State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University

Faculty

Current Faculty

Ming Li Ph.D.Systems Neuroscience mingli842#163.com

Educational Experience

2014-2018, Ph. D. in Academy for Advanced Interdisciplinary Studies, Peking University, P. R. China

2002-2006, B. Eng. in School of Electrical and Electronic Engineering, North China Electric Power University, P. R. China

Professional Experience

2020-now, Lecturer, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University

2018-2020, Post doctor, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University

2011-2014, Technician, School of Lifesciences, Peking University

2009-2011, Technician, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University

2006-2009, Technician, Institute of Biophysics, Chinese Academy of Science

Research Description

The brain is one of the most complex systems in the universe, and our understanding of the working mechanism of the brain is far lower than our understanding of the universe. This situation is caused by the lack of research tools and methods. Taking the visual system of rodents and non-human primates as the research objects, we study the neural mechanism behind various visual related cognitive phenomena from the aspects of genes, molecules, cells, and behaviors by advancing the most advanced imaging, circuit tracing and operation technologies on living animals.

Publications

1. Jiang, R., Andolina, I.M., Li, M., Tang, S., 2021. Clustered functional domains for curves and corners in cortical area V4. Elife 10. https://doi.org/10.7554/eLife.63798

2. Liu, Y., Li, M., Zhang, X., Lu, Y., Gong, H., Yin, J., Chen, Z., Qian, L., Yang, Y., Andolina, I.M., Shipp, S., Mcloughlin, N., Tang, S., Wang, W., 2020. Hierarchical Representation for Chromatic Processing across Macaque V1, V2, and V4. Neuron 108, 538-550.e5. https://doi.org/10.1016/j.neuron.2020.07.037

3. Zhang, Y., Lee, T.S., Li, M., Liu, F., Tang, S., 2019. Convolutional neural network models of V1 responses to complex patterns. J. Comput. Neurosci. 46, 33–54. https://doi.org/10.1007/s10827-018-0687-7

4. Tang, S., Zhang, Y., Li, Z., Li, M., Liu, F., Jiang, H., Lee, T.S., 2018. Large-scale two-photon imaging revealed super-sparse population codes in the V1 superficial layer of awake monkeys. Elife 7, 1–27. https://doi.org/10.7554/eLife.33370

5. Zhang, J., Liu, X., Xu, W., Luo, W., Li, M., Chu, F., Xu, L., Cao, A., Guan, J., Tang, S., Duan, X., 2018. Stretchable Transparent Electrode Arrays for Simultaneous Electrical and Optical Interrogation of Neural Circuits in Vivo. Nano Lett. 18, 2903–2911. https://doi.org/10.1021/acs.nanolett.8b00087

6. Tang, S., Lee, T.S., Li, M., Zhang, Y., Xu, Y., Liu, F., Teo, B., Jiang, H., 2018. Complex Pattern Selectivity in Macaque Primary Visual Cortex Revealed by Large-Scale Two-Photon Imaging. Curr. Biol. 28, 38-48.e3. https://doi.org/10.1016/j.cub.2017.11.039

7. Li, M., Liu, F., Jiang, H., Lee, T.S., Tang, S., 2017. Long-Term Two-Photon Imaging in Awake Macaque Monkey. Neuron 93, 1049-1057.e3. https://doi.org/10.1016/j.neuron.2017.01.027

8. Li, M., Liu, F., Juusola, M., Tang, S., 2014. Perceptual Color Map in Macaque Visual Area V4. J. Neurosci. 34, 202–217. https://doi.org/10.1523/JNEUROSCI.4549-12.2014