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101 lines
3.0 KiB
Matlab
101 lines
3.0 KiB
Matlab
function [y,s,r]=test_attn_spatial_pair_poor(figoffset)
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if nargin<1 || isempty(figoffset), figoffset=0; end
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iterations=25;
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offTime=20;
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plotIntermediate=1;
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%DEFINE V1 PREDICTION NEURON RECEPTIVE FIELDS
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phases=[0,180]; %even only
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%phases=[90,270]; %odd only
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%phases=[0,180,90,270] %even and odd
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texture=0;
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lateral=0;
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[w,v,v1Masks,lgnMasks]=filter_definitions_V1_simple_diffGauss([],[],1, [0,0],phases);
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if texture
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[w,v,v1Masks]=filter_definitions_V1_simple_diffGauss(w,v,1, [v1Masks,0],phases);
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phases=[phases;phases];
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end
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fbMasks=1;
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for i=1:fbMasks
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for j=1:v1Masks
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mask=gauss2D(2,0,1,0);
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%top-down, attentional, weights to V1
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w{j,lgnMasks+i}=mask;
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v{j,lgnMasks+i}=mask;
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end
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end
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if lateral
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[w,v]=filter_definitions_V1_recurrent(w,v,0.5, [0,lgnMasks+fbMasks],phases);
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end
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if phases(1,1)==90
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coordsPref(1)=coordsPref(1)-2;
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end
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%=PAIR OF STIMULI: SPATIAL ATTENTION TO POOR==================================
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%DEFINE STIMULI AND ATTENTIONAL STATES
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I=zeros(35,35); I(16,14:18)=1; Ipref=I; coordsPref=[16,16];
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I=zeros(35,35); I(17:21,19)=1; Ipoor=I; coordsPoor=[19,19];
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Ipair=Ipref+Ipoor;
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nodePref=9;
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nodePoor=13;
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clear I;
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nTrials=4;
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%pref attend away
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Amasks{1}=[]; Acoords{1}=[]; I{1}=Ipref;
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%poor attend away
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Amasks{2}=[]; Acoords{2}=[]; I{2}=Ipoor;
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%pair attend away
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Amasks{3}=[]; Acoords{3}=[]; I{3}=Ipair;
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%pair attend poor
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Amasks{4}=1; Acoords{4}=coordsPoor; I{4}=Ipair;
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X=define_input_with_cutoff_and_attn(I,nTrials,fbMasks,Amasks,Acoords,offTime,iterations);
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%SIMULATE MODEL
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if plotIntermediate, figoffset=figoffset+1; figure(figoffset), clf, end
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for trial=1:nTrials
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%iterate model
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[y,E,R,ytrace]=dim_activation_conv_recurrent(w,X{trial},[],iterations,v);
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%plot and record results
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if offTime<iterations,
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for j=1:length(y),
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y{j}=ytrace{j}(:,:,offTime);
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end
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end
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if plotIntermediate
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ymax=max(cat(3,y{1:v1Masks}),[],3);
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maxsubplot(4,nTrials,trial), plot_cropped_image(X{trial}{1}(:,:,1)-X{trial}{2}(:,:,1));
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maxsubplot(4,nTrials,trial+nTrials), plot_cropped_image(y{nodePref},0,[0,0.25]);
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maxsubplot(4,nTrials,trial+2*nTrials), plot_cropped_image(y{nodePoor},0,[0,0.25]);
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maxsubplot(4,nTrials,trial+3*nTrials), plot_cropped_image(ymax,0,[0,0.25]);
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end
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resp(trial,:)=cat(2,ytrace{nodePref}(coordsPref(1),coordsPref(2),:));
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end
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%PLOT RESULTS
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resp=[zeros(nTrials,1),resp];
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figoffset=figoffset+1; figure(figoffset), clf
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%plot(resp','LineWidth',4);
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plot([0:iterations],resp(1,:),'b--','LineWidth',3);hold on;
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plot([0:iterations],resp(2,:),'b-.','LineWidth',3);hold on;
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plot([0:iterations],resp(3,:),'b-','LineWidth',3);hold on;
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plot([0:iterations],resp(4,:),'-','Color',[0,0.7,0],'LineWidth',5);hold on;
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ax=axis;
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axis([0,iterations,0,ax(4)]);
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set(gca,'FontSize',18);
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ylabel('Response')
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xlabel('Time')
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set(gca,'YTick',[],'XTick',[]);
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drawnow;
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set(gcf,'PaperPosition',[0,0,9,12])
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if plotIntermediate
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legend(['pref attend away';'poor attend away';'pair attend away';'pair attend pref'],'Location','NorthWest')
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else
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print -depsc2 attn_spatial_pair_poor_dim.eps
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end
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