Hodgkin-Huxley simplifed 2D and 3D models (Lundstrom et al. 2009)

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Accession:117330
"Neuronal responses are often characterized by the firing rate as a function of the stimulus mean, or the f–I curve. We introduce a novel classification of neurons into Types A, B−, and B+ according to how f–I curves are modulated by input fluctuations. ..."
Reference:
1 . Lundstrom BN, Famulare M, Sorensen LB, Spain WJ, Fairhall AL (2009) Sensitivity of firing rate to input fluctuations depends on time scale separation between fast and slow variables in single neurons J Comput Neurosci
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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):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: C or C++ program; XPPAUT;
Model Concept(s): Temporal Pattern Generation; Simplified Models; Bifurcation;
Implementer(s):
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LundstromEtAl2009
readme.html
hh2TypeAnoiseTau.ode
hh3d.c
screenshot.jpg
                            
# Simplified 2D HH model
# formatted for use with XPPAUT

# Parameters as in the model of Figure 8, Lundstrom et al, J Comp Neurosci
# Note: the z variable introduces stimulus noise and must be removed for bifurcation analysis

wiener nz
v' = -(Gl*(v - El) + Gk*n^4*(v - Ek) + Gna*minf^3*h*(v - Ena))/cm + i/cm + z
n' = (ninf - n) / ntau  
z'=-z/tau + nsig*sqrt(2/tau)*nz
par tau=1

par i=0, mVh=-40,mk=7,nVh=-45,nk=15, Gna=50,Gk=36,Gl=5,Ena=50,Ek=-77,El=-54,cm=1
par nsig=0

par Cbase=3,Camp=50,Vmax=-50,sig=1

ntau = Cbase + Camp*exp(-(Vmax - V)^2/sig^2)
ninf = 1.0 / (1+exp( (nVh - v)/nk) )
minf = 1.0 / (1+exp( (mVh - v)/mk) )
h = .89 - 1.1*n

init v=-65,n=0.3

@ meth=euler,total=20ee0,dt=.005,nout=50