吴国榕，男，福建尤溪人，硕士生导师。
Email:gronwu@gmail.com
个人主页：https://guorongwu.github.io/Lab/WU.html
研究兴趣及方向：发展基于神经影像数据的动态脑功能活动和脑连接分析算法，开发相应的集成工具包，与统计分析方法相结合应用于心理学和临床疾病研究中。近年来开始关注无创脑刺激(TMS, tDCS)在临床治疗上的脑神经机制(包括抑郁症，酒精成瘾等)。
教育及工作经历：
2017.07-今，西南大学心理学部，副研究员
2014.03-2017.06，西南大学心理学部，讲师
2015.06-2015.11，Ghent University，Assistant
2011.11-2015.10，Ghent University，Statistical Data Analysis，理学博士
2010.09-2013.12，电子科技大学，生物医学工程专业，工学博士
2008.09-2010.06，电子科技大学，应用数学专业，转为硕博连读
2004.09-2008.06，福建师范大学，数学与应用数学专业，理学学士
科研项目：
国家自然科学基金面上项目，无创脑刺激治疗酒精使用障碍的因果调控机制研究，2019.01—2022.12，主持。
国家自然科学基金青年项目，时空点过程重构的静息态fMRI动态有向脑连接研究，2015.01—2017.12，主持。
讲授课程：
心理统计学, 高等数学, 磁共振研究与技术，动态脑连接
软件开发：
rsHRF ( https://www.nitrc.org/projects/rshrf)
DynamicBC( http://restfmri.net/forum/DynamicBC)
Rat-fMRI
Brain GPS
研究论文：( *通讯, ^#共同第一)
详见https://guorongwu.github.io/Lab/WU.html
http://scholar.google.com/citations?hl=en&user=BC0dWQsAAAAJ
Guo-Rong Wu, Chris Baeken, Peter Van Schuerbeek, Johan De Mey, Minghua Bi, Sarah C. Herremans*. “Accelerated repetitive transcranial magnetic stimulation does not influence grey matter volumes in regions related to alcohol relapse: an open-label exploratory study.” Drug and Alcohol Dependence, 2018(191), 210-214.
Guo-Rong Wu, Chris Baeken*. “Longer depressive episode duration negatively influences HF-rTMS treatment response: a cerebellar metabolic deficiency?” Brain Imaging and Behavior, 2017, 11(1), 8-16.
Guo-Rong Wu*, Daniele Marinazzo. “Sensitivity of the resting state haemodynamic response function estimation to autonomic nervous system fluctuations.” Philosophical Transactions of the Royal Society A, 2016, 374: **.
Guo-Rong Wu, Daniele Marinazzo*. “Point-process deconvolution of fMRI BOLD signal reveals effective connectivity alterations in chronic pain patients.” Brain Topography, 2014, 28(4): 541-547.
Guo-Rong Wu, Wei Liao, Sebastiano Stramaglia, Ju-Rong Ding, Huafu Chen, Daniele Marinazzo*. “A blind deconvolution approach to recover effective connectivity brain networks from resting state fMRI data.” Medical Image Analysis, 2013,17:365-374.
Guo-Rong Wu, Sebastiano Stramaglia, Huafu Chen, Wei Liao*, Daniele Marinazzo*. ”Mapping the voxel-wise effective connectome in resting state fMRI.” PLoS ONE, 2013,8(9): e73670.
Guo-Rong Wu, Wei Liao, Sebastiano Stramaglia, Huafu Chen, Daniele Marinazzo*. “Recovering directed networks in neuroimaging datasets using partially conditioned Granger causality.” Brain Connectivity, 2013, 3(3): 294-301.
Guorong Wu, Xujun Duan, Wei Liao, Qing Gao, and Huafu Chen*. “Kernel canonical-correlation Granger causality for multiple time series.” Physical Review E,2011,83: 041921.
Guo-Rong Wu, Fuyong Chen, Dezhi Kang, Daniele Marinazzo*, Huafu Chen*. ”Multi-scale causal connectivity analysis by canonical correlation: theory and application to epileptic brain.” IEEE Trans Biomed Eng,2011,58(11): 3088 - 3096.
Guo-Rong Wu, Rudi De Raedt, Peter Van Schuerbeek, Chris Baeken*. “Opposite subgenual Cingulate Cortical functional connectivity and metabolic activity patterns in refractory melancholic Major Depression.” Brain Imaging and Behavior, 2018, in press.
Luqing Wei^#, Nana Guo^#, Chris Baeken, Minghua Bi, Xiaowan Wang, Jiang Qiu,Guo-Rong Wu*. Grey matter volumes in the executive attention system predict individual differences in effortful control in young adults. Brain Topography, 2019, 32(1): 111-117.
Luqing Wei, Hong Chen*,Guo-Rong Wu*. “Structural Covariance of the Prefrontal-Amygdala Pathways Associated with Heart Rate Variability.” Frontiers in Human Neuroscience, 2018, 12:2.
Luqing Wei, Hong Chen*,Guo-Rong Wu*. “Heart rate variability associated with grey matter volumes in striatal and limbic structures of the central autonomic network.” Brain Research, 2018, 1681: 14–20.
Xiaowan Wang, Chris Baeken, Mengxia Fang, Jiang Qiu, Hong Chen,Guo-Rong Wu*. Predicting trait-like individual differences in fear of pain in the healthy state using gray matter volume. Brain Imaging and Behavior, 2018, in press.
Wei Liao^#*,Guo-Rong Wu^#*, Qiang Xu^#, Gong-Jun Ji, Zhiqiang Zhang, Yu-Feng Zang, Guangming Lu. “DynamicBC: A MATLAB Toolbox for Dynamic Brain Connectome Analysis.” Brain Connectivity, 2014, 4(10):780-90.