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51 lines
1.3 KiB
Matlab
51 lines
1.3 KiB
Matlab
function keller_fit
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%plot the experimental data predicted by the Zmarz and Keller model of V1
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%mismatch neurons
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%define ranges used to bin running speed (p) and visual flow (v)
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p=exp(-2.772588722:0.693147181:4.16);
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v=exp(4.158883083:-0.693147181:-2.78);
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[P V]=meshgrid(p,v);
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%Zmarz and Keller's model
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%A=0.049; % parameter value given in paper
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A=16; % parameters value that fits the data
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d=0.049;
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a=0.012;
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b=0.009;
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sat=0.08;
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r=d+A./(1+exp(-(a.*P-b.*V)./sat)); % parameters that seem to fit data
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figured(1), plot_fit(r,p,v)
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%subtractive model
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r=0.25.*(P-V); max(max(r))
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figured(2),plot_fit(r,p,v);title('P-V')
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%print_fig('keller_fit_randb_linear.pdf');
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%print_fig('keller_fit_randb_linear.eps');
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%subtractive model - in log space
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r=2.5.*(log(P)-log(V)); max(max(r))
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figured(3),plot_fit(r,p,v);title('log(P)-log(V)')
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%print_fig('keller_fit_randb_log.pdf');
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%print_fig('keller_fit_randb_log.eps');
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function plot_fit(r,p,v)
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clf
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imagesc(r,[0,16]), axis('equal','tight'),
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s=[0.06,0.25,1,4,16,64];
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%colorbar
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tolabelp=3:2:12;
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tolabelv=1:2:10;
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set(gca,'XTick',tolabelp-0.25,'YTick',tolabelv+0.5,'XTickLabel',p(tolabelp),'YTickLabel',v(tolabelv),'FontSize',19);
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%set(gca,'XTick',[],'YTick',[],'FontSize',21);
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ylabel('visual flow speed (V)')
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xlabel('running speed (P)')
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colormap('jet')
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set(gcf, 'Color', 'w'); |