A Moth MGC Model-A HH network with quantitative rate reduction (Buckley & Nowotny 2011)

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Accession:144403
We provide the model used in Buckley & Nowotny (2011). It consists of a network of Hodgkin Huxley neurons coupled by slow GABA_B synapses which is run alongside a quantitative reduction described in the associated paper.
Reference:
1 . Buckley CL, Nowotny T (2011) Multiscale model of an inhibitory network shows optimal properties near bifurcation. Phys Rev Lett 106:238109 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism:
Cell Type(s): Hodgkin-Huxley neuron;
Channel(s): I K; I K,leak; I M; I K,Ca; I Q; I Na, leak;
Gap Junctions:
Receptor(s): GabaB;
Gene(s):
Transmitter(s): Gaba;
Simulation Environment: C or C++ program;
Model Concept(s): Activity Patterns; Bifurcation; Multiscale;
Implementer(s): Buckley, Christopher [chrisbuckley at brain.riken.jp];
Search NeuronDB for information about:  GabaB; I K; I K,leak; I M; I K,Ca; I Q; I Na, leak; Gaba;
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Buckley2011
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CNlib2
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CN_absynapse.cc
CN_absynapse.h
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//--------------------------------------------------------------------------
// 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 <cmath>

// parameters of the HH neuron, they are identical for all neurons used
// (and therefore made global to save memory)

#define Val_IVARNO 5
#define Val_PNO 12

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
  0.025,         // 4 - gl: leak conductance in 1/(mOhms * cm^2)
  -63.0,         // 5 - El: leak equi potential in mV
  0.143,         // 6 - Cmem: membr. capacity density in muF/cm^2
  0.0,           // 7 - noise amplitude
  1.0,           // 8 - gVV: coupling between compartments
  0.143,         // 9 - Cden: capacitance of dendrite compartment
  0.021,         // 10 - gleakden: leak conductance dendrite
  0.0            // 11 - IDC: DC current input into soma
};

double *Val_p= stdVal_p;

const 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 - Cmem: membr. capacity density in muF/cm^2",
  "7 - noise amplitude",
  "8 - gVV: coupling between compartments",
  "9 - Cden: capacitance of dendrite compartment",
  "10 - gleakden: leak conductance dendrite",
  "11 - IDC: DC current input into soma"
};

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
  -60.0                         // 4 - membrane potential of dendrite
};

const 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",
  "4 - membrane potential of dendrite"
};


// Valentins HH neuron class itself

class Valneuron: public neuron
{
 private:
  double Isyn;
  double _a, _b;
 public:
  Valneuron(int, double *);
  Valneuron(int, vector<int>, double *);
  ~Valneuron() { }
  inline virtual double E(double *);
  inline virtual double Esoma(double *);
  virtual void derivative(double *, double *);
  virtual void noise(double *, double *);  
  virtual void spike_detect(double *);
};

#endif




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