//-------------------------------------------------------------------------- // 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_VALNEURON_H #define CN_VALNEURON_H #include "CN_neuron.h" #include // parameters of the HH neuron, they are identical for all neurons used // (and therefore made global to save memory) #define Val_IVARNO 4 #define Val_PNO 10 double stdVal_p[Val_PNO]= { 7.15, // 0 - gNa: Na conductance in 1/(mOhms * cm^2) 50.0, // 1 - ENa: Na equi potential in mV 1.43, // 2 - gK: K conductance in 1/(mOhms * cm^2) -95.0, // 3 - EK: K equi potential in mV 0.021, // 4 - gl: leak conductance in 1/(mOhms * cm^2) -55.0, // 5 - El: leak equi potential in mV 0.00572, // 6 - gKl: potassium leakage conductivity -95.0, // 7 - EKl: potassium leakage equi pot in mV 65.0, // 8 - V0: ~ total equi potential (?) 0.143 // 9 - Cmem: membr. capacity density in muF/cm^2 }; double *Val_p= stdVal_p; char *Val_p_text[Val_PNO]= { "0 - gNa: Na conductance in 1/(mOhms * cm^2)", "1 - ENa: Na equi potential in mV", "2 - gK: K conductance in 1/(mOhms * cm^2)", "3 - EK: K equi potential in mV", "4 - gl: leak conductance in 1/(mOhms * cm^2)", "5 - El: leak equi potential in mV", "6 - gKl: potassium leakage conductivity", "7 - EKl: potassium leakage equi pot in mV", "8 - V0: ~ total equi potential (?)", "9 - Cmem: membr. capacity density in muF/cm^2" }; double Val_INIVARS[Val_IVARNO]= { -60.0, // 0 - membrane potential E 0.0529324, // 1 - prob. for Na channel activation m 0.3176767, // 2 - prob. for not Na channel blocking h 0.5961207 // 3 - prob. for K channel activation n }; char *Val_INIVARSTEXT[Val_IVARNO]= { "0 - membrane potential E", "1 - prob. for Na channel activation m", "2 - prob. for not Na channel blocking h", "3 - prob. for K channel activation n" }; // Valentins HH neuron class itself class Valneuron: public neuron { private: double Isyn; double _a, _b; public: Valneuron(int, double *); Valneuron(int, tnvector, double *); ~Valneuron() { } inline virtual double E(double *); virtual void derivative(double *, double *); }; #endif