Timelimit02_ERP_statsclusterplot.m

%% Find and plot significant clusters
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% AUTHOR: Bianca Trovo (bianca.trovo@alumni.unitn.it)
% DATE: created on June 2019; modified on july 2019.
% EXPERIMENT: Timelimit_2018

%{

    SCOPE: 

    OUTPUT: 
    FIXME: 

%}
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%% START of the script 

%% Housekeeping
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% clear workspace (if needed)
if input('clear all?  (1/0) ... ')
    clearvars; close all;
end

% set paths (if needed)
BT_setpath

% choose subj & go to the right folder
BT_getsubj

clear LevelAnalysis name numlines prompt subj_folders 

%% More specific paths (maybe set this in the start script)
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behavioral_folder= [results_Path, '/Behaviour']; % it can be also current_subj_folder
if ~exist(fullfile(behavioral_folder)); mkdir(fullfile(behavioral_folder)); end;

timeseries_folder= [results_Path, '/Timeseries']; % it can be also current_subj_folder
if ~exist(fullfile(timeseries_folder)); mkdir(fullfile(timeseries_folder)); end;
cd(timeseries_folder);

powerspectra_folder= [results_Path, '/Powerspect']; % it can be also current_subj_folder
    if ~exist(fullfile(powerspectra_folder)); mkdir(fullfile(powerspectra_folder)); end;
    cd(powerspectra_folder);
    
correlation_folder= [results_Path, '/Correlations']; % it can be also current_subj_folder
    if ~exist(fullfile(correlation_folder)); mkdir(fullfile(correlation_folder)); end;  
    
regression_folder= [results_Path, '/Regressions']; % it can be also current_subj_folder
    if ~exist(fullfile(regression_folder)); mkdir(fullfile(regression_folder)); end;
    
statistics_folder= [results_Path, '/Statistics']; % it can be also current_subj_folder
    if ~exist(fullfile(statistics_folder)); mkdir(fullfile(statistics_folder)); end;
    
%% load stats

cd(statistics_folder);
load 

%% Find significant time-points

ntimes = size(stat.posclusterslabelmat,2)
sig_times = zeros(1, ntimes);
%
%Cz= 30;
%ROI = [20 21 29 30 31 39 40];

for j= 1: ntimes
    
   if sum(stat.posclusterslabelmat(28,j)==1)>0 % choose channel here / put 2 if another significant cluster
    sig_times(j) =1;
   end
    
end

effect= stat.time(sig_times==1)

save effect1_corrER1_nr_22 effect; save effect1_regrER1_nr_22 effect; 
save effect_corrER2_nr_12 effect; save effect1_regrER2_nr_12 effect;

%% topoplot with the Fieldtrip way 

figure;
cfg= [];
cfg.layout= 'eeg_64_NM20884N.lay';
cfg.xlim= [effect(1) effect(end)];
cfg.parameter= 'stat';
ft_topoplotER(cfg,stat);

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%% singleplotER, the Fieldtrip way, with a mask

% POSITIVE CLUSTERS
stat.stat2= stat.stat.*(stat.posclusterslabelmat == 1);
cfg_fig= [];
cfg_fig.parameter= 'stat2';
cfg_fig.zlim= 'maxabs';
figure; ft_singleplotER(cfg_fig,stat);

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% NEGATIVE CLUSTERS
% stat.stat_neg= stat.stat.*(stat.negclusterslabelmat == 1);
% cfg= [];
% cfg.parameter= 'stat3';
% cfg.zlim= 'maxabs';
% figure; ft_singleplotER(cfg,stat);

%% clusterplot 

cfg = [];
% cfg.alpha  = 0.05;
% cfg.parameter = 'raweffect';
% cfg.zlim   = [-1e-27 1e-27];
cfg.layout = 'eeg_64_NM20884N.lay';
% cfg.saveaspng= 'clusterplot4';  
ft_clusterplot(cfg,stat);  

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%% END