FS_neuron::FS_neuron(const vector<double>& param)
{
// set neuron params from vector
V = param[0];
ENa = param[1]; // mv Na reversal potential
EK = param[2]; // mv K reversal potential
El = param[3]; // mv Leakage reversal potential
gbarNa = param[4]; // mS/cm^2 Na conductance
gbarK = param[5]; // mS/cm^2 K conductance
gl = param[6];
fi = param[7];
Iextmean = param[8];
variance = param[9];
unsigned int seed = chrono::system_clock::now().time_since_epoch().count();
generator = new default_random_engine (seed);
normRand = new normal_distribution <double> (Iextmean, variance);
Iext = (*normRand)(*generator); // Iext generate from normal distribution
m = alpha_m() / (alpha_m() + beta_m());
n = alpha_n() / (alpha_n() + beta_n());
h = alpha_h() / (alpha_h() + beta_h());
gNa = gbarNa*m*m*m*h;
gK = gbarK*n*n*n*n;
Isyn = 0;
countSp = true;
th = -20;
}
double tau_n(const double V_tilde) { return 1./(alpha_n(V_tilde)+beta_n(V_tilde)); }
double n_inf(const double V_tilde) { return alpha_n(V_tilde)/(alpha_n(V_tilde)+beta_n(V_tilde)); }
static inline double tau_n(double V) {
return 1.0 / (alpha_n(V) + beta_n(V));
}
static inline double n_inf(double V) {
return alpha_n(V) / (alpha_n(V) + beta_n(V));
}
double FS_neuron::n_integrate(double dt)
{
double n_0 = alpha_n() / (alpha_n() + beta_n());
double tau_n = 1 / (alpha_n() + beta_n());
return n_0 -(n_0 - n)*exp(-dt/tau_n);
}
