Duane Q. Nykamp

Assistant Professor
School of Mathematics

Contact Information

Duane Nykamp
School of Mathematics
University of Minnesota
127 Vincent Hall, 206 Church St. S.E.
Minneapolis, MN 55455

Office: 202 Vincent Hall
Phone: (612) 625-0338
Department Fax: (612) 626-2017
E-mail: nykamp@math.umn.edu
Web site: http://www.math.umn.edu/~nykamp/

Teaching

Fall 2008, Math 5485, Introduction to Numerical Methods I

Fall 2008, Math 5447, Mathematical Neuroscience

Past courses

Online readings about Multivariable Calculus and Vector Analysis

Curriculum Vitae

PDF

Research Interests

Mathematical neuroscience

developing methods to characterize biological neural networks through analysis of single and multiple neuron recordings
modeling the neural networks of the primary visual cortex
developing efficient methods for neural network simulation

Publications

C.-Y. Liu and D. Q. Nykamp. A kinetic theory approach to capturing interneuronal correlation: The feedforward case. Journal of Computational Neuroscience, to appear. PDF

M. E. Koelling and D. Q. Nykamp. Computing linear approximations to nonlinear neuronal response. Network: Computation in Neural Systems, to appear. PDF

D. Q. Nykamp. A stimulus-dependent connectivity analysis of neuronal networks. Journal of Mathematical Biology, 2008. PDF, Publisher's web site

D. Q. Nykamp. Pinpointing connectivity despite hidden nodes within stimulus-driven networks. Physical Review E, 78:021902, 2008. PDF, Publisher's web site

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

Professional and Educational Experience

2003-present, Assistant Professor, School of Mathematics, University of Minnesota
2000-2003, NSF Mathematical Sciences Postdoctoral Fellow, Department of Mathematics, UCLA
2001-2002, CAM Assistant Professor, Department of Mathematics, UCLA
May 2000, Ph.D. Mathematics, Courant Institute of Mathematical Sciences, New York University
December 1994, B.S., Honors Mathematics and General Physics, University of Michigan

Last Modified: September 25, 2008