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@AyaKabbara
AyaKabbara committed Jul 21, 2022
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212 changes: 91 additions & 121 deletions src/eeglab/eeglab_preprocessing.m
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% % % % % EEGLAB history file generated on the 04-Jan-2022
% % % % % ------------------------------------------------
% % % % %
% % % %
% % % % % 1st pass: detect bad electrodes using clean_artifacts
% %
% % cd('/Users/ayakabbara/Desktop/projects/EEG_PreProcessing/Raw Data Part 1'); %Find and change working folder to raw EEG data
% % filenames = dir('*.vhdr')
% % nb=500;
% % for participant = 1:nb %Cycle through participants
% %
% % % Get participant name information
% % disp(['Participant: ', num2str(participant)]) %Display current participant being processed
% % participant_number = strsplit(filenames(participant).name(1:end-5),'_'); %Split filename into components
% %
% % EEG = pop_loadbv('/Users/ayakabbara/Desktop/projects/EEG_PreProcessing/Raw Data Part 1/', filenames(participant).name);
% % % ajouter chanlocs
% % EEG=pop_chanedit(EEG, 'lookup','/Users/ayakabbara/Desktop/projects/EEG_PreProcessing/eeglab2021.1/functions/supportfiles/Standard-10-20-Cap81.ced');
% %
% % % % passer à 32 channels: use the eeglab function
% % % %
% % try
% % if(EEG.nbchan > 32)
% % EEG = pop_select(EEG, 'channel',{'Fp1'
% % 'Fz'
% % 'F3'
% % 'F7'
% % 'FC5'
% % 'FC1'
% % 'Cz'
% % 'C3'
% % 'T7'
% % 'CP5'
% % 'CP1'
% % 'Pz'
% % 'P3'
% % 'P7'
% % 'O1'
% % 'POz'
% % 'O2'
% % 'P4'
% % 'P8'
% % 'CP6'
% % 'CP2'
% % 'C4'
% % 'T8'
% % 'FC6'
% % 'FC2'
% % 'FCz'
% % 'F4'
% % 'F8'
% % 'Fp2'
% % 'TP10'
% % 'TP9'});
% % end
% % catch
% % disp('Problem');
% % rm_channels{participant}='';
% % continue;
% % end
% %
% % EEG = pop_eegfiltnew(EEG, 'locutoff',0.1,'hicutoff',30);
% % [eeg2,HP,BUR,removed_channels] = clean_artifacts(EEG);
% % rm_channels{participant}=find(removed_channels);
% % end
% % save('eeglab_removedchans500','rm_channels');

% % --- This is the preprocessing workflow reproduced by EEGLAB functions---
% % For contact: [email protected]

%% 1st pass: detect bad electrodes using clean_artifacts
cd('/Raw Data'); %Find and change working folder to raw EEG data

filenames = dir('*.vhdr')
nb=500;
for participant = 1:nb %Cycle through participants

% Get participant name information
disp(['Participant: ', num2str(participant)]) %Display current participant being processed
participant_number = strsplit(filenames(participant).name(1:end-5),'_'); %Split filename into components

EEG = pop_loadbv('/Raw Data Part 1/', filenames(participant).name);
% add the channel location file
EEG=pop_chanedit(EEG, 'lookup','/eeglab2021.1/functions/supportfiles/Standard-10-20-Cap81.ced');

% % passer à 32 channels: use the eeglab function

try
if(EEG.nbchan > 32)
EEG = pop_select(EEG, 'channel',{'Fp1'
'Fz'
'F3'
'F7'
'FC5'
'FC1'
'Cz'
'C3'
'T7'
'CP5'
'CP1'
'Pz'
'P3'
'P7'
'O1'
'POz'
'O2'
'P4'
'P8'
'CP6'
'CP2'
'C4'
'T8'
'FC6'
'FC2'
'FCz'
'F4'
'F8'
'Fp2'
'TP10'
'TP9'});
end
catch
disp('Problem');
rm_channels{participant}='';
continue;
end

EEG = pop_eegfiltnew(EEG, 'locutoff',0.1,'hicutoff',30);
[eeg2,HP,BUR,removed_channels] = clean_artifacts(EEG);
rm_channels{participant}=find(removed_channels);
end
% save the detected bad channels
save('eeglab_removedchans500','rm_channels');

% % 2nd pass: pre-process signals using the same paper's pipeline
clear all;
clc;
load('eeglab_removedchans500');
cd('/Users/ayakabbara/Desktop/projects/EEG_PreProcessing/Raw Data Part 1'); %Find and change working folder to raw EEG data
cd('/Raw Data Part 1'); %Find and change working folder to raw EEG data
filenames = dir('*.vhdr')
nb=500;
for participant = 1:nb %Cycle through participants

%Get participant name information
disp(['Participant: ', num2str(participant)]) %Display current participant being processed
participant_number = strsplit(filenames(participant).name(1:end-5),'_'); %Split filename into components
% participant_varname = ['eeglab_RewardProcessing_S2Final_',participant_number{2}]; %Create new file name

EEG = pop_loadbv('/Users/ayakabbara/Desktop/projects/EEG_PreProcessing/Raw Data Part 1/', filenames(participant).name);
%ajouter chanlocs
EEG = pop_loadbv('/Raw Data Part 1/', filenames(participant).name);

EEG=pop_chanedit(EEG, 'lookup','/Users/ayakabbara/Desktop/projects/EEG_PreProcessing/eeglab2021.1/functions/supportfiles/Standard-10-20-Cap81.ced');
%% add the chanlocation file
EEG=pop_chanedit(EEG, 'lookup','/eeglab2021.1/functions/supportfiles/Standard-10-20-Cap81.ced');

%passer à 32 channels: use the eeglab function
%% reduce to 32 channels

try
if(EEG.nbchan > 32)
Expand Down Expand Up @@ -120,25 +119,24 @@
'TP10'
'TP9'});
end
% % interpolate the detected bad channels

%% interpolate the detected bad channels
EEG = pop_interp(EEG, rm_channels{participant}, 'spherical');

%renseigner les channels reference
%% re-reference
EEG=pop_chanedit(EEG, 'seteeglab',{'1:31','TP10 TP9'});
EEG = pop_reref( EEG ,{'TP9','TP10'});

%interpoler les channels eeglab == ici il faut pas interpolet TP9 et TP10,
%mais AFZ

%filtre passe bande 0.1-30
%% filter signals
EEG = pop_eegfiltnew(EEG, 'locutoff',0.1,'hicutoff',30);

%segment data
%% segment data
markers = {'S110','S111'}; %Loss, win
[EEG] = doSegmentData(EEG,markers,[-500 1298]); %Segment Data (S110 = Loss, S111 = Win). The segment window of interest is -200 to 1000ms, and we here add 300 ms before and after this because time-frequency edge artifacts (this is different than the first pass because we were being more conservative then)
[EEG] = doSegmentData(EEG,markers,[-500 1298]); %Segment Data (S110 = Loss, S111 = Win). The segment window of interest is -200 to 1000ms, and we here add 300 ms before and after this because time-frequency edge artifacts (this is different than the first pass because we were being more conservative then)
EEG = pop_rmbase( EEG, [-200/1000,0]);
try
% % trials removal
%% trials removal
EEG = pop_eegthresh(EEG,1,[1:29] ,-50,50,-0.2,1.2,0,1);
%ERP
[EEG.ERP] = doERP(EEG,markers,0); %Conduct ERP Analyses
Expand All @@ -156,49 +154,21 @@
end
end

%% save outputs


save('All_ERP_eeglab500', 'All_ERP_eeglab'); %Save ERP Data
save('All_ERP_eeglab', 'All_ERP_eeglab'); %Save ERP Data

All_ERP=All_ERP_eeglab(:,151:750,:,:);
chanOfInterest=17;
% % channelof interest is FCz :
% % =17 as resulted by EEGLAB

% %% RewP_Waveforms_AllPs
chanOfInterest=17;
% channel of interest 17 is FCz
%% RewP_Waveforms_AllPs
tt1=squeeze(All_ERP(chanOfInterest,:,1,:));
tt2=squeeze(All_ERP(chanOfInterest,:,2,:));

idx1 = isnan(tt1) ;
[r1,c1]=find(tt1==0);
[r1,c3]=find(idx1);

% tt1(:,unique(c1))=[];
% tt2(:,unique(c1))=[];

idx2 = isnan(tt2) ;
[r2,c2]=find(tt2==0);
[r1,c4]=find(idx2);

% tt2(:,unique(c2))=[];
% tt1(:,unique(c2))=[];
%
toberemoved=unique([unique(c1) ;unique(c2); unique(c3); unique(c4)]);
tKept1=[];tKept2=[];
kept_eeglab=[];
for su=1:500
if(length(find(toberemoved==su))==0)
% % the subject su is present
kept_eeglab(end+1)=su;
tKept1(:,end+1)=tt1(:,su);
tKept2(:,end+1)=tt2(:,su);

end
end
% %% RewP_Waveforms
csvwrite('eeglab_RewP_Waveforms_thresh100.csv',[(-200:2:998)',nanmean(squeeze(All_ERP(chanOfInterest,:,1,kept_eeglab)),2),nanmean(squeeze(All_ERP(chanOfInterest,:,2,kept_eeglab)),2),nanmean(squeeze(All_ERP(chanOfInterest,:,1,kept_eeglab)),2)-nanmean(squeeze(All_ERP(chanOfInterest,:,2,kept_eeglab)),2)]); %Export data. Conditions: Time, Loss, Win, Difference. Electrode 26 is FCz.
csvwrite('eeglab_RewP_Waveforms_AllPs_thresh100.csv',[tKept1,tKept2]'); %Export data. Conditions: Loss, Win. Electrode 26 is FCz.
% %% RewP_Latency
[~,peak_loc] = max(squeeze(All_ERP(chanOfInterest,226:276,1,kept_eeglab))-squeeze(All_ERP(chanOfInterest,226:276,2,kept_eeglab))); %Determine where the peak amplitude is for each participant. Electrode 26 is FCz.
% %% RewP_Waveforms
csvwrite('eeglab_RewP_Waveforms.csv',[(-200:2:998)',nanmean(squeeze(All_ERP(chanOfInterest,:,1,:)),2),nanmean(squeeze(All_ERP(chanOfInterest,:,2,:)),2),nanmean(squeeze(All_ERP(chanOfInterest,:,1,:)),2)-nanmean(squeeze(All_ERP(chanOfInterest,:,2,:)),2)]); %Export data. Conditions: Time, Loss, Win, Difference. Electrode 26 is FCz.
csvwrite('eeglab_RewP_Waveforms_AllPs.csv',[tt1,tt2]'); %Export data. Conditions: Loss, Win. Electrode 26 is FCz.
% %% RewP_Latency
[~,peak_loc] = max(squeeze(All_ERP(chanOfInterest,226:276,1,:))-squeeze(All_ERP(chanOfInterest,226:276,2,:))); %Determine where the peak amplitude is for each participant. Electrode 26 is FCz.
peak_loc = (((peak_loc+225)*2)-200)/1000; %Convert into seconds
csvwrite('eeglab_RewP_Latency_thresh100.csv',peak_loc'); %Export data
csvwrite('eeglab_RewP_Latency.csv',peak_loc'); %Export data

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