Associate Professor of Neural Science, NYU Shanghai
Email: sukbin.lim@nyu.edu
Phone: 021-2059-5244
Office: Room S707, 567 West Yangsi Road, Shanghai
Computational neuroscience, Learning and memory, Network interactions, Dynamical systems
Utilizing a broad spectrum of dynamical systems theory, the theory of stochastic processes, and information and control theories, Professor Lim develops and analyzes neural network models and synaptic plasticity rules for learning and memory. It accompanies the analysis of neural data and collaboration with experimentalists to provide and test biologically plausible models.
2009 Ph. D., Mathematics, New York University
2003 B.S., Mathematics and Physics, Seoul National University
2012 – 2015 Postdoctoral Fellow, The University of Chicago
2009 – 2012 Postdoctoral Fellow, University of California, Davis
2009 Sandra Bleistein Prize
- S. Lim (2019) Mechanism underlying sharpening of visual response dynamics with familiarity, eLife, 8: e44098.
- S.J. Sylvester, M.M. Lee, A.D. Ramirez, S. Lim, M.S. Goldman, E.R.F. Aksay (2017) Population-scale organization of cerebellar granule neuron signaling during a visuomotor behavior, Scientific Reports, 7, 16240.
- S. Lim, J.L. Mckee, D.J. Freedman, Y. Amit, D.L. Sheinberg, N. Brunel (2015) Inferring learning rules from distributions of firing rates in cortical neurons, Nature Neuroscience, 18: 1804-1810.
- S. Lim [co-corresponding author], M.S. Goldman (2014) Balanced cortical microcircuitry for spatial working memory based on corrective feedback control, Journal of Neuroscience, 34: 6790-6806.
- S. Lim, M.S. Goldman (2013) Balanced cortical microcircuitry for maintaining information in working memory, Nature Neuroscience, 16: 1306-1314.
- S. Lim, M.S. Goldman (2012) Noise tolerance of attractor and feedforward memory models, Neural Computation, 24: 332-390.
- S. Lim [corresponding author], J. Rinzel (2010) Noise-induced transitions in slow wave neuronal dynamics, Journal Computational Neuroscience, 28: 1-17.