陶乐天 Emailtaolt@mail.cbi.pku.edu.cn
联系电话
所在院系北京大学生命科学学院
实验室主页研究员


详细描述
1986—1990年哈佛大学物理系学士学位
1990—1995年芝加哥大学物理系博士学位
1995—1997年剑桥大学应用数学与理论物理系博士后
1997—2000年哥伦比亚大学天文系NSF博士后奖
2000—2003年纽约大学科朗研究院 副研究员
2003—2007年新泽西理工学院数学科学系助理教授
Select Recent Publications：
1. Tao, L., Praissman, J., and Sornborger, A.T., “Improved dimensionally-reduced visual cortical network using stochastic noise modeling,” J. Comput. Neurosci., 32, 367-376, 2012
2. Tao, L., Lauderdale, J.D. and Sornborger, A.T., “Mapping functional connectivity between neuronal ensembles with larval zebrafish transgenic for a ratiometric calcium indicator,” Frontiers in Neural Circuits 5, 2, 2011
Carceras, M.J., Carrillo, J.A., and Tao, L., “A numerical solver for a nonlinear Fokker-Planck equation representation of neuronal network dynamics,” J. Comput. Phys. 230, 1084, 2011
3. Tao, L. and Sornborger, A.T. “Dimensionally-reduced visual cortical network model predicts network response and connects system- and cellular-level descriptions,” J. Comput. Neurosci. 28, 91-106, 2010.
4. Kovacic, G., Tao, L., Rangan, A.V., and Cai, D., “Fokker-Planck description of conductance-based integrate-and-fire neuronal networks,” Phys. Rev. E 80, 021904, 2009
5. Cai, D., Tao, L., Rangan, A.V. and McLaughlin, D.W., Kinetic theory for neuronal network dynamics, Comm. Math. Sci., 4, 97-127, 2006
6. Tao, L., Cai, D., McLaughlin, D., Shelley, M. and Shapley, R., Orientation selectivity in visual cortex by fluctuation-controlled criticality, Proc. Natl. Acad. Sci. USA, 103, 12911-12916, 2006
7. Cai, D., Tao, L., and McLaughlin, D., An embedded network approach for scale-up of fluctuation-driven systems with preservation of spike information, Proc. Natl. Acad. Sci. USA, 101, 14288-14293, 200
8. Cai, D., Tao, L., Shelley, M. and McLaughlin, D., An effective kinetic representation of fluctuation-driven neuronal networks with application to simple & complex cells in primary visual cortex, Proc. Natl. Acad. Sci. USA, 101, 7757-7762, 2004
9. Tao, L., Shelley, M., McLaughlin, D. and Shapley, R. An egalitarian network model for the emergence of Simple and Complex cells in visual cortex,Proc. Natl. Acad. Sci. USA,101, 366-371, 2004