Stochastic versions of the Hodgkin-Huxley equations (Goldwyn, Shea-Brown 2011)

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A Matlab gui for simulating different channel noise models using the Hodgkin-Huxley equations. Methods provided and reviewed in Goldwyn and Shea-Brown (2011) are: current noise, subunit noise, conductance noise, and Markov chain, as well as the standard deterministic Hodgkin-Huxley model.
1 . Goldwyn JH, Shea-Brown E (2011) The what and where of adding channel noise to the Hodgkin-Huxley Equations. PLoS Computational Biology 7(11):e1002247 [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): Hodgkin-Huxley neuron;
Gap Junctions:
Simulation Environment: MATLAB;
Model Concept(s): Action Potential Initiation; Ion Channel Kinetics; Action Potentials;
Implementer(s): Goldwyn, Joshua [jhgoldwyn at];
ReadMe File for Matlab code that accompanies:

JH Goldwyn and E Shea-Brown (2011). The what and where of channel
noise in the Hodgkin-Huxley equations.


* RunHH_gui.m -- a user-friendly gui that generates spike trains for
  deterministic HH equations, Markov chain versions of HH equations,
  and the stochastic versions reviewed in the paper
* StochasticHH_func -- matlab functions that solve HH, stochastic
  versions of HH, and Markov chain version of HH using Euler method,
  Euler-Maruyama, and Gillespie methods.


1) Run Gui
>> RunHH_gui

2) Solve HH equations with subunit noise and plot results in command line
>> Y = Y = StochasticHH_func([0:0.01:100], @(t) 0, [], 100,'Subunit');
>> plot(Y(:,1), Y(:,2)), title('Voltage vs. Time')
>> plot(Y(:,1), Y(:,3)), title('Fraction of Open Na channels vs. Time')
>> plot(Y(:,1), Y(:,4)), title('Fraction of Open K channels vs. Time')

20150416 A minor typo fix sent by Josh Goldwyn where a matrix valued
function AK (line 166) had its second row fixed from
4*alphan(V), -3*alphan(V)-betan(V), 0 , 0, 0; corrected to
4*alphan(V), -3*alphan(V)-betan(V), 2*betan(V), 0, 0;

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