Research

Introducation of the Yan Lab

Founded in June 2015, the R-fMRI lab is aimed to resolve issues related to the computational methodology of resting-state fMRI, the platform of brain imaging analysis and sharing, spontaneous brain activity, and its application for depressive disorders. At present, there are 8 members in the R-fMRI lab, namely Professor Chao-Gan Yan, Dr. Huixia Zhou, Post-doc Dr. Le Li, Ph.D. student Xiao Chen and Ningxuan Chen, master student Bin Lu and Huixian Li, and research assistant Yangqian Shen. In addition, there are several visiting students from multiple research institutes, including Peking University Sixth Hospital, Fudan University Huashan Hospital, University of Chinese Academy of Sciences, etc., which have built strong cooperation with us. The lab members are passionate to innovate and eager to learn with high productivity.  

On the platform of Neuro Imaging information processing, the R-fMRI lab developed the DPABI (Yan*, Wang, Zuo & Zang, 2016, Neuroinformatics), a toolbox for Data Processing & Analysis of Brain Imaging.he DPABI/DPARSF Stand-Alone Version without purchasing a MATLAB license. DPABI incorporated the DPARSF, a pipeline data processing toolbox for Data Processing & Analysis of Brian Imaging. The latest algorithms to control for head motion, noise reduction, and measurement standardization are incorporated into DPABI , which emphasizes the effect of Quality control and TRT reliability on brain imaging data analysis DPABI (includes a module for macaque monkeys and a module for rats) also provides a user-friendly pipeline data processing toolbox to facilitate R-fMRI research on the animal model. Based on DPABI/DPARSF, our lab has built a resting-state functional big data platform, known as the R-fMRI Maps Project (RMP, http://rfmri.org/maps) that shares resting-state indexes. It offers the global users to accumulate database of the spontaneous brain activity for healthy and multiple brain disease for their related research. At present, RMP has shared nearly 5000 subjects’ resting-state data. The work ofbuilding the R-fMRI Maps project-Consortium for depression and bipolar disorders (http://rfmri.org/RMP-CDBD) is ongoing, together with the team of Prof. Zuo Xinian from Institute of Psychology, Chinese Academy of Sciences and the Prof. Zang Yufeng from Hangzhou Normal University. to push forward depression resting-state fMRI multi-center project (REST-meta-MDD). More than thirty hospitals have taken part in this project.

For the application of resting-state fMRI to mental disease, our lab members and colleagues from New York University adopts a rat model and resting-state functional magnetic resonance imaging (R-fMRI) to explore the neural mechanism of maternal maltreatment affecting the spontaneous brain activity (Yan#, Rincon-Cortes#, Raineki , Sarro, Colcombe, Guifoyle, Yang, Gerum, Biswal, Miham, Sullivan & Castellanos, 2017, Translational Psychiatry). To be specific, compared to the control rats, maltreated rats showed more depressive-like behaviors, social withdraws, and abnormal brain developments. The R-fMRI results indicated that the amygdala-prefrontal cortex (PFC) functional connectivity was increased significantly from the adolescence and adulthoodperiods in control rats but not in maltreated rats. Meanwhile, the spontaneous activity of the medial prefrontal cortex showed early maturing and ceased to develop later. These findings human being and rodents early-life adversity cross-species. In addition, collaborated with the team of Prof. Si Tianmei from Peking University the Sixth Hospital, our lab has examined the intrinsic functional brain architecture of patients with bulimia nervosa (Wang, Kong, Li, Li, Zeng, Chen, Qian, Feng, Li, Su, Correll, Mitchell, Yan*, Zhang, Si*, 2017, Journal of Psychiatry & Neuroscience). Patients with bulimia nervosa showed increased local efficiency and decreased global efficiency, and also the nodal strength in the visual areas, subcortical and limbic regions was abnormally higher in patients. These findings indicated that patients have large-scale network level dysfunctional integration.

For public services, our lab provides online courses related to the basic principles, method and data processing of resting-state fMRI for vast introductory researcher (http://rfmri.org/course). We collect feedback and give responses the users of DPABI/DPARSF through the R-fMRI network (http://rfmri.org). We offer support to promote research ideas, data processing and review recommendations. The weekly R-fMRI journal club is conducted through the online live platform to discuss the research in the domain of resting-state fMRI. In December 2016, our lab had successfully held the “human brain connectome neuroimaging seminar” and the “brain imaging data analysis paper writing training camp”. More than 100 participants were involved in this seminar, and 30 of them participated the training camp, which had promoted their research process into a higher level.

In addition, our lab goes for a joyful and productive team spirit, trying to provide the best working and study condition for each member. We have a roomy working place equipped with advanced facilities and office tools. Prof. Yan Chaogan was trying to students learning situation, project debriefing rigorous and careful planning and help, not only research area macro guidance but also specific suggestion. Our lab encourages the postgraduate students and visiting students from other placements to explore the topics that they are interested with full support.