Abstract

The neuron models with passive dendritic cables are often used for detailed cortical network simulations (Protopapas et al., 1998; Suarez et al., 1995). For this, the compartment model based on finite volume or finite difference discretization was used. In this paper, we propose an eigenfunction expansion approach combined with singular perturbation and demonstrate that the proposed scheme can achieve an order of magnitude accuracy improvement with the same number of equations. Moreover, it is also shown that the proposed scheme converges much faster to attain a given accuracy. Hence, for a network simulation of the neurons with passive dendritic cables, the proposed scheme can be an attractive alternative to the compartment model, that leads to a low order model with much higher accuracy or that converges faster for a given accuracy.

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