Phase oscillator models for lamprey central pattern generators (Varkonyi et al. 2008)

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Accession:118392
In our paper, Varkonyi et al. 2008, we derive phase oscillator models for the lamprey central pattern generator from two biophysically based segmental models. We study intersegmental coordination and show how these models can provide stable intersegmental phase lags observed in real animals.
Reference:
1 . Várkonyi PL, Kiemel T, Hoffman K, Cohen AH, Holmes P (2008) On the derivation and tuning of phase oscillator models for lamprey central pattern generators. J Comput Neurosci 25:245-61 [PubMed]
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Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network; Connectionist 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; Spatio-temporal Activity Patterns; Parameter Fitting; Parameter sensitivity; Phase Response Curves;
Implementer(s): Varkonyi, Peter [vpeter at mit.bme.hu];
function y=williams(t,x)

ve=x(7);
vl=x(8);
vc=x(9);
%parameter=x(7);
x=x(1:6);



VIN=[0 1 1 0 0 0;0 0 -1 0 0 0;0 0 0 -1 -1 -1];
VIN=[VIN;-1 -1 -1 0 0 0;0 0 0 -1 0 0;0 0 0 1 1 0];


%exc=excszorzo*[0.025 0.01 .1 .1 0.01 0.025]'; %excitation from brain
exc=[ve vl vc vc vl ve]';
%E-L-C-C-L-E
th=0; %activity threshold
tau=.1;%timescaling
tcells=[1 1 1 1 1 1]';
r=0;%resting potential
vex=1;
W=abs(sign(VIN));

% switch parameter
%     case {1}


X=x*ones(1,length(x)); %x of other unit; X' used for x ofown unit
% VIN([2 5],:)=0;
% VIN(:,[2 5])=0;
 %connection weights all 1
%exc=exc+x-th;%overall activity of cells
% W
% (X-th)
% (VIN-X')
% % (sum(W.*(X-th).*(VIN-X'),1))'
y=tcells.*(exc.*(vex-x)+tau*(r-x)+(sum(W.*max(0,X-th).*(VIN-X'),1))');

y(7:9)=0;


%




%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %feloszcillator
% X=x*ones(1,length(x)); %x of other unit; X' used for x of own unit
% exc=excszorzo*[.1 .01 .1 ]'; %excitation from brain
% %E-L-C
% th=0; %activity threshold
% tau=.1;%timescaling
% r=0;%resting potential
% vex=1;
% tcells=[1 1 1]';
% VIN=[0 1 1 ;0 0 -1 ;0 0 0 ];
% W=abs(sign(VIN)); %connection weights all 1
% %exc=exc+x-th;%overall activity of cells
% % W
% % (X-th)
% % (VIN-X')
% % (sum(W.*(X-th).*(VIN-X'),1))'
% y=tcells.*(exc.*(vex-x)+tau*(r-x)+(sum(W.*(max(0,X-th)).*(VIN-X'),1))');