Simple and accurate Diffusion Approximation algor. for stochastic ion channels (Orio & Soudry 2012)

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" ... We derived the (Stochastic Differential Equations) SDE explicitly for any given ion channel kinetic scheme. The resulting generic equations were surprisingly simple and interpretable – allowing an easy, transparent and efficient (Diffusion Approximation) DA implementation, avoiding unnecessary approximations. The algorithm was tested in a voltage clamp simulation and in two different current clamp simulations, yielding the same results as (Markov Chains) MC modeling. Also, the simulation efficiency of this DA method demonstrated considerable superiority over MC methods, except when short time steps or low channel numbers were used."
1 . Orio P, Soudry D (2012) Simple, fast and accurate implementation of the diffusion approximation algorithm for stochastic ion channels with multiple States PLoS One 7(5):e36670 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell;
Brain Region(s)/Organism:
Cell Type(s):
Channel(s): I Na,t; I K;
Gap Junctions:
Simulation Environment: NEURON; MATLAB; SciLab;
Model Concept(s): Action Potentials; Markov-type model; Stochastic simulation;
Implementer(s): Orio, Patricio [patricio.orio at];
Search NeuronDB for information about:  I Na,t; I K;
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