TTX-R Na+ current effect on cell response (Herzog et al 2001) (MATLAB)

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Accession:120117
"Small dorsal root ganglion (DRG) neurons, which include nociceptors, express multiple voltage-gated sodium currents. In addition to a classical fast inactivating tetrodotoxin-sensitive (TTX-S) sodium current, many of these cells express a TTX-resistant (TTX-R) sodium current that activates near -70 mV and is persistent at negative potentials. To investigate the possible contributions of this TTX-R persistent (TTX-RP) current to neuronal excitability, we carried out computer simulations using the Neuron program with TTX-S and -RP currents, fit by the Hodgkin-Huxley model, that closely matched the currents recorded from small DRG neurons. ..." See paper for more and details.
Reference:
1 . Herzog RI, Cummins TR, Waxman SG (2001) Persistent TTX-resistant Na+ current affects resting potential and response to depolarization in simulated spinal sensory neurons. J Neurophysiol 86:1351-64 [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,p; I Na,t; I K;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: MATLAB;
Model Concept(s): Ion Channel Kinetics; Nociception;
Implementer(s): Andersson, Thomas [toma at math.su.se];
Search NeuronDB for information about:  I Na,p; I Na,t; I K;
clear
% MAIN SIMULATION MODULE - SUBFUNCTIONS BELOW
Cm=0.81; % Capacitance
Ena=62.94; % Reversal potential Na (mV)
Ek=-92.34; % Reversal potential K (mV)
El=-54.3; % Reversal potential Leak (mV)
gnats=35.135; % Peak Conductance Na TTX-S (mS/cm2)
gnatr=6.9005; % Peak Conductance Na TTX-R (mS/cm2)
gkdr=2.1; % Peak Conductance Potassium (mS/cm2)
gl=0.14; % Peak Conductance Leak (mS/cm2)
dt=.1; % Integration step (ms)
tmax=1000; % Simulation time (ms)
T=1:dt:tmax; % Timeline (ms)
% Memory allocation;
Inats(size(T))=0;
Inatr(size(T))=0;
Ikdr(size(T))=0;
If(size(T))=0;
Il(size(T))=0;
Is(size(T))=0;
ms(size(T))=0;
hs(size(T))=0;
mr(size(T))=0;
hr(size(T))=0;
sr(size(T))=0;
n(size(T))=0;
f(size(T))=0;
% Initial values
Vm(1)=-65;
[tmNats,pmNats,thNats,phNats]=Nats(Vm(1));
ms(1)=pmNats;
hs(1)=phNats;
[tmNatr,pmNatr,thNatr,phNatr,tsNatr,psNatr]=Natr(Vm(1));
mr(1)=pmNatr;
hr(1)=phNatr;
sr(1)=psNatr;
[tnKdr,pnKdr]=Kdr(Vm(1));
n(1)=pnKdr;
for i=1:size(T,2)
    Inats(i)=gnats*(ms(i)^3)*hs(i)*(Vm(i)-Ena);
    Inatr(i)=gnatr*mr(i)*hr(i)*sr(i)*(Vm(i)-Ena);
    Ikdr(i)=gkdr*n(i)*(Vm(i)-Ek);
    Il(i)=gl*(Vm(i)-El);
    Vm(i+1)=Vm(i)-(dt/Cm)*(Inats(i)+Inatr(i)+Ikdr(i)+Il(i));
    [tmNats,pmNats,thNats,phNats]=Nats(Vm(i+1));
    [dpms]=dp(dt,tmNats,pmNats,ms(i));
    ms(i+1)=ms(i)+dpms;
    [dphs]=dp(dt,thNats,phNats,hs(i));
    hs(i+1)=hs(i)+dphs;
    [tmNatr,pmNatr,thNatr,phNatr,tsNatr,psNatr]=Natr(Vm(i+1));
    [dpmr]=dp(dt,tmNatr,pmNatr,mr(i));
    mr(i+1)=mr(i)+dpmr;
    [dphr]=dp(dt,thNatr,phNatr,hr(i));
    hr(i+1)=hr(i)+dphr;
    [dphs]=dp(dt,tsNatr,psNatr,sr(i));
    sr(i+1)=sr(i)+dphs;
    [tnKdr,pnKdr]=Kdr(Vm(i+1));
    [dpkdr]=dp(dt,tnKdr,pnKdr,n(i));
    n(i+1)=n(i)+dpkdr;
end
plot(Vm)

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