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严超赣
认知与发展心理学研究室 研究员
电 话:  86-10-64101582
传 真:  86-10-64101582
通讯地址:  北京市朝阳区林萃路16号院中国科学院心理研究所
邮政编码:  100101
电子邮件:  yancg@psych.ac.cn
课题组网站:  http://rfmri.org/yan

简历:

严超赣博士是中国科学院心理研究所研究员,博士生导师,心理所磁共振成像研究中心副主任,脑功能成像实验室PI。2006年毕业于北京科技大学获学士学位,2011年毕业于北京师范大学获博士学位。随后赴美留学,在美国内森克兰精神病学研究所和纽约大学儿童与青少年精神病学系先后担任研究科学家(Research Scientist)和研究助理教授(Research Assistant Professor)职位。2015 年作为中国科学院“百人计划”研究员加入中国科学院心理研究所工作。严超赣博士的主要研究领域集中在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脑疾病中的应用。他为一系列困扰静息态功能磁共振成像的方法学问题提出了广受领域认可和引用的解决方案,包括头动、标准化和多重比较校正等。他还对静息态功能磁共振成像的计算方法进行了规范化,建立了被引1400余次的脑成像流水线式计算平台DPARSF,并建立了脑成像分析与共享平台DPABI。他将静息态功能磁共振成像应用于抑郁症研究,发现了早期不良抚育可致大脑自发活动异常发育,与后期抑郁样行为有关。他在国际主流学术期刊(如Cerebral Cortex, NeuroImage, Human Brain Mapping, Translational Psychiatry, Neuroinformatics, Molecular Psychiatry 等)共发表48篇学术论文,其中17篇为第一作者和/或通讯作者。研究成果得到国际同行的高度关注,总引用7000余次,h指数27(Google Scholar),并有3篇第一/通讯作者论文入选ESI Top 1%高被引论文。他是《Frontiers in Psychiatry》客座副主编,国际人脑图谱学会通讯委员会(OHBM Communications Committee)委员。 

教育与工作经历
2002-2006  北京科技大学  自动化                       学士
2
006-2011  北京师范大学  认知神经科学                    博士
2011-2015  The Nathan S. Kline Institute for Psychiatric Research       研究科学家
2013-2015  Department of Child and Adolescent Psychiatry, New York University 研究助理教授
2015 –  中国科学院心理研究所                        研究员

课题组网站http://rfmri.org/yan

研究领域:

静息态功能磁共振成像方法学、数据分析软件平台、脑自发活动机制及其在脑疾病中的应用

学术资源链接:
DPARSF: http://rfmri.org/DPARSF 
DPABI: http://rfmri.org/DPABI 
The R-fMRI Course: http://rfmri.org/Course 
The R-fMRI Network: http://rfmri.org
The R-fMRI Journal Club: http://rnet.co/jc
微信公众号:RFMRILab

社会任职:
获奖及荣誉:

教育部博士学术新人奖(2010)
葛兰素史克明日之星奖(2011)
中国科学院“百人计划”(2015) 

代表论著:

1. Chen X, Lu B, Yan CG* (2018) Reproducibility of R-fMRI metrics on the impact of different strategies for multiple comparison correction and sample sizes. Human Brain Mapping. 39: 300-318.
2. 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) Aberrant intrinsic functional connectivity in thalamo-cortical networks in major depressive disorder. CNS Neuroscience & Therapeutics. In Press.
3. Yan CG*, Yang Z, Colcombe S, Zuo XN, Milham MP (2017) Concordance among indices of intrinsic brain function: insights from inter-individual variation and temporal dynamics. Science Bulletin. 62: 1572-1584.
4. 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) Aberrant development of intrinsic brain activity in a rat model of caregiver maltreatment of offspring. Translational Psychiatry. 7: e100.
5. 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) Altered intrinsic functional brain architecture in female patients with bulimia nervosa. Journal of Psychiatry & Neuroscience. 42: 414-423.
6. Yan CG*, Wang XD, Zuo XN, Zang YF (2016) DPABI: Data processing & analysis for (resting-state) brain imaging. Neuroinformatics. 14: 339-351.
7. Di Martino A, Yan CG#, Li Q#, Denio E, Castellanos FX, Alaerts K, Anderson JS, Assaf M, Bookheimer SY, Dapretto M, Deen B, Delmonte S, Dinstein I, Ertl-Wagner B, Fair DA, Gallagher L, Kennedy DP, Keown CL, Keysers C, Lainhart JE, Lord C, Luna B, Menon V, Minshew N, Monk CS, Mueller S, Muller RA, Nebel MB, Nigg JT, O’Hearn K, Pelphrey KA, Peltier SJ, Rudie JD, Sunaert S, Thioux M, Tyszka JM, Uddin LQ, Verhoeven JS, Wenderoth N, Wiggins JL, Mostofsky SH, Milham MP (2014) The Autism Brain Imaging Data Exchange: towards large-scale evaluation of the intrinsic brain architecture in Autism. Molecular Psychiatry. 19: 659-667.
8. Yan CG, Cheung B, Kelly C, Colcombe S, Craddock RC, Di Martino A, Li Q, Zuo XN, Castellanos FX, Milham MP (2013) A comprehensive assessment of regional variation in the impact of head micromovements on functional connectomics. Neuroimage. 76:183-201.
9. Yan CG, Craddock RC, Zuo XN, Zang YF, Milham MP (2013) Standardizing the intrinsic brain: towards robust measurement of inter-individual variation in 1000 functional connectomes. Neuroimage. 80: 246-262.
10. Dai ZJ#, Yan CG#, Wang ZQ, Wang JH, Xia MR, Li KC, He Y (2012) Discriminative analysis of early Alzheimer’s disease using multi-modal imaging and multi-level characterization with multi-classifier (M3). Neuroimage. 59: 2187-2195.
11. Yan CG, Gong GL, Wang JH, Wang DY, Liu DQ, Zhu CZ, Chen ZJ, Evans A, Zang YF, He Y (2011) Sex- and brain size-related small-world structural cortical networks in young adults: a DTI tractography study. Cerebral Cortex. 21: 449-458.
12. Yan CG and He Y. (2011) Driving and driven architectures of directed small-world human brain functional networks. PLoS ONE. 6(8): e23460.
13. Wang ZQ#, Yan CG#, Zhao C, Qi ZG, Zhou WD, Lu J, He Y, Li KC (2011) Spatial patterns of intrinsic brain activity in mild cognitive impairment and Alzheimer’s disease: A resting-state functional MRI study. Human Brain Mapping. 32: 1720-1740. (From the cover)
14. Yan CG* and Zang YF* (2010) DPARSF: a MATLAB toolbox for "pipeline" data analysis of resting-state fMRI. Frontiers in Systems Neuroscience. 4(13).
15. Yan CG, Liu DQ, He Y, Zou QH, Zhu CZ, Zuo XN, Long XY, Zang YF (2009) Spontaneous brain activity in the default mode network is sensitive to different resting-state conditions with limited cognitive load. PLoS ONE. 4(5): e5743.
 (*Corresponding author #Equal contribution)

更多成果信息请见:http://ir.psych.ac.cn/yancg@psych.ac.cn

承担科研项目情况: