The brain is a complex network. It perfectly extracts and integrates all kinds of information from various external and internal stimuli. To better explore the spatiotemporal pattern of the brain connectome. The human brain connectome is divided into three hierarchy: structural networks based on neuroanatomy; functional networks due to the dynamics of neuronal clusters, and effective networks that emphasize the causal interaction between nodes. Research of brain connectome is aiming to comprehend the dynamic evolution mechanism of the brain, understand the brain's advanced cognitive awareness, and ultimately return to ourselves.
Title: Brain Network of Social Anxiety Disorder
Dr. Huafu Chen, distinguished professor of Yangtze river scholar, winner of national outstanding youth fund. Deputy Director of key laboratory of the ministry of education. Main research direction: magnetic resonance imaging pattern recognition method, and the brain cognitive, neurological and psychiatric disease, cerebral shadow application research, detection caused by brain disease network loop changes and characteristics of typical imaging and provide imaging basis for clinical diagnosis and evaluation. He presided over more than 20 scientific research projects, including the 863 project of the ministry of science and technology, the key projects of the national natural fund, the national outstanding youth fund project etc. He has published 150 SCI papers included: IEEE Tran BME/MI, Brain, NeuroImage, Human Brain mapping etc. His published papers were cited over 4000 times by SCI paper published in the international journal of Nature Reviews Neuroscience and PNAS etc.
Title: Multimodal Brain Connetomics on Epilepsy
Dr. Wei Liao received the B.S., M.S. and Ph.D. degrees from the University of Electronic Science and Technology of China (UESTC), Chengdu, China, in 2004, 2008, and 2011, respectively. He is currently a Professor at the School of Life Science and Technology, UESTC. From July 2015 to July 2016, he was a Visiting Assistant Professor with Department of Psychology, University of South Carolina, USA. He has authored about 80 articles in SCI journals, such as Brain, Radiology, NeuroImage, Human Brain Mapping, IEEE Trans. Medical Imaging, etc. His research interests include functional magnetic resonance imaging and brain networks.
Title: Controllability and Trajectories of Brain State Transitions
Dr. Shi Gu, professor in the Department of Computer Science and Engineering, winner of 1000 young talent program. Main research direction: computational neuroscience, neural development, pattern recognition and machine learning in neural imaging. He proposed a model of analyzing the brain networks from the controllability perspective and developed it into a detailed framework of analyzing the brain networks from the dynamic trajectories and associated energy forms. He has published SCI papers included: PNAS, Nature Communications, NeuroImage and HBM.
Changsong Zhou(Hong Kong Baptist University)
Title: Complex Neural Connectivity and Activity: Perspective from Cost-Efficiency Trade-off
Dr. Changsong Zhou, Professor, Department of Physics, Director of Centre for Nonlinear Studies, Hong Kong Baptist University (HKBU). He obtained his PhD degree at Nankai University, and served as Postdoctoral Fellow at National University of Singapore (1997-1999), Visiting Research Scholar at HKBU (1999-2000) and Humboldt Research Fellow and Research Scientist at University of Potsdam, Germany (2000-2007). He joined HKBU as Assistant Professor in 2007 and received HKBU President’s Award for Outstanding Young Researcher 2011. Dr. Zhou’s research interest is dynamical processes on complex systems. His current emphasis is on analysis and modeling connectivity and activity in neural systems in collaboration with experimental neuroscientists, using the approaches of oscillatory dynamics networks and covering broad scales from network of excitatory-inhibitory neurons to interacting functional brain regions and functional EEG and cognitive variability and disorders. He has published over 110 research papers in interdisciplinary journals, including PNAS, Physical Review Letters, Physics Reports and PLoS Computational Biology etc. His work has received citations over 7000 (h-index 34) in SCI and over 11500 in Google Scholar (h-index 41). He currently serves as Academic Editors of Scientific Reports and PLoS One.
Daoqiang Zhang(Nanjing University of Aeronautics and Astronautics)
Title: Mining Brain Connectivity Networks with Applications
Dr. Daoqiang Zhang received the B.Sc. and Ph.D. degrees in Computer Science from Nanjing University of Aeronautics and Astronautics, China, in 1999 and 2004, respectively. He joined the Department of Computer Science and Engineering of Nanjing University of Aeronautics and Astronautics in 2004, and is a professor at present. His research interests include machine learning, pattern recognition, data mining, and medical image analysis. In these areas he has published over 150 technical papers in referred journals or conference proceedings, including reputable international journals such as IEEE Trans. Pattern Analysis and Machine Intelligence, IEEE Trans. Medical Imaging, Neuroimage, Human Brain Mapping, Medical Image Analysis, etc., and top-tier international conferences such as NIPS, IJCAI, AAAI, MICCAI, CVPR, etc., with 7000+ citations by Google Scholar. He served as a program committee member for several international and native conferences.
Jie Zhang(Fudan University)
Title: Data Driven dynamic brain network analysis and the underlying mechanisms
Dr. Jie Zhang received Ph.D. degree from Hong Kong Polytechnic University in 2008, and is currently a Professor with the Institute of Science and Technology for Brain-inspired Intelligence (ISTBI) in Fudan University. He has won the "Hong Kong Young Scientists Award" nomination award, and is a honorary member of "System Modeling Analysis and Prediction" laboratory of the University of Oxford. His research interests include dynamic brain networks and chaotic time series analysis. He has published more than 50 SCI papers in journals including PNAS, PRL, Brain, and Cerebral Cortex. 2 of his papers are ESI top-1% highly-cited papers. One of his paper published in Brain 2006 on dynamic brain networks was selected as a cover paper, and Professor Dani Bassett, the 2014 MacArthur Prize winner in the United States, wrote a commentary for this paper in Brain.
Ling-Li Zeng(National University of Defense Technology)
Title: Pattern analysis of the brain connectome
Dr. Ling-Li Zeng received the B.Sc., M.Sc. and Ph.D. degrees from the National University of Defense Technology, China, in 2007, 2009, and 2014, respectively. From November 2012 to November 2013, he was a visiting Ph.D. student with the Harvard Medical School & Massachusetts General Hospital. He is currently an Associate Professor with the College of Mechatronics and Automation, National University of Defense Technology. He has authored 40 papers in journals, such as PNAS, Brain, Human Brain Mapping, etc. He is the recipient of the Outstanding Doctoral Dissertation Award of the Chinese Association for Artificial Intelligence (2015) and the Excellent Young Scholars Award of National Science Foundation of China (2017). His research interests include cognitive neuroscience, image processing, and pattern recognition in neuroimaging.
Title: Higher-order organization of topological motifs in human brain networks
After receiving a Bachelor of science in applied psychology from Chengdu University, Hao Wang earned a Master's degree in Clinical Cognitive Neuroscience at the Center for Cognition and Brain Disorders of Hangzhou Normal University. He has won the National Scholarship twice (2011, 2016), Jing Hengyi President’s Scholarship (2016), Outstanding Graduate of Zhejiang Province (2017), and Ma Yun (Jack Ma) Youth Leader Award (2017). He has authored two papers published in journals Radiology and Brain and Behavior, respectively. Currently he is 1st year PhD student of University of Electronic Science and Technology of China, studying Complex Systems and Social Computing, mainly focuses on complex brain networks, network neuroscience, MRI data processing, and link prediction problem, under the guidance of Prof. Linyuan Lü.