Duane Q. NykampSpring 2008, Math 5447, Mathematical Neuroscience
Spring 2007, Math 2374, IT Multivariable Calculus and Vector Analysis
Spring 2007, Math 1282, Calculus with Biological Emphasis II
Fall 2006, Math 1281, Calculus with Biological Emphasis I
Spring 2006, Math 2374, IT Multivariable Calculus and Vector Analysis
Online readings about Multivariable Calculus and Vector Analysis
D. Q. Nykamp. Pinpointing connectivity despite hidden nodes within stimulus-driven networks. Physical Review E, to appear. PDF
D. Q. Nykamp. Exploiting history-dependent effects to infer network connectivity. SIAM Journal on Applied Mathematics, 68:354-391, 2007. PDF, Publisher's web site
D. Q. Nykamp. A mathematical framework for inferring connectivity in probabilistic neuronal networks. Mathematical Biosciences, 205: 204-251, 2007. PDF, Publisher's web site
D. Q. Nykamp. Revealing pairwise coupling in linear-nonlinear networks. SIAM Journal on Applied Mathematics, 65:2005-2032, 2005. PDF, Publisher's web site
N. Wu, A. Enomoto, S. Tanaka, C.-F. Hsiao, D. Q. Nykamp, E. Izhikevich, and S. H. Chandler. Persistent sodium currents in mesencephalic V neurons participate in burst generation and control of membrane excitability. Journal of Neurophysiology, 93:2710-2722, 2005. Publisher's web site
D. Q. Nykamp. Measuring linear and quadratic contributions to neuronal response. Network: Computation in Neural Systems, 14:673-702, 2003. PDF, Publisher's web site
D. Q. Nykamp. Reconstructing stimulus-driven neural networks from spike times. In S. Becker, S. Thrun, and K. Obermayer, editors, Advances in Neural Information Processing Systems 15, pages 309-316. MIT Press, Cambridge, MA, 2003. PDF, Gzipped Postscript
D. Q. Nykamp. White noise analysis of coupled linear-nonlinear systems. SIAM Journal on Applied Mathematics, 63:1208-1230, 2003. PDF, Gzipped Postscript, Publisher's web site
D. Q. Nykamp. Spike correlation measures that eliminate stimulus effects in response to white noise. Journal of Computational Neuroscience, 14:193-209, 2003. PDF, Gzipped Postscript, Publisher's web site
D. Q. Nykamp and D. L. Ringach. Full identification of a linear-nonlinear system via cross-correlation analysis. Journal of Vision, 2:1-11, 2002. HTML/PDF
E. Haskell, D. Q. Nykamp, and D. Tranchina. Population density methods for large-scale modeling of neuronal networks with realistic synaptic kinetics: Cutting the dimension down to size. Network: Computation in Neural Systems, 12:141-174, 2001. PDF, Publisher's web site
D. Q. Nykamp and D. Tranchina. A population density approach that facilitates large-scale modeling of neural networks: Extension to slow inhibitory synapses. Neural Computation, 13:511-546, 2001. PDF, Gzipped Postscript, Publisher's web site
D. Q. Nykamp and D. Tranchina. Fast neural network simulations with population density methods. Neurocomputing. 32:487-492, 2000. PDF, Gzipped Postscript
D. Q. Nykamp and D. Tranchina. A population density approach that facilitates large-scale modeling of neural networks: analysis and an application to orientation tuning. Journal of Computational Neuroscience, 8:19-50, 2000. PDF, Gzipped Postscript, Publisher's web site
Last Modified: July 2, 2008