|
|
| clear; clc; close all;
|
| datalocation='D:\Project_EEG_CC\CC_Results_step1\'; % Data are here
|
| cd(datalocation);
|
|
|
| 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');
|
| [num_rest,txt_rest,raw_rest]=xlsread('D:\Project_EEG_CC\PD_Rest_Data\REST_ICAs.xlsx'); %% needed file
|
|
|
| PDsx=[801:811,813:823,825:829]; % 824 S2 CC is bad (mange in Step 3) %%%%do 824 saperatly at the end
|
| CTLsx=[8010,8070,8060,890:914]; % 911 S1 CC is bad (mange in Step 3)
|
|
|
| %% ########################
|
| for subj= [CTLsx(end:-1:1),PDsx(end:-1:1)] % [PDsx,CTLsx] %
|
|
|
| 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;
|
|
|
|
|
| % ---------------- REST!!! ---------------- ---------------- ----------------
|
| disp([num2str(subj),'_',num2str(session),'_PDDys_REST.mat'])
|
|
|
| if subj==803 && session==1;
|
| load([num2str(subj),'_',num2str(2),'_PDDys_REST.mat'],'EEG'); % 803 S1 is bad, use their S2 instead.
|
| else
|
| load([num2str(subj),'_',num2str(session),'_PDDys_REST.mat'],'EEG'); %%% needed those files
|
| end
|
|
|
| % Get Subj Info
|
| temp1=cell2mat(raw_rest(find(num_rest(:,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;
|
|
|
| REST=EEG; clear EEG;
|
| %%% save data for channels Cue locked
|
| CHANS=(1:60);
|
| for chani = 1:60
|
| mData_REST{:,chani} = nanmean(squeeze(REST.data(CHANS(chani),:,:)),2);
|
| end
|
| % ---------------- ---------------- ---------------- ---------------- ----------------
|
|
|
| % &&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&& % &&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&
|
| 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;
|
| % &&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&& % &&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&
|
|
|
|
|
| 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;
|
|
|
| % Get the good info out of the epochs
|
| for aai=1:size(EEG.epoch,2)
|
| EEG.epoch(aai).TYPE=NaN; EEG.epoch(aai).RESP=NaN; EEG.epoch(aai).RT=NaN;
|
| RESP_VECTOR(aai,1:2)=NaN;
|
| for bbi=1:size(EEG.epoch(aai).eventlatency,2)
|
| % Get STIMTYPE
|
| if EEG.epoch(aai).eventlatency{bbi}==0 % If this bi is the event
|
| % Get StimType
|
| FullName=EEG.epoch(aai).eventtype{bbi};
|
| % IF TRN CUE
|
| if any(str2num(FullName(2:end))==[CONGRU,INCONGRU])
|
| EEG.epoch(aai).TYPE=str2num(FullName(2:end)) ;
|
| if any(str2num(FullName(2:end))==CONGRU)
|
| VECTOR(aai)=5;
|
| elseif any(str2num(FullName(2:end))==INCONGRU)
|
| VECTOR(aai)=6;
|
| end
|
| % If anything is next
|
| if size(EEG.epoch(aai).eventlatency,2)>=bbi
|
| % If RESP
|
| tempName=EEG.epoch(aai).eventtype{bbi+1};
|
| if any(str2num(tempName(2:end))==[CORRECT,ERROR])
|
| EEG.epoch(aai).RESP=str2num(tempName(2:end)) ;
|
| EEG.epoch(aai).RT=EEG.epoch(aai).eventlatency{bbi+1};
|
| RESP_VECTOR(aai,1)=str2num(tempName(2:end));
|
| RESP_VECTOR(aai,2)=EEG.epoch(aai).eventlatency{bbi+1};
|
| end
|
| end
|
| else
|
| EEG.epoch(aai).TYPE=str2num(FullName(2:end)) ;
|
| VECTOR(aai)=str2num(FullName(2:end));
|
| end
|
| clear FullName tempName
|
| end
|
| end
|
| end
|
|
|
| % 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])
|
| Cue_to_Resp=RESP_VECTOR(ai,2) ./ (1000/EEG.srate);
|
| 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))];
|
| if any(RESP_VECTOR(ai,1)==CORRECT)
|
| VECTOR_resp(respct,1)=1; VECTOR_resp(respct,2)=Cue_to_Resp;
|
| elseif any(RESP_VECTOR(ai,1)==ERROR)
|
| VECTOR_resp(respct,1)=2; VECTOR_resp(respct,2)=Cue_to_Resp;
|
| end
|
| respct=respct+1;
|
| clear Cue_to_Resp;
|
| end
|
| end
|
|
|
| % Set Times
|
| tx=-1500:2:4998;
|
| b1=find(tx==-1500); b2=find(tx==0); %%% I changed it
|
| t1=find(tx==-1500); t2=find(tx==1000);
|
| tx2disp=-500:2:1000;
|
|
|
| % ------------------------ Get the goods
|
| X_CUE{1}=5; % CONGRU
|
| X_CUE{2}=6; % INCONGRU
|
| X_RESP{1}=1; % CORRECT RESP
|
| X_RESP{2}=2; % ERROR RESP
|
|
|
|
|
| %%% save data for channels Cue locked
|
| CHANS=(1:60); % ALL Chans
|
| for chani = 1:60
|
| mData_Cue{:,chani} = nanmean(squeeze(EEG.data(CHANS(chani),:,:)),2);
|
| end
|
|
|
| save(['D:\Project_EEG_CC\TopoFigure\Data_Topo_new\',num2str(subj),'_Session_',num2str(session),'_PDDys_CC_ALL_TOPO.mat'],...
|
| 'VECTOR','VECTOR_resp','RESP_VECTOR','mData_Cue', 'mData_REST');
|
|
|
| end
|
| end
|
| end
|
| end
|
|
|
|
|
| |
