graphical model joint estimation partial correlation precision matrix sMRI |
| DOI | 10.1109/TBME.2020.2964724 |
| 通讯作者 | Falakshahi, Haleh(hfalakshahi@gatech.edu) |
| 英文摘要 | Objective: Multimodal measurements of the same phenomena provide complementary information and highlight different perspectives, albeit each with their own limitations. A focus on a single modality may lead to incorrect inferences, which is especially important when a studied phenomenon is a disease. In this paper, we introduce a method that takes advantage of multimodal data in addressing the hypotheses of disconnectivity and dysfunction within schizophrenia (SZ). Methods: We start with estimating and visualizing links within and among extracted multimodal data features using a Gaussian graphical model (GGM). We then propose a modularity-based method that can be applied to the GGM to identify links that are associated with mental illness across a multimodal data set. Through simulation and real data, we show our approach reveals important information about disease-related network disruptions that are missed with a focus on a single modality. We use functional MRI (fMRI), diffusion MRI (dMRI), and structural MRI (sMRI) to compute the fractional amplitude of low frequency fluctuations (fALFF), fractional anisotropy (FA), and gray matter (GM) concentration maps. These three modalities are analyzed using our modularity method. Results: Our results show missing links that are only captured by the cross-modal information that may play an important role in disconnectivity between the components. Conclusion: We identified multimodal (fALFF, FA and GM) disconnectivity in the default mode network area in patients with SZ, which would not have been detectable in a single modality. Significance: The proposed approach provides an important new tool for capturing information that is distributed among multiple imaging modalities. |
| WOS关键词 | INDEPENDENT COMPONENT ANALYSIS ; WHITE-MATTER ABNORMALITIES ; DEFAULT MODE ; CONNECTIVITY ANALYSIS ; COGNITIVE DYSMETRIA ; NETWORK ; FMRI ; DYSFUNCTION ; DISORDER ; REVEALS |
| 资助项目 | NIH[R01EB020407] ; NIH[R01EB006841] ; NIH[P20GM103472] ; NIH[P30GM122734] ; NSF[1539067] |
| WOS研究方向 | Engineering |
| 语种 | 英语 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| WOS记录号 | WOS:000562053800017 |
| 资助机构 | NIH ; NSF |
| 源URL | [http://ir.ia.ac.cn/handle/173211/40553]  |
| 专题 | 自动化研究所_脑网络组研究中心 |
| 通讯作者 | Falakshahi, Haleh |
| 作者单位 | 1.Triinst Ctr Translat Res Neuroimaging & Data Sci, Atlanta, GA 30300 USA 2.Georgia Inst Technol, Dept Elect & Comp Engn, Atlanta, GA 30322 USA 3.Emory Univ, Atlanta, GA 30322 USA 4.Georgia State Univ, Dept Psychol, Univ Plaza, Atlanta, GA 30303 USA 5.Univ Chinese Acad Sci, Chinese Acad Sci, Inst Automat, Beijing, Peoples R China 6.Univ N Carolina, Dept Psychiat, Sch Med, Chapel Hill, NC 27515 USA 7.Univ Minnesota, Dept Psychiat, Minneapolis, MN 55455 USA 8.Duke Univ, Dept Radiol, Durham, NC 27706 USA 9.Univ Calif, Dept Psychiat, Davis, CA USA 10.Georgia State Univ, Dept Comp Sci, Atlanta, GA 30303 USA |
| 推荐引用方式 GB/T 7714 | Falakshahi, Haleh,Vergara, Victor M.,Liu, Jingyu,et al. Meta-Modal Information Flow: A Method for Capturing Multimodal Modular Disconnectivity in Schizophrenia[J]. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING,2020,67(9):2572-2584. |
| APA | Falakshahi, Haleh.,Vergara, Victor M..,Liu, Jingyu.,Mathalon, Daniel H..,Ford, Judith M..,...&Calhoun, Vince D..(2020).Meta-Modal Information Flow: A Method for Capturing Multimodal Modular Disconnectivity in Schizophrenia.IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING,67(9),2572-2584. |
| MLA | Falakshahi, Haleh,et al."Meta-Modal Information Flow: A Method for Capturing Multimodal Modular Disconnectivity in Schizophrenia".IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING 67.9(2020):2572-2584. |
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