/*-------------------------------------------------------------------------- Author: Thomas Nowotny Institute: Institute for Nonlinear Dynamics University of California San Diego La Jolla, CA 92093-0402 email to: tnowotny@ucsd.edu initial version: 2005-08-17 --------------------------------------------------------------------------*/ #ifndef CN_HHNEURON_CC #define CN_HHNEURON_CC #include "CN_neuron.cc" #include "CN_HHneuronNS.h" HHneuron::HHneuron(int inlabel, double *inp= HH_p): neuron(inlabel, HH_IVARNO, HHNEURON, inp, HH_PNO) { } HHneuron::HHneuron(int inlabel, vector inpos, double *inp= HH_p): neuron(inlabel, HH_IVARNO, HHNEURON, inpos, inp, HH_PNO) { } inline double HHneuron::E(double *x) { return x[idx]; } void HHneuron::derivative(double *x, double *dx) { Isyn= 0.0; forall(den, den_it) { Isyn+= (*den_it)->Isyn(x); } // differential eqn for E, the membrane potential dx[idx]= p[9]*(-(pw3(x[idx+1])*x[idx+2]*p[0]*(x[idx]-p[1])+ pw4(x[idx+3])*p[2]*(x[idx]-p[3])+p[4]*(x[idx]-p[5]) -Isyn-p[8])/p[6]); // diferential eqn for m, the probability for Na channel activation _a= (3.5+0.1*x[idx]) / (1.0-exp(-3.5-0.1*x[idx])); _b= 4.0*exp(-(x[idx]+60.0)/18.0); dx[idx+1]= p[9]*(_a*(1.0-x[idx+1])-_b*x[idx+1]); // differential eqn for h, the probability for Na channel inactivation _a= 0.07*exp(-x[idx]/20.0-3.0); _b= 1.0 / (exp(-3.0-0.1*x[idx])+1.0); dx[idx+2]= p[9]*(_a*(1.0-x[idx+2])-_b*x[idx+2]); // differential eqn for n, the probability for K channel activation _a= (-0.5-0.01*x[idx]) / (exp(-5.0-0.1*x[idx])-1.0); _b= 0.125*exp(-(x[idx]+60.0)/80.0); dx[idx+3]= p[9]*(_a*(1.0-x[idx+3])-_b*x[idx+3]); } void HHneuron::noise(double *x, double *dx) { dx[idx]= p[7]*RG.n(); for (int i= 1; i < iVarNo; i++) dx[idx+i]= 0.0; } #endif