%% Step2: PostProcessing data for Post-Correct and Post-Error trials: ERP analysis; Time-Frequncy analaysis, ITPC analysis clear; clc datalocation='D:\Project_EEG_CC\CC_Results_step1\'; % Data are here savedir = 'D:\Project_EEG_CC\CC_PD_Figures_Manuscript\CC_Manuscript\Manuscript_Scripts_PREDICT\Data\PostError\'; % save data here cd(savedir); load('D:\Project_EEG_CC\mFiles\ONOFF.mat','ONOFF') load('D:\Project_EEG_CC\mFiles\BV_Chanlocs_60.mat'); [num_cc,txt_cc,raw_cc]=xlsread('D:\Project_EEG_CC\CC_ICAs.xlsx'); PDsx=[801:811,813:823,825:829]; % 824 S2 CC is bad (mange in Step 3) CTLsx=[8010,8070,8060,890:914]; % 911 S1 CC is bad (mange in Step 3) %%%%%%%%% or run 824 afterwards since session 2 is bad OR use sessiosn 1 %%%%%%%%% for both OFF and ON %% for subj= 801%[CTLsx(end:-1:1),PDsx(end:-1:1)] for session=1:2 if (subj>850 && session==1) || subj<850 % If not ctl, do session 2 if 1 % exist([num2str(subj),'_Session_',num2str(session),'_PDDys_CC.mat'])~=2; % ---------------- GET PD and Control DATA ---------------- ---------------- ---------------- % &&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&& % &&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&& disp([num2str(subj),'_Session_',num2str(session),'_PDDys_CC.mat']) load([num2str(subj),'_Session_',num2str(session),'_PDDys_CC.mat'],'EEG','bad_chans','bad_epochs','bad_ICAs'); % Get Subj Info temp1=cell2mat(raw_cc(find(num_cc(:,1)==subj),session+1)); if isnumeric(temp1) bad_ICAs_To_Remove=temp1; elseif strmatch('NaN',temp1) bad_ICAs_To_Remove=NaN; else bad_ICAs_To_Remove=str2num(temp1); end clear temp1; % Remove the (presumptive) bad ICAs: if ~(isnan(bad_ICAs_To_Remove)) EEG = pop_subcomp( EEG, bad_ICAs_To_Remove, 0); end clear bad_ICAs_To_Remove; %% %%%%%%%%%% &&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&& GET Epochs % &&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&& CONGRU=[111,112,113,114,211,212,213,214]; INCONGRU=[121,122,123,124,221,222,223,224]; CORRECT=[101,102]; ERROR=[103,104]; REW=8; PUN=9; % It will added 3 column at the EEG.epochs with TYPE, RESP and RT...this code will find STIM CONG and INCONG and Response and latency of Response % &&&&&&&&& Get the good info out of the epochs &&&&&&&&&& for aai=1:size(EEG.epoch,2) % look for total size of epoch..how many epochs are there EEG.epoch(aai).TYPE=NaN; EEG.epoch(aai).RESP=NaN; EEG.epoch(aai).RT=NaN; % add TYPE; RESP and RT column at the end of epoch RESP_VECTOR(aai,1:2)=NaN; % create variable "RESP_VECTOR" for all epochs for Correct and Error resp for bbi=1:size(EEG.epoch(aai).eventlatency,2) % look the size of each epoch via eventlatency.. %%% Get STIMTYPE if EEG.epoch(aai).eventlatency{bbi}==0 % If this bi is the event % if the eventlatency shows "0"in each epoch..means data were epchoed ("0") at stim...then %%% Get StimType FullName=EEG.epoch(aai).eventtype{bbi}; % look the name for the eventtype for each event/stimuli for each epoch %%% IF TRN CUE (Training Cue) %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%looking for the TRAINING CUE if any(str2num(FullName(2:end))==[CONGRU,INCONGRU]) % if any Fullname of stim match to Cong and Incong stim..then EEG.epoch(aai).TYPE=str2num(FullName(2:end)) ; % mention the full name in TYPE coulmn...ELSE..send to them in VECTOR variable if any(str2num(FullName(2:end))==CONGRU) % if any Fullname stim match to Cong then add 5 in Vector VECTOR(aai)=55; % CONGRUENT elseif any(str2num(FullName(2:end))==INCONGRU) % if any Fullname stim match to Incong then add 6 in Vector VECTOR(aai)=66; % INCONGRUENT end % %%% If anything is next if size(EEG.epoch(aai).eventlatency,2)>= bbi % if the size of eventtype is greater or equal to size of latency for each epoch then %%% If RESP &&& Simplely look for RESP after the STIM that's why eventtype+1..if there is resp after stim tempName=EEG.epoch(aai).eventtype{bbi+1}; % tempname would be +1 to evenettype if any(str2num(tempName(2:end))==[CORRECT,ERROR]) % if tempname is equal to Corrcet and Error EEG.epoch(aai).RESP=str2num(tempName(2:end)) ; % Add name for Correct and Error response EEG.epoch(aai).RT=EEG.epoch(aai).eventlatency{bbi+1}; % Add latency for Corrcet and Error Response RESP_VECTOR(aai,1)=str2num(tempName(2:end)); % Add Correct and Error stim RESP_VECTOR(aai,2)=EEG.epoch(aai).eventlatency{bbi+1};% Add latency for Correct and Erroe Response end end else EEG.epoch(aai).TYPE=str2num(FullName(2:end)) ; % if the epoch type is not Cong and Incong stim then VECTOR(aai)=str2num(FullName(2:end)); % create VECTOR and add the info here..if Cong (5) and Incong (6) else other stim type end clear FullName tempName end end end % &&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&& % %% get the VECTOR here with all stimuli for aai=1:size(EEG.epoch,2) EEG.epoch(aai).resp_num = 0; EEG.epoch(aai).VECTOR = VECTOR(aai); if any(EEG.epoch(aai).RESP==CORRECT) EEG.epoch(aai).resp_num = 1; elseif any(EEG.epoch(aai).RESP==ERROR) EEG.epoch(aai).resp_num = 2; end EEG.epoch(aai).VECTOR2= EEG.epoch(aai).VECTOR; end % %%% find poet-error Cue: Cong and Incong for aai=1:length(EEG.epoch) %%% get post correct Cue all if any(EEG.epoch(aai).resp_num == 1) if EEG.epoch(aai).VECTOR2 == 55 % cong EEG.epoch(aai).VECTOR2 = 5; %%%% All correct Cong Cue = 5 elseif EEG.epoch(aai).VECTOR2 == 66 % Incong EEG.epoch(aai).VECTOR2 = 5; %%%% All correct Incong Cue = 5 end end %%%%%%%% to get post -error Cue all if any(EEG.epoch(aai).resp_num == 2) && any(EEG.epoch(aai+1).resp_num == 1) if EEG.epoch(aai+1).VECTOR2 == 55 % cong EEG.epoch(aai+1).VECTOR2 = 6; %%%% post-error Cong Cue = 6 elseif EEG.epoch(aai+1).VECTOR2 == 66 % Incong EEG.epoch(aai+1).VECTOR2 = 6; %%%% post-error Incong Cue = 6 end end end VECTOR_PE= [EEG.epoch.VECTOR2]; % %%%%%%%%%&&&&&&&&&&& Aggregate accelerometer data &&&&&&&&&&&&&& EEG.X=EEG.X-repmat(mean(EEG.X),3250,1); EEG.Y=EEG.Y-repmat(mean(EEG.Y),3250,1); EEG.Z=EEG.Z-repmat(mean(EEG.Z),3250,1); % Add to EEG.data as 61st channel - but not the rejected trials if subj==824 && session==2, clear bad_epochs; bad_epochs{1}=zeros(1,size(EEG.data,3)); end % B/c 824 S2 is bad - hack this EEG.data(61,:,:)=(EEG.X(:,bad_epochs{1}~=1).^2)+(EEG.Y(:,bad_epochs{1}~=1).^2)+(EEG.Z(:,bad_epochs{1}~=1).^2); dims=size(EEG.data); % ******************************************************************************************************************************************************* % Lock to Response, Stim, and Cue respct=1; for ai=1:size(EEG.epoch,2) if any(RESP_VECTOR(ai,1)==[CORRECT,ERROR]) % look for the Correct and Error resp in Response vector Cue_to_Resp=RESP_VECTOR(ai,2) ./ (1000/EEG.srate); % convert latency into data points cueTOresp (eg. RT=770 ms; 1000 ms=500samples; 2ms=1sample; 770ms = 385 samples ) if isnan(Cue_to_Resp), Cue_to_Resp=1; end EEG.resp(:,:,respct)=[squeeze(EEG.data(:,Cue_to_Resp:end,ai)),zeros(dims(1),(Cue_to_Resp-1))]; % get the All Cahnnles (61) X fulllength epoch (3250 smaples) X epoch numbers Resp-locked % EEG.resp is locked to Resp: see the epoch size(EEG.data(all chan :,Cue_to_Resp in time to: end of the epoch, look in all epochs in "for" loop ) % size of EEG.resp is different so add Zeros at the end to make size equal to EEG.data. if any(RESP_VECTOR(ai,1)==CORRECT) % if RESP_VECTOR has Correct Resp then..creat VECTOR_resp VECTOR_resp(respct,1)=1; VECTOR_resp(respct,2)=Cue_to_Resp; % VECTOR_resp: 1st column = 1 ; 2nd column = Cue to Correct Resp in samples elseif any(RESP_VECTOR(ai,1)==ERROR) % if RESP_VECTOR has Error Resp then VECTOR_resp(respct,1)=2; VECTOR_resp(respct,2)=Cue_to_Resp; % VECTOR_resp: 1st column = 2 ; 2nd column = Cue to Error Resp in samples end respct=respct+1; clear Cue_to_Resp; end end clear RESP_VECTOR; % %%%%%%%% Look for the Post-error response: only Correct Response RespID = zeros(length(VECTOR_resp),3); RespID(:,1) = VECTOR_resp(:,1); RespID(:,2) = VECTOR_resp(:,2).*2; % convert in RT %%%%% find post-error Cue: Cong and Incong for rpi=1:length(RespID(:,1))-1 if any(RespID(rpi,1)==1) && any(RespID(rpi+1,1)==1) RespID(rpi+1,3)= 1; %%%% post-correct response elseif any(RespID(rpi,1)==2) && any(RespID(rpi+1,1)==1) RespID(rpi+1,3)= 2; %%%% post-error response end end VECTOR_respPE = [RespID(:,3) RespID(:,2)]; %^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ % Set Times tx=-1500:2:4998; b1=find(tx==-500); b2=find(tx==-200); %% original t1=find(tx==-500); t2=find(tx==1000); tx2disp=-500:2:1000; % ------------------------ Get the goods X_CUE{1}=5; % post- Correct CUE X_CUE{2}=6; % post-error CUE X_RESP{1}=1; % POST-CORRECT RESP X_RESP{2}=2; % POST-ERROR RESP (correct) %% %% ################################################################################################################################### % ---------- % ---------- % ---------- % ---------- TF stuff % ---------- % ---------- % ---------- % Setup Wavelet Params num_freqs=50; frex=logspace(.01,1.7,num_freqs); s=logspace(log10(3),log10(10),num_freqs)./(2*pi*frex); t=-2:1/EEG.srate:2; % Definte Convolution Parameters n_wavelet = length(t); half_of_wavelet_size = (n_wavelet-1)/2; clear dims % -------- cue/fb dims{1} = size(EEG.data); n_data{1} = dims{1}(2)*dims{1}(3); n_convolution{1} = n_wavelet+n_data{1}-1; n_conv_pow2{1} = pow2(nextpow2(n_convolution{1})); % -------- resp dims{2} = size(EEG.resp); n_data{2} = dims{2}(2)*dims{2}(3); n_convolution{2} = n_wavelet+n_data{2}-1; n_conv_pow2{2} = pow2(nextpow2(n_convolution{2})); CHANS= (1:60); % ALL Channels for chani=1:60 % get FFT of data EEG_fft{1} = fft(reshape(EEG.data(CHANS(chani),:,:),1,n_data{1}),n_conv_pow2{1}); EEG_fft{2} = fft(reshape(EEG.resp(CHANS(chani),:,:),1,n_data{2}),n_conv_pow2{2}); for fi=1:num_freqs wavelet{1} = fft( exp(2*1i*pi*frex(fi).*t) .* exp(-t.^2./(2*(s(fi)^2))) , n_conv_pow2{1} ); wavelet{2} = fft( exp(2*1i*pi*frex(fi).*t) .* exp(-t.^2./(2*(s(fi)^2))) , n_conv_pow2{2} ); % convolution for convo=1:2 EEG_conv = ifft(wavelet{convo}.*EEG_fft{convo}); EEG_conv = EEG_conv(1:n_convolution{convo}); EEG_conv = EEG_conv(half_of_wavelet_size+1:end-half_of_wavelet_size); EEG_multi_conv{convo} = reshape(EEG_conv,dims{convo}(2),dims{convo}(3)); clear EEG_conv; temp_POWER{convo} = abs(EEG_multi_conv{convo}(t1:t2,:)).^2; %%% -500 to 1000 ms end % Baseline from pre-cue {1} BASE = mean(mean(abs( EEG_multi_conv{1}(b1:b2,VECTOR_PE<7)).^2)); % Average FIRST for condi=1:2 temp_POWER_avg(:,condi,1) = mean(temp_POWER{1}(:,VECTOR_PE==X_CUE{condi}),2); temp_POWER_avg(:,condi,2) = mean(temp_POWER{2}(:,VECTOR_respPE==X_RESP{condi}),2); % ------------------- ITPC(chani,fi,:,condi,1) = abs(mean(exp(1i*( angle(EEG_multi_conv{1}(t1:t2,VECTOR_PE==X_CUE{condi})) )),2)); ITPC(chani,fi,:,condi,2) = abs(mean(exp(1i*( angle(EEG_multi_conv{2}(t1:t2,VECTOR_respPE==X_RESP{condi})) )),2)); end % dB correct power by base for condi=1:2 for event=1:2 POWER(chani,fi,:,condi,event) = 10*( log10(temp_POWER_avg(:,condi,event)) - log10(repmat(BASE,size(temp_POWER_avg(:,condi,event),1),1)) ); end end % Actually, save these for later Baselines(chani,fi,1)=BASE; clear temp* EEG_multi_conv wavelet BASE PE; end clear *_fft; end %% ############################################################################################################## % ---------- % ---------- % ---------- % ---------- ERP stuff % ---------- % ---------- % ---------- % Filter for ERPs dims=size(EEG.data); EEG.data=eegfilt(EEG.data,500,[],20); EEG.data=reshape(EEG.data,dims(1),dims(2),dims(3)); dims=size(EEG.resp); EEG.resp=eegfilt(EEG.resp,500,[],20); EEG.resp=reshape(EEG.resp,dims(1),dims(2),dims(3)); % Basecor your ERPs here so they are pretty ------------> BASE1=squeeze( mean(EEG.data(:,b1:b2,:),2) ); BASE2=squeeze( mean(EEG.resp(:,b1:b2,:),2) ); for chani=1:dims(1) %% for all channels EEG.data(chani,:,:)=squeeze(EEG.data(chani,:,:))-repmat( BASE1(chani,:),dims(2),1 ); EEG.resp(chani,:,:)=squeeze(EEG.resp(chani,:,:))-repmat( BASE2(chani,:),dims(2),1 ); end for condi=1:2 %% for both conditions or conflicts % Mean for ERPs ERPs(1:60,:,condi,1)=mean(EEG.data(1:60,t1:t2, VECTOR_PE==X_CUE{condi} ),3); %%% PreCue-locked ERPs ERPs(1:60,:,condi,2)=mean(EEG.resp(1:60,t1:t2, VECTOR_respPE==X_RESP{condi} ),3); %%% Response-locked ERPs end %%%% save data save([savedir,num2str(subj),'_Session_',num2str(session),'_PDDys_CC_ALL_GOODS.mat'],... 'ERPs','VECTOR','VECTOR_PE','VECTOR_resp','VECTOR_respPE','POWER','ITPC','Baselines'); clearvars -except datalocation ONOFF PDsx CTLsx session subj num_cc txt_cc raw_cc savedir end end end end