%% Calculate Data clear all; clc datapath=('Y:\EEG_Data\PDDys\BEH\'); cd(datapath); SUBJS=[8010,8070,8060,890:914]; for subno=SUBJS for session=1 disp(['VV Beh --- Subno: ',num2str(subno),' Session: ',num2str(session)]); disp(' '); % TRAIN fileID=dir([num2str(subno),'_S',num2str(session),'*']); load(fileID.name); clear fileID % ----- Columns are: ----- % 1 = block % 2 = trial % 3 = (cTrialID) % 4 = Forced choice % 6 = S1 % 8 = S2 % 10 = S1 is left % 11 = Stim Selected % 13 = Reward (1 or 0) % 14 = RT % ----------- Re-make With More Simpleness ABchoose=[1,2]; CDchoose=[3,4]; WXmatch=[5,6]; YZmatch=[7,8]; for ai=1:length(task_struct.trainTrials) if any(task_struct.trainTrials(ai,6)==ABchoose) CONDI=1; elseif any(task_struct.trainTrials(ai,6)==CDchoose) CONDI=2; elseif any(task_struct.trainTrials(ai,6)==WXmatch) CONDI=3; elseif any(task_struct.trainTrials(ai,6)==YZmatch) CONDI=4; end TRAIN(ai,1)=CONDI; clear CONDI; % Condi: 1=ABchoose 2=CDchoose 3=ABmatch 4=CDmatch TRAIN(ai,2)=mod(task_struct.trainTrials(ai,11),2); % Optimal choice (odd num are optimal: 1,3,5,7) TRAIN(ai,3)=task_struct.trainTrials(ai,14); % RT TRAIN(ai,4)=task_struct.trainTrials(ai,13); % was rewarded or not end % ----------- Re-make With More Simpleness for ai=1:length(task_struct.testTrials) ThisSet=task_struct.testTrials(ai,[6,8]); ThisSet=str2num(cat(2,num2str(ThisSet(1)),num2str(ThisSet(2)))); ThisChoice=task_struct.testTrials(ai,11); if any(ThisSet==[12,21]), CONDI='AB'; elseif any(ThisSet==[13,31]), CONDI='AC'; elseif any(ThisSet==[14,41]), CONDI='AD'; elseif any(ThisSet==[15,51]), CONDI='AW'; elseif any(ThisSet==[16,61]), CONDI='AX'; elseif any(ThisSet==[17,71]), CONDI='AY'; elseif any(ThisSet==[18,81]), CONDI='AZ'; elseif any(ThisSet==[23,32]), CONDI='BC'; elseif any(ThisSet==[24,42]), CONDI='BD'; elseif any(ThisSet==[25,52]), CONDI='BW'; elseif any(ThisSet==[26,62]), CONDI='BX'; elseif any(ThisSet==[27,72]), CONDI='BY'; elseif any(ThisSet==[28,82]), CONDI='BZ'; elseif any(ThisSet==[34,43]), CONDI='CD'; elseif any(ThisSet==[35,53]), CONDI='CW'; elseif any(ThisSet==[36,63]), CONDI='CX'; elseif any(ThisSet==[37,73]), CONDI='CY'; elseif any(ThisSet==[38,83]), CONDI='CZ'; elseif any(ThisSet==[45,54]), CONDI='DW'; elseif any(ThisSet==[46,64]), CONDI='DX'; elseif any(ThisSet==[47,74]), CONDI='DY'; elseif any(ThisSet==[48,84]), CONDI='DZ'; elseif any(ThisSet==[56,65]), CONDI='WX'; elseif any(ThisSet==[57,75]), CONDI='WY'; elseif any(ThisSet==[58,85]), CONDI='WZ'; elseif any(ThisSet==[67,76]), CONDI='XY'; elseif any(ThisSet==[68,86]), CONDI='XZ'; elseif any(ThisSet==[78,87]), CONDI='YZ'; end TEST(ai).condi=CONDI; % Condi TEST(ai).choice=ThisChoice; % This Choice TEST(ai).RT=task_struct.testTrials(ai,14); % RT clear ThisSet ThisChoice CONDI; end save([num2str(subno),'_sess',num2str(session),'_VVbeh.mat'],'TRAIN','TEST'); clear task_struct disp_struct AB* CD* TRAIN TEST end end row=0; for subno=SUBJS for session=1; row=row+1; load([num2str(subno),'_sess',num2str(session),'_VVbeh.mat'],'TRAIN','TEST'); MEGA(row).ID=subno; MEGA(row).session=session; MEGA(row).TRN_blocks=size(TRAIN,1)./40; MEGA(row).TRN_ACC=mean(TRAIN(:,2)); MEGA(row).TRN_RT=mean(TRAIN(:,3)); for bi=1:4 % Condi: 1=ABchoose 2=CDchoose 3=ABmatch 4=CDmatch MINISET=TRAIN(TRAIN(:,1)==bi,:); MINISET(:,[5,6])=[MINISET(2:end,[2,3]);[NaN,NaN]]; MINISET(:,6)=MINISET(:,6)-MINISET(:,3); % RT diff % -------- WINS=MINISET(MINISET(:,4)==1,[2,5,6]); LOSSES=MINISET(MINISET(:,4)==0,[2,5,6]); % -------- WinStay(bi)=mean(WINS(:,1)==WINS(:,2)); LoseSwitch(bi)=mean(LOSSES(:,1)~=LOSSES(:,2)); WinSpeed(bi)=mean(WINS(WINS(:,1)==WINS(:,2),3)); % -------- clear MINISET WINS LOSSES end MEGA(row).WinStay=WinStay; MEGA(row).LoseSwitch=LoseSwitch; MEGA(row).WinSpeed=WinSpeed; % ******************************************************** for ci=1:128 RT(ci,1)=TEST(ci).RT; % ^^^^ General Accuracy A,B,C,D == W,X,Y,Z - 4 of each set ACC=NaN; PARSE=NaN; if strmatch(TEST(ci).condi,'AB'); if TEST(ci).choice==1, ACC=1; elseif TEST(ci).choice==2, ACC=0; end; PARSE=1; elseif strmatch(TEST(ci).condi,'WX'); if TEST(ci).choice==5, ACC=1; elseif TEST(ci).choice==6, ACC=0; end; PARSE=2; elseif strmatch(TEST(ci).condi,'CD'); if TEST(ci).choice==3, ACC=1; elseif TEST(ci).choice==4, ACC=0; end; PARSE=3; elseif strmatch(TEST(ci).condi,'YZ'); if TEST(ci).choice==7, ACC=1; elseif TEST(ci).choice==8, ACC=0; end; PARSE=4; end % ^^^^ free vs. forced A,B,C,D == W,X,Y,Z - 8 of each set BIAS=NaN; if strmatch(TEST(ci).condi,'AW'); if TEST(ci).choice==1, BIAS=1; elseif TEST(ci).choice==5, BIAS=0; end; PARSE=5; elseif strmatch(TEST(ci).condi,'CY'); if TEST(ci).choice==3, BIAS=1; elseif TEST(ci).choice==7, BIAS=0; end; PARSE=6; elseif strmatch(TEST(ci).condi,'DZ'); if TEST(ci).choice==4, BIAS=1; elseif TEST(ci).choice==8, BIAS=0; end; PARSE=7; elseif strmatch(TEST(ci).condi,'BX'); if TEST(ci).choice==2, BIAS=1; elseif TEST(ci).choice==6, BIAS=0; end; PARSE=8; end % ^^^^ WITHINSET=NaN; if strmatch(TEST(ci).condi,'AC'); if TEST(ci).choice==1, WITHINSET=1; elseif TEST(ci).choice==3, WITHINSET=0; end; PARSE=9; elseif strmatch(TEST(ci).condi,'AD'); if TEST(ci).choice==1, WITHINSET=1; elseif TEST(ci).choice==4, WITHINSET=0; end; PARSE=10; elseif strmatch(TEST(ci).condi,'BC'); if TEST(ci).choice==3, WITHINSET=1; elseif TEST(ci).choice==2, WITHINSET=0; end; PARSE=11; elseif strmatch(TEST(ci).condi,'BD'); if TEST(ci).choice==4, WITHINSET=1; elseif TEST(ci).choice==2, WITHINSET=0; end; PARSE=12; elseif strmatch(TEST(ci).condi,'WY'); if TEST(ci).choice==5, WITHINSET=1; elseif TEST(ci).choice==7, WITHINSET=0; end; PARSE=13; elseif strmatch(TEST(ci).condi,'WZ'); if TEST(ci).choice==5, WITHINSET=1; elseif TEST(ci).choice==8, WITHINSET=0; end; PARSE=14; elseif strmatch(TEST(ci).condi,'XY'); if TEST(ci).choice==7, WITHINSET=1; elseif TEST(ci).choice==6, WITHINSET=0; end; PARSE=15; elseif strmatch(TEST(ci).condi,'XZ'); if TEST(ci).choice==8, WITHINSET=1; elseif TEST(ci).choice==6, WITHINSET=0; end; PARSE=16; end % ^^^^ EASY=NaN; if strmatch(TEST(ci).condi,'AX'); if TEST(ci).choice==1, EASY=1; elseif TEST(ci).choice==5, EASY=0; end; PARSE=17; elseif strmatch(TEST(ci).condi,'AY'); if TEST(ci).choice==1, EASY=1; elseif TEST(ci).choice==7, EASY=0; end; PARSE=18; elseif strmatch(TEST(ci).condi,'AZ'); if TEST(ci).choice==1, EASY=1; elseif TEST(ci).choice==8, EASY=0; end; PARSE=19; elseif strmatch(TEST(ci).condi,'BW'); if TEST(ci).choice==5, EASY=1; elseif TEST(ci).choice==2, EASY=0; end; PARSE=20; elseif strmatch(TEST(ci).condi,'CW'); if TEST(ci).choice==5, EASY=1; elseif TEST(ci).choice==3, EASY=0; end; PARSE=21; elseif strmatch(TEST(ci).condi,'DW'); if TEST(ci).choice==5, EASY=1; elseif TEST(ci).choice==4, EASY=0; end; PARSE=22; end % ^^^^ MEDIUM=NaN; if strmatch(TEST(ci).condi,'CX'); if TEST(ci).choice==3, MEDIUM=1; elseif TEST(ci).choice==6, MEDIUM=0; end; PARSE=23; elseif strmatch(TEST(ci).condi,'CZ'); if TEST(ci).choice==3, MEDIUM=1; elseif TEST(ci).choice==8, MEDIUM=0; end; PARSE=24; elseif strmatch(TEST(ci).condi,'BY'); if TEST(ci).choice==7, MEDIUM=1; elseif TEST(ci).choice==2, MEDIUM=0; end; PARSE=25; elseif strmatch(TEST(ci).condi,'DY'); if TEST(ci).choice==7, MEDIUM=1; elseif TEST(ci).choice==4, MEDIUM=0; end; PARSE=26; end % ^^^^ HARD=NaN; if strmatch(TEST(ci).condi,'BZ'); if TEST(ci).choice==8, HARD=1; elseif TEST(ci).choice==2, HARD=0; end; PARSE=27; elseif strmatch(TEST(ci).condi,'DX'); if TEST(ci).choice==4, HARD=1; elseif TEST(ci).choice==6, HARD=0; end; PARSE=28; end % ^^^^ TST_ACC(ci,1)=ACC; TST_BIAS(ci,1)=BIAS; TST_WITHINSET(ci,1)=WITHINSET; TST_EASY(ci,1)=EASY; TST_MEDIUM(ci,1)=MEDIUM; TST_HARD(ci,1)=HARD; TST_PARSE(ci,1)=PARSE; clear ACC BIAS WITHINSET EASY MEDIUM HARD PARSE; end for di=1:4 ACCURACIES(di)=nanmean(TST_ACC(TST_PARSE==di)); end for di=5:8 BIASES(di-4)=nanmean(TST_BIAS(TST_PARSE==di)); end for di=9:16 WITHINSETS(di-8)=nanmean(TST_WITHINSET(TST_PARSE==di)); end for di=17:22 EASYS(di-16)=nanmean(TST_EASY(TST_PARSE==di)); end for di=23:26 MEDIUMS(di-22)=nanmean(TST_MEDIUM(TST_PARSE==di)); end for di=27:28 HARDS(di-26)=nanmean(TST_HARD(TST_PARSE==di)); end MEGA(row).TST_ACC=ACCURACIES; MEGA(row).TST_BIAS=BIASES; MEGA(row).TST_WITHINSET=WITHINSETS; MEGA(row).TST_EASY=EASYS; MEGA(row).TST_MEDIUM=MEDIUMS; MEGA(row).TST_HARD=HARDS; MEGA(row).TST_RT=mean(RT); clearvars -except MEGA subjcount subno session RT row ONOFF SUBJS; end end save('VV_Behavior_CTL.mat','MEGA'); clear RT row session subno %% row=0; for subno=SUBJS row=row+1; CTL.ID(row,:)=MEGA(row).ID; CTL.session(row,:)=MEGA(row).session; CTL.TRN_ACC(row,:)=MEGA(row).TRN_ACC; CTL.TRN_RT(row,:)=MEGA(row).TRN_RT; CTL.WinStay(row,:)=MEGA(row).WinStay; CTL.LoseSwitch(row,:)=MEGA(row).LoseSwitch; CTL.WinSpeed(row,:)=MEGA(row).WinSpeed; CTL.TST_ACC(row,:)=MEGA(row).TST_ACC; CTL.TST_BIAS(row,:)=MEGA(row).TST_BIAS; CTL.TST_WITHINSET(row,:)=MEGA(row).TST_WITHINSET; CTL.TST_EASY(row,:)=MEGA(row).TST_EASY; CTL.TST_MEDIUM(row,:)=MEGA(row).TST_MEDIUM; CTL.TST_HARD(row,:)=MEGA(row).TST_HARD; CTL.TST_RT(row,:)=MEGA(row).TST_RT; CTL.Blocks(row,:)=MEGA(mi).TRN_blocks; end save('VV_Behavior_CTL.mat','MEGA','CTL'); BigN=length(SUBJS); jitter=rand(1,BigN)./2.5; jitter=jitter-mean(jitter); %% figure; subplot(1,5,1); hold on bar(1,mean(CTL.TRN_ACC),'g'); errorbar(1,mean(CTL.TRN_ACC),std(CTL.TRN_ACC)./sqrt(BigN),'k.'); set(gca,'xlim',[0 2],'xtick',[1:1:1],'xticklabel',{'CTL'},'ylim',[.5 1]); title('TRN Acc'); subplot(1,5,2:3); hold on bar(1:4,mean(CTL.TST_ACC),.4,'g'); errorbar(1:4,mean(CTL.TST_ACC),std(CTL.TST_ACC)./sqrt(BigN),'k.'); plot(1:4,CTL.TST_ACC,'b.'); set(gca,'xlim',[0 5],'xtick',[1:1:4],'xticklabel',{'AB','WX','CD','YZ'}); title('TST Acc'); subplot(1,5,4:5); hold on bar(1:4,mean(CTL.TST_BIAS),.4,'g'); errorbar(1:4,mean(CTL.TST_BIAS),std(CTL.TST_BIAS)./sqrt(BigN),'k.'); plot(1:4,CTL.TST_BIAS,'b.'); set(gca,'xlim',[0 5],'xtick',[1:1:4],'xticklabel',{'AW','CY','DZ','BX'}); title('TST BIAS'); %% % % % clc; % % % disp([num2str(subno),'_sess',num2str(session),'_VVbeh']) % % % disp(' ') % % % disp('Accuracy: >.5 shows that they learned optimal choice') % % % disp([' choose: AB (90/10)',' match: WX (90/10)',' choose: CD (70/30)',' match: YZ (70/30)']) % % % disp(['Test Acc: ',num2str(MEGA(row).TST_ACC)]) % % % disp(' ') % % % disp('BIAS: >.5 is prefer Choose over Match (may only happen for first 2)') % % % disp([' AW (90/90)',' CY (70/70)',' DZ (30/30)',' BX (30/30)']) % % % disp(['Test BIAS: ',num2str(MEGA(row).TST_BIAS)]) %%