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

Faculty

Current Faculty

Wu Li Ph.D.Visual Cortical Processing liwu#bnu.edu.cn

Educational Experience

1989 – 1994, Shanghai Institute of Physiology, Chinese Academy of Sciences, Shanghai, China. (Ph.D. in Neurophysiology, 1994)

1984 – 1989, University of Science and Technology of China, Hefei, China. (B.S. in Biophysics, 1989)

Professional Experience

Dec 2011 – present, Director, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China

Aug 2012 – present, Director, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China

June 2007 – present, Professor, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China

June 1999 – June 2007, Research Associate/Research Assistant Professor, Laboratory of Neurobiology, The Rockefeller University, New York, USA

July 1996 – May 1999, Research Associate, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany

August 1994 – June 1996, Postdoctoral Fellow, Division of Neurobiology, University of California, Berkeley, USA.

Research Description

Wu Li’s research group studies visual image processing in the brain. The ongoing projects focus on how image components are grouped and segmented in multilayered cortical circuitry to form coherent visual percepts; how cognitive and emotional factors influence visual information processing; and how training and experience remodel cortical processes and reshape visual perception.

Publications

1. Jing, R., Yang, C., Huang, X., and Li, W. (2021). Perceptual learning as a result of concerted changes in prefrontal and visual cortex. Current Biology.

2. Zhang, E., and Li, W. (2020). Improved fidelity of orientation perception: a learning effect dissociable from enhanced discriminability. Scientific Reports 10, 6572.

3. Li, Z., Yan, A., Guo, K., and Li, W. (2019). Fear-related signals in the primary visual cortex. Current Biology 29, 4078-4083.

4. Guo, K., Li, Z., Yan, Y., and Li, W. (2019). Viewing heterospecific facial expressions: an eye-tracking study of human and monkey viewers. Experimental Brain Research 237, 2045-2059.

5. Gong, X.J., Li, W., and Liang, H.L. (2019). Spike-field Granger causality for hybrid neural data analysis. Journal of Neurophysiology 122, 809-822.

6. Damon, F., Li, Z., Yan, Y., Li, W., Guo, K., Quinn, P.C., Pascalis, O., and Méary, D. (2019). Preference for attractive faces is species-specific. Journal of Comparative Psychology 133, 262-271.

7. Yan, Y., Zhaoping, L., and Li, W. (2018). Bottom-up saliency and top-down learning in the primary visual cortex of monkeys. Proceedings of the National Academy of Sciences of the United States of America 115, 10499-10504.

8. Hu, M., Li, W., and Liang, H. (2018). A copula-based granger causality measure for the analysis of neural spike train data. IEEE/ACM Transactions on Computational Biology and Bioinformatics 15, 562-569.

9. Liang, H., Gong, X., Chen, M., Yan, Y., Li, W., and Gilbert, C.D. (2017). Interactions between feedback and lateral connections in the primary visual cortex. Proceedings of the National Academy of Sciences 114, 8637-8642.

10. Li, W., and Gilbert, C.D. (2017). Perceptual learning: Neural mechanisms. In Reference Module in Neuroscience and Biobehavioral Psychology (Elsevier).

11. Kuai, S.G., Li, W., Yu, C., and Kourtzi, Z. (2017). Contour integration over time: Psychophysical and fMRI evidence. Cerebral Cortex 27, 3042-3051.

12. Chen, R., Wang, F., Liang, H., and Li, W. (2017). Synergistic processing of visual contours across cortical layers in V1 and V2. Neuron 96, 1388-1402.

13. Wang, R., Wang, J., Zhang, J.-Y., Xie, X.-Y., Yang, Y.-X., Luo, S.-H., Yu, C., and Li, W. (2016). Perceptual learning at a conceptual level. Journal of Neuroscience 36, 2238-2246.

14. Wang, F., Huang, J., Lv, Y., Ma, X., Yang, B., Wang, E., Du, B., Li, W., and Song, Y. (2016). Predicting perceptual learning from higher-order cortical processing. NeuroImage 124, 682-692.

15. Li, W. (2016). Perceptual learning: Use-dependent cortical plasticity. Annual Review of Vision Science 2, 109-130.

16. Hu, M., Li, M., Li, W., and Liang, H. (2016). Data on copula modeling of mixed discrete and continuous neural time series. Data in Brief 7, 1364-1369.

17. Hu, M., Li, M., Li, W., and Liang, H. (2016). Joint analysis of spikes and local field potentials using copula. NeuroImage 133, 457-467.

18. Yan, Y., Zhang, E., and Li, W. (2015). Neural mechanisms of visual perceptual learning. Chinese Bulletin of Life Sciences 27, 867-875.

19. Wang, F., Chen, M., Yan, Y., Zhaoping, L., and Li, W. (2015). Modulation of neuronal responses by exogenous attention in macaque primary visual cortex. Journal of Neuroscience 35, 13419-13429.

20. Abe, H., McManus, J.N.J., Ramalingam, N., Li, W., Marik, S.A., Meyer zum Alten Borgloh, S., and Gilbert, C.D. (2015). Adult cortical plasticity studied with chronically implanted electrode arrays. Journal of Neuroscience 35, 2778-2790.

21. Yan, Y., Rasch, M.J., Chen, M., Xiang, X., Huang, M., Wu, S., and Li, W. (2014). Perceptual training continuously refines neuronal population codes in primary visual cortex. Nature Neuroscience 17, 1380-1387.

22. Meary, D., Li, Z., Li, W., Guo, K., and Pascalis, O. (2014). Seeing two faces together: preference formation in humans and rhesus macaques. Animal Cognition 17, 1107-1119.

23. Chen, M., Yan, Y., Gong, X., Gilbert, C.D., Liang, H., and Li, W. (2014). Incremental integration of global contours through interplay between visual cortical areas. Neuron 82, 682-694.

24. Zhang, E., Zhang, G.-L., and Li, W. (2013). Spatiotopic perceptual learning mediated by retinotopic processing and attentional remapping. European Journal of Neuroscience 38, 3758-3767.

25. Ramalingam, N., McManus, J.N.J., Li, W., and Gilbert, C.D. (2013). Top-down modulation of lateral interactions in visual cortex. Journal of Neuroscience 33, 1773-1789.

26. Piëch, V., Li, W., Reeke, G.N., and Gilbert, C.D. (2013). Network model of top-down influences on local gain and contextual interactions in visual cortex. Proceedings of the National Academy of Sciences of the United States of America 110, E4108-4117.

27. McFarland, R., Roebuck, H., Yan, Y., Majolo, B., Li, W., and Guo, K. (2013). Social interactions through the eyes of macaques and humans. PLOS One 8, e56437.

28. Li, W., and Gilbert, C.D. (2013). Perceptual learning and plasticity in primary visual cortex. In The New Visual Neurosciences, J.S. Werne, and L.M. Chalupa, eds. (Cambridge: MIT Press), pp. 1001-1012.

29. Gilbert, C.D., and Li, W. (2013). Top-down influences on visual processing. Nature Reviews Neuroscience 14, 350-363.

30. Zhang, E., Zhang, G.-L., and Li, W. (2012). Spatiotopic location specificity of perceptual learning in orientation discrimination. Journal of Vision 12, 1140.

31. Xing, D., Shen, Y., Burns, S., Yeh, C.-I., Shapley, R., and Li, W. (2012). Stochastic generation of gamma-band activity in primary visual cortex of awake and anesthetized monkeys. Journal of Neuroscience 32, 13873-13880.

32. Pan, Y., Chen, M., Yin, J., An, X., Zhang, X., Lu, Y., Gong, H., Li, W., and Wang, W. (2012). Equivalent representation of real and illusory contours in macaque V4. Journal of Neuroscience 32, 6760-6770.

33. Gilbert, C.D., and Li, W. (2012). Adult visual cortical plasticity. Neuron 75, 250-264.

34. McManus, J.N.J., Li, W., and Gilbert, C.D. (2011). Adaptive shape processing in primary visual cortex. Proceedings of the National Academy of Sciences of the United States of America 108, 9739-9746.