EBioMedicine (Sep 2019)
Discriminating schizophrenia using recurrent neural network applied on time courses of multi-site FMRI dataResearch in context
- Weizheng Yan,
- Vince Calhoun,
- Ming Song,
- Yue Cui,
- Hao Yan,
- Shengfeng Liu,
- Lingzhong Fan,
- Nianming Zuo,
- Zhengyi Yang,
- Kaibin Xu,
- Jun Yan,
- Luxian Lv,
- Jun Chen,
- Yunchun Chen,
- Hua Guo,
- Peng Li,
- Lin Lu,
- Ping Wan,
- Huaning Wang,
- Huiling Wang,
- Yongfeng Yang,
- Hongxing Zhang,
- Dai Zhang,
- Tianzi Jiang,
- Jing Sui
Affiliations
- Weizheng Yan
- National Laboratory of Pattern Recognition and Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
- Vince Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) Center, Atlanta 30303, GA, USA
- Ming Song
- National Laboratory of Pattern Recognition and Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
- Yue Cui
- National Laboratory of Pattern Recognition and Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
- Hao Yan
- Peking University Sixth Hospital, Institute of Mental Health, Beijing 100191, China; Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing 100191, China
- Shengfeng Liu
- National Laboratory of Pattern Recognition and Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
- Lingzhong Fan
- National Laboratory of Pattern Recognition and Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
- Nianming Zuo
- National Laboratory of Pattern Recognition and Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
- Zhengyi Yang
- National Laboratory of Pattern Recognition and Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
- Kaibin Xu
- National Laboratory of Pattern Recognition and Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
- Jun Yan
- Peking University Sixth Hospital, Institute of Mental Health, Beijing 100191, China; Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing 100191, China
- Luxian Lv
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, Henan, China; Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang 453002, Henan, China
- Jun Chen
- Department of Radiology, Renmin Hospital of Wuhan University, Wuhan 430060, Hubei, China
- Yunchun Chen
- Department of Psychiatry, Xijing Hospital, The Fourth Military Medical University, Xi’an 710032, Shaanxi, China
- Hua Guo
- Zhumadian Psychiatric Hospital, Zhumadian 463000, Henan, China
- Peng Li
- Peking University Sixth Hospital, Institute of Mental Health, Beijing 100191, China; Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing 100191, China
- Lin Lu
- Peking University Sixth Hospital, Institute of Mental Health, Beijing 100191, China; Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing 100191, China
- Ping Wan
- Zhumadian Psychiatric Hospital, Zhumadian 463000, Henan, China
- Huaning Wang
- Department of Psychiatry, Xijing Hospital, The Fourth Military Medical University, Xi’an 710032, Shaanxi, China
- Huiling Wang
- Department of Radiology, Renmin Hospital of Wuhan University, Wuhan 430060, Hubei, China
- Yongfeng Yang
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, Henan, China; Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang 453002, Henan, China; Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, Sichuan, China
- Hongxing Zhang
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, Henan, China; Department of Psychology, Xinxiang Medical University, Xinxiang 453002, Henan, China
- Dai Zhang
- Peking University Sixth Hospital, Institute of Mental Health, Beijing 100191, China; Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing 100191, China; Center for Life Sciences/PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing 100871, China
- Tianzi Jiang
- National Laboratory of Pattern Recognition and Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China; Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, Sichuan, China; Queensland Brain Institute, University of Queensland, Brisbane 4072, QLD, Australia; CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; Corresponding authors at: Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China.
- Jing Sui
- National Laboratory of Pattern Recognition and Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China; CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; Corresponding authors at: Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China.
- Journal volume & issue
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Vol. 47
pp. 543 – 552
Abstract
Background: Current fMRI-based classification approaches mostly use functional connectivity or spatial maps as input, instead of exploring the dynamic time courses directly, which does not leverage the full temporal information. Methods: Motivated by the ability of recurrent neural networks (RNN) in capturing dynamic information of time sequences, we propose a multi-scale RNN model, which enables classification between 558 schizophrenia and 542 healthy controls by using time courses of fMRI independent components (ICs) directly. To increase interpretability, we also propose a leave-one-IC-out looping strategy for estimating the top contributing ICs. Findings: Accuracies of 83·2% and 80·2% were obtained respectively for the multi-site pooling and leave-one-site-out transfer classification. Subsequently, dorsal striatum and cerebellum components contribute the top two group-discriminative time courses, which is true even when adopting different brain atlases to extract time series. Interpretation: This is the first attempt to apply a multi-scale RNN model directly on fMRI time courses for classification of mental disorders, and shows the potential for multi-scale RNN-based neuroimaging classifications. Fund: Natural Science Foundation of China, the Strategic Priority Research Program of the Chinese Academy of Sciences, National Institutes of Health Grants, National Science Foundation. Keywords: Recurrent neural network (RNN), Schizophrenia, Multi-site classification, fMRI, Striatum, Cerebellum, Deep learning