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%% 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
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