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严超赣
yancg@psych.ac.cn
中文, 英语
北京
中国科学院
institute of psychology CAS
  • 2002-2006 学士:北京科技大学
  • 2006-2011 博士:北京师范大学
  • 国家优秀青年科学基金获得者
  • 爱思唯尔中国高被引学者(2019-2022)
  • 国际人脑图谱学会青年科学家奖
  • 北京市科学技术奖自然科学奖二等奖
  • 中国科学院优秀导师奖
  • 2011-2015 - 美国内森克兰精神病学研究所 - 研究科学家
  • 2013-2015 - 纽约大学儿童与青少年精神病学系 - 研究助理教授
  • 2015-今 - 中国科学院心理研究所 - 研究员
  • 2023:中国科学院优秀党务工作者奖
  • 2021:北京市科学技术奖自然科学奖二等奖
  • 2021:国际人脑图谱学会青年科学家奖
  • 2019-2023:斯坦福全球前2%顶尖科学家
  • 2019-2022:爱思唯尔中国高被引学者
  • 2020:中国科学院优秀导师奖
静息态功能磁共振方法学
数据分析软件平台
脑自发活动机制及其在抑郁症中的应用
  • Comprehensive evaluation of harmonization on functional brain imaging for multisite data-fusion, Wang, Y.W., Chen, X., Yan, C.G., 2023
  • Neural representations of self-Generated thought during think-aloud fMRI, Li, H.X., Lu, B., Wang, Y.W., Li, X.Y., Chen, X., Yan, C.G., 2023
  • The Changes of Histone Methylation Induced by Adolescent Social Stress Regulate the Resting-State Activity in mPFC, Wang, J., Zhang, W., Xu, H., Ellenbroek, B., Dai, J., Wang, L., Yan, C.G., Wang, W.W., 2023
  • A practical Alzheimer’s disease classifier via brain imaging-based deep learning on 85,721 samples, Lu, B., Li, H.-X., Chang, Z.-K., Li, L., Chen, N.-X., Zhu, Z.-C., Zhou, H.-X., Li, X.-Y., Wang, Y.-W., Cui, S.-X., Deng, Z.-Y., Fan, Z., Yang, H., Chen, X., Thompson, P.M., Castellanos, F.X., Yan, C.G., 2022
  • The DIRECT consortium and the REST-meta-MDD project: towards neuroimaging biomarkers of major depressive disorder, Chen, X., Lu, B., Li, H.-X., Li, X.-Y., Wang, Y.-W., Castellanos, F.X., Cao, L.-P., Chen, N.-X., Chen, W., Cheng, Y.-Q., Cui, S.-X., Deng, Z.-Y., Fang, Y.-R., Gong, Q.-Y., Guo, W.-B., Hu, Z.-J.-Y., Kuang, L., Li, B.-J., Li, L., Li, T., Lian, T., Liao, Y.-F., Liu, Y.-S., Liu, Z.-N., Lu, J.-P., Luo, Q.-H., Meng, H.-Q., Peng, D.-H., Qiu, J., Shen, Y.-D., Si, T.-M., Tang, Y.-Q., Wang, C.-Y., Wang, F., Wang, H.-N., Wang, K., Wang, X., Wang, Y., Wang, Z.-H., Wu, X.-P., Xie, C.-M., Xie, G.-R., Xie, P., Xu, X.-F., Yang, H., Yang, J., Yao, S.-Q., Yu, Y.-Q., Yuan, Y.-G., Zhang, K.-R., Zhang, W., Zhang, Z.-J., Zhu, J.-J., Zuo, X.-N., Zhao, J.-P., Zang, Y.-F., consortium, t.D., Yan, C.G., 2022
  • Exploring self-generated thoughts in a resting state with natural language processing, Li, H.X., Lu, B., Chen, X., Li, X.Y., Castellanos, F.X., Yan, C.G., 2022
  • Altered cerebral activities and functional connectivity in depression: a systematic review of fMRI studies, Li, X.Y., Chen, X., Yan, C.G., 2022
  • Atypicalities in the developmental trajectory of cortico-striatal functional connectivity in autism spectrum disorder, Ma, Z.H., Lu, B., Li, X., Mei, T., Guo, Y.Q., Yang, L., Wang, H., Tang, X.Z., Ji, Z.Z., Liu, J.R., Xu, L.Z., Yang, Y.L., Cao, Q.J., Yan, C.G., Liu, J., 2022
  • Frequency-specific age-related changes in the amplitude of spontaneous fluctuations in autism, Mei, T., Ma, Z.H., Guo, Y.Q., Lu, B., Cao, Q.J., Chen, X., Yang, L., Wang, H., Tang, X.Z., Ji, Z.Z., Liu, J.R., Xu, L.Z., Wang, L.Q., Yang, Y.L., Li, X., Yan, C.G., Liu, J., 2022
  • Disrupted intrinsic functional brain topology in patients with major depressive disorder, Yang, H., Chen, X., Chen, Z.B., Li, L., Li, X.Y., Castellanos, F.X., Bai, T.J., Bo, Q.J., Cao, J., Chang, Z.K., Chen, G.M., Chen, N.X., Chen, W., Cheng, C., Cheng, Y.Q., Cui, X.L., Duan, J., Fang, Y., Gong, Q.Y., Guo, W.B., Hou, Z.H., Hu, L., Kuang, L., Li, F., Li, H.X., Li, K.M., Li, T., Liu, Y.S., Liu, Z.N., Long, Y.C., Lu, B., Luo, Q.H., Meng, H.Q., Peng, D., Qiu, H.T., Qiu, J., Shen, Y.D., Shi, Y.S., Si, T.M., Tang, Y.Q., Wang, C.Y., Wang, F., Wang, K., Wang, L., Wang, X., Wang, Y., Wang, Y.W., Wu, X.P., Wu, X.R., Xie, C.M., Xie, G.R., Xie, H.Y., Xie, P., Xu, X.F., Yang, J., Yao, J.S., Yao, S.Q., Yin, Y.Y., Yuan, Y.G., Zang, Y.F., Zhang, A.X., Zhang, H., Zhang, K.R., Zhang, L., Zhang, Z.J., Zhao, J.P., Zhou, R., Zhou, Y.T., Zhu, J.J., Zhu, Z.C., Zou, C.J., Zuo, X.N., Yan, C.G., 2021
  • DPABISurf: data processing & analysis for brain imaging on surface, Yan, C.-G., Wang, X.-D., Lu, B., 2021
  • Hypostability in the default mode network and hyperstability in the frontoparietal control network of dynamic functional architecture during rumination, Chen, X., Yan, C.-G., 2021
  • Eight-week antidepressant treatment reduces functional connectivity in first-episode drug-naïve patients with major depressive disorder, Li, L., Su, Y.A., Wu, Y.K., Castellanos, F.X., Li, K., Li, J.T., Si, T.M., Yan, C.G., 2021
  • The contributions of brain structural and functional variance in predicting age, sex and treatment, Chen, N.-X., Fu, G., Chen, X., Li, L., Milham, M.P., Lui, S., Yan, C.-G., 2021
  • The subsystem mechanism of default mode network underlying rumination: a reproducible neuroimaging study, Chen, X., Chen, N.X., Shen, Y.Q., Li, H.X., Li, L., Lu, B., Zhu, Z.C., Fan, Z., Yan, C.G., 2020
  • Stability of dynamic functional architecture differs between brain networks and states, Li, L., Lu, B., Yan, C.G., 2020
  • Rumination and the default mode network: Meta-analysis of brain imaging studies and implications for depression, Zhou, H.-X., Chen, X., Shen, Y.-Q., Li, L., Chen, N.-X., Zhu, Z.-C., Castellanos, F.X., Yan, C.-G., 2020
  • Meditation effect in changing functional integrations across large-scale brain networks: Preliminary evidence from a meta-analysis of seed-based functional connectivity, Shen, Y.-Q., Zhou, H.-X., Chen, X., Castellanos, F.X., Yan, C.-G., 2020
  • Biotypes of major depressive disorder: Neuroimaging evidence from resting-state default mode network patterns, Liang, S., Deng, W., Li, X., Greenshaw, A.J., Wang, Q., Li, M., Ma, X., Bai, T.J., Bo, Q.J., Cao, J., Chen, G.M., Chen, W., Cheng, C., Cheng, Y.Q., Cui, X.L., Duan, J., Fang, Y.R., Gong, Q.Y., Guo, W.B., Hou, Z.H., Hu, L., Kuang, L., Li, F., Li, K.M., Liu, Y.S., Liu, Z.N., Long, Y.C., Luo, Q.H., Meng, H.Q., Peng, D.H., Qiu, H.T., Qiu, J., Shen, Y.D., Shi, Y.S., Si, T.M., Wang, C.Y., Wang, F., Wang, K., Wang, L., Wang, X., Wang, Y., Wu, X.P., Wu, X.R., Xie, C.M., Xie, G.R., Xie, H.Y., Xie, P., Xu, X.F., Yang, H., Yang, J., Yu, H., Yao, J.S., Yao, S.Q., Yin, Y.Y., Yuan, Y.G., Zang, Y.F., Zhang, A.X., Zhang, H., Zhang, K.R., Zhang, Z.J., Zhao, J.P., Zhou, R.B., Zhou, Y.T., Zou, C.J., Zuo, X.N., Yan, C.G., Li, T., 2020
  • Reduced default mode network functional connectivity in patients with recurrent major depressive disorder, Yan, C.-G., Chen, X., Li, L., Castellanos, F.X., Bai, T.-J., Bo, Q.-J., Cao, J., Chen, G.-M., Chen, N.-X., Chen, W., Cheng, C., Cheng, Y.-Q., Cui, X.-L., Duan, J., Fang, Y.-R., Gong, Q.-Y., Guo, W.-B., Hou, Z.-H., Hu, L., Kuang, L., Li, F., Li, K.-M., Li, T., Liu, Y.-S., Liu, Z.-N., Long, Y.-C., Luo, Q.-H., Meng, H.-Q., Peng, D.-H., Qiu, H.-T., Qiu, J., Shen, Y.-D., Shi, Y.-S., Wang, C.-Y., Wang, F., Wang, K., Wang, L., Wang, X., Wang, Y., Wu, X.-P., Wu, X.-R., Xie, C.-M., Xie, G.-R., Xie, H.-Y., Xie, P., Xu, X.-F., Yang, H., Yang, J., Yao, J.-S., Yao, S.-Q., Yin, Y.-Y., Yuan, Y.-G., Zhang, A.-X., Zhang, H., Zhang, K.-R., Zhang, L., Zhang, Z.-J., Zhou, R.-B., Zhou, Y.-T., Zhu, J.-J., Zou, C.-J., Si, T.-M., Zuo, X.-N., Zhao, J.-P., Zang, Y.-F., 2019
  • Physiological significance of R-fMRI indices: Can functional metrics differentiate structural lesions (brain tumors)?, Fan, Z., Chen, X., Qi, Z.X., Li, L., Lu, B., Jiang, C.L., Zhu, R.Q., Yan, C.G., Chen, L., 2019
  • Striatal functional connectivity alterations after two-week antidepressant treatment associated to enduring clinical improvement in major depressive disorder, An, J., Li, L., Wang, L., Su, Y.A., Wang, Y., Li, K., Zeng, Y., Kong, Q., Yan, C.G., Si, T.M., 2019
  • Reproducibility of R-fMRI metrics on the impact of different strategies for multiple comparison correction and sample sizes, Chen X, Lu B, Yan CG, 2018
  • Aberrant intrinsic functional connectivity in thalamo-cortical networks in major depressive disorder, Kong QM, Qiao H, Liu CZ, Zhang P, Li K, Wang L, Li JT, Su YA, Li KQ, Yan CG, Mitchell, PB, Si TM, 2018
  • Total salvianolic acid balances brain functional network topology in rat hippocampi overexpressing miR-30e, Li Q, Wang L, Li XY, Chen X, Lu B, Cheng L, Yan CG, Xu Y, 2018
  • Concordance among indices of intrinsic brain function: insights from inter-individual variation and temporal dynamics, Yan CG, Yang Z, Colcombe S, Zuo XN, Milham MP, 2017
  • Aberrant development of intrinsic brain activity in a rat model of caregiver maltreatment of offspring, Yan CG, Rincon-Cortes M, Raineki C, Sarro E, Colcombe S, Guilfoyle DN, Yang Z, Gerum S, Biswal BB, Milham MP, Sullivan RM, Castellanos FX, 2017
  • Altered intrinsic functional brain architecture in female patients with bulimia nervosa, Wang L, Kong QM, Li K, Li XN, Zeng YW, Chen C, Qian Y, Feng SJ, Li JT, Su YA, Correll CU, Mitchell PB, Yan CG, Zhang DR, Si TM, 2017
  • DPABI: Data processing & analysis for (resting-state) brain imaging, Yan CG, Wang XD, Zuo XN, Zang YF, 2016
  • PRN: a preprint service for catalyzing R-fMRI and neuroscience related studies, Yan CG, Li Q, Gao L, 2015
  • Localizing hand motor area using resting-state fMRI: validated with direct cortical stimulation, Qiu TM, Yan CG, Tang WJ, Wu JS, Zhuang DX, Yao CJ, Lu JF, Zhu FP, Mao Y, Zhou LF, 2014
  • A comprehensive assessment of regional variation in the impact of head micromovements on functional connectomics, Yan CG, Cheung B, Kelly C, Colcombe S, Craddock RC, Di Martino A, Li Q, Zuo XN, Castellanos FX, Milham MP, 2013
  • Standardizing the intrinsic brain: towards robust measurement of inter-individual variation in 1000 functional connectomes, Yan CG, Craddock RC, Zuo XN, Zang YF, Milham MP, 2013
  • Addressing head motion dependencies for small-world topologies in functional connectomics, Yan CG, Craddock RC, He Y, Milham MP, 2013
  • Discriminative analysis of early Alzheimer’s disease using multi-modal imaging and multi-level characterization with multi-classifier (M3), Dai ZJ, Yan CG, Wang ZQ, Wang JH, Xia MR, Li KC, He Y, 2012
  • Sex- and brain size-related small-world structural cortical networks in young adults: a DTI tractography study, Yan CG, Gong GL, Wang JH, Wang DY, Liu DQ, Zhu CZ, Chen ZJ, Evans A, Zang YF, He Y, 2011
  • Driving and driven architectures of directed small-world human brain functional networks, Yan CG and He Y., 2011
  • Spatial patterns of intrinsic brain activity in mild cognitive impairment and Alzheimer’s disease: A resting-state functional MRI study, Wang ZQ, Yan CG, Zhao C, Qi ZG, Zhou WD, Lu J, He Y, Li KC, 2011
  • DPARSF: a MATLAB toolbox for \"pipeline\" data analysis of resting-state fMRI, Yan CG and Zang YF, 2010
  • Spontaneous brain activity in the default mode network is sensitive to different resting-state conditions with limited cognitive load, Yan CG, Liu DQ, He Y, Zou QH, Zhu CZ, Zuo XN, Long XY, Zang YF, 2009
  • 功能磁共振脑影像学, 严超赣, 李雪莹, 鲁彬, 2020
  • 孤独症脑自发活动动态性及其整合的异常机制, 鲁彬, 陈骁, 李乐, 沈杨千, 陈宁轩, 梅婷, 周会霞, 刘靖, 严超赣, 2018
  • 大数据时代的静息态功能磁共振成像——走向精神疾病诊疗应用, 严超赣, 2018
静息态功能磁共振 方法学 数据分析 软件平台 脑活动 抑郁症 自发活动 神经影像 功能连接 脑网络

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