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;
}
void FS_neuron::integrate (double dt, double duraction)
{
double t=0;
int i=0;
while (t < duraction) {
V = V + dt*(gNa*(ENa - V) + gK*(EK - V) + gl*(El - V) - Isyn + Iext);
m = alpha_m() / (alpha_m() + beta_m());
n = n_integrate(dt);
h = h_integrate(dt);
gNa = gbarNa*m*m*m*h;
gK = gbarK*n*n*n*n;
Iext = (*normRand)(*generator);
Isyn = 0;
i++;
t+=dt;
}
}
double m_inf(const double V_tilde) { return alpha_m(V_tilde)/(alpha_m(V_tilde)+beta_m(V_tilde)); }
static inline double tau_m(double V) {
return 1.0 / (alpha_m(V) + beta_m(V));
}
static inline double m_inf(double V) {
return alpha_m(V) / (alpha_m(V) + beta_m(V));
}
