姓 名:
李晟
职 称:
研究员 博导
研究领域:
认知神经科学
通信地址:
北京大学王克桢楼 100080
电子邮件:
sli@pku.edu.cn
个人主页:
http://mgv.pku.edu.cn/?co=posts&ac=faculty&catalog=cnpiintro&pname=cn_Li_Sheng
个人简历
研究兴趣
发表论著
长聘副教授,兼任北京大学机器感知与智能教育部重点实验室及麦戈文脑科学研究所研究员,博士生导师。1998年毕业于北京邮电大学计算机科学与技术系,获工学学士学位。2006年毕业于英国萨塞克斯大学信息学系,获计算机科学与人工智能方向博士学位。2006年至2009年在英国伯明翰大学心理学院从事博士后研究。2009年入选“北京大学优秀青年人才”计划,并获“百人计划”特聘研究员职位。2012年入选教育部“新世纪优秀人才支持计划”。2013年获北京大学黄廷芳/信和青年杰出学者奖。现任BMC Neuroscience期刊编委会成员。
李晟研究员主要从事认知神经科学方向的研究,包括视觉知觉、决策、与学习的神经机制,功能性脑成像方法与建模。主要研究手段包括心理物理学,功能性磁共振成像(fMRI),脑电(EEG),以及机器学习等计算分析方法。李晟研究员在国际学术刊物上发表论文多篇,包括 Neuron,Journal of Neuroscience,Cerebral Cortex,Journal of Experimental Psychology: Human Perception and Performance,IEEE Transactions on Neural Networks等权威杂志。其研究受国家自然科学基金,科技部,教育部等多个项目支持。
近年来科研项目:
2011–2013,基金委面上项目,视觉分类决策过程中不确定性的神经机制,项目负责人。
2012–2015,科技部863课题,脑机协同视听觉信息处理关键技术及平台研究,子课题负责人。
2013–2016,基金委面上项目,利用多模态脑成像技术研究形状学习的神经机制,项目负责人。
2013–2017,基金委重点项目,人类视觉信息加工的可塑性研究,主要参与人。
2015–2018,基金委面上项目,奖赏学习对基本认知过程的调节机制,项目负责人。
1. 知觉学习与知觉决策。
2. 奖赏学习的认知机制。
3. 功能性脑成像。
英文论著
Journal Papers
Li, Y., Wang, Y., & Li, S. (2019). Recurrent processing of contour integration in the human visual cortex as revealed by fMRI-guided TMS. Cerebral Cortex, 29(1): 17–26.
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. (2018). Single-trial dynamics explain magnitude sensitive decision making. BMC neuroscience, 19(1), 54.
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
Wen, W., Hou, Y., & Li, S. (2018) Memory guidance in distractor suppression is governed by the availability of cognitive control. Attention, Perception, & Psychophysics, 80, 1157–1168.
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)
Jia, K., & Li, S. (2017). Motion direction discrimination training reduces perceived motion repulsion. Attention, Perception, & Psychophysics, 79:878–887.
Gong, M., Yang, F., & Li, S. (2016). Reward association facilitates distractor suppression in human visual search. European Journal of Neuroscience, 43:942-953.
Li, Y., & Li, S. (2015). Contour integration, attentional cuing, and conscious awareness: An investigation on the processing of collinear and orthogonal contours. Journal of Vision, 15(16):10, 1–16.
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.
Xue, X., Zhou, X., & Li, S. (2015). Unconscious reward facilitates motion perceptual learning. Visual Cognition, 23(1-2), 161-178.
Yang, F., Wu, Q., & Li, S. (2014). Learning-induced uncertainty reduction in perceptual decisions is task-dependent. Frontiers in Human Neuroscience, 8, 282.
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.
Gong, M., & Li, S. (2014). Learned reward association improves visual working memory. Journal of Experimental Psychology: Human Perception and Performance, 40(2): 841-856.
Mu, T., & Li, S. (2013). The neural signature of spatial frequency-based information integration in scene perception. Experimental Brain Research, 227(3), 367-377.
Li, S., & Yang, F. (2012). Task‐dependent uncertainty modulation of perceptual decisions in the human brain. European Journal of Neuroscience, 36(12), 3732-3739.
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.
中文论著
龚梦园, 贾珂,李晟. (2018)奖赏学习对视觉注意的调控. 应用心理学, 24(2): 99-112.
李晟(2012),结合功能性脑成像与模式分类方法研究人脑分类决策的神经机制。唐孝威、郭爱克等主编,《神经信息学与计算神经科学》,210-228页,浙江科学技术出版社。