Neural model of frog ventilatory rhythmogenesis (Horcholle-Bossavit and Quenet 2009)

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Accession:123987
"In the adult frog respiratory system, periods of rhythmic movements of the buccal floor are interspersed by lung ventilation episodes. The ventilatory activity results from the interaction of two hypothesized oscillators in the brainstem. Here, we model these oscillators with two coupled neural networks, whose co-activation results in the emergence of new dynamics. .. The biological interest of this formal model is illustrated by the persistence of the relevant dynamical features when perturbations are introduced in the model, i.e. dynamic noises and architecture modifications. The implementation of the networks with clock-driven continuous time neurones provides simulations with physiological time scales."
Reference:
1 . Horcholle-Bossavit G, Quenet B (2009) Neural model of frog ventilatory rhythmogenesis. Biosystems 97:35-43 [PubMed]
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Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism:
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: MATLAB;
Model Concept(s): Temporal Pattern Generation; Oscillations; Synchronization;
Implementer(s):
%Biosystems. 2009 Jul;97(1):35-43.
%Horcholle-Bossavit G, Quenet B.
%Neural model of frog ventilatory rhythmogenesis.

global cumul

germe=1;
facteur=0.15;
nombrerreur=0;
matdep =[ 0  0  -1   
          1  0  -1   
          0  1  0 ];                      
Rdep=[1 0 0 ]; 
matL=[0 -1 0 ; 0 -1 0; 0 0 0];
X=6;
Y=2;
mattoub=boucladj(matdep,Rdep', X, [4,2],1, [2,5], -1);  
Spre=mattoub(:,1:end-1);
Rpre=mattoub(:,end);
Spara=bouclpara(Spre,Rpre, Y); 
R=Spara(:,end);
S=Spara(:,1:end-1);
R=R';
vectv=zeros(size(S,1),1);
vecth=zeros(1, size(S,2));
inhibsl=[];
for y=1:Y
    inhibsl=[inhibsl, [0:X-1]*2+3+(y-1)*((X*2)+1)];
end
inhibsl;
excitateurs=[1,[1:X]*2];
for y=2:Y
    excitateursy=[1+(y-1)*((X*2)+1),[1:X]*2+(y-1)*((X*2)+1)];
    excitateurs=[excitateurs;excitateursy];
end
excitateurs;
taillantiphase=2;
groupebc=[ ];
groupebd=[ ];
for i=1:size(excitateurs,2)
    if mod(floor((i-1)/taillantiphase),2)==0
        groupebc=[groupebc,excitateurs(1,i)];
    else
        groupebd=[groupebd,excitateurs(1,i)];
    end
end
groupebc=groupebc(2:end);

for y=2:Y
    groupebcy=[ ];
    groupebdy=[ ];
    for i=1:size(excitateurs,2)
        if mod(floor((i-1)/taillantiphase),2)==0
            groupebcy=[groupebcy,excitateurs(y,i)];
        else
            groupebdy=[groupebdy,excitateurs(y,i)];
        end
    end
    groupebc=[groupebc,groupebcy(2:end)];
    groupebd=[groupebd,groupebdy];
end
groupebdin=groupebd+1;                  %inhibiteurs de Bd repérés
vectv(groupebd)=0;                      %ceci permet de ne pas synchroniser les neurones de bd par l1
vectv(groupebdin)=0;           
S=completelop(matL,vectv,vecth,S,1);
R=[0 1 0,R];
inhibsl=inhibsl+3;
excitateurs=excitateurs+3;
groupebc=groupebc+3;
groupebd=groupebd+3;
groupebdin=groupebdin+3;
excitateurs=excitateurs(:,2:end);
excitateurs=reshape(excitateurs',1,size(excitateurs,1)*size(excitateurs,2));
v=1:Y;
for i=1:X
    for j=1:Y
        for k=1:Y
            S(excitateurs((k-1)*X+i),inhibsl((j-1)*X+i))=-1;
        end
    end
end
S1=matmodif(S,nombrerreur,facteur,germe);
S=S1;
B=nnz(S1);
groupex=find(sum(S1)>=0);
groupin=find(sum(S1)<0); 
Ne=length(groupex);
Ni=length(groupin);
retards=ones(Ne+Ni);
th=[0.5*ones(Ne,1); 	0.5*ones(Ni,1)];
Ne=length(groupex);     Ni=length(groupin);
retards=ones(Ne+Ni);
th=[0.5*ones(Ne,1); 	0.5*ones(Ni,1)];

modul=1;                              
vseuiL=[1;zeros(Ne+Ni-1,1)];    %vecteur qui permet de mettre un seuil variable sur L1
Init=zeros(Ne+Ni,1);
type=(sign(sum(S)))';
groupe=[2;zeros(Ne+Ni-1,1)];
groupe(groupebc)=1;
groupe(groupebd)=-1;
nirings=[zeros(sum(Init),1),find(Init==1),type((Init==1)),groupe((Init==1))];
hstock=zeros(Ne+Ni,Tsim);
hstock(:,1)=Init;
matact=zeros(Ne+Ni,Tsim);
matact(:,1)=Init;
Eml1=0;
retL=1;                     
Tomax=max(max(retards));
cumul=0;
Ac=0;
rand('seed', sd);
randn('seed', sd);
for t=1:Tsim
    feu=[];
    matfiltre=zeros(Ne+Ni);
    h=R';
    if ~isempty(nirings)
       for ret=1:max(max(retards))
           fincre=zeros(Ne+Ni);                           
           inter=find(nirings(:,1)==t-ret);               
           feu=[feu; ret+0*inter,inter];                  
           finter=[[nirings(inter,2)]', Ne+Ni+1];          
           fincre(1:Ne+Ni,finter)=1;                       
           fincre=fincre(:,1:Ne+Ni);                       
           matinter=(retards==ret);                        
           matfiltre=matfiltre+((matinter==fincre)&(matinter>0));   
       end
       tfire=nirings(feu(:,2),1);                          
       firedt=nirings(feu(:,2),2);                         
       st=sort(firedt); 
       
                                          
       if ~isempty(st)                                    
           dst=diff(st);                                   
           y=st(dst>0);
           firedtone=[y;st(end)];                          
           Sfiltre=S.*matfiltre;                           
           h=h+sum(Sfiltre(:,firedtone),2);  
       end
        
       inter1=find(nirings(:,1)==t-retL);   
       finter1=[nirings(inter1,2)];
       finter2=[nirings(inter1,1)];
       lfire=(sum(finter1==1)>0);   
       modulation(lfire);
  
    end
    randh=randn(Ne+Ni,1);
    hent=h+Eml1(end)*(modul==1)*vseuiL+epsilon*randh-th;                                                            
    hstock(:,t+1)=hent;
    n=(hent>0);                                                
    fired=find(n>0);
    matact(:,t+1)=n;                                      
    if ~isempty(fired);
        nirings=[nirings; t+0*fired,fired,type(fired),groupe(fired)];                 
    end
end

groupebc=groupebc(2:end);
matactbc=matact(groupebc,:);
matactbd=matact(groupebd,:);
matactl=matact(1,:);

actotbc=sum(matact(groupebc,:));

actotbd=sum(matact(groupebd,:));
actot=sum(matact(groupex,:))+matact(1,:);