Wang-Buzsaki Interneuron (Talathi et al., 2010)

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Accession:136308
The submitted code provides the relevant C++ files, matlabfiles and the data files essential to reproduce the figures in the JCNS paper titled Control of neural synchrony using channelrhodopsin-2: A computational study.
Reference:
1 . Talathi SS, Carney PR, Khargonekar PP (2011) Control of neural synchrony using channelrhodopsin-2: a computational study. J Comput Neurosci 31:87-103 [PubMed]
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Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell; Synapse;
Brain Region(s)/Organism:
Cell Type(s): Neocortex fast spiking (FS) interneuron; Abstract Wang-Buzsaki neuron;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s): Gaba;
Simulation Environment: C or C++ program;
Model Concept(s): Synchronization;
Implementer(s): Talathi Sachin [talathi at ufl.edu];
Search NeuronDB for information about:  Gaba;
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JCNS-2010-CodeAndData
simul_lrn
CNlib
CVS
readme *
CN_absynapse.cc *
CN_absynapse.h *
CN_absynapseECplast1.cc *
CN_absynapseECplast1.h *
CN_absynapseECplast2.cc *
CN_absynapseECplast2.h *
CN_absynapseECplast3.cc *
CN_absynapseECplast3.h *
CN_DCInput.cc *
CN_DCInput.h *
CN_ECneuron.cc *
CN_ECneuron.h *
CN_HHneuron.cc *
CN_HHneuron.h *
CN_inputneuron.cc *
CN_inputneuron.cc~
CN_inputneuron.h *
CN_LPneuronAstrid.cc *
CN_LPneuronAstrid.h *
CN_LPneuronRafi4.cc *
CN_LPneuronRafi4.h *
CN_multifire_inputneuron.cc *
CN_multifire_inputneuron.h *
CN_neuron.cc *
CN_neuron.h *
CN_NeuronModel.cc *
CN_NeuronModel.h *
CN_Poissonneuron.cc *
CN_Poissonneuron.h *
CN_Rallsynapse.cc *
CN_Rallsynapse.h *
CN_rk65n.cc *
CN_rk65n.h *
CN_rk65n.o
CN_synapse.cc *
CN_synapse.h *
CN_synapseAstrid.cc *
CN_synapseAstrid.h *
CN_TimeNeuron.cc *
CN_TimeNeuron.h *
CN_Valneuron.cc *
CN_Valneuron.h *
CN_Valneuron2.cc *
CN_Valneuron2.h *
ids.h *
Makefile *
testCN *
testCN.cc *
testCN.o
                            
/*--------------------------------------------------------------------------
   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_POISSONNEURON_CC
#define CN_POISSONNEURON_CC

#include "CN_neuron.cc"

Poissonneuron::Poissonneuron(int inlabel, tnvector<int> inpos,
			     double *the_p= POI_p):
  neuron(inlabel, POI_IVARNO, POISSONNEURON,
	      inpos, the_p, POI_PNO)
{
  firing= 0;
  refract= 0;
  fire_t= 0.0;
  myx= new double[1];
  myxn= new double[1];
  myx[0]= p[2];
  myxn[0]= p[2];
  setIdx(-1);
}

Poissonneuron::~Poissonneuron()
{
  delete[] myx;
  delete[] myxn;
}

double Poissonneuron::E(double *x)
{
  return myx[0];
}

void Poissonneuron::validate_E(double *x, double dt)
{
  if (firing) {
    if (x[0] - fire_t > p[0]) { // remember: x[0] is the time
      firing= 0;
      refract= 1;
    }
  }
  else {
    if (refract) {
      if (x[0] - fire_t > p[1]) refract=0;
    }
    else {
      if (R.n() <= p[4]*dt) {
	firing= 1;
	fire_t= x[0];
      }
    }
  }
  if (firing) myxn[0]= p[3];
  else myxn[0]= p[2];
}

void Poissonneuron::step()
{
  myx[0]= myxn[0];
}

void Poissonneuron::init(double *x, double *iniVars)
{
  myx[0]= iniVars[0];
  myxn[0]= iniVars[0];
}

#endif