/*--------------------------------------------------------------------------
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_ABSYNAPSE_CC
#define CN_ABSYNAPSE_CC
#include "CN_synapse.cc"
// This is the constructor to be used by derived classes passing the new
// internal var number, parameter number and type tag
absynapse::absynapse(neuron *insource, neuron *intarget,
double ingsyn, double inEsyn, double inEpre,
double inasyn, double inbsyn, double inVslope,
double nslevel,
int inIVARNO, int inPNO, int inTYPE):
synapse(insource, intarget, inIVARNO, inPNO, inTYPE)
{
p[0]= ingsyn; // gsyn strength of synapse
p[1]= inEsyn; // Esyn reversal potential in mV
p[2]= inEpre; // Epre presyn threshold potential in mV
p[3]= inasyn; // alpha timescale in 1/msec
p[4]= inbsyn; // beta timescale in 1/msec
p[5]= inVslope; // slope of activation
p[6]= nslevel; // noise level
}
// This is the constructor to be used directly ...
absynapse::absynapse(neuron *insource, neuron *intarget,
double ingsyn, double inEsyn, double inEpre,
double inasyn, double inbsyn, double inVslope,
double nslevel):
synapse(insource, intarget, ABSYNIVARNO, ABSYNPNO, ABSYN)
{
p[0]= ingsyn; // gsyn strength of synapse
p[1]= inEsyn; // Esyn reversal potential in mV
p[2]= inEpre; // Epre presyn threshold potential in mV
p[3]= inasyn; // alpha timescale in 1/msec
p[4]= inbsyn; // beta timescale in 1/msec
p[5]= inVslope; // time of transmitter release
p[6]= nslevel; // noise level
}
absynapse::absynapse(neuron *insource, neuron *intarget, double *inp):
synapse(insource, intarget, ABSYNIVARNO, ABSYNPNO, ABSYN)
{
set_p(inp);
}
absynapse::~absynapse()
{
}
double absynapse::gsyn()
{
return p[0];
}
void absynapse::set_gsyn(double ingsyn)
{
p[0]= ingsyn;
}
double absynapse::Isyn(double *x)
{
return -p[0]*(1-x[idx])*(target->E(x)-p[1]);
}
void absynapse::derivative(double *x, double *dx)
{
static double s;
s= 0.5*(tanh((source->E(x) - p[2])/p[5])+1.0);
// dx[idx]= p[3]*(s-x[idx])*s - p[4]*x[idx]*(1.0-x[idx]);
dx[idx]= -p[3]*x[idx]*s+p[4]*(1-x[idx])*x[idx];
}
double absynapse::the_s(double *x)
{
return 0.5*(tanh((source->E(x) - p[2])/p[5])+1.0);
}
void absynapse::noise(double *x, double *dx)
{
dx[idx]= p[6]*abs(RG.n());
}
// end of class implementation
#endif
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