(1) Fast whole brain mapping and deep-learning analysis of rodents and primates.
(2) Emerging properties of neuronal network underlying learning and memory.
ResearchWe work interdisciplinarily with people from physics, chemistry, engineering and computer sciences, aiming at deciphering both the infrastructure of the brain and cellular mechanisms underlying learning and memory.
“Seeing is believing”. We developed microscopes to mapping the whole brain at sub-micron resolution to image how neurons connected to each other at the brain-wide scale. We are also tracking neuronal activities with calcium indicators and voltage indicators to uncover mechanisms how neuronal firing encode information.
Biography2019 – Associate professor, Shenzhen Institutes of Advanced Technology, CAS
2016 – 2019: Postdoc, University of Science and Technology of China
2009 – 2016: Ph.D. student, University of Science and Technology of China
2005 – 2009: B.S., University of Science and Technology of China
Selected publications1. Xu, Zhi-Qin John, Fang Xu, Guoqiang Bi, Douglas Zhou, and David Cai. "A cautionary tale of entropic criteria in assessing the validity of the maximum entropy principle." EPL (Europhysics Letters) 126, no. 3 (2019): 38005.
2. Wang, Hao, Qingyuan Zhu, Lufeng Ding, Yan Shen, Chao-Yu Yang, Fang Xu, Chang Shu et al. "Scalable volumetric imaging for ultrahigh-speed brain mapping at synaptic resolution." National Science Review (2019).
3. Fang Xu, Dong-Qing Shi, Pak-Ming Lau, Michael Z. Lin, and Guo-Qiang Bi. "Excitation wavelength optimization improves photostability of ASAP-family GEVIs." Molecular brain 11, no. 1 (2018): 32.
4. Shen, Xu, Xinmei Tian, Tongliang Liu, Fang Xu, and Dacheng Tao. "Continuous Dropout." IEEE transactions on neural networks and learning systems (2017).
5. Gerkin, Richard C., David W. Nauen, Fang Xu, and Guo-Qiang Bi. "Homeostatic regulation of spontaneous and evoked synaptic transmission in two steps." Molecular brain 6, no. 1 (2013): 38.