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TimeFreq_Figures.m
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TimeFreq_Figures.m
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%% FIGURES
% Version 0.4 / 13.07.2020
%% ------------ XXX ---------- %%
%% Author(s)
% Corentin Wicht (script, protocol)
% GitHub : https://github.com/CorentinWicht
% If you have questions or want to contribute to this pipeline, feel free
% to contact [email protected]
% This work is licensed under a Creative Commons Attribution-NonCommercial
% 4.0 International License (CC BY-NC)
clear variables
%% This script enable to repeat the plotting operation while adjusting parameters
% TO DO:
%- Implement for ANOVAs and other stats designs !
% + one-sided tests
addpath(genpath(strcat(pwd,'/Functions/Functions')));
addpath(strcat(pwd,'/Functions/eeglab14_1_2b'));
% Loading the excel output file
[file,path] = uigetfile([pwd '/.xlsx'],'Select the excel file to load');
Table = readtable([path file]);
% Loading the statistics RawTFData (mat files)
path = uigetdir(pwd,'Select the folder containing STATS data (Stats folder)');
AllFiles = dir ([path '\**/*' '.mat']);
StatsFiles = AllFiles(contains({AllFiles.folder},'Stats'));
for k=1:length(StatsFiles)
TempNames = strsplit(StatsFiles(k).name,'.');
StatsData.(TempNames{1}) = load([StatsFiles(k).folder '\' StatsFiles(k).name]);
end
StatsDataFN = fieldnames(StatsData);
% Loading the raw data files (mat files)
[file,path] = uigetfile([pwd '*.mat'],'Select the file containing RAW data (RawTFData.mat in Raw folder)');
RawTFData = load([path file]);
% Loading the parameters
ParamFile = dir (['**/*' 'TimeFreq_Param.mat']);
load([ParamFile.folder '\' ParamFile.name])
% Table headers
TableHeaders = Table.Properties.VariableNames;
% Retrieve data from the table
Analyses = table2cell(Table(:,contains(TableHeaders,'Analysis')));
FreqBands = table2cell(Table(:,contains(TableHeaders,'FrequencyBand')));
Level1 = table2cell(Table(:,contains(TableHeaders,'Level1')));
Level2 = table2cell(Table(:,contains(TableHeaders,'Level2')));
Level3 = table2cell(Table(:,contains(TableHeaders,'Level3')));
% For t-tests
if contains(StatsData.(StatsDataFN{1}).Stats.Test,'t-test')
Idx = contains(TableHeaders,'ClusterThreshold');
if sum(Idx) == 1
Threshold = table2array(Table(:,Idx));
SigClust = table2array(Table(:,contains(TableHeaders,'SigClusters')));
end
% For ANOVAs
elseif contains(StatsData.(StatsDataFN{1}).Stats.Test,'ANOVA')
Threshold = table2array(Table(:,contains(TableHeaders,'ClusterThreshold')));
SigClust = table2array(Table(:,contains(TableHeaders,'SigClusters')));
end
% Statistics specifications
Pval = str2double(PromptInputs{5});
Normalization = upper(answer{8});
% Frequency bands
BandsList=BandsList(all(~cellfun('isempty', BandsList),2),:);
% Creating the Design structure separating Within and Between factors
Design=[];
for k=1:size(DesignList,2) % (MAY CHANGE !!!)
if strcmpi(DesignList{1,k},'W')
Design.Within=DesignList(~cellfun('isempty',DesignList(:,k)),k);
elseif strcmpi(DesignList{1,k},'B')
Design.Between=DesignList(~cellfun('isempty',DesignList(:,k)),k);
end
end
% % Removing empty lines
% DesignFN=fieldnames(Design);
% for k=1:length(DesignFN)
% FactorsFN = fieldnames(Design.(DesignFN{k}));
% for j=1:length(FactorsFN)
% Design.(DesignFN{k}).(FactorsFN{j})=Design.(DesignFN{k}).(FactorsFN{j}) ...
% (~cellfun('isempty',Design.(DesignFN{k}).(FactorsFN{j})));
% end
% end
% Starting EEGLAB to retrieve one example file
eeglab
close gcf
% List of EEG files
EEGFiles = dir([data_folder '\**/*' '.set']);
% Loading the first file as example
EEG = pop_loadset('filename',EEGFiles(1).name,'filepath',EEGFiles(1).folder);
% Average referencing Cz
% if strcmpi(answer{6},'Y')
% EEG = average_ref(EEG,EEG.chaninfo.nodatchans);
% end
% Retrieving labels
Labels = {EEG.chanlocs.labels};
%% Looping over each analysis
% Until user is satisfied
FirstRun = 1;
DispText = '';
Num = 1;
for k=1:size(Table,1)
% Retrieving the condition labels
if isfield(Design,'Between')
BetweenLevels = Design.Between(3:end);
end
if isfield(Design,'Within')
WithinLevels = Design.Within(3:end);
end
CurrentBand = FreqBands{k};
% Listing all subjects + loading the frequency bins
TempData = RawTFData.(Analyses{k}).(Level1{k}).(Level2{k}).Data;
SubjFN = fieldnames(TempData);
AllStats = StatsData.([Analyses{k} '_' Level1{k} '_' Level2{k} '_' FreqBands{k}]).Stats.TFCE;
AllFreqs = RawTFData.(Analyses{k}).(Level1{k}).(Level2{k}).Freqs.(SubjFN{1});
%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% 1) T-TESTS
if contains(StatsData.(StatsDataFN{1}).Stats.Test,'t-test')
% Thresholding the statistics based on alpha (e.g. 0.05)
AllStats.P_Values(AllStats.P_Values>Pval) = 0;
AllStats.Obs(AllStats.P_Values==0) = 0;
% Only if significant clusters survived thresholding
if SigClust(k)>0
% Looking for index of frequency boundaries
CurrentBounds=str2num(BandsList{contains(BandsList(:,1),CurrentBand),2});
BoundsIdx=find(ge(AllFreqs,CurrentBounds(1)) & le(AllFreqs,CurrentBounds(2)));
% Assigning each participant data to its condition
p=[1 1];
for m=1:length(SubjFN)
if contains(SubjFN{m},BetweenLevels{1})
GroupRawData.(BetweenLevels{1})(p(1),:,:) = squeeze(mean(TempData.(SubjFN{m})(:,BoundsIdx,:),2));
p(1)=p(1)+1;
elseif contains(SubjFN{m},BetweenLevels{2})
GroupRawData.(BetweenLevels{2})(p(2),:,:)= squeeze(mean(TempData.(SubjFN{m})(:,BoundsIdx,:),2));
p(2)=p(2)+1;
end
end
% Averaging over participants
GroupRawData = structfun(@(x) squeeze(mean(x,1)),GroupRawData,'UniformOutput',false);
%% Settings
% SHOULD LET THE POSSIBILITY TO DEFINE THE RANGE FOR EACH TOPOPLOT.
% Hence, at the end of the loop, if re-run, clear the variables
% link the time range and below only create them is doesn't exit
% (hence, if prompt here is empty for time range).
% Prompt allowing to adjust on the first figure the colormap
% options
ColorMap={};
% Only for the 1st figure
while FirstRun
PromptSetup = {['1) Enter the name of the ColorMap to use for MEANS:'...
newline 'e.g. parula, jet, hsv, hot, bluewhitered'...
newline 'If left empty, opens a software to design it manually!'],...
['2) Enter the name of the ColorMap to use for STATS and TOPOPLOTS:'...
newline 'If left empty, opens a software to design it manually!']...
'Enter the number of Color bins:'...
'Range of topoplots (is ms, optional)'};
PromptInputs = inputdlg(PromptSetup,'Figure ColorMap Settings',1,{'jet','hot','50',''});
% Manual configuration of the color maps
% COLORMAP 1
if isempty(PromptInputs{1}) && isempty(ColorMap) || ...
isempty(PromptInputs{1}) && strcmpi(ColorMap,'Second ColorMap')
if exist('ColParam1','var')
[ColMap1,ColParam1] = cubehelix_view(size(ColMap1,1),ColParam1(1),...
ColParam1(2),ColParam1(3),ColParam1(4),ColParam1(5:6),ColParam1(7:8));
else
[ColMap1,ColParam1] = cubehelix_view(str2double(PromptInputs{3}));
end
% Reversing the direction of the Colormap
ColMap1 = flipud(ColMap1);
end
% COLORMAP 2
if isempty(PromptInputs{2}) && isempty(ColorMap) || ...
isempty(PromptInputs{1}) && strcmpi(ColorMap,'First ColorMap')
if exist('ColParam2','var')
[ColMap2,ColParam2] = cubehelix_view(size(ColMap2,1),ColParam2(1),...
ColParam2(2),ColParam2(3),ColParam2(4),ColParam2(5:6),ColParam2(7:8));
else
[ColMap2,ColParam2] = cubehelix_view(str2double(PromptInputs{3}));
end
% Reversing the direction of the Colormap
ColMap2 = flipud(ColMap2);
end
% Determine if dependent/independent samples t-test
if exist('BetweenLevels','var')
CurrentLevels = BetweenLevels;
elseif exist('WithinLevels','var')
CurrentLevels = WithinLevels;
end
%% PLOTTING
% plot tresholded results
Fig = figure; clf
% More space if no bar
set(gcf, 'MenuBar', 'None', 'ToolBar','None')
% Grand title over all subplots
Str1=sprintf('%s-%s-%s: %s [%d-%d Hz]',Analyses{k},Level1{k},Level2{k},...
FreqBands{k},CurrentBounds(1),CurrentBounds(end));
Str2=sprintf('%s_%s_%s_%s',Analyses{k},Level1{k},Level2{k},FreqBands{k});
annotation('textbox',[.35 .5 .5 .5],'String',...
Str1,'FitBoxToText','on','FontSize',20,'EdgeColor','w');
% Data to plot
DataToPlot1=GroupRawData.(CurrentLevels{1});
DataToPlot2=GroupRawData.(CurrentLevels{2});
MinVal=min([min(min(min(DataToPlot1))) min(min(min(DataToPlot2)))]);
MaxVal=max([max(max(max(DataToPlot1))) max(max(max(DataToPlot2)))]);
% Axes
XTStr = round(EEG.xmin*1000):50:round(EEG.xmax*1000,-1);
Ticks = linspace(1,size(DataToPlot1,2),size(XTStr,2));
% ColorMap
if ~exist('ColMap1','var')
ColMap1 = [PromptInputs{1} '(' PromptInputs{3} ')'];
end
if ~exist('ColMap2','var')
ColMap2 = [PromptInputs{2} '(' PromptInputs{3} ')'];
end
% 1) Original power of group 1 (mean)
subplot(4,4,[1 2 5 6])
imagesc(DataToPlot1)
xlabel('Time (ms)'), ylabel('Channels')
hold on; contour(logical(AllStats.Obs),1,'linecolor','k'); hold off;
title(sprintf('Power for group: %s',strrep(CurrentLevels{1},'_','-')))
set(gca,'ydir','norm')
set(gca,'XTick',Ticks,'XTickLabel',num2cell(XTStr));
set(gca,'YTick',1:2:length({EEG.chanlocs.labels}),'YTickLabel',Labels(1:2:end));
% COLORBAR
colormap(gca,ColMap1)
hcb1=colorbar;
if strcmpi(Normalization,'Y')
set(get(hcb1,'XLabel'),'String','Power (10*log10(\muV^2/Hz))');
else
set(get(hcb1,'XLabel'),'String','Power (\muV)');
end
caxis([MinVal MaxVal])
grid on
% 2) Original power of group 2 (mean)
subplot(4,4,[3 4 7 8])
imagesc(DataToPlot2)
xlabel('Time (ms)'), ylabel('Channels')
hold on; contour(logical(AllStats.Obs),1,'linecolor','k'); hold off;
title(sprintf('Power for group: %s',strrep(CurrentLevels{2},'_','-')))
set(gca,'ydir','norm')
set(gca,'XTick',Ticks,'XTickLabel',num2cell(XTStr));
set(gca,'YTick',2:2:length({EEG.chanlocs.labels}),'YTickLabel',Labels(2:2:end));
% COLORBAR
colormap(gca,ColMap1)
hcb2=colorbar;
caxis([MinVal MaxVal])
if strcmpi(Normalization,'Y')
set(get(hcb2,'XLabel'),'String','Power (10*log10(\muV^2/Hz))');
else
set(get(hcb2,'XLabel'),'String','Power (\muV)');
end
grid on
% 3) Permutation-corrected t-values
subplot(4,4,[9 10 13 14])
h=imagesc(AllStats.Obs);
xlabel('Time (ms)'), ylabel('Channels')
title(sprintf('TFCE permutation-corrected test [threshold for sig : %.2f]',...
Threshold(k)))
set(gca,'ydir','normal')
set(gca,'XTick',Ticks,'XTickLabel',num2cell(XTStr));
set(gca,'YTick',1:2:length({EEG.chanlocs.labels}),'YTickLabel',Labels(1:2:end));
% COLORBAR
% Set 0 (i.e. non-sig) values to transparent :
set(h,'alphadata',AllStats.Obs~=0)
cmap = colormap(gca,ColMap2);
hcb3=colorbar;
% Everything below/above the t-critical should be white
% BETTER METHOD BUT UNSURE WILL WORK WITH 2-SIDED EFFECTS !!!!!
StepSize = (hcb3.Limits(2)-hcb3.Limits(1))/size(cmap,1);
Steps = hcb3.Limits(2):-StepSize:hcb3.Limits(1);
Idx=Steps<abs(Threshold(k)) & Steps>-abs(Threshold(k));
% cmap(flip(Idx(2:end)),:)=repmat([1 1 1],[sum(Idx)-1,1]); % WHY -1 ?? Works if no -1 (for negative and positive values)
caxis([min(Steps(~Idx)) max(Steps(~Idx))+500])
% I ADDED THE + 500 otherwise couldn't see the results on top!!!!
colormap(gca,cmap);
title(hcb3, 'TFCE-values');
grid on
% Timing of significant electrodes
PosTopoplot = [11 12 15 16];
[SigElect,SigPoints]=find(AllStats.P_Values~=0);
SigPoints = unique(SigPoints);
SigElect = unique(SigElect);
SigLength = (SigPoints(end) - SigPoints(1))/2;
ExactPoints = EEG.xmin*EEG.srate:EEG.xmax*EEG.srate;
ExactTimes = round(SigPoints(1):SigLength:SigPoints(end));
% Retrieve the most significant electrode/time point
[~, MostSigPoints] = find(AllStats.P_Values==min(min(AllStats.P_Values(AllStats.P_Values~=0))));
% Min/max values for the color bar
MinVal(1) = min(min(DataToPlot1(:,MostSigPoints(1):MostSigPoints(end))));
MinVal(2) = min(min(DataToPlot2(:,MostSigPoints(1):MostSigPoints(end))));
MaxVal(1) = max(max(DataToPlot1(:,MostSigPoints(1):MostSigPoints(end))));
MaxVal(2) = max(max(DataToPlot2(:,MostSigPoints(1):MostSigPoints(end))));
% for each topoplot
for f=1:4
% 4) Prepare the subplots
subplot(4,4,PosTopoplot(f))
% Time in titles
if isempty(PromptInputs{4})
MinTime = round(ExactPoints(MostSigPoints(1))/EEG.srate*1000);
MaxTime = round(ExactPoints(MostSigPoints(end))/EEG.srate*1000,-1);
else
Temp = str2num(PromptInputs{4});
MinTime = Temp(1);
MaxTime = Temp(end);
MostSigPoints = ExactPoints(round(MinTime/EEG.srate*1000)): ...
ExactPoints(round(MaxTime/EEG.srate*1000)); % NOT SURE ABOUT THIS !!!
end
if f==1
% Topoplots
topoplotIndie(DataToPlot1(:,MostSigPoints(1):MostSigPoints(end)),...
EEG.chanlocs,'sigelect',SigElect,'colsigelect','k');
title(sprintf('%s [%d-%d ms]',strrep(CurrentLevels{1},'_','-'),...
MinTime,MaxTime))
% Colorbar
cmap = colormap(gca,ColMap1);
hcb4=colorbar;
caxis([min(MinVal) max(MaxVal)])
if strcmpi(Normalization,'Y')
set(get(hcb4,'XLabel'),'String','Power (10*log10(\muV^2/Hz))');
else
set(get(hcb4,'XLabel'),'String','Power (\muV)');
end
elseif f==2
% Topoplots
topoplotIndie(DataToPlot2(:,MostSigPoints(1):MostSigPoints(end)),...
EEG.chanlocs,'sigelect',SigElect,'colsigelect','k');
title(sprintf('%s [%d-%d ms]',strrep(CurrentLevels{2},'_','-'),...
MinTime,MaxTime))
% Colorbar
cmap = colormap(gca,ColMap1);
hcb4=colorbar;
caxis([min(MinVal) max(MaxVal)])
if strcmpi(Normalization,'Y')
set(get(hcb4,'XLabel'),'String','Power (10*log10(\muV^2/Hz))');
else
set(get(hcb4,'XLabel'),'String','Power (\muV)');
end
else
% Topoplots
topoplotIndie(DataToPlot1(:,ExactTimes(f-2):ExactTimes(f-1))- ...
DataToPlot2(:,ExactTimes(f-2):ExactTimes(f-1)),EEG.chanlocs,'sigelect',SigElect,'colsigelect','k');
title(sprintf('\\Delta %s - %s [%d-%d ms]',...
strrep(CurrentLevels{1},'_','-'),strrep(CurrentLevels{2},'_','-'),...
ExactPoints(round(ExactTimes(f-2)/EEG.srate*1000)), ...
ExactPoints(round(ExactTimes(f-1)/EEG.srate*1000))))
% Colorbar
cmap = colormap(gca,ColMap2);
hcb4=colorbar;
if strcmpi(Normalization,'Y')
set(get(hcb4,'XLabel'),'String','Power (10*log10(\muV^2/Hz))');
else
set(get(hcb4,'XLabel'),'String','Power (\muV)');
end
end
end
% Set figure as fullscreen
set(Fig, 'Units', 'Normalized', 'OuterPosition', [0 0 1 1]);
%% Export
% Exporting figures
% Export input
Export = questdlg('What would you like to do?', 'Figure export',...
'Export in .fig', 'Export in .bmp','Do not export','Export in .bmp');
if ~strcmpi(Export,'Do not export')
% Create export folders
mkdir ([save_folder '/Figures'])
end
% Are you satisfied?
Satisfy = questdlg('Are you satisfied with your colormap choice & figure export format specifications ?', 'Processing all figures',...
'yes', 'no','no');
if strcmpi(Satisfy,'no') && exist('ColParam1','var') || ...
strcmpi(Satisfy,'no') && exist('ColParam2','var')
ColorMap = questdlg(['Would you like to keep the ColorMap that you defined manually ?'...
newline 'IF NOT, CLOSE THE WINDOW'], 'Manual ColorMaps',...
'First ColorMap', 'Second ColorMap','Both ColorMaps','Both ColorMaps');
end
if strcmpi(Satisfy,'yes')
FirstRun = 0;
% Exporting
if strcmpi(Export,'Export in .bmp')
SaveFigures(gcf,[save_folder '/Figures/' Str2],'w','bmp');
elseif strcmpi(Export,'Export in .fig')
savefig([save_folder '/Figures/' Str2])
close gcf
elseif strcmpi(Export,'Do not export')
close gcf
end
% Free space
clear GroupRawData
elseif strcmpi(Satisfy,'no')
close gcf
elseif isempty(Satisfy)
disp('The program has been stopped');
break
end
end
end
%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% 2) ANOVAs ( CURRENTLY ONLY FOR MIXED 2x2 ! )
elseif contains(StatsData.(StatsDataFN{1}).Stats.Test,'Mixed ANOVA')
% For both main effects + interaction
% A = Within-subject main
% B = Between-subject main
% AB = Interaction
EffectsStr = fieldnames(AllStats);
for t=1:3
% Current statistic
CurrentStats = AllStats.(EffectsStr{t});
% Thresholding the statistics based on alpha (e.g. 0.05)
CurrentStats.P_Values(CurrentStats.P_Values>Pval) = 0;
CurrentStats.Obs(CurrentStats.P_Values==0) = 0;
% Only if significant clusters survived thresholding
if SigClust(k,t)>0
% Looking for index of frequency boundaries
CurrentBounds=str2num(BandsList{contains(BandsList(:,1),CurrentBand),2});
BoundsIdx=find(ge(AllFreqs,CurrentBounds(1)) & le(AllFreqs,CurrentBounds(2)));
% Assigning each participant data to its group/condition
% Columns are Between-subject factors (B)
% Lines are Within-subject (A)
TempDataCell = struct2cell(TempData);
for m=1:length(BetweenLevels)
for l=1:length(WithinLevels)
Idx = find(contains(SubjFN,BetweenLevels{m})+contains(SubjFN,WithinLevels{l}) == 2);
DataTemp = cellfun(@(x) squeeze(mean(x(:,BoundsIdx,:),2)),TempDataCell(Idx),'UniformOutput',0);
for u=1:length(DataTemp)
GroupRawData{m,l}(u,:,:) = DataTemp{u};
end
end
end
% Averaging over participants
GroupRawData = cellfun(@(x) squeeze(mean(x,1)),GroupRawData,'UniformOutput',false);
%% Settings
% SHOULD LET THE POSSIBILITY TO DEFINE THE RANGE FOR EACH TOPOPLOT.
% Hence, at the end of the loop, if re-run, clear the variables
% link the time range and below only create them is doesn't exit
% (hence, if prompt here is empty for time range).
% Prompt allowing to adjust on the first figure the colormap
% options
ColorMap={};
% Only for the 1st figure
while FirstRun
PromptSetup = {['1) Enter the name of the ColorMap to use for MEANS:'...
newline 'e.g. parula, jet, hsv, hot, bluewhitered'...
newline 'If left empty, opens a software to design it manually!'],...
['2) Enter the name of the ColorMap to use for STATS and TOPOPLOTS:'...
newline 'If left empty, opens a software to design it manually!']...
'Enter the number of Color bins:'...
'Range of topoplots (is ms, optional)'};
PromptInputs = inputdlg(PromptSetup,'Figure ColorMap Settings',1,{'jet','hot','50',''});
% Manual configuration of the color maps
% COLORMAP 1
if isempty(PromptInputs{1}) && isempty(ColorMap) || ...
isempty(PromptInputs{1}) && strcmpi(ColorMap,'Second ColorMap')
if exist('ColParam1','var')
[ColMap1,ColParam1] = cubehelix_view(size(ColMap1,1),ColParam1(1),...
ColParam1(2),ColParam1(3),ColParam1(4),ColParam1(5:6),ColParam1(7:8));
else
[ColMap1,ColParam1] = cubehelix_view(str2double(PromptInputs{3}));
end
% Reversing the direction of the Colormap
ColMap1 = flipud(ColMap1);
end
% COLORMAP 2
if isempty(PromptInputs{2}) && isempty(ColorMap) || ...
isempty(PromptInputs{1}) && strcmpi(ColorMap,'First ColorMap')
if exist('ColParam2','var')
[ColMap2,ColParam2] = cubehelix_view(size(ColMap2,1),ColParam2(1),...
ColParam2(2),ColParam2(3),ColParam2(4),ColParam2(5:6),ColParam2(7:8));
else
[ColMap2,ColParam2] = cubehelix_view(str2double(PromptInputs{3}));
end
% Reversing the direction of the Colormap
ColMap2 = flipud(ColMap2);
end
%% PLOTTING
% plot tresholded results
Fig = figure; clf
% More space if no bar
set(gcf, 'MenuBar', 'None', 'ToolBar','None')
% Grand title over all subplots
Str1=sprintf('%s-%s-%s-%s: %s [%d-%d Hz]',Analyses{k},Level1{k},Level2{k},...
['Contrast' EffectsStr{t}],FreqBands{k},CurrentBounds(1),CurrentBounds(end));
Str2=sprintf('%s_%s_%s_%s_%s',Analyses{k},Level1{k},Level2{k},['Contrast' EffectsStr{t}],FreqBands{k});
annotation('textbox',[.35 .5 .5 .5],'String',...
Str1,'FitBoxToText','on','FontSize',20,'EdgeColor','w');
% DATA TO PLOT + SETTINGS
% Main Effects
if t == 1 % Within
DataToPlot1=mean(reshape([GroupRawData{1,1} GroupRawData{1,2}],...
[size(GroupRawData{1,1},1) size(GroupRawData{1,1},2) 2]),3);
DataToPlot2=mean(reshape([GroupRawData{2,1} GroupRawData{2,2}],...
[size(GroupRawData{2,1},1) size(GroupRawData{2,1},2) 2]),3);
% Min/max (for scale)
MinVal=min([min(min(min(DataToPlot1))) min(min(min(DataToPlot2)))]);
MaxVal=max([max(max(max(DataToPlot1))) max(max(max(DataToPlot2)))]);
% Define current levels
CurrentLevels = WithinLevels;
% Position of subplots
Plot1 = [1 2 5 6]; Plot2 = [3 4 7 8];
elseif t == 2 % Between
DataToPlot1=mean(reshape([GroupRawData{1,1} GroupRawData{2,1}],...
[size(GroupRawData{1,1},1) size(GroupRawData{1,1},2) 2]),3);
DataToPlot2=mean(reshape([GroupRawData{1,2} GroupRawData{2,2}],...
[size(GroupRawData{1,2},1) size(GroupRawData{1,2},2) 2]),3);
% Min/max (for scale)
MinVal=min([min(min(min(DataToPlot1))) min(min(min(DataToPlot2)))]);
MaxVal=max([max(max(max(DataToPlot1))) max(max(max(DataToPlot2)))]);
% Define current levels
CurrentLevels = BetweenLevels;
% Number of subplots
Plot1 = [1 2 5 6]; Plot2 = [3 4 7 8];
% Interaction
else
% Within
DataToPlot1=mean(reshape([GroupRawData{1,1} GroupRawData{1,2}],...
[size(GroupRawData{1,1},1) size(GroupRawData{1,1},2) 2]),3);
DataToPlot2=mean(reshape([GroupRawData{2,1} GroupRawData{2,2}],...
[size(GroupRawData{2,1},1) size(GroupRawData{2,1},2) 2]),3);
% Between
DataToPlot3=mean(reshape([GroupRawData{1,1} GroupRawData{2,1}],...
[size(GroupRawData{1,1},1) size(GroupRawData{1,1},2) 2]),3);
DataToPlot4=mean(reshape([GroupRawData{1,2} GroupRawData{2,2}],...
[size(GroupRawData{1,2},1) size(GroupRawData{1,2},2) 2]),3);
% Min/max (for scale)
MinVal=min([min(min(min(DataToPlot1))) min(min(min(DataToPlot2))) ...
min(min(min(DataToPlot3))) min(min(min(DataToPlot4)))]);
MaxVal=max([max(max(max(DataToPlot1))) max(max(max(DataToPlot2)))...
max(max(max(DataToPlot3))) max(max(max(DataToPlot4)))]);
% Number of subplots
Plot1 = [1 2]; Plot2 = [3 4];
Plot3 = [5 6]; Plot4 = [7 8];
% Define current levels (concatenate all)
CurrentLevels = [WithinLevels;BetweenLevels];
end
% Axes
XTStr = round(EEG.xmin*1000):50:round(EEG.xmax*1000,-1);
Ticks = linspace(1,size(DataToPlot1,2),size(XTStr,2));
% ColorMap
if ~exist('ColMap1','var')
ColMap1 = [PromptInputs{1} '(' PromptInputs{3} ')'];
end
if ~exist('ColMap2','var')
ColMap2 = [PromptInputs{2} '(' PromptInputs{3} ')'];
end
%% SUBPLOTS
StringCompare = {'condition','group'};
% for main effects
if t<3
%% 1) Observed power of group/condition 1
subplot(4,4,Plot1)
imagesc(DataToPlot1)
xlabel('Time (ms)'), ylabel('Channels')
hold on; contour(logical(CurrentStats.Obs),1,'linecolor','k'); hold off;
title(sprintf('Power for %s: %s',StringCompare{t},strrep(CurrentLevels{1},'_','-')))
set(gca,'ydir','norm')
set(gca,'XTick',Ticks,'XTickLabel',num2cell(XTStr));
set(gca,'YTick',1:2:length({EEG.chanlocs.labels}),'YTickLabel',Labels(1:2:end));
% COLORBAR
colormap(gca,ColMap1)
hcb1=colorbar;
if strcmpi(Normalization,'Y')
set(get(hcb1,'XLabel'),'String','Power (10*log10(\muV^2/Hz))');
else
set(get(hcb1,'XLabel'),'String','Power (\muV)');
end
caxis([MinVal MaxVal])
grid on
%% 2) Observed power of group/condition 2
subplot(4,4,Plot2)
imagesc(DataToPlot2)
xlabel('Time (ms)'), ylabel('Channels')
hold on; contour(logical(CurrentStats.Obs),1,'linecolor','k'); hold off;
title(sprintf('Power for %s: %s',StringCompare{t},strrep(CurrentLevels{2},'_','-')))
set(gca,'ydir','norm')
set(gca,'XTick',Ticks,'XTickLabel',num2cell(XTStr));
set(gca,'YTick',2:2:length({EEG.chanlocs.labels}),'YTickLabel',Labels(2:2:end));
% COLORBAR
colormap(gca,ColMap1)
hcb2=colorbar;
caxis([MinVal MaxVal])
if strcmpi(Normalization,'Y')
set(get(hcb2,'XLabel'),'String','Power (10*log10(\muV^2/Hz))');
else
set(get(hcb2,'XLabel'),'String','Power (\muV)');
end
grid on
% for interaction
elseif t == 3
%% 1) Observed power for Condition 1
subplot(4,4,Plot1)
imagesc(DataToPlot1)
xlabel('Time (ms)'), ylabel('Channels')
hold on; contour(logical(CurrentStats.Obs),1,'linecolor','k'); hold off;
title(sprintf('Power for %s: %s',StringCompare{1},strrep(CurrentLevels{1},'_','-')))
set(gca,'ydir','norm')
set(gca,'XTick',Ticks,'XTickLabel',num2cell(XTStr));
set(gca,'YTick',1:2:length({EEG.chanlocs.labels}),'YTickLabel',Labels(1:2:end));
% COLORBAR
colormap(gca,ColMap1)
hcb1=colorbar;
if strcmpi(Normalization,'Y')
set(get(hcb1,'XLabel'),'String','Power (10*log10(\muV^2/Hz))');
else
set(get(hcb1,'XLabel'),'String','Power (\muV)');
end
caxis([MinVal MaxVal])
grid on
%% 2) Observed power for Condition 2
subplot(4,4,Plot2)
imagesc(DataToPlot2)
xlabel('Time (ms)'), ylabel('Channels')
hold on; contour(logical(CurrentStats.Obs),1,'linecolor','k'); hold off;
title(sprintf('Power for %s: %s',StringCompare{1},strrep(CurrentLevels{2},'_','-')))
set(gca,'ydir','norm')
set(gca,'XTick',Ticks,'XTickLabel',num2cell(XTStr));
set(gca,'YTick',2:2:length({EEG.chanlocs.labels}),'YTickLabel',Labels(2:2:end));
% COLORBAR
colormap(gca,ColMap1)
hcb2=colorbar;
caxis([MinVal MaxVal])
if strcmpi(Normalization,'Y')
set(get(hcb2,'XLabel'),'String','Power (10*log10(\muV^2/Hz))');
else
set(get(hcb2,'XLabel'),'String','Power (\muV)');
end
grid on
%% 3) Observed power for Group 1
subplot(4,4,Plot3)
imagesc(DataToPlot3)
xlabel('Time (ms)'), ylabel('Channels')
hold on; contour(logical(CurrentStats.Obs),1,'linecolor','k'); hold off;
title(sprintf('Power for %s: %s',StringCompare{2},strrep(CurrentLevels{3},'_','-')))
set(gca,'ydir','norm')
set(gca,'XTick',Ticks,'XTickLabel',num2cell(XTStr));
set(gca,'YTick',1:2:length({EEG.chanlocs.labels}),'YTickLabel',Labels(1:2:end));
% COLORBAR
colormap(gca,ColMap1)
hcb1=colorbar;
if strcmpi(Normalization,'Y')
set(get(hcb1,'XLabel'),'String','Power (10*log10(\muV^2/Hz))');
else
set(get(hcb1,'XLabel'),'String','Power (\muV)');
end
caxis([MinVal MaxVal])
grid on
%% 4) Observed power for Group 2
subplot(4,4,Plot4)
imagesc(DataToPlot4)
xlabel('Time (ms)'), ylabel('Channels')
hold on; contour(logical(CurrentStats.Obs),1,'linecolor','k'); hold off;
title(sprintf('Power for %s: %s',StringCompare{2},strrep(CurrentLevels{4},'_','-')))
set(gca,'ydir','norm')
set(gca,'XTick',Ticks,'XTickLabel',num2cell(XTStr));
set(gca,'YTick',2:2:length({EEG.chanlocs.labels}),'YTickLabel',Labels(2:2:end));
% COLORBAR
colormap(gca,ColMap1)
hcb2=colorbar;
caxis([MinVal MaxVal])
if strcmpi(Normalization,'Y')
set(get(hcb2,'XLabel'),'String','Power (10*log10(\muV^2/Hz))');
else
set(get(hcb2,'XLabel'),'String','Power (\muV)');
end
grid on
end
%% 3) Permutation-corrected t-values
subplot(4,4,[9 10 13 14])
h=imagesc(CurrentStats.Obs);
xlabel('Time (ms)'), ylabel('Channels')
title(sprintf('TFCE permutation-corrected test [threshold for sig : %.2f]',...
Pval))
set(gca,'ydir','normal')
set(gca,'XTick',Ticks,'XTickLabel',num2cell(XTStr));
set(gca,'YTick',1:2:length({EEG.chanlocs.labels}),'YTickLabel',Labels(1:2:end));
% COLORBAR
% Set 0 (i.e. non-sig) values to transparent :
set(h,'alphadata',CurrentStats.Obs~=0)
cmap = colormap(gca,ColMap2);
hcb3=colorbar;
% Everything below/above the t-critical should be white
% BETTER METHOD BUT UNSURE WILL WORK WITH 2-SIDED EFFECTS !!!!!
% THIS WILL ONLY WORK IF I REPORT THE TFCE RESULTS...
% StepSize = (hcb3.Limits(2)-hcb3.Limits(1))/size(cmap,1);
% Steps = hcb3.Limits(2):-StepSize:hcb3.Limits(1);
% Idx=Steps<abs(Threshold(k)) & Steps>-abs(Threshold(k));
% caxis([min(Steps(~Idx)) max(Steps(~Idx))+500])
% I ADDED THE + 500 otherwise couldn't see the results on top!!!!
colormap(gca,cmap);
title(hcb3, 't-values');
grid on
% Position to plot the topoplots
PosTopoplot = [11 12 15 16];
% Timing of significant electrodes
[SigElect,SigPoints]=find(CurrentStats.P_Values~=0);
SigPoints = unique(SigPoints);
SigElect = unique(SigElect);
SigLength = (SigPoints(end) - SigPoints(1))/2;
ExactPoints = EEG.xmin*EEG.srate:EEG.xmax*EEG.srate;
ExactTimes = round(SigPoints(1):SigLength:SigPoints(end));
% Retrieve the most significant electrode/time point
[~, MostSigPoints] = find(CurrentStats.P_Values==min(min(CurrentStats.P_Values(CurrentStats.P_Values~=0))));
% For main effects
if t<3
% Min/max values for the color bar
MinVal(1) = min(min(DataToPlot1(:,MostSigPoints(1):MostSigPoints(end))));
MinVal(2) = min(min(DataToPlot2(:,MostSigPoints(1):MostSigPoints(end))));
MaxVal(1) = max(max(DataToPlot1(:,MostSigPoints(1):MostSigPoints(end))));
MaxVal(2) = max(max(DataToPlot2(:,MostSigPoints(1):MostSigPoints(end))));
% for each topoplot
for f=1:4
% 4) Prepare the subplots
subplot(4,4,PosTopoplot(f))
% Time in titles
if isempty(PromptInputs{4})
MinTime = round(ExactPoints(MostSigPoints(1))/EEG.srate*1000);
MaxTime = round(ExactPoints(MostSigPoints(end))/EEG.srate*1000,-1);
else
Temp = str2num(PromptInputs{4});
MinTime = Temp(1);
MaxTime = Temp(end);
MostSigPoints = ExactPoints(round(MinTime/EEG.srate*1000)): ...
ExactPoints(round(MaxTime/EEG.srate*1000)); % NOT SURE ABOUT THIS !!!
end
if f==1
% Topoplots
topoplotIndie(DataToPlot1(:,MostSigPoints(1):MostSigPoints(end)),...
EEG.chanlocs,'sigelect',SigElect,'colsigelect','k');
title(sprintf('%s [%d %dms]',strrep(CurrentLevels{1},'_','-'),...
MinTime,MaxTime))
% Colorbar
cmap = colormap(gca,ColMap1);
hcb4=colorbar;
caxis([min(MinVal) max(MaxVal)])
if strcmpi(Normalization,'Y')
set(get(hcb4,'XLabel'),'String','Power (10*log10(\muV^2/Hz))');
else
set(get(hcb4,'XLabel'),'String','Power (\muV)');
end
elseif f==2
% Topoplots
topoplotIndie(DataToPlot2(:,MostSigPoints(1):MostSigPoints(end)),...
EEG.chanlocs,'sigelect',SigElect,'colsigelect','k');
title(sprintf('%s [%d %dms]',strrep(CurrentLevels{2},'_','-'),...
MinTime,MaxTime))
% Colorbar
cmap = colormap(gca,ColMap1);
hcb4=colorbar;
caxis([min(MinVal) max(MaxVal)])
if strcmpi(Normalization,'Y')
set(get(hcb4,'XLabel'),'String','Power (10*log10(\muV^2/Hz))');
else
set(get(hcb4,'XLabel'),'String','Power (\muV)');
end
else
% Topoplots
topoplotIndie(DataToPlot1(:,ExactTimes(f-2):ExactTimes(f-1))- ...
DataToPlot2(:,ExactTimes(f-2):ExactTimes(f-1)),EEG.chanlocs,'sigelect',SigElect,'colsigelect','k');
title(sprintf('\\Delta %s - %s [%d %dms]',...
strrep(CurrentLevels{1},'_','-'),strrep(CurrentLevels{2},'_','-'),...
ExactPoints(round(ExactTimes(f-2)/EEG.srate*1000)), ...
ExactPoints(round(ExactTimes(f-1)/EEG.srate*1000))))
% Colorbar
cmap = colormap(gca,ColMap2);
hcb4=colorbar;
if strcmpi(Normalization,'Y')
set(get(hcb4,'XLabel'),'String','Power (10*log10(\muV^2/Hz))');
else
set(get(hcb4,'XLabel'),'String','Power (\muV)');
end
end
end
% For interaction effect
elseif t == 3
% Min/max values for the color bar
MinVal(1) = min(min(DataToPlot1(:,MostSigPoints(1):MostSigPoints(end))));
MinVal(2) = min(min(DataToPlot2(:,MostSigPoints(1):MostSigPoints(end))));
MinVal(3) = min(min(DataToPlot3(:,MostSigPoints(1):MostSigPoints(end))));
MinVal(4) = min(min(DataToPlot4(:,MostSigPoints(1):MostSigPoints(end))));
MaxVal(1) = max(max(DataToPlot1(:,MostSigPoints(1):MostSigPoints(end))));
MaxVal(2) = max(max(DataToPlot2(:,MostSigPoints(1):MostSigPoints(end))));
MaxVal(3) = max(max(DataToPlot3(:,MostSigPoints(1):MostSigPoints(end))));
MaxVal(4) = max(max(DataToPlot4(:,MostSigPoints(1):MostSigPoints(end))));
% for each topoplot
for f=1:4
% 4) Prepare the subplots
subplot(4,4,PosTopoplot(f))
% Time in titles
if isempty(PromptInputs{4})
MinTime = round(ExactPoints(MostSigPoints(1))/EEG.srate*1000);
MaxTime = round(ExactPoints(MostSigPoints(end))/EEG.srate*1000,-1);
else
Temp = str2num(PromptInputs{4});
MinTime = Temp(1);
MaxTime = Temp(end);
MostSigPoints = ExactPoints(round(MinTime/EEG.srate*1000)): ...
ExactPoints(round(MaxTime/EEG.srate*1000)); % NOT SURE ABOUT THIS !!!
end
if f<3
% Topoplots
Pos = 1;
topoplotIndie(DataToPlot1(:,ExactTimes(Pos):ExactTimes(Pos+1))- ...
DataToPlot2(:,ExactTimes(Pos):ExactTimes(Pos+1)),EEG.chanlocs,'sigelect',SigElect,'colsigelect','k');
title(sprintf('\\Delta %s - %s [%d %dms]',...
strrep(CurrentLevels{1},'_','-'),strrep(CurrentLevels{2},'_','-'),...
ExactPoints(round(ExactTimes(Pos)/EEG.srate*1000)), ...
ExactPoints(round(ExactTimes(Pos+1)/EEG.srate*1000))))
% Colorbar
cmap = colormap(gca,ColMap2);
hcb4=colorbar;
if strcmpi(Normalization,'Y')
set(get(hcb4,'XLabel'),'String','Power (10*log10(\muV^2/Hz))');
else
set(get(hcb4,'XLabel'),'String','Power (\muV)');
end
else
Pos = 2;
% Topoplots
topoplotIndie(DataToPlot3(:,ExactTimes(Pos):ExactTimes(Pos+1))- ...
DataToPlot4(:,ExactTimes(Pos):ExactTimes(Pos+1)),EEG.chanlocs,'sigelect',SigElect,'colsigelect','k');
title(sprintf('\\Delta %s - %s [%d %dms]',...
strrep(CurrentLevels{3},'_','-'),strrep(CurrentLevels{4},'_','-'),...
ExactPoints(round(ExactTimes(Pos)/EEG.srate*1000)), ...
ExactPoints(round(ExactTimes(Pos+1)/EEG.srate*1000))))
% Colorbar
cmap = colormap(gca,ColMap2);
hcb4=colorbar;
if strcmpi(Normalization,'Y')
set(get(hcb4,'XLabel'),'String','Power (10*log10(\muV^2/Hz))');
else
set(get(hcb4,'XLabel'),'String','Power (\muV)');
end
end
end
end
% Set figure as fullscreen
set(Fig, 'Units', 'Normalized', 'OuterPosition', [0 0 1 1]);
%% Export
% Exporting figures
% Export input
Export = questdlg('What would you like to do?', 'Figure export',...
'Export in .fig', 'Export in .bmp','Do not export','Export in .bmp');
if ~strcmpi(Export,'Do not export')
% Create export folders
mkdir ([save_folder '/Figures'])
end
% Are you satisfied?
Satisfy = questdlg('Are you satisfied with your colormap choice & figure export format specifications ?', 'Processing all figures',...
'yes', 'no','no');
if strcmpi(Satisfy,'no') && exist('ColParam1','var') || ...
strcmpi(Satisfy,'no') && exist('ColParam2','var')
ColorMap = questdlg(['Would you like to keep the ColorMap that you defined manually ?'...
newline 'IF NOT, CLOSE THE WINDOW'], 'Manual ColorMaps',...
'First ColorMap', 'Second ColorMap','Both ColorMaps','Both ColorMaps');