|
|
|
|
|
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)]) |
|
|
|
|
|
|
|
|
|
|
|
%% |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|