%% Calculate Data clear all; clc datapath=('Y:\EEG_Data\PDDys\BEH\'); cd(datapath); SUBJS=[801:811,813:829]; % Only include here if they have BOTH sessions done! for subno=SUBJS for session=1:2 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 load('Y:\EEG_Data\PDDys\ONOFF.mat','ONOFF') row=0; for subno=SUBJS for session=1:2; row=row+1; if subno~=ONOFF(row,1) || session~=ONOFF(row,2), BOOM; end % Kills it if mismatch in ON/OFF Matrix! load([num2str(subno),'_sess',num2str(session),'_VVbeh.mat'],'TRAIN','TEST'); MEGA(row).ID=subno; MEGA(row).session=session; MEGA(row).ONOFF=ONOFF(row,3); 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.mat','MEGA'); clear ONOFF RT row session subno %% clear all; clc datapath=('Y:\EEG_Data\PDDys\BEH\'); cd(datapath); SUBJS=[801:811,813:829]; % Only include here if they have BOTH sessions done! load('Y:\EEG_Data\PDDys\PD_Moderators.mat','Mods','Mods_Hdr') load('VV_Behavior.mat','MEGA'); row=0; for subno=SUBJS row=row+1; for mi=1:size(MEGA,2) if MEGA(mi).ID==subno && MEGA(mi).ONOFF==1 ON.ID(row,:)=MEGA(mi).ID; ON.session(row,:)=MEGA(mi).session; ON.TRN_ACC(row,:)=MEGA(mi).TRN_ACC; ON.TRN_RT(row,:)=MEGA(mi).TRN_RT; ON.WinStay(row,:)=MEGA(mi).WinStay; ON.LoseSwitch(row,:)=MEGA(mi).LoseSwitch; ON.WinSpeed(row,:)=MEGA(mi).WinSpeed; ON.TST_ACC(row,:)=MEGA(mi).TST_ACC; ON.TST_BIAS(row,:)=MEGA(mi).TST_BIAS; ON.TST_WITHINSET(row,:)=MEGA(mi).TST_WITHINSET; ON.TST_EASY(row,:)=MEGA(mi).TST_EASY; ON.TST_MEDIUM(row,:)=MEGA(mi).TST_MEDIUM; ON.TST_HARD(row,:)=MEGA(mi).TST_HARD; ON.TST_RT(row,:)=MEGA(mi).TST_RT; ON.Blocks(row,:)=MEGA(mi).TRN_blocks; elseif MEGA(mi).ID==subno && MEGA(mi).ONOFF==0 OFF.ID(row,:)=MEGA(mi).ID; OFF.session(row,:)=MEGA(mi).session; OFF.TRN_ACC(row,:)=MEGA(mi).TRN_ACC; OFF.TRN_RT(row,:)=MEGA(mi).TRN_RT; OFF.WinStay(row,:)=MEGA(mi).WinStay; OFF.LoseSwitch(row,:)=MEGA(mi).LoseSwitch; OFF.WinSpeed(row,:)=MEGA(mi).WinSpeed; OFF.TST_ACC(row,:)=MEGA(mi).TST_ACC; OFF.TST_BIAS(row,:)=MEGA(mi).TST_BIAS; OFF.TST_WITHINSET(row,:)=MEGA(mi).TST_WITHINSET; OFF.TST_EASY(row,:)=MEGA(mi).TST_EASY; OFF.TST_MEDIUM(row,:)=MEGA(mi).TST_MEDIUM; OFF.TST_HARD(row,:)=MEGA(mi).TST_HARD; OFF.TST_RT(row,:)=MEGA(mi).TST_RT; OFF.Blocks(row,:)=MEGA(mi).TRN_blocks; end end end save('BEH_VV_PD','ON','OFF'); BigN=length(SUBJS); jitter=rand(1,BigN)./2.5; jitter=jitter-mean(jitter); % % SOMESX=double(repmat((Mods(:,9)>nanmedian(Mods(:,9))),1,4)); % % SOMESX(SOMESX==0)=NaN; % % ON.TST_BIAS=ON.TST_BIAS.*SOMESX; % % OFF.TST_BIAS=OFF.TST_BIAS.*SOMESX; %% figure; subplot(1,3,1); hold on bar(1:4,mean(ON.WinStay),.25,'w'); bar(1.25:4.25,mean(OFF.WinStay),.25,'r'); errorbar(1:4,mean(ON.WinStay),std(ON.WinStay)./sqrt(BigN),'k.'); errorbar(1.25:4.25,mean(OFF.WinStay),std(OFF.WinStay)./sqrt(BigN),'k.'); set(gca,'xlim',[0 5],'xtick',[1:1:4],'xticklabel',{'AB','CD','WY','XZ'},'ylim',[.5 1]); title('TRN WinStay'); subplot(1,3,2); hold on bar(1:4,nanmean(ON.LoseSwitch),.25,'w'); bar(1.25:4.25,nanmean(OFF.LoseSwitch),.25,'r'); errorbar(1:4,nanmean(ON.LoseSwitch),nanstd(ON.LoseSwitch)./sqrt(BigN),'k.'); errorbar(1.25:4.25,nanmean(OFF.LoseSwitch),nanstd(OFF.LoseSwitch)./sqrt(BigN),'k.'); set(gca,'xlim',[0 5],'xtick',[1:1:4],'xticklabel',{'AB','CD','WY','XZ'}); title('TRN LoseSwitch'); subplot(1,3,3); hold on bar(1:4,nanmean(ON.WinSpeed),.25,'w'); bar(1.25:4.25,nanmean(OFF.WinSpeed),.25,'r'); errorbar(1:4,nanmean(ON.WinSpeed),nanstd(ON.WinSpeed)./sqrt(BigN),'k.'); errorbar(1.25:4.25,nanmean(OFF.WinSpeed),nanstd(OFF.WinSpeed)./sqrt(BigN),'k.'); set(gca,'xlim',[0 5],'xtick',[1:1:4],'xticklabel',{'AB','CD','WY','XZ'}); title('TRN WinSpeed'); %% figure; subplot(2,5,1); hold on bar(1,mean(ON.TRN_ACC),'w'); bar(2,mean(OFF.TRN_ACC),'r'); errorbar(1,mean(ON.TRN_ACC),std(ON.TRN_ACC)./sqrt(BigN),'k.'); errorbar(2,mean(OFF.TRN_ACC),std(OFF.TRN_ACC)./sqrt(BigN),'k.'); % plot(1,ON.TRN_ACC,'b.'); plot(2,OFF.TRN_ACC,'b.'); % plot([1 2],[ON.TRN_ACC OFF.TRN_ACC],'b-'); set(gca,'xlim',[0 3],'xtick',[1:1:2],'xticklabel',{'ON','OFF'},'ylim',[.5 1]); title('TRN Acc'); subplot(2,5,2:3); hold on bar(1:4,mean(ON.TST_ACC),.25,'w'); bar(1.25:1:4.25,mean(OFF.TST_ACC),.25,'r'); errorbar(1:4,mean(ON.TST_ACC),std(ON.TST_ACC)./sqrt(BigN),'k.'); errorbar(1.25:1:4.25,mean(OFF.TST_ACC),std(OFF.TST_ACC)./sqrt(BigN),'k.'); % plot(1:4,ON.TST_ACC,'b.'); plot(1.25:1:4.25,OFF.TST_ACC,'b.'); % plot([1 1.25],[ON.TST_ACC(:,1) OFF.TST_ACC(:,1)],'b-'); % plot([2 2.25],[ON.TST_ACC(:,2) OFF.TST_ACC(:,2)],'b-'); % plot([3 3.25],[ON.TST_ACC(:,3) OFF.TST_ACC(:,3)],'b-'); % plot([4 4.25],[ON.TST_ACC(:,4) OFF.TST_ACC(:,4)],'b-'); set(gca,'xlim',[0 5],'xtick',[1:1:4],'xticklabel',{'AB','WX','CD','YZ'}); title('TST Acc'); subplot(2,5,4:5); hold on bar(1:4,nanmean(ON.TST_BIAS),.25,'w'); bar(1.25:1:4.25,nanmean(OFF.TST_BIAS),.25,'r'); errorbar(1:4,nanmean(ON.TST_BIAS),nanstd(ON.TST_BIAS)./sqrt(BigN),'k.'); errorbar(1.25:1:4.25,nanmean(OFF.TST_BIAS),nanstd(OFF.TST_BIAS)./sqrt(BigN),'k.'); % plot(1:4,ON.TST_BIAS,'b.'); plot(1.25:1:4.25,OFF.TST_BIAS,'b.'); % plot([1 1.25],[ON.TST_BIAS(:,1) OFF.TST_BIAS(:,1)],'b-'); % plot([2 2.25],[ON.TST_BIAS(:,2) OFF.TST_BIAS(:,2)],'b-'); % plot([3 3.25],[ON.TST_BIAS(:,3) OFF.TST_BIAS(:,3)],'b-'); % plot([4 4.25],[ON.TST_BIAS(:,4) OFF.TST_BIAS(:,4)],'b-'); set(gca,'xlim',[0 5],'xtick',[1:1:4],'xticklabel',{'AW','CY','DZ','BX'}); title('TST BIAS'); subplot(2,5,6); hold on bar(1,mean(ON.TRN_ACC-OFF.TRN_ACC),'b'); errorbar(1,mean(ON.TRN_ACC-OFF.TRN_ACC),std(ON.TRN_ACC-OFF.TRN_ACC)./sqrt(BigN),'k.'); set(gca,'xlim',[0 2],'xtick',[1:1:1]); title('TRN Acc DIFF'); subplot(2,5,7:8); hold on bar(1:4,mean(ON.TST_ACC-OFF.TST_ACC),.25,'b'); errorbar(1:4,mean(ON.TST_ACC-OFF.TST_ACC),std(ON.TST_ACC-OFF.TST_ACC)./sqrt(BigN),'k.'); set(gca,'xlim',[0 5],'xtick',[1:1:4],'xticklabel',{'AB','WX','CD','YZ'}); title('TST Acc'); subplot(2,5,9:10); hold on bar(1:4,nanmean( ON.TST_BIAS-OFF.TST_BIAS ),.25,'w'); errorbar(1:4,nanmean(ON.TST_BIAS-OFF.TST_BIAS ),std(ON.TST_BIAS-OFF.TST_BIAS )./sqrt(BigN),'k.'); % for plotdiffi=1:4 % plot(plotdiffi+jitter',(ON.TST_BIAS(:,plotdiffi)-OFF.TST_BIAS(:,plotdiffi)),'mo'); % end set(gca,'xlim',[0 5],'xtick',[1:1:4],'xticklabel',{'AW','CY','DZ','BX'}); title('TST BIAS'); %% MODS=9; BigDiff=ON.TST_BIAS-OFF.TST_BIAS; for polyi=1:BigN POLY{1}(polyi)=corr(ON.TST_BIAS(polyi,:)',(1:4)'); POLY{2}(polyi)=corr(OFF.TST_BIAS(polyi,:)',(1:4)'); POLY{3}(polyi)=corr(BigDiff(polyi,:)',(1:4)'); end dispidx=3; figure; subplot(1,2,1); hold on bar(mean(POLY{dispidx}),'w'); plot(.86:.01:1.13,POLY{dispidx},'bd'); errorbar(mean(POLY{dispidx}),std(POLY{dispidx})./sqrt(BigN),'k.') set(gca,'xlim',[0 2],'xtick',[1:1:2]) ylabel('Slope in Accuracy Difference'); [H,P,CI,STATS]=ttest(POLY{dispidx}) title(['BIAS t=',num2str(STATS.tstat),' p=',num2str(P)]); subplot(1,2,2); hold on scatter( Mods(:,MODS) , POLY{dispidx}' ,'k'); lsline [rho,p]=corr( Mods(:,MODS) , POLY{dispidx}' ,'type','Spearman','rows','complete' ); text(.4,.1,['r=',num2str(rho),' p=',num2str(p)],'sc') title(['POLY & ',Mods_Hdr{MODS}]) FORSPSS=[BigDiff,POLY{3}']; for slopei=1:4 if slopei==1, X=ON.TST_BIAS; elseif slopei==2, X=OFF.TST_BIAS; elseif slopei==3, X=CTL.TST_BIAS; elseif slopei==4, X=ON.TST_BIAS-OFF.TST_BIAS; end for polyi=1:length(X) SLOPES{slopei}(polyi)=corr(X(polyi,:)',(1:4)'); end end figure; subplot(2,2,1); hold on bar(1,mean(SLOPES{1}),'w'); bar(2,mean(SLOPES{2}),'r'); bar(3,mean(SLOPES{3}),'g'); errorbar(1,mean(SLOPES{1}),std(SLOPES{1})./sqrt(BigN),'k.'); errorbar(2,mean(SLOPES{2}),std(SLOPES{2})./sqrt(BigN),'k.'); errorbar(3,mean(SLOPES{3}),std(SLOPES{3})./sqrt(BigN_ctl),'k.'); ylabel('Slope in Accuracy Difference'); subplot(2,2,2); hold on scatter( Mods(:,MODS) , SLOPES{4} ,'b'); lsline [rho,p]=corr( Mods(:,MODS) , SLOPES{4}' ,'type','Spearman','rows','complete' ); text(.4,.1,['r=',num2str(rho),' p=',num2str(p)],'sc') title(['ON-OFF & ',Mods_Hdr{MODS}]) subplot(2,2,3); hold on scatter( Mods(:,MODS) , SLOPES{1} ,'k'); lsline [rho,p]=corr( Mods(:,MODS) , SLOPES{1}' ,'type','Spearman','rows','complete' ); text(.4,.1,['r=',num2str(rho),' p=',num2str(p)],'sc') title(['ON & ',Mods_Hdr{MODS}]) subplot(2,2,4); hold on scatter( Mods(:,MODS) , SLOPES{2} ,'r'); lsline [rho,p]=corr( Mods(:,MODS) , SLOPES{2}' ,'type','Spearman','rows','complete' ); text(.4,.1,['r=',num2str(rho),' p=',num2str(p)],'sc') title(['OFF & ',Mods_Hdr{MODS}]) %% % LED & win-speed diff % LED & BX bias diff MOD_IDX=2; A1=sum(OFF.TST_BIAS(:,1),2) A2=sum(ON.TST_BIAS(:,1),2) A3=A1-A2; figure; subplot(1,3,1); hold on scatter( Mods(:,MOD_IDX) , A1 ,'k'); lsline [rho,p]=corr( Mods(:,MOD_IDX) , A1 ,'type','Spearman','rows','complete' ); text(.4,.1,['r=',num2str(rho),' p=',num2str(p)],'sc') title(['OFF & ',Mods_Hdr{MOD_IDX}]) subplot(1,3,2); hold on scatter( Mods(:,MOD_IDX) ,A2 ,'k' ); lsline [rho,p]=corr( Mods(:,MOD_IDX) , A2 ,'type','Spearman','rows','complete' ); text(.4,.1,['r=',num2str(rho),' p=',num2str(p)],'sc') title(['ON & ',Mods_Hdr{MOD_IDX}]) subplot(1,3,3); hold on scatter( Mods(:,MOD_IDX) , A3 ,'k' ); lsline [rho,p]=corr( Mods(:,MOD_IDX) , A3 ,'type','Spearman','rows','complete' ); text(.4,.1,['r=',num2str(rho),' p=',num2str(p)],'sc') title(['OFF-ON & ',Mods_Hdr{MOD_IDX}]) %% load('VV_Behavior_CTL.mat','CTL'); BigN=length(SUBJS); jitter=rand(1,BigN)./2.5; jitter=jitter-mean(jitter); BigN_ctl=size(CTL.ID,1); noise_ctl=rand(1,BigN_ctl)./100; figure; subplot(2,5,1); hold on bar(1,mean(ON.TRN_ACC),'w'); bar(2,mean(OFF.TRN_ACC),'r'); bar(3,mean(CTL.TRN_ACC),'g'); errorbar(1,mean(ON.TRN_ACC),std(ON.TRN_ACC)./sqrt(BigN),'k.'); errorbar(2,mean(OFF.TRN_ACC),std(OFF.TRN_ACC)./sqrt(BigN),'k.'); errorbar(3,mean(CTL.TRN_ACC),std(CTL.TRN_ACC)./sqrt(BigN_ctl),'k.'); set(gca,'xlim',[0 4],'xtick',[1:1:3],'xticklabel',{'ON','OFF','CTL'},'ylim',[.5 1]); title('TRN Acc'); subplot(2,5,2:3); hold on bar(1-.25:4-.25,mean(ON.TST_ACC),.25,'w'); bar(1:1:4,mean(OFF.TST_ACC),.25,'r'); bar(1.25:1:4.25,mean(CTL.TST_ACC),.25,'g'); errorbar(1-.25:4-.25,mean(ON.TST_ACC),std(ON.TST_ACC)./sqrt(BigN),'k.'); errorbar(1:1:4,mean(OFF.TST_ACC),std(OFF.TST_ACC)./sqrt(BigN),'k.'); errorbar(1.25:1:4.25,mean(CTL.TST_ACC),std(CTL.TST_ACC)./sqrt(BigN_ctl),'k.'); set(gca,'xlim',[0 5],'xtick',[1:1:4],'xticklabel',{'AB','WX','CD','YZ'}); title('TST Acc'); subplot(2,5,4:5); hold on bar(1-.25:4-.25,mean(ON.TST_BIAS),.25,'w'); bar(1:1:4,mean(OFF.TST_BIAS),.25,'r'); bar(1.25:1:4.25,mean(CTL.TST_BIAS),.25,'g'); errorbar(1-.25:4-.25,mean(ON.TST_BIAS),std(ON.TST_BIAS)./sqrt(BigN),'k.'); errorbar(1:1:4,mean(OFF.TST_BIAS),std(OFF.TST_BIAS)./sqrt(BigN),'k.'); errorbar(1.25:1:4.25,mean(CTL.TST_BIAS),std(CTL.TST_BIAS)./sqrt(BigN_ctl),'k.'); set(gca,'xlim',[0 5],'xtick',[1:1:4],'xticklabel',{'AW','CY','DZ','BX'}); title('TST BIAS'); [H,P,CI,STATS]=ttest2(ON.TST_BIAS(:,1),CTL.TST_BIAS(:,1)) [H,P,CI,STATS]=ttest2(OFF.TST_BIAS(:,1),CTL.TST_BIAS(:,1)) subplot(2,5,6); hold on bar(1,mean(ON.TRN_ACC-OFF.TRN_ACC),'b'); errorbar(1,mean(ON.TRN_ACC-OFF.TRN_ACC),std(ON.TRN_ACC-OFF.TRN_ACC)./sqrt(BigN),'k.'); set(gca,'xlim',[0 2],'xtick',[1:1:1]); title('TRN Acc DIFF'); subplot(2,5,7:8); hold on bar(1:4,mean(ON.TST_ACC-OFF.TST_ACC),.25,'b'); errorbar(1:4,mean(ON.TST_ACC-OFF.TST_ACC),std(ON.TST_ACC-OFF.TST_ACC)./sqrt(BigN),'k.'); set(gca,'xlim',[0 5],'xtick',[1:1:4],'xticklabel',{'AB','WX','CD','YZ'}); title('TST Acc DIFF'); subplot(2,5,9:10); hold on bar(1:4,mean(ON.TST_BIAS-OFF.TST_BIAS),.25,'w'); errorbar(1:4,mean(ON.TST_BIAS-OFF.TST_BIAS),std(ON.TST_BIAS-OFF.TST_BIAS)./sqrt(BigN),'k.'); % % for plotdiffi=1:4 % % plot(plotdiffi+jitter',(ON.TST_BIAS(:,plotdiffi)-OFF.TST_BIAS(:,plotdiffi)),'mo'); % % end set(gca,'xlim',[0 5],'xtick',[1:1:4],'xticklabel',{'AW','CY','DZ','BX'}); title('TST BIAS DIFF'); %% %% figure; subplot(3,2,1:2) hold on bar(1-.25:1:8-.25,mean(VV.CTL.TST_WITHINSET),.25,'g'); bar(1:1:8,mean(VV.ON.TST_WITHINSET),.25,'w'); bar(1+.25:1:8+.25,mean(VV.OFF.TST_WITHINSET),.25,'r'); errorbar(1-.25:1:8-.25,mean(VV.CTL.TST_WITHINSET),std(VV.CTL.TST_WITHINSET)./sqrt(BigN_ctl),'k.'); errorbar(1:1:8,mean(VV.ON.TST_WITHINSET),std(VV.ON.TST_WITHINSET)./sqrt(BigN),'k.'); errorbar(1+.25:1:8+.25,mean(VV.OFF.TST_WITHINSET),std(VV.OFF.TST_WITHINSET)./sqrt(BigN),'k.'); plot([0 9],[.5 .5],'b:') set(gca,'xlim',[0 9],'xtick',[1:1:8],'xticklabel',{'AC','AD','CB','BD','WY','WZ','YX','XZ'},'ytick',[0:.25:1]); title('TST w/in set Acc'); subplot(3,2,3:4) hold on bar(1-.25:1:6-.25,nanmean(VV.CTL.TST_EASY),.25,'g'); bar(1:1:6,nanmean(VV.ON.TST_EASY),.25,'w'); bar(1+.25:1:6+.25,nanmean(VV.OFF.TST_EASY),.25,'r'); errorbar(1-.25:1:6-.25,nanmean(VV.CTL.TST_EASY),nanstd(VV.CTL.TST_EASY)./sqrt(BigN_ctl),'k.'); errorbar(1:1:6,nanmean(VV.ON.TST_EASY),nanstd(VV.ON.TST_EASY)./sqrt(BigN),'k.'); errorbar(1+.25:1:6+.25,nanmean(VV.OFF.TST_EASY),nanstd(VV.OFF.TST_EASY)./sqrt(BigN),'k.'); plot([0 7],[.5 .5],'b:') set(gca,'xlim',[0 7],'xtick',[1:1:6],'xticklabel',{'AX','AY','AZ','WB','WC','WD'},'ytick',[0:.25:1]); title('TST EASY Acc'); subplot(3,2,5) hold on bar(1-.25:1:4-.25,nanmean(VV.CTL.TST_MEDIUM),.25,'g'); bar(1:1:4,nanmean(VV.ON.TST_MEDIUM),.25,'w'); bar(1+.25:1:4+.25,nanmean(VV.OFF.TST_MEDIUM),.25,'r'); errorbar(1-.25:1:4-.25,nanmean(VV.CTL.TST_MEDIUM),nanstd(VV.CTL.TST_MEDIUM)./sqrt(BigN_ctl),'k.'); errorbar(1:1:4,nanmean(VV.ON.TST_MEDIUM),nanstd(VV.ON.TST_MEDIUM)./sqrt(BigN),'k.'); errorbar(1+.25:1:4+.25,nanmean(VV.OFF.TST_MEDIUM),nanstd(VV.OFF.TST_MEDIUM)./sqrt(BigN),'k.'); plot([0 5],[.5 .5],'b:') set(gca,'xlim',[0 5],'xtick',[1:1:4],'xticklabel',{'CX','CZ','YB','YD'},'ytick',[0:.25:1]); title('TST MEDIUM Acc'); subplot(3,2,6) hold on bar(1-.25:1:2-.25,nanmean(VV.CTL.TST_HARD),.25,'g'); bar(1:1:2,nanmean(VV.ON.TST_HARD),.25,'w'); bar(1+.25:1:2+.25,nanmean(VV.OFF.TST_HARD),.25,'r'); errorbar(1-.25:1:2-.25,nanmean(VV.CTL.TST_HARD),nanstd(VV.CTL.TST_HARD)./sqrt(BigN_ctl),'k.'); errorbar(1:1:2,nanmean(VV.ON.TST_HARD),nanstd(VV.ON.TST_HARD)./sqrt(BigN),'k.'); errorbar(1+.25:1:2+.25,nanmean(VV.OFF.TST_HARD),nanstd(VV.OFF.TST_HARD)./sqrt(BigN),'k.'); plot([0 3],[.5 .5],'b:') set(gca,'xlim',[0 3],'xtick',[1:1:2],'xticklabel',{'ZB','DX'},'ytick',[0:.25:1]); title('TST HARD Acc'); % ^^^^^^ figure; subplot(3,2,1:2) hold on bar(1-.3:1:8-.3,nanmean(VV.ON.TST_WITHINSET(Esx,:)),.15,'w'); bar(1-.1:1:8-.1,nanmean(VV.OFF.TST_WITHINSET(Esx,:)),.15,'r'); bar(1+.1:1:8+.1,nanmean(VV.ON.TST_WITHINSET(Lsx,:)),.15,'w'); bar(1+.3:1:8+.3,nanmean(VV.OFF.TST_WITHINSET(Lsx,:)),.15,'r'); errorbar(1-.3:1:8-.3,mean(VV.ON.TST_WITHINSET(Esx,:)),std(VV.ON.TST_WITHINSET(Esx,:))./sqrt(EarlyN),'k.'); errorbar(1-.1:1:8-.1,mean(VV.OFF.TST_WITHINSET(Esx,:)),std(VV.OFF.TST_WITHINSET(Esx,:))./sqrt(EarlyN),'k.'); errorbar(1+.1:1:8+.1,mean(VV.ON.TST_WITHINSET(Lsx,:)),std(VV.ON.TST_WITHINSET(Lsx,:))./sqrt(LateN),'k.'); errorbar(1+.3:1:8+.3,mean(VV.OFF.TST_WITHINSET(Lsx,:)),std(VV.OFF.TST_WITHINSET(Lsx,:))./sqrt(LateN),'k.'); plot([0 9],[.5 .5],'b:') set(gca,'xlim',[0 9],'xtick',[1:1:8],'xticklabel',{'AC','AD','CB','BD','WY','WZ','YX','XZ'},'ytick',[0:.25:1]); title('TST w/in set Acc'); subplot(3,2,3:4) hold on bar(1-.3:1:6-.3,nanmean(VV.ON.TST_EASY(Esx,:)),.15,'w'); bar(1-.1:1:6-.1,nanmean(VV.OFF.TST_EASY(Esx,:)),.15,'r'); bar(1+.1:1:6+.1,nanmean(VV.ON.TST_EASY(Lsx,:)),.15,'w'); bar(1+.3:1:6+.3,nanmean(VV.OFF.TST_EASY(Lsx,:)),.15,'r'); errorbar(1-.3:1:6-.3,mean(VV.ON.TST_EASY(Esx,:)),std(VV.ON.TST_EASY(Esx,:))./sqrt(EarlyN),'k.'); errorbar(1-.1:1:6-.1,mean(VV.OFF.TST_EASY(Esx,:)),std(VV.OFF.TST_EASY(Esx,:))./sqrt(EarlyN),'k.'); errorbar(1+.1:1:6+.1,mean(VV.ON.TST_EASY(Lsx,:)),std(VV.ON.TST_EASY(Lsx,:))./sqrt(LateN),'k.'); errorbar(1+.3:1:6+.3,mean(VV.OFF.TST_EASY(Lsx,:)),std(VV.OFF.TST_EASY(Lsx,:))./sqrt(LateN),'k.'); plot([0 7],[.5 .5],'b:') set(gca,'xlim',[0 7],'xtick',[1:1:6],'xticklabel',{'AX','AY','AZ','WB','WC','WD'},'ytick',[0:.25:1]); title('TST EASY Acc'); subplot(3,2,5) hold on bar(1-.3:1:4-.3,nanmean(VV.ON.TST_MEDIUM(Esx,:)),.15,'w'); bar(1-.1:1:4-.1,nanmean(VV.OFF.TST_MEDIUM(Esx,:)),.15,'r'); bar(1+.1:1:4+.1,nanmean(VV.ON.TST_MEDIUM(Lsx,:)),.15,'w'); bar(1+.3:1:4+.3,nanmean(VV.OFF.TST_MEDIUM(Lsx,:)),.15,'r'); errorbar(1-.3:1:4-.3,mean(VV.ON.TST_MEDIUM(Esx,:)),std(VV.ON.TST_MEDIUM(Esx,:))./sqrt(EarlyN),'k.'); errorbar(1-.1:1:4-.1,mean(VV.OFF.TST_MEDIUM(Esx,:)),std(VV.OFF.TST_MEDIUM(Esx,:))./sqrt(EarlyN),'k.'); errorbar(1+.1:1:4+.1,mean(VV.ON.TST_MEDIUM(Lsx,:)),std(VV.ON.TST_MEDIUM(Lsx,:))./sqrt(LateN),'k.'); errorbar(1+.3:1:4+.3,mean(VV.OFF.TST_MEDIUM(Lsx,:)),std(VV.OFF.TST_MEDIUM(Lsx,:))./sqrt(LateN),'k.'); plot([0 5],[.5 .5],'b:') set(gca,'xlim',[0 5],'xtick',[1:1:4],'xticklabel',{'CX','CZ','YB','YD'},'ytick',[0:.25:1]); title('TST MEDIUM Acc'); subplot(3,2,6) hold on bar(1-.3:1:2-.3,nanmean(VV.ON.TST_HARD(Esx,:)),.15,'w'); bar(1-.1:1:2-.1,nanmean(VV.OFF.TST_HARD(Esx,:)),.15,'r'); bar(1+.1:1:2+.1,nanmean(VV.ON.TST_HARD(Lsx,:)),.15,'w'); bar(1+.3:1:2+.3,nanmean(VV.OFF.TST_HARD(Lsx,:)),.15,'r'); errorbar(1-.3:1:2-.3,mean(VV.ON.TST_HARD(Esx,:)),std(VV.ON.TST_HARD(Esx,:))./sqrt(EarlyN),'k.'); errorbar(1-.1:1:2-.1,mean(VV.OFF.TST_HARD(Esx,:)),std(VV.OFF.TST_HARD(Esx,:))./sqrt(EarlyN),'k.'); errorbar(1+.1:1:2+.1,mean(VV.ON.TST_HARD(Lsx,:)),std(VV.ON.TST_HARD(Lsx,:))./sqrt(LateN),'k.'); errorbar(1+.3:1:2+.3,mean(VV.OFF.TST_HARD(Lsx,:)),std(VV.OFF.TST_HARD(Lsx,:))./sqrt(LateN),'k.'); plot([0 3],[.5 .5],'b:') set(gca,'xlim',[0 3],'xtick',[1:1:2],'xticklabel',{'ZB','DX'},'ytick',[0:.25:1]); title('TST HARD Acc'); %% % % % 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)]) %%