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Matlab

function [Y2,Y1]=nonlinear_PCBC_attention_model(x,W2,attn,eta,stim_off)
%set network parameters
iterations=20;
[n,m]=size(W2);
[W2,W2hat]=norm_weights(W2);
W1=eye(m);
[W1,W1hat]=norm_weights(W1);
%initialise activation values
y1=zeros(m,1);
y2=zeros(n,1);
z2=zeros(m,1);
Y2=y2;
Y1=y1;
%iterate to calculate node activations
for t=2:iterations
%calculate response of 1st processing stage
[y1]=nonlinear_PCBC_iteration(x,y1,W1,W1hat,z2,attn(:,:,1),eta);
%calculate response of 2nd processing stage
[y2,z2,e2]=nonlinear_PCBC_iteration(y1,y2,W2,W2hat,0,attn(1:n,:,2),eta);
Y2=[Y2,y2]; %return time varying response of stage 2
Y1=[Y1,y1]; %return time varying response of stage 1
%remove input to network
if t==stim_off, x=x.*0; end
end