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demo.m
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Drift diffusion tutorial (Luyckx)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%addpath(~/Location/of/your/function)
%% Default model
pm = struct; % create empty structure
[RT,decision,evidence,pm] = driftdiff(pm); % run default simulation
% Plot outcome with custom function 'plotDrift'
figure;
plotDrift(RT,decision,evidence,pm);
%% Standard model for comparison
pm = struct; % empty structure
pm.driftrate = 1; % evidence for option A
[RT,decision,evidence,pm] = driftdiff(pm);
figure; plotDrift(RT,decision,evidence,pm,20);
%% Changing drift rate
pm = struct; % empty structure
pm.driftrate = 1; % evidence for option A
figure;
% Default model
[RT,decision,evidence,pm] = driftdiff(pm);
subplot(2,1,1); plotDrift(RT,decision,evidence,pm,20);
title(['v = ' num2str(pm.driftrate(1))]);
% Higher drift model
pm = struct; % empty structure
pm.driftrate = 2; % more evidence for option A
[RT,decision,evidence,pm] = driftdiff(pm);
subplot(2,1,2); plotDrift(RT,decision,evidence,pm,20);
title(['v = ' num2str(pm.driftrate(1))]);
%% Changing the drift rate SD
pm = struct; % empty structure
pm.driftrate = 1; % evidence for option A
figure;
% Lower noise model
pm.noise = 5; % decrease noise level
[RT,decision,evidence,pm] = driftdiff(pm);
plotDrift(RT,decision,evidence,pm,20);
title(['eta = ' num2str(pm.noise(1)) ' instead of ' num2str(15)]);
%% Changing the bounds
pm = struct; % empty structure
pm.driftrate = 1; % evidence for option A
figure;
% Default model
[RT,decision,evidence,pm] = driftdiff(pm);
subplot(2,1,1);
plotDrift(RT,decision,evidence,pm,20);
title(['a = ' num2str(pm.upperbound(1))]);
% Decreased bounds model
pm = struct; % empty structure
pm.upperbound = 300; % decrease bound a
[RT,decision,evidence,pm] = driftdiff(pm);
subplot(2,1,2);
plotDrift(RT,decision,evidence,pm,20);
title(['a = ' num2str(pm.upperbound(1))]);
%% Changing the bias
pm = struct; % empty structure
figure;
% Biased model
pm.bias = .7; % bias for option A
pm.biasrange = .05;
[RT,decision,evidence,pm] = driftdiff(pm);
plotDrift(RT,decision,evidence,pm,20);
%% Changing the non-decision time
pm = struct; % empty structure
pm.driftrate = 1; % evidence for option A
figure;
% Default model
[RT,decision,evidence,pm] = driftdiff(pm);
subplot(2,1,1);
plotDrift(RT,decision,evidence,pm,20);
title(['t_0 = ' num2str(pm.nondectime(1))]);
% Delayed model
pm = struct; % empty structure
pm.nondectime = 200; % wait 200 ms before integration
pm.ndcrange = 25; % waiting time varies between 175 and 225 ms
[RT,decision,evidence,pm] = driftdiff(pm);
subplot(2,1,2);
plotDrift(RT,decision,evidence,pm,20);
title(['t_0 = ' num2str(round(mean(pm.nondectime)))]);