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个人简介

教育经历 2002-09--2007-03 北京理工大学,光电学院 ,工学博士 1998-09--2002-07 北京理工大学,计算机学院,辅修学位 1998-09--2002-07 北京理工大学,光电学院 ,工学学士 工作经历 2021-至今 北京师范大学认知神经科学与学习国家重点实验室,研究员 2016-2021 中国科学院大学未来技术学院,岗位教授 2015-2020 中国科学院脑科学与智能技术卓越创新中心,青年骨干 2013-2021 中国科学院自动化研究所,研究员、博导 2007-2013 美国The Mind Research Network神经影像研究所,历任博士后、研究科学家和助理教授

研究领域

课题组面向脑科学、心理学与人工智能的交叉学科前沿,近年来专注于脑发育障碍与精神疾病的计算医学模型研究,尤其是多模态影像组学协同分析理论与定量预测算法,研究成果被系统应用于几十种脑疾病的临床分析与诊疗。主要研究方向包括: (1) 多模态脑影像大数据融合分析与个体化预测评估理论 (2) 儿童青少年发育/学习障碍的客观影像学标记检测 (3) 基于多模态神经影像的脑疾病早期预警与干预性研究

近期论文

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Sui J*, Qi S, van Erp TGM, Bustillo J, Jiang R, Lin D, Turner JA, Damaraju E, Mayer AR, Cui Y, Fu Z, Du Y,Chen J, Potkin SG, Preda A, Mathalon DH, Ford JM, Voyvodic J, Mueller BA, Belger A, McEwen SC,O'Leary DS, McMahon A, Jiang T, Calhoun VD. Multimodal neuromarkers in schizophrenia via cognition-guided MRI fusion. Nature Communications 2018;9(1):3028. Sui J*, Jiang R, Bustillo J, Calhoun VD. 2020. Neuroimaging-based Individualized Prediction of Cognition and Behavior for Mental Disorders and Health: Methods and Promises. Biological Psychiatry. 88 (11):818-828. Qi S#, Schumann G#, Bustillo, J, Turner, J A, Jiang, R, Zhi, D, Fu, Z, Mayer, A R, Vergara, V M, Silva, R F, Iraji, A, Chen, J, Damaraju, E, Ma, X, Yang, X, Stevens, M, Mathalon, D H, Ford, J M, Voyvodic, J, Mueller, B A, Belger, A, Potkin, S G, Preda, A, Zhuo, C, Xu, Y, Chu, C, Banaschewski, T, Barker, G J, Bokde, A L W, Quinlan, E B, Desrivieres, S, Flor, H, Grigis, A, Garavan, H, Gowland, P, Heinz, A, Martinot, J L, Paillere Martinot, M L, Artiges, E, Nees, F, Orfanos, D P, Paus, T, Poustka, L, Hohmann, S, Frohner JH, Smolka MN, Walter H, Whelan R, Calhoun VD*, Sui J*, IMAGEN Consortium. 2021. Reward Processing in Novelty Seekers: A Transdiagnostic Psychiatric Imaging Biomarker. Biological Psychiatry. 90(8): 529-539. Sui J*, Pearlson, G.D., Du, Y., Yu, Q., Jones, T.R., Chen, J., Jiang, T., Bustillo, J., Calhoun, V.D., 2015. In Search of Multimodal Neuroimaging Biomarkers of Cognitive Deficits in Schizophrenia. Biological Psychiatry. 78(11):794-804. Qi S, Yang X, Zhao L, Calhoun VD, Perrone-Bizzozero N, Liu S, Jiang R, Jiang T, Sui J*, Ma X*. 2018. MicroRNA132 associated multimodal neuroimaging patterns in unmedicated major depressive disorder. Brain. 141(3):916-926. Sui J, Li Xiang, Towel S, Bell R, Meade C. 2020. Structural and functional brain abnormalities in HIV disease revealed by multimodal MRI fusion: association with cognitive function. Clinical Infectious Diseases. In press. Qi, S., Calhoun, V.D., van Erp, T.G.M., Bustillo, J., Damaraju, E., Turner, J.A., Du, Y., Yang, J., Chen, J., Yu, Q., Mathalon, D.H., Ford, J.M., Voyvodic, J., Mueller, B.A., Belger, A., McEwen, S., Potkin, S.G., Preda, A., Jiang, T., and Sui J*. Multimodal Fusion with Reference: Searching for Joint Neuromarkers of Working Memory Deficits in Schizophrenia. IEEE Trans Medical Imaging, 2018. 1(37):93-105. Liu S, Wang H, Song M, Lv L,Cui Y, Liu Y, Fan L, Zuo N, Xu K, Du Y, Yu Q, Luo N, Qi S, Yang J, Xie S, Li J, Chen J, Chen Y, Wang H, Guo H, Wan P, Yang Y, Li P, Lu L, Yan H, Yan J, Wang H, Zhang H, Zhang D, Calhoun VD, Jiang T, Sui J*. 2019. Linked 4-way multimodal brain changes in schizophrenia in a large chinese han population. Schizophrenia Bulletin. 45(2):436-449. Qi S, Morris R, Turner JA, Fu Z, Jiang R, Deramus TP, Zhi D, Calhoun VD, Sui J*. Common and unique multimodal co-varying patterns in Autism Spectrum Disorder subtypes. 2020. Molecular Autism. In press. Yan W, Calhoun V, Song M, Cui Y, Yan H, Liu S, Fan L, Zuo N, Yang Z, Xu K, Yan J, Lv L, Chen J, Chen Y, Guo H, Li P, Lu L, Wan P, Wang H, Wang H, Yang Y, Zhang H, Zhang D, Jiang T, Sui J* (2019): Discriminating schizophrenia using recurrent neural network applied on time courses of multi-site FMRI data. EBioMedicine. 47:543-552. Luo N, Sui J*, Chen J, Zhang F, Tian L, Lin D, Song M, Calhoun VD, Cui Y, Yan H, Yan J, Vergara VM, Zheng F, Liu J, Yang Z, Zuo N, Fan L, Xu K, Liu S, Li J, Xu Y, Liu S, Lv L, Chen J, Chen Y, Guo H, Li P, Lu L, Wan P, Wang H, Yang Y, Zhang H, Zhang D, Jiang T*.(2018). A Schizophrenia-related Genetic-Brain-Cognition Pathway Revealed in a Large Chinese Population. EBioMedicine. 37:471-482. Jiang R, Calhoun VD, Fan L, Zuo N, Jung R, Qi S, Lin D, Li J, Zhuo C, Song M, Fu Z, Jiang T, Sui J* (2019): Gender Differences in Connectome-based Predictions of Individualized Intelligence Quotient and Sub-domain Scores. Cerebral Cortex. 30:888-900. Luo N, Sui J*, Abrol A, Turner JA, Damaraju E, Fu Z, Fan L, Chen J, Lin D, Zhuo C, Xu Y Glahn DC, Rodrigue A, Banich MT, Pearlson GD, Calhoun VD*.2020. Structural brain architectures match intrinsic functional networks and vary across domains: A study from 15000+ individuals. Cerebral Cortex. 30 (10), 5460-5470 Jiang R, Calhoun VD, Zuo N, Lin D, Li J, Fan L, Qi S, Sun H, Fu Z, Song M, Jiang T, Sui J*. Connectome-based individualized prediction of temperament trait scores. NeuroImage 2018; 183:366-374. Jiang R, Calhoun VD, Zuo N, Lin D, Li J, Fan L, Qi S, Sun H, Fu Z, Song M, Jiang T, Sui J*. Task-induced brain connectivity promotes the detection of individual differences in brain-behavior relationships. NeuroImage 2019. 207, 116370. Meng X, Jiang R, Lin D, Bustillo J, Jones T, Chen J, Yu Q, Du Y, Zhang Y, Jiang T, Sui J*, Calhoun VD. Predicting individualized clinical measures by a generalized prediction framework and multimodal fusion of MRI data. NeuroImage 2017. 145 (Pt B):218-229. Arbabshirani MR, Plis S, Sui J, Calhoun VD. Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls. NeuroImage Jan 15 2017;145(Pt B):137-165. Qi S; Bustillo J; Turner JA; Jiang R; Zhi D; Fu Z; Deramus T; Vergara V; Ma X; Yang X; Stevens M; Zhuo C; Xu Y; Calhoun V; Sui J*. The relevance of transdiagnostic shared networks to the severity of symptoms and cognitive deficits in schizophrenia: a multimodal brain imaging fusion study. Translational Psychiatry. 2020. 10, 149. Wang L, Li, J, Zhang, S, Zhang, X, Zhang, Q, Chan, M F, Yang, R, Sui, J* 2020. Multi-task autoencoder based classification-regression model for patient-specific VMAT QA. Physics in Medicine and Biology 65, 235023. . Sui J*, Huster R, Yu Q, Judith M. Segall, Vince D Calhoun. 2014. Function-Structure Associations of the Brain: Evidence from Multimodal Connectivity and Covariance Studies. Neuroimage. 102:11-23. Sui J, He H, Pearlson GD, Adali T, Yu Q, Clark VP, White T, Mueller BA, Ho BC, Andreasen NC, Calhoun VD. 2013. Three-Way (N-way) Fusion of Brain Imaging Data Based on mCCA+jICA and Its Application to Discriminating Schizophrenia. Neuroimage. 2(66):119-132. (IF:5.812) Sui J, Pearlson GD, Adali T, Caprihan A, Liu J, Yamamoto J, Calhoun VD. 2011. Discriminating Schizophrenia and Bipolar Disorder by Fusing FMRI and DTI in a CCA+ICA Based Model. Neuroimage. 57(7):839-855. Sui J, Adali T, Pearlson GD, Yang H, Sponheim SR, White T, Calhoun VD 2010. A CCA+ICA Based Model for Multi-Task Brain Imaging Data Fusion And Its Application to Schizophrenia. Neuroimage. 51(5):123-134. Sui J, Adali T, Pearlson GD, Calhoun VD. 2009. An ICA-based method for the identification of optimal FMRI features and components using combined group-discriminative techniques. Neuroimage 46(1):73- 86. Sui J Adali T, Pearlson GD, Clark VP, Calhoun VD. 2009. A method for accurate group difference detection by constraining the mixing coefficients in an ICA framework. Hum Brain Mapping 30(9): 2953-2970. (IF:4.554) Luo N, Sui J*, Abrol A, Lin D, Chen J, Vergara VM, Fu Z, Du Y, Damaraju E, Xu Y, Turner JA, Calhoun VD*. 2019. Age-related Structural and Functional Variations in 5967 Individuals across the adult lifes-pan. Human Brain Mapping. 41 (7), 1725-1737. (IF:4.554) Qi S, Abbott CC*, Narr KL, Jiang R, Upston J, McClintock SM, Espinoza R, Jones T, Zhi D, Sun H, Yang X, Sui J*, Calhoun VD. 2020. Electroconvulsive therapy treatment responsive multimodal brain networks. Human Brain Mapping. 41 (7), 1775-1785 Gao S, Calhoun VD, Sui J*. 2018.Machine learning in major depression: From classification to treatment outcome prediction. CNS Neurosci Ther 24(11):1037-1052 (IF:3.394) Abbott CC, Loo D, Sui J. 2016. Determining Electroconvulsive Therapy Response With Machine Learning. JAMA Psychiatry. 6(73):545-546 Yu Q, Du Y, Chen J, Sui J, Adali T, Pearlson GD, Calhoun VD. 2018: Application of Graph Theory to Assess Static and Dynamic Brain Connectivity: Approaches for Building Brain Graphs.

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