| Discriminating Bipolar Disorder From Major Depression Based on SVM-FoBa: Efficient Feature Selection With Multimodal Brain Imaging Data | |
Jie, Nan-Feng1,2 ; Zhu, Mao-Hu3; Ma, Xiao-Ying5; Osuch, Elizabeth A.4; Wammes, Michael4; Theberge, Jean4; Li, Huan-Dong1,2; Zhang, Yu1,2; Jiang, Tian-Zi1,2; Sui, Jing1,2,6; Calhoun, Vince D.7,8
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| 发表期刊 | IEEE TRANSACTIONS ON AUTONOMOUS MENTAL DEVELOPMENT
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| 2015-12-01 | |
| 卷号 | 7期号:4页码:320-331 |
| 文章类型 | Article |
| 摘要 | Discriminating between bipolar disorder (BD) and major depressive disorder (MDD) is a major clinical challenge due to the absence of known biomarkers; hence a better understanding of their pathophysiology and brain alterations is urgently needed. Given the complexity, feature selection is especially important in neuroimaging applications, however, feature dimension and model understanding present serious challenges. In this study, a novel feature selection approach based on linear support vector machine with a forward-backward search strategy (SVM-FoBa) was developed and applied to structural and resting-state functional magnetic resonance imaging data collected from 21 BD, 25 MDD and 23 healthy controls. Discriminative features were drawn from both data modalities, with which the classification of BD and MDD achieved an accuracy of 92.1% (1000 bootstrap resamples). Weight analysis of the selected features further revealed that the inferior frontal gyrus may characterize a central role in BD-MDD differentiation, in addition to the default mode network and the cerebellum. A modality-wise comparison also suggested that functional information outweighs anatomical by a large margin when classifying the two clinical disorders. This work validated the advantages of multimodal joint analysis and the effectiveness of SVM-FoBa, which has potential for use in identifying possible biomarkers for several mental disorders. |
| 关键词 | Bipolar Disorder Classification Feature Selection Major Depression Multimodal Fusion |
| WOS标题词 | Science & Technology ; Technology ; Life Sciences & Biomedicine |
| DOI | 10.1109/TAMD.2015.2440298 |
| 关键词[WOS] | SUPPORT VECTOR MACHINES ; 1ST EPISODE SCHIZOPHRENIA ; VOXEL-BASED MORPHOMETRY ; UNIPOLAR DEPRESSION ; GRAY-MATTER ; FUNCTIONAL CONNECTIVITY ; PATTERN-ANALYSIS ; MOOD DISORDERS ; FRONTAL-LOBE ; MRI ANALYSIS |
| 收录类别 | SCI ; SSCI |
| 语种 | 英语 |
| 项目资助者 | National High-Tech Development Plan (863)(2015AA020513) ; "100 Talents Plan" of the Chinese Academy of Sciences (CAS) ; Strategic Priority Research Program of the CAS(XDB02060005) ; Chinese National Science Foundation(81471367) ; Ph.D. Research Startup Foundation of Jiangxi Normal University(6247) ; Lawson Health Research Institute(LHR D1374) ; Pfizer Independent Investigator Award(WS2249136) ; Strategic Priority Research Program of the Chinese Academy of Sciences(XDB02060005 ; National Key Basic Research and Development Program (973)(2011CB707800) ; National Institutes of Health(R01EB006841 ; XDB02030300) ; R01EB005846 ; P20GM103472) |
| WOS研究方向 | Computer Science ; Robotics ; Neurosciences & Neurology |
| WOS类目 | Computer Science, Artificial Intelligence ; Robotics ; Neurosciences |
| WOS记录号 | WOS:000366614800006 |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.ia.ac.cn/handle/173211/10558 |
| 专题 | 脑图谱与类脑智能实验室_脑网络组研究 |
| 作者单位 | 1.Chinese Acad Sci, Brainnetome Ctr, Beijing 100083, Peoples R China 2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100083, Peoples R China 3.Jiangxi Normal Univ, Elementary Educ Coll, Nanchang, Peoples R China 4.Univ Western Ontario, Dept Med Biophys, London, ON N6G 1G9, Canada 5.Lanzhou Univ, Sch Informat Sci & Engn, Lanzhou 730000, Peoples R China 6.Chinese Acad Sci, Inst Automat, CAS Ctr Excellence Brain Sci & Intelligence Techn, Beijing 100083, Peoples R China 7.Univ New Mexico, LBERI, Mind Res Network, Albuquerque, NM 87106 USA 8.Univ New Mexico, Dept Elect & Comp Engn, Albuquerque, NM 87106 USA |
| 第一作者单位 | 模式识别国家重点实验室 |
| 推荐引用方式 GB/T 7714 | Jie, Nan-Feng,Zhu, Mao-Hu,Ma, Xiao-Ying,et al. Discriminating Bipolar Disorder From Major Depression Based on SVM-FoBa: Efficient Feature Selection With Multimodal Brain Imaging Data[J]. IEEE TRANSACTIONS ON AUTONOMOUS MENTAL DEVELOPMENT,2015,7(4):320-331. |
| APA | Jie, Nan-Feng.,Zhu, Mao-Hu.,Ma, Xiao-Ying.,Osuch, Elizabeth A..,Wammes, Michael.,...&Calhoun, Vince D..(2015).Discriminating Bipolar Disorder From Major Depression Based on SVM-FoBa: Efficient Feature Selection With Multimodal Brain Imaging Data.IEEE TRANSACTIONS ON AUTONOMOUS MENTAL DEVELOPMENT,7(4),320-331. |
| MLA | Jie, Nan-Feng,et al."Discriminating Bipolar Disorder From Major Depression Based on SVM-FoBa: Efficient Feature Selection With Multimodal Brain Imaging Data".IEEE TRANSACTIONS ON AUTONOMOUS MENTAL DEVELOPMENT 7.4(2015):320-331. |
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| FoBa Multimodal_IEEE（1662KB） | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 | |
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