Olfactory bulb network model of gamma oscillations (Bathellier et al. 2006; Lagier et al. 2007)

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Accession:91387
This model implements a network of 100 mitral cells connected with asynchronous inhibitory "synapses" that is meant to reproduce the GABAergic transmission of ensembles of connected granule cells. For appropriate parameters of this special synapse the model generates gamma oscillations with properties very similar to what is observed in olfactory bulb slices (See Bathellier et al. 2006, Lagier et al. 2007). Mitral cells are modeled as single compartment neurons with a small number of different voltage gated channels. Parameters were tuned to reproduce the fast subthreshold oscillation of the membrane potential observed experimentally (see Desmaisons et al. 1999).
References:
1 . Bathellier B, Lagier S, Faure P, Lledo PM (2006) Circuit properties generating gamma oscillations in a network model of the olfactory bulb. J Neurophysiol 95:2678-91 [PubMed]
2 . Lagier S, Panzanelli P, Russo RE, Nissant A, Bathellier B, Sassoè-Pognetto M, Fritschy JM, Lledo PM (2007) GABAergic inhibition at dendrodendritic synapses tunes gamma oscillations in the olfactory bulb. Proc Natl Acad Sci U S A 104:7259-64 [PubMed]
3 . Bathellier B, Lagier S, Faure P, Lledo PM (2006) Corrigendum for Bathellier et al., J Neurophysiol 95 (4) 2678-2691. J Neurophysiol 95:3961-3962
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Olfactory bulb;
Cell Type(s): Olfactory bulb main mitral GLU cell;
Channel(s): I Na,p; I Na,t; I A; I K;
Gap Junctions:
Receptor(s): GabaA;
Gene(s):
Transmitter(s):
Simulation Environment: C or C++ program;
Model Concept(s): Oscillations; Delay; Olfaction;
Implementer(s):
Search NeuronDB for information about:  Olfactory bulb main mitral GLU cell; GabaA; I Na,p; I Na,t; I A; I K;
/**************************************************************************

	NoiseI.h												JJS 9/06/95
	
		addition to CONICAL, the Computational Neuroscience Class Library.
		Fonction that generate a white gaussian noise centered around zero with
        standard    
	
	
	Requires:
		math library		-- ANSI math functions, defined in <math.h>
		
**************************************************************************/

#ifndef NOISESOURCE_H
#define NOISESOURCE_H

#include <math.h>
#include<stdlib.h>
#include<time.h>
#ifndef real
#define real double
#endif


// Homogeneous distribution -1 to 1
inline real Var(){return 2*double(rand())/32767-1;}

// Gaussian distribution
inline real NoiseI(real max)
{
	double a1,a2,X,V1,V2, S;
    

do{
    a1=rand();
    V1=2*a1/32767-1;
    a2=rand();
    V2=2*a2/32767-1;
    S= V1*V1 + V2*V2;
}while(S>=1);
   

    
    X= sqrt(-2*log(S) / S) * V1; //bruit blanc normalisé 
    
    return max*X;
}

inline int fact(int i){
   int res=1;
   if(i=0){ return 1;}
   else{ 
     for(int k=2; k<i+1; k++){res=res*k;}
     return res;
   } 
}

inline int NoisePoiss(real m){
   real x;
   real Part=0;
   int r=0;

   x=rand()/32767;
   do{
      Part+=exp(-m)*(pow(m,r)/fact(r));
      r++;
   }while(Part<x);
   
   return r-1;

}

#endif

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