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).
Reference:
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
Citations  Citation Browser
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;
//***********************************************************************//
//*********************** Builds the network ****************************//
//***********************************************************************//



/******************** Creates input distribution ************************/

if(read==0){
     for(int m1=0; m1<NetSize; m1+=1){
       for(int k1=0; k1<NetSize; k1++){  
          input[m1][k1]= new Input(&cell[m1][k1],InpR,InpD,gInput*(1+Var()*DeltaGI)*Area);
          input[m1][k1]->SetE(0);              // reversal potential for glutamatergic input synapses
          cell[m1][k1].SetV(EREST);	           // Start at rest
       }
    }

}

else
{
     int Idx;
     Idx=0;
     real data[Ncell];           // file contains an undermined number of integer values
     ifstream fin;     // declare stream variable name

     fin.open("InpResIdI7E0.txt",ios::in);    // open file
     assert (!fin.fail( ));     
     fin >> data[Idx];        // get first number from the file (priming the input statement)
                              // You must attempt to read info prior to an eof( ) test.
     while (!fin.eof( ))      //if not at end of file, continue reading numbers
     {
          Idx++;
          fin >> data[Idx];         //get next number from file
     } 
     fin.close( );       //close file 
     //assert(!fin.fail( ));
     
    for(int m1=0; m1<NetSize; m1+=1){
       for(int k1=0; k1<NetSize; k1++){  
        input[m1][k1]= new Input(&cell[m1][k1],InpR,InpD,data[k1+10*m1]*Area);
        input[m1][k1]->SetE(0);            // reversal potential for glutamatergic input synapses
        cell[m1][k1].SetV(EREST);	       // Start at rest
       }
    }
    
   
     
}

  

/********************  Defines synaptic strength ************************/

// Creates synaptic strengths

if(read==0){
  // for lateral inhibition

   for(int k1=0; k1<NetSize; k1++){
      for(int k2=0; k2<NetSize; k2++){
          for(int m1=0; m1<NetSize; m1++){
             for(int m2=0; m2<NetSize; m2++){
               Ji[m1][k1][m2][k2]=2*gI*exp(-pow((k1-k2)/Li,2)-pow((m1-m2)/Li,2))*rand()/32767;
             }
          }
      }
   } 
 // then for self inhibition

   for(int k1=0; k1<NetSize; k1++){
      for(int m1=0; m1<NetSize; m1++){  
         Ji[m1][k1][m1][k1]=SgI*(1+0.5*Var());
      }   
   }
} 
else{
      int Idx2, Idx1;
      char marker[10];
     Idx2=0;
     Idx1=0;
     
     ifstream fin;     // declare stream variable name

     fin.open("SynIResIdI7E0.txt",ios::in);    // open file
     assert (!fin.fail( ));     
      
for(int m1=0; m1<NetSize; m1++){
    for(int k1=0; k1<NetSize; k1++){
        for(int m2=0; m2<NetSize; m2++){
           for(int k2=0; k2<NetSize; k2++){                   
            fin >> Ji[m1][k1][m2][k2];         //get next number from file
           }   
        }
            fin>>marker;         
    }
}
     fin.close( );       //close file 
     //assert(!fin.fail( ));    
}





  // for lateral exitation 
  for(int k1=0; k1<NetSize; k1++){
    for(int k2=0; k2<NetSize; k2++){
        for(int m1=0; m1<NetSize; m1++){
           for(int m2=0; m2<NetSize; m2++){
             Je[m1][k1][m2][k2]=2*gE*(1+Var()*0.2);
           }
        }
    }
  }
  // then for self exitation

  for(int k1=0; k1<NetSize; k1++){
    for(int m1=0; m1<NetSize; m1++){  
       Je[m1][k1][m1][k1]=SgE*(1+0.5*Var());
    }   
  } 

     



 
/*********************  Creates links between cells  *******************/
/*********** !!!!! Maximal latency 500 time steps **********************/    
  
 // Inhibition  
 for(int m1=0; m1<NetSize; m1++){
    for(int k1=0; k1<NetSize; k1++){
       for(int m2=0; m2<NetSize; m2++){
          for(int k2=0; k2<NetSize; k2++){
            SynS[m1][k1][m2][k2] = new AlphaSynS(&cell[m1][k1], &cell[m2][k2], Ji[m1][k1][m2][k2], LatI,0);
            if(m1==m2 && k1==k2){
              SetUpSynS( *SynS[m1][k1][m2][k2], STaudI, STaurI, Threshold);// sink / source / Gmax / Fmax / tau1 / tau2 / Fsat / Mean
            }
            else{
              SetUpSynS( *SynS[m1][k1][m2][k2], TaudI, TaurI, Threshold);// sink / source / Gmax / Fmax / tau1 / tau2 / Fsat / Mean
            }     
          }
        }                                                  
     }
  }
                        //   !!!!!  Whatever is added here : check in Destruct&Close.h that it is later removed
                               
        
 // Exitation 
 for(int m1=0; m1<NetSize; m1++){
    for(int k1=0; k1<NetSize; k1++){
       for(int m2=0; m2<NetSize; m2++){
          for(int k2=0; k2<NetSize; k2++){
             if(Je[m1][k1][m2][k2]>0.005){                                
                SynE[m1][k1][m2][k2] = new AlphaSyn(&cell[m1][k1], &cell[m2][k2], Je[m1][k1][m2][k2]*Area, LatE*(1+0.5*Var()) ); 
                SetUpSynE( *SynE[m1][k1][m2][k2], TaudE, TaurE, Threshold);
             }          
          }
       }
    }
 }