Dr. Sheng Li is an associate professor with tenure at the School of Psychological and Cognitive Sciences, Peking University. He received his B.Eng degree from Beijing University of Posts and Telecommunications, China, in 1998 and D.Phil degree from the University of Sussex, UK, in 2006. From 2006 to 2009, he was a postdoctoral research fellow at the School of Psychology, University of Birmingham, UK. His research interests cover from cognitive neuroscience with functional brain imaging techniques (fMRI, EEG, MEG) to theoretical modelling of neural information processing in the human brain. Currently, he focuses on the neural mechanism of human visual category learning and perceptual decision making.
List of Publications
Jia, K., Xue, X., Lee, J.H., Fang, F., Zhang, J., & Li, S. (2018). Visual perceptual learning modulates decision network in the human brain: the evidence from psychophysics, modeling, and functional magnetic resonance imaging. Journal of Vision. 18, 9.
Pirrone, A., Wen, W., Li, S. Baker, D., & Milne, E. (2018). Autistic traits in the neurotypical population do not predict increased response conservativeness in perceptual decision making. Perception. 47, 1081-1096.
Wang, Q., Hu, Y., Shi, D., Zhang, Y., Zou, X., Li, S., Fang, F., Yi, L. (2018). Children with autism spectrum disorder prefer looking at repetitive movements in a preferential looking paradigm. Journal of Autism and Developmental Disorders, doi: 10.1007/s10803-018-3546-5
Wang, L., Li, S., Zhou, X., & Theeuwes, J. (2018). Stimuli that signal the availability of reward break into attentional focus. Vision research, 144, 20-28.
Li, T., Wang, X., Pan,J., Feng, S., Gong, M., Wu, Y., Li, G., Li, S.*, & Yi, L.* (2017) Reward learning modulates the attentional processing of faces in children with and without autism spectrum disorder. Autism Research, DOI: 10.1002/aur.1823 (*co-corresponding authors)
Gong, M.†, Jia, K.†, & Li, S. (2017). Perceptual competition promotes suppression of reward salience in behavioral selection and neural representation. Journal of Neuroscience, 37(26): 6242-6252. (†co-first authors)
Chen, N., Bi, T., Zhou, T., Li, S., Liu, Z., & Fang, F. (2015). Sharpened cortical tuning and enhanced cortico-cortical communication contribute to the long-term neural mechanisms of visual motion perceptual learning. Neuroimage, 115, 17-29.
Wuyun, G., Shu, M., Cao, Z., Huang, W., Zou, X., Li, S., Zhang, X., Luo, H., & Wu, Y. (2014). Neural representations of the self and the mother for Chinese individuals. PloS ONE, 9(3), e91556.
Li, S.†, Mayhew, S. D.†, & Kourtzi, Z. (2012). Learning shapes spatiotemporal brain patterns for flexible categorical decisions. Cerebral Cortex, 22(10), 2322-2335.(†co-first authors)
Mayhew, S. D.†, Li, S.†, & Kourtzi, Z. (2012). Learning acts on distinct processes for visual form perception in the human brain. Journal of Neuroscience, 32(3), 775-786.(†co-first authors)
Li, S. (2011). Multivariate pattern analysis in functional brain imaging. Acta Physiologica Sinica, 63(5), 472-476.
Peterson, M. F., Das, K., Sy, J. L., Li, S., Giesbrecht, B., Kourtzi, Z., & Eckstein, M. P. (2010). Ideal observer analysis for task normalization of pattern classifier performance applied to EEG and fMRI data. Journal of the Optical Society of America A, 27(12), 2670-2683.
Chen, D.†, Li, S.†, Kourtzi, Z., & Wu, S. (2010). Behavior-constrained support vector machines for fMRI data analysis. IEEE Transactions on Neural Networks, 21(10), 1680-1685.(†co-first authors)
Mayhew, S. D., Li, S., Storrar, J. K., Tsvetanov, K. A., & Kourtzi, Z. (2010). Learning shapes the representation of visual categories in the aging human brain. Journal of Cognitive Neuroscience, 22(12), 2899-2912.
Duncan, K. K., Hadjipapas, A., Li, S., Kourtzi, Z., Bagshaw, A., & Barnes, G. (2010). Identifying spatially overlapping local cortical networks with MEG. Human Brain Mapping, 31(7), 1003-1016.
Li, S., Mayhew, S. D., & Kourtzi, Z. (2009). Learning shapes the representation of behavioral choice in the human brain. Neuron, 62(3), 441-452.
Preston, T. J., Li, S., Kourtzi, Z., & Welchman, A. E. (2008). Multivoxel pattern selectivity for perceptually relevant binocular disparities in the human brain. Journal of Neuroscience, 28(44), 11315-11327.
Ostwald, D., Lam, J. M., Li, S., & Kourtzi, Z. (2008). Neural coding of global form in the human visual cortex. Journal of Neurophysiology, 99(5), 2456-2469.
Li, S., Ostwald, D., Giese, M., & Kourtzi, Z. (2007). Flexible coding for categorical decisions in the human brain. Journal of Neuroscience, 27(45), 12321-12330.
Li, S., & Wu, S. (2007). Robustness of neural codes and its implication on natural image processing. Cognitive Neurodynamics, 1(3), 261-272.
Williams, P., Li, S., Feng, J., & Wu, S. (2007). A geometrical method to improve performance of the support vector machine. IEEE Transactions on Neural Networks, 18(3), 942-947.
Li, S., & Wu, S. (2005). On the variability of cortical neural responses: a statistical interpretation. Neurocomputing, 65, 409-414.
Book Chapters and Conference Papers
Pirrone,A., Zhang,Q., Li,S. (2016) Dissociable effects of cue validity on bias formation and reversal. Papafragou, A., Grodner, D., Mirman, D., & Trueswell, J.C. (Eds.) Proceedings of the 38th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society..
Das,K., Li,S., Giesbrecht,B., Kourtzi,K., Eckstein,MP. (2010) Predicting perceptual performance from neural activity. In Advances in Understanding Human Performance: Neuroergonomics, Human Factors Design, and Special Populations. T. Marek, W. Karwowski, V. Rice Eds. CRC Press.
Williams,P., Li,S., Feng, J. and Wu,S. (2005) Scaling the kernel function to improve performance of the support vector machine. Advances in Neural Networks - ISNN 2005, Lecture Notes in Computer Science 3496: pp. 831-836.