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This article is part of the supplement: Nineteenth Annual Computational Neuroscience Meeting: CNS*2010

Open Access Poster Presentation

Toward a minimal model of a large spiking cell

Anthony R Kellems and Steven J Cox*

Author Affiliations

Department of Computational & Applied Mathematics, Rice University, Houston, TX, 77005, USA

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BMC Neuroscience 2010, 11(Suppl 1):P145  doi:10.1186/1471-2202-11-S1-P145

The electronic version of this article is the complete one and can be found online at:

Published:20 July 2010

© 2010 Cox and Kellems; licensee BioMed Central Ltd.

Poster Presentation

Experimentalists will soon be able to ascertain the highly nonuniform morphology and channel distributions of the large, pyramidal cells that populate the mammalian cortex. This advance is captured and quantified via tens of thousands of coupled nonlinear ordinary differential equations, per cell. The circuit modeler then asks, "How many of these equations must I keep in order to guarantee a fixed level of accuracy in the input-output map?" We demonstrate that the combined application of Balanced Truncation [1] to the weakly excitable portion of the tree and Principal Orthogonal Decomposition and the Discrete Empirical Interpolation Method [2] to the strongly excitable portion of the cell permit one to reduce the system size by more than one order of magnitude and decrease simulation time by a factor of 5 without sacrificing synaptic specificity in space or time.


NIBIB Grant No. 1T32EB006350-01A1


  1. Kellems AR, Roos D, Xiao N, Cox SJ: Low-dimensional, morphologically accurate models of subthreshold membrane potential.

    J Comput Neurosci 2009, 27:161-176. PubMed Abstract | Publisher Full Text OpenURL

  2. Kellems AR, Chaturantabut S, Sorensen DC, Cox SJ: Morphologically accurate reduced order modeling of spiking neurons,. [] webcite

    TR09-12, CAAM, Rice U 2009. OpenURL