% load MDM
mdm = xff('*.mdm');

% load VOI
voi = xff('*.voi');

% get list of conditions from first protocol
prt = xff(mdm.XTC_RTC{1, 2});
conds = prt.ConditionNames;

% extract average timecourses for all conditions with options:
% - baseline window is from -2000 through 2000 milliseconds (sampled in 2s intervals)
% - motion parameters from mdm.RunTimeVars are used (if present) to remove nuisance variance
% - FFX grouping
% - the sampling of the average time courses is in 100ms steps
% - the error term returned is SE (SD / sqrt(N))
[fmtc, fmtcse] = mdm.VOICondAverage( ...
    voi, conds, struct( ...
        'basewin', [-2000:1000:2000], ...
        'motpars', true, ...
        'group',   'ffx', ...
        'samptr',  100, ...
        'sdse',    'se'));

% create list of colors
col = [1, 0, 0; 0.8, 0.2, 0.2; 0, 0, 1; 0.2, 0.2, 0.8];

% the plots were then created as follows:
% - get the VOI names
vn = voi.VOINames;

% loop over VOIs
for vc = 1:numel(vn)

    % create a figure and axes object
    f(vc) = figure;
    a = axes;
    
    % loop over condidions
    for x=1:numel(conds)
    
        % use tcplot to plot into the same axes
        l(x) = tcplot(a, 0:0.1:20, fmtc(:, x, vc), fmtcse(:, x, vc), fmtcse(:, x, vc), ...
            struct('color', col(x, :), 'spalpha', 0.2, 'lwidth', 3));
        end
        
        % add title and legend
        title(vn{vc});
        legend(l(:), conds{:});
    end
end

% set figures to same size
set(f, 'Position', [200, 200, 400, 300]);