State dependent drug binding to sodium channels in the dentate gyrus (Thomas & Petrou 2013)

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Accession:149174
A Markov model of sodium channels was developed that includes drug binding to fast inactivated states. This was incorporated into a model of the dentate gyrus to investigate the effects of anti-epileptic drugs on neuron and network properties.
Reference:
1 . Thomas EA, Petrou S (2013) Network-specific mechanisms may explain the paradoxical effects of carbamazepine and phenytoin. Epilepsia 54:1195-202 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network; Neuron or other electrically excitable cell; Axon; Channel/Receptor;
Brain Region(s)/Organism:
Cell Type(s): Dentate gyrus granule GLU cell; Dentate gyrus mossy cell; Dentate gyrus basket cell; Dentate gyrus hilar cell;
Channel(s): I Na,t; I A; I_AHP;
Gap Junctions:
Receptor(s): GabaA; AMPA;
Gene(s):
Transmitter(s): Gaba; Glutamate;
Simulation Environment: NEURON; MATLAB;
Model Concept(s): Ion Channel Kinetics; Epilepsy; Calcium dynamics; Drug binding; Markov-type model;
Implementer(s): Thomas, Evan [evan at evan-thomas.net];
Search NeuronDB for information about:  Dentate gyrus granule GLU cell; GabaA; AMPA; I Na,t; I A; I_AHP; Gaba; Glutamate;
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ThomasPetrou2013
Fig 2A
HHrates.m
Q.m
Vclamp.m
                            
function [m_a m_b h_a h_b] = HHrates(V, mode)

if nargin==2 && strcmp(mode, 'inf')==1
	m_a = m_inf(V);
	m_b = h_inf(V);
else
	m_a = m_alpha(V);
	m_b = m_beta(V);
	h_a = h_alpha(V);
	h_b = h_beta(V);
end


function x = m_alpha(V)
x = m_inf(V)./tau_m(V);

function x = m_beta(V)
x = (1-m_inf(V))./tau_m(V);

function x = m_inf(V)
Vhalf   = 16.7159;
a       = 10.4440;
x = 1./(1+exp(-(V+Vhalf)/a));

function x = tau_m(V)
tau_m_A = 0.1068;
tau_m_B = 0.0248;
x = tau_m_A*exp(-tau_m_B*V);

function x = h_alpha(V)
x = h_inf(V)./tau_h(V);

function x = h_beta(V)
x = (1-h_inf(V))./tau_h(V);

function x = h_inf(V)
Vhalf_h = 53.6314;
a_h     = -5.5285;
x = 1./(1+exp(-(V+Vhalf_h)/a_h));

function x = tau_h(V)
tau_h_A = 0.4640;
tau_h_B = 0.0712;
x = tau_h_A*exp(-tau_h_B*V);

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