Du, BosenSorensen, DannyCox, Steven J.2015-01-082015-01-082014Du, Bosen, Sorensen, Danny and Cox, Steven J.. "Model reduction of strong-weak neurons." <i>Frontiers in Computational Neuroscience,</i> 8, (2014) Frontiers Media: http://dx.doi.org/10.3389/fncom.2014.00164.https://hdl.handle.net/1911/78907We consider neurons with large dendritic trees that are weakly excitable in the sense that back propagating action potentials are severly attenuated as they travel from the small, strongly excitable, spike initiation zone. In previous work we have shown that the computational size of weakly excitable cell models may be reduced by two or more orders of magnitude, and that the size of strongly excitable models may be reduced by at least one order of magnitude, without sacrificing the spatio-temporal nature of its inputs (in the sense we reproduce the cell's precise mapping of inputs to outputs). We combine the best of these two strategies via a predictor-corrector decomposition scheme and achieve a drastically reduced highly accurate model of a caricature of the neuron responsible for collision detection in the locust.engThis is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.Journal articleLGMDpredictor-correctorquasi-activeproper orthogonal decompositiondiscrete empirical interpolationhttp://dx.doi.org/10.3389/fncom.2014.00164