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clear all; clc
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addpath('Y:\EEG_Data\Flankers OCDII\');
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datalocation='Y:\EEG_Data\Flankers OCDII\Raw Data\'; % Data are here
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savedir='Y:\EEG_Data\Flankers OCDII\Processed Data\'; % Save processed data here
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appledir='Y:\EEG_Data\Flankers OCDII\Processed Data\APPLE Outputs\';
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erpdir='Y:\EEG_Data\Flankers OCDII\Processed Data\ERPs\';
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locpath=('Y:\Programs\eeglab12_0_2_1b\plugins\dipfit2.2\standard_BESA\standard-10-5-cap385.elp'); % Generic EEGlab locs
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cd(datalocation);
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% Data are 67 chans. 1:64 are EEG, incl. M1/2 and CB1/2. 65=HEOG 66=VEOG 67=EKG
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FILZ=dir('*.cnt');
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for si=[21,32,45] %1:length(FILZ)
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subname=FILZ(si).name;
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subno=str2num(subname(1:3));
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% Load .cnt file and import channel locations
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EEG = pop_loadcnt([datalocation,subname], 'dataformat', 'int32', 'keystroke', 'on');
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% Get Locs
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EEG = pop_chanedit(EEG, 'lookup', locpath);
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EEG = eeg_checkset( EEG );
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NUMSTIM=121:168;
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for ai=1:length(NUMSTIM)
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ALLSTIM{ai}=num2str(NUMSTIM(ai));
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end
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% Epoch
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EEG = pop_epoch( EEG, ALLSTIM, [-2 2], 'newname', 'Epochs', 'epochinfo', 'yes');
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EEG = eeg_checkset( EEG );
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% Remove mean
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EEG = pop_rmbase(EEG,[],[]);
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% Extract peripherals
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EEG.VEOG=squeeze(EEG.data(65,:,:)) ;
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EEG.HEOG=squeeze(EEG.data(66,:,:)) ;
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% EEG.EKG=squeeze(EEG.data(67,:,:)) ;
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EEG.MASTOIDS=squeeze(mean(cat(1,EEG.data(33,:,:),EEG.data(43,:,:)),1));
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% reref!
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EEG = pop_reref(EEG,[find(strcmpi('M1',{EEG.chanlocs.labels})) find(strcmpi('M2',{EEG.chanlocs.labels}))]);
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% Strip to 60: 33=M1, 43=M2, 60=CB1, 64=CB2, 65=HEOG, 66=VEOG
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EEG = pop_select(EEG,'nochannel',[find(strcmpi('CB1',{EEG.chanlocs.labels})) find(strcmpi('CB2',{EEG.chanlocs.labels})) ...
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find(strcmpi('HEOG',{EEG.chanlocs.labels})) find(strcmpi('EKG',{EEG.chanlocs.labels})) find(strcmpi('VEOG',{EEG.chanlocs.labels}))]);
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CONGRU=[121, 124, 125, 128, 131, 134, 135, 138, 141, 144, 145, 148, 151, 154, 155, 158, 161, 164, 165, 168];
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INCONGRU=[122, 123, 126, 127, 132, 133, 136, 137, 142, 143, 146, 147, 152, 153, 156, 157, 162, 163, 166, 167];
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NeedLeft=[121,123,126,128,131,133,136,138,141,143,146,148,151,153,156,158,161,163,166,168];
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NeedRight=[122,124,125,127,132,134,135,137,142,144,145,147,152,154,155,157,162,164,165,167];
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% Get the good info out of the epochs
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for ai=1:size(EEG.epoch,2)
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EEG.epoch(ai).STIM=NaN; EEG.epoch(ai).CONGRU=NaN; EEG.epoch(ai).RightLeft=NaN;
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EEG.epoch(ai).RT=NaN; EEG.epoch(ai).ACC=NaN; EEG.epoch(ai).BlockStart=0;
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EEG.epoch(ai).TRIALNUM=NaN;
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BEH_VECTOR(ai,1:8)=NaN;
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for bi=1:size(EEG.epoch(ai).eventlatency,2)
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% Get STIMTYPE
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if EEG.epoch(ai).eventlatency{bi}==0 % If this bi is the event
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EEG.epoch(ai).TRIALNUM=ai;
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% ID what stimtype it was
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temp=str2num(EEG.epoch(ai).eventtype{bi});
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EEG.epoch(ai).STIM=temp;
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% And if it was congruent (1) or conflict (0)
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if any(temp==CONGRU)
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EEG.epoch(ai).CONGRU=1;
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elseif any(temp==INCONGRU);
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EEG.epoch(ai).CONGRU=0;
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end
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clear temp;
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% --- Now, find out what their next response was
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if bi<size(EEG.epoch(ai).eventlatency,2) && length(EEG.epoch(ai).eventtype{bi+1})==7 % IF something is next && it was a response
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if strmatch(EEG.epoch(ai).eventtype{bi+1}(1:6),'keypad') % another verification
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% ID what stimtype it was [Right=1, Left=2]
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EEG.epoch(ai).RightLeft=str2num(EEG.epoch(ai).eventtype{bi+1}(7));
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% And what the RT was
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EEG.epoch(ai).RT=EEG.epoch(ai).eventlatency{bi+1};
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% And if it was correct
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temp=str2num(EEG.epoch(ai).eventtype{bi+1}(7));
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if any(EEG.epoch(ai).STIM==NeedRight)
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if temp==1, EEG.epoch(ai).ACC=1;
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elseif temp==2, EEG.epoch(ai).ACC=0;
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end
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elseif any(EEG.epoch(ai).STIM==NeedLeft);
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if temp==2, EEG.epoch(ai).ACC=1;
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elseif temp==1, EEG.epoch(ai).ACC=0;
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end
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end
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clear temp
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end
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end
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end
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BEH_VECTOR(ai,1)=EEG.epoch(ai).TRIALNUM;
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BEH_VECTOR(ai,2)=EEG.epoch(ai).STIM;
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BEH_VECTOR(ai,3)=EEG.epoch(ai).CONGRU;
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BEH_VECTOR(ai,4)=EEG.epoch(ai).RightLeft;
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BEH_VECTOR(ai,5)=EEG.epoch(ai).RT;
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BEH_VECTOR(ai,6)=EEG.epoch(ai).ACC;
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end
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% Determine beginning of new blocks
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if ai==1, EEG.epoch(ai).BlockStart=1; toggle=1;
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else
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temp=num2str(EEG.epoch(ai).STIM); temp2=str2num(temp(3));
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if temp2<5
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newtoggle=1;
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elseif temp2>4
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newtoggle=2;
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end
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if newtoggle~=toggle
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EEG.epoch(ai).BlockStart=1;
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toggle=newtoggle;
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end
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clear temp temp2 newtoggle;
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end
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BEH_VECTOR(ai,7)=EEG.epoch(ai).BlockStart;
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% Determine if pre or post error
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if ai>1
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EEG.epoch(ai).PREVTRIAL.TRIALNUM=EEG.epoch(ai-1).TRIALNUM;
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EEG.epoch(ai).PREVTRIAL.STIM=EEG.epoch(ai-1).STIM;
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EEG.epoch(ai).PREVTRIAL.CONGRU=EEG.epoch(ai-1).CONGRU;
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EEG.epoch(ai).PREVTRIAL.RightLeft=EEG.epoch(ai-1).RightLeft;
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EEG.epoch(ai).PREVTRIAL.RT=EEG.epoch(ai-1).RT;
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EEG.epoch(ai).PREVTRIAL.ACC=EEG.epoch(ai-1).ACC;
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EEG.epoch(ai).PREVTRIAL.BlockStart=EEG.epoch(ai-1).BlockStart;
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end
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end
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% ----------------------
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% Setup APPLE to interp chans, reject epochs, & ID bad ICs. Output will be Avg ref'd and ICA'd.
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eeg_chans=1:60;
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Do_ICA=1;
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ref_chan=19; % Re-Ref to FCz [WEIRD STEP, BUT THIS IS FOR FASTER, which is a part of APPLE]
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% % EEG = pop_reref(EEG,ref_chan,'keepref','on');
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% Run APPLE
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[EEG,EEG.bad_chans,EEG.bad_epochs,EEG.bad_ICAs]=APPLE_OCDII(EEG,eeg_chans,ref_chan,Do_ICA,subno,EEG.VEOG,appledir);
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% Save
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save([savedir,num2str(subno),'_FLANKERS.mat'],'EEG');
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save([savedir,num2str(subno),'_BEH_VECTOR.mat'],'BEH_VECTOR');
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% Let's just do this for display
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dims=size(EEG.data);
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EEG.data=eegfilt(EEG.data,500,[],20);
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EEG.data=reshape(EEG.data,dims(1),dims(2),dims(3));
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tx=-2000:2:1998;
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b1=find(tx==-200); b2=find(tx==0);
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t1=find(tx==-500); t2=find(tx==1000);
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N2topo1=find(tx==200); N2topo2=find(tx==350); N2toporangetot=200:2:350;
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P3topo1=find(tx==400); P3topo2=find(tx==600); P3toporangetot=400:2:600;
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tx2disp=-500:2:1000;
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BASE=squeeze( mean(EEG.data(:,b1:b2,:),2) );
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for ai=1:dims(1)
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EEG.data(ai,:,:)=squeeze(EEG.data(ai,:,:))-repmat( BASE(ai,:),dims(2),1 );
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end
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for ai=1:length(EEG.epoch)
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CONDIS(ai)=EEG.epoch(ai).CONGRU;
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end
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figure;
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subplot(2,4,1:3); hold on
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site=19;
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ERP4topo=mean(EEG.data(site,N2topo1:N2topo2,:),3);
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topomax_N2=N2toporangetot(find(ERP4topo==min(ERP4topo)));
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topotoplot_N2=find(tx==topomax_N2);
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plot(tx2disp,mean(EEG.data(site,t1:t2,CONDIS==1),3),'b');
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plot(tx2disp,mean(EEG.data(site,t1:t2,CONDIS==0),3),'r');
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plot([topomax_N2 topomax_N2],[-4 4],'m');
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title(['FCz Subno: ',num2str(subno)]);
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subplot(2,4,4); hold on
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TOPLOT=mean(EEG.data(:,topotoplot_N2,CONDIS==0),3) - mean(EEG.data(:,topotoplot_N2,CONDIS==1),3);
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topoplot( TOPLOT, EEG.chanlocs); cbar
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subplot(2,4,5:7); hold on
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site=46;
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ERP4topo=mean(EEG.data(site,P3topo1:P3topo2,:),3);
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topomax_P3=P3toporangetot(find(ERP4topo==max(ERP4topo)));
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topotoplot_P3=find(tx==topomax_P3);
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plot(tx2disp,mean(EEG.data(site,t1:t2,CONDIS==1),3),'b');
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plot(tx2disp,mean(EEG.data(site,t1:t2,CONDIS==0),3),'r');
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plot([topomax_P3 topomax_P3],[-4 4],'m');
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title(['Pz Subno: ',num2str(subno)]);
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subplot(2,4,8); hold on
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TOPLOT=mean(EEG.data(:,topotoplot_P3,CONDIS==0),3) - mean(EEG.data(:,topotoplot_P3,CONDIS==1),3);
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topoplot( TOPLOT, EEG.chanlocs); cbar
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saveas(gcf, [erpdir,num2str(subno),'_ERPs.png'],'png');
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close all;
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clear BEH_VECTOR EEG ai bi subno toggle CONDIS TOPLOT topomax_P3 topotoplot_P3 topomax_N2 topotoplot_N2 ERP4topo;
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end
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