On stochastic diff. eq. models for ion channel noise in Hodgkin-Huxley neurons (Goldwyn et al. 2010)

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" ... We analyze three SDE models that have been proposed as approximations to the Markov chain model: one that describes the states of the ion channels and two that describe the states of the ion channel subunits. We show that the former channel-based approach can capture the distribution of channel noise and its effect on spiking in a Hodgkin-Huxley neuron model to a degree not previously demonstrated, but the latter two subunit-based approaches cannot. ..."
1 . Goldwyn JH, Imennov NS, Famulare M, Shea-Brown E (2011) Stochastic differential equation models for ion channel noise in Hodgkin-Huxley neurons. Phys Rev E Stat Nonlin Soft Matter Phys 83:041908 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell; Channel/Receptor;
Brain Region(s)/Organism:
Cell Type(s): Squid axon;
Channel(s): I Sodium; I Potassium;
Gap Junctions:
Simulation Environment: FORTRAN;
Model Concept(s): Ion Channel Kinetics; Action Potentials; Methods; Noise Sensitivity;
Implementer(s): Goldwyn, Joshua [jhgoldwyn at gmail.com];
Search NeuronDB for information about:  I Sodium; I Potassium;

# Run all models in voltage clamp (voltage clamp to 20 mV) for 100 ms
# (1E4 time steps with 0.01ms step size)
# Write out time, voltage, proportion of open Na channels and
# proportion of open K channels

for ((i=0;i<=END;i++)); do
    echo running method $i
    ./HH_run $i 100 1E4 0.01 100 20. 0. 0. 0. 1 1 123 > ${i}_output.txt

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