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%% 3AOB JFC
clear all; clc
addpath('Z:\EXPERIMENTS\mTBICoBRE\EEG\');
addpath(genpath('Y:\Programs\eeglab12_0_2_1b'));
rmpath('Y:\Programs\eeglab12_0_2_1b\functions\octavefunc');
rmpath('Y:\Programs\eeglab14_0_0b\functions\octavefunc');
datadir='Y:\EEG_Data\mTBICoBRE\'; % Data are here
saveloc='Z:\EXPERIMENTS\mTBICoBRE\EEG\3AOB Preproc\';
load('Z:\EXPERIMENTS\mTBICoBRE\EEG\BV_Chanlocs_60.mat');
cd(saveloc);
sx_dirs=dir([datadir,'M*']);
for sxi=1:length(sx_dirs)
for ses=1:3
sessdir=[datadir,sx_dirs(sxi).name,'\eeg\RawEEG\'];
sx_sess{sxi}{1,ses}=dir([sessdir,'*_',num2str(ses),'_ODDBALL.vhdr']);
sx_sess{sxi}{2,ses}=sessdir;
sx_sess{sxi}{3,ses}=sx_dirs(sxi).name;
end
end
LOG=[];
for sxi=1:size(sx_sess,2)
for sess=1:3
if ~isempty( sx_sess{sxi}{1,sess} )
subno=str2num(sx_sess{sxi}{1,sess}.name(1:4));
URSI=sx_sess{sxi}{3,sess};
LOG(subno-3000,sess+1)=subno;
LOG(subno-3000,1)=str2num(URSI(end-4:end));
end
end
end
for sxi=1:size(sx_sess,2)
for sess=1:3
if ~isempty( sx_sess{sxi}{1,sess} )
subno=str2num(sx_sess{sxi}{1,sess}.name(1:4));
thisdir=sx_sess{sxi}{2,sess};
URSI=sx_sess{sxi}{3,sess};
LOG2(sxi,sess)=subno;
if ~exist([saveloc,num2str(subno),'_',num2str(sess),'_3AOB.mat']);
% Data are 65 chans: 1=63 is EEG, 64 is VEOG, 65 is EKG Ref'd to CPz - - will want to retrieve that during re-referencing
EEG = pop_loadbv(thisdir,[num2str(subno),'_',num2str(sess),'_ODDBALL.vhdr']); clc; disp(['Loading ',num2str(subno),' s',num2str(sess)]);
% Run PATCH for sx<3003 s<2 AND for bad templates
PATCH
% Get Locs
locpath=('Y:\Programs\eeglab12_0_2_1b\plugins\dipfit2.2\standard_BESA\standard-10-5-cap385.elp');
EEG = pop_chanedit(EEG, 'lookup', locpath);
EEG = eeg_checkset( EEG );
% Get event types
for ai=2:length(EEG.event); clear temp; temp=EEG.event(ai).type;
if isempty(strmatch('boundary',temp)); TYPES(ai)=str2num(temp(2:end)) ; clear temp; end
end
UNIQUE_TYPES=unique(TYPES);
for ai=1:length(UNIQUE_TYPES); UNIQUE_TYPES_COUNT(ai)=sum(TYPES==UNIQUE_TYPES(ai)); end
clc; TRIGGERS=[UNIQUE_TYPES;UNIQUE_TYPES_COUNT] % Trigger type, Frequency
% Epoch
All_STIM={'S201','S200','S202'}; % Std, Target, Novel
EEG = pop_epoch( EEG, All_STIM, [-2 2], 'newname', 'Epochs', 'epochinfo', 'yes');
EEG = eeg_checkset( EEG );
% Remove VEOG and EKG
EEG.EKG=squeeze(EEG.data(65,:,:));
EEG.VEOG=squeeze(EEG.data(64,:,:));
EEG.data=EEG.data(1:63,:,:);
EEG.nbchan=63;
EEG.chanlocs(65)=[]; EEG.chanlocs(64)=[];
% Fix BV-specific issue - - - only needed for APPLE
for ai=1:size(EEG.urevent,2), EEG.urevent(ai).bvtime=EEG.urevent(ai).bvmknum; end
for ai=1:size(EEG.event,2), EEG.event(ai).bvtime=EEG.event(ai).bvmknum; end
for ai=1:size(EEG.epoch,2), EEG.epoch(ai).eventbvtime=EEG.epoch(ai).eventbvmknum; end
% Add CPz
EEG = pop_chanedit(EEG,'append',63,'changefield',{64 'labels' 'CPz'});
EEG = pop_chanedit(EEG,'lookup', locpath);
% Re-Ref to Average Ref and recover CPz
EEG = pop_reref(EEG,[],'refloc',struct('labels',{'CPz'},'type',{''},'theta',{180},'radius',{0.12662},'X',{-32.9279},'Y',{-4.0325e-15},'Z',{78.363},...
'sph_theta',{-180},'sph_phi',{67.208},'sph_radius',{85},'urchan',{64},'ref',{''}),'keepref','on');
% Remove everything else NOW that CPz has been reconstructed from the total
EEG.MASTOIDS = squeeze(mean(EEG.data([10,21],:,:),1));
EEG.data = EEG.data([1:4,6:9,11:20,22:26,28:64],:,:);
EEG.nbchan=60;
EEG.chanlocs(27)=[]; EEG.chanlocs(21)=[]; EEG.chanlocs(10)=[]; EEG.chanlocs(5)=[]; % Have to be in this order!
% Should probably re-ref to average again now that the contaminated channels are gone
EEG = pop_reref(EEG,[]);
% Remove mean
EEG = pop_rmbase(EEG,[],[]);
% ----------------------
% Setup APPLE to interp chans, reject epochs, & ID bad ICs. Output will be Avg ref'd and ICA'd.
eeg_chans=1:60;
Do_ICA=1;
ref_chan=36; % Re-Ref to FCz [WEIRD STEP, BUT THIS IS FOR FASTER, which is a part of APPLE]
EEG = pop_reref(EEG,ref_chan,'keepref','on');
% Run APPLE (will re-ref data to avg ref)
[EEG,EEG.bad_chans,EEG.bad_epochs,EEG.bad_ICAs]=APPLE_3AOB(EEG,eeg_chans,ref_chan,Do_ICA,subno,EEG.VEOG,sess,BV_Chanlocs_60);
% Save
save([num2str(subno),'_',num2str(sess),'_3AOB.mat'],'EEG');
% ----------------------
%% Remove the (presumptive) bad ICAs:
bad_ICAs_To_Remove=EEG.bad_ICAs{2};
if bad_ICAs_To_Remove==0, bad_ICAs_To_Remove=1; end
EEG = pop_subcomp( EEG, bad_ICAs_To_Remove, 0);
% Get the good info out of the epochs
for ai=1:size(EEG.epoch,2)
% Initialize
EEG.epoch(ai).CUE=NaN;
for bi=1:size(EEG.epoch(ai).eventlatency,2)
% Get STIMTYPE
if EEG.epoch(ai).eventlatency{bi}==0 && isempty(strmatch(EEG.epoch(ai).eventtype{bi},'N999')); % If this bi is the event
% Get StimType
FullName=EEG.epoch(ai).eventtype{bi};
EEG.epoch(ai).CUE=str2num(FullName(2:end)) ;
clear FullName
VECTOR(ai,1)=EEG.epoch(ai).CUE;
end
end
end
% Let's just do this for display
dims=size(EEG.data);
EEG.data=eegfilt(EEG.data,500,[],20);
EEG.data=reshape(EEG.data,dims(1),dims(2),dims(3));
% Set Params
tx=-2000:2:1998;
b1=find(tx==-200); b2=find(tx==0);
t1=find(tx==-500); t2=find(tx==1000);
toporange1=find(tx==250); toporange2=find(tx==600); toporangetot=250:2:600;
tx2disp=-500:2:1000;
MAPLIMS=[-8 8];
% Basecor your ERPs here so they are pretty.
BASE=squeeze( mean(EEG.data(:,b1:b2,:),2) );
for ai=1:dims(1)
EEG.data(ai,:,:)=squeeze(EEG.data(ai,:,:))-repmat( BASE(ai,:),dims(2),1 );
end
% Get max of P2 across all condis
site=11; % Pz
ERP4topo=mean(EEG.data(site,toporange1:toporange2,VECTOR(:,1)==200),3);
topomax_P3b=toporangetot(find(ERP4topo==max(ERP4topo)));
topotoplot_P3b=find(tx==topomax_P3b);
site=36; % FCz
ERP4topo=mean(EEG.data(site,toporange1:toporange2,VECTOR(:,1)==202),3);
topomax_P3a=toporangetot(find(ERP4topo==max(ERP4topo)));
topotoplot_P3a=find(tx==topomax_P3a);
% --------------
figure;
site=11; % Pz
subplot(3,4,1:4); hold on
plot(tx2disp,mean(EEG.data(site,t1:t2,VECTOR(:,1)==201),3),'k');
plot(tx2disp,mean(EEG.data(site,t1:t2,VECTOR(:,1)==200),3),'r');
plot(tx2disp,mean(EEG.data(site,t1:t2,VECTOR(:,1)==202),3),'b');
plot([topomax_P3b topomax_P3b],[-2 2],'m','linewidth',2); % indicate the max with a magenta line
title(['Pz Subno: ',num2str(subno),' Sess:',num2str(sess)]);
legend({'Std','Target','Novel'},'Location','NorthWest');
% --------------
site=36; % FCz
subplot(3,4,5:8); hold on
plot(tx2disp,mean(EEG.data(site,t1:t2,VECTOR(:,1)==201),3),'k');
plot(tx2disp,mean(EEG.data(site,t1:t2,VECTOR(:,1)==200),3),'r');
plot(tx2disp,mean(EEG.data(site,t1:t2,VECTOR(:,1)==202),3),'b');
plot([topomax_P3a topomax_P3a],[-2 2],'m','linewidth',2); % indicate the max with a magenta line
title(['FCz Subno: ',num2str(subno),' Sess:',num2str(sess)]);
% --------------
subplot(3,4,9); hold on
topoplot( mean(EEG.data(:,topotoplot_P3b,VECTOR(:,1)==201),3) , BV_Chanlocs_60,'maplimits',MAPLIMS); title('Std @ P3b')
subplot(3,4,10); hold on
topoplot( mean(EEG.data(:,topotoplot_P3b,VECTOR(:,1)==200),3) , BV_Chanlocs_60,'maplimits',MAPLIMS); title('Targ')
subplot(3,4,11); hold on
topoplot( mean(EEG.data(:,topotoplot_P3a,VECTOR(:,1)==202),3) , BV_Chanlocs_60,'maplimits',MAPLIMS); title('Novel')
saveas(gcf, [num2str(subno),'_',num2str(sess),'_3AOB_ERPs.png'],'png');
close all;
clear EEG VECTOR BASE PROBE TRIGGERS TYPES UNIQUE* did* topo* ERP* URSI dims eeg_chans;
end
end
end
end
%%
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