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@@ -531,366 +531,6 @@ saveas(hfig,[most_recent_folder 'span' num2str(Nspan) 'ms_lag' num2str(Nlag) 'ms
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end
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-% subplot(1,4,2);
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-% spy(vectorisen(~isnan(poolspksqmat_shRalgn(:,cumsum(nccs),:)),1:2));
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-% subplot(1,4,3);
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-% spy(vectorisen(~isnan(pooleposxmat_shLalgn(:,cumsum(nccs),:)),1:2));
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-% subplot(1,4,4);
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-% spy(vectorisen(~isnan(pooleposxmat_shRalgn(:,cumsum(nccs),:)),1:2));
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-% title('Aligned to shifts');
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-
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-
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-% SET ALIGNMENT
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-% figure('units','normalized','position',[0 0 1 1]);
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-% subplot(2,1,1); shtr=1:length(isSR); plot(rerange(ccpex(isSR(shtr),:)',ccpex(:))); hold on
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-% plot(stR(shtr),arrayfun(@(xx) rerange(ccpex(isSR(xx),stR(xx)),ccpex(:)), shtr),'rx');
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-% plot(get(gca,'XLim'),[0 0],'k:'); ylim([-1 1]); title(sprintf('sample cell, shift R detection, n_s_h_R=%d', sum(nuR)));
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-%
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-% subplot(2,1,2); shtr=1:length(isSL); plot(rerange(ccpex(isSL(shtr),:)',ccpex(:))); hold on
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-% plot(stL(shtr),arrayfun(@(xx) rerange(ccpex(isSL(xx),stL(xx)),ccpex(:)), shtr),'rx');
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-% plot(get(gca,'XLim'),[0 0],'k:'); ylim([-1 1]); title(sprintf('sample cell, shift L detection, n_s_h_L=%d', sum(nuL)));
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-%
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-% %
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-% figure('units','normalized','position',[0 0 1 1]);
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-% subplot(2,1,1);
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-% plot(vectorisen(pooleposxmat_shRalgn(:,end,:),1:2)'./max(abs(pooleposxmat_shRalgn(:)))); hold on;
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-% plot(get(gca,'XLim'),[0 0],'k:'); ylim([-1 1]); title(sprintf('sample cell, shift R detection, n_s_h_R=%d', sum(nuR)));
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-%
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-% subplot(2,1,2);
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-% plot(vectorisen(pooleposxmat_shLalgn(:,end,:),1:2)'./max(abs(pooleposxmat_shLalgn(:)))); hold on;
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-% plot(get(gca,'XLim'),[0 0],'k:'); ylim([-1 1]); title(sprintf('sample cell, shift L detection, n_s_h_L=%d', sum(nuL)));
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-
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-
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-% firstL offer1 - thenR delay2
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-% firstR offer1 - thenL delay2
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-% firstR offer1 - thenR delay2
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-
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-%%
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-if 0
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- % re-defined on vtps_ds
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- o1LLinterval=20; %x10ms=200ms
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- d1LRinterval=20; %x10ms=200ms
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- o2LRinterval=20; %x10ms=200ms
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- d2LLinterval=20; %x10ms=200ms
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- chLLinterval=44;
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- Offer1LLtime=sum(rtmes_ds(1:2))-o1LLinterval+(1:o1LLinterval);
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- Delay1LRtime=sum(rtmes_ds(1:3))-d1LRinterval+(1:d1LRinterval);
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- Offer2LRtime=sum(rtmes_ds(1:4))-o2LRinterval+(1:o2LRinterval);
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- Delay2LLtime=sum(rtmes_ds(1:5))-d2LLinterval+(1:d2LLinterval);
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- ChoiceLLtime=sum(rtmes_ds(1:8))-chLLinterval+(1:chLLinterval);
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-
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-
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- pooleposxmat_vds=pooleposxmat_ds(:,:,vtps_ds==1);
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- pooleposxmat_vrds=rmnans(vectorisen(pooleposxmat_ds(:,cumsum(nccs),vtps_ds==1),1:2));
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- xvro1LL=vectorise(nanmean(pooleposxmat_vrds(:,Offer1LLtime),2)<0);
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- xvrd1LR=vectorise(nanmean(pooleposxmat_vrds(:,Delay1LRtime),2)>0);
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- xvro2LR=vectorise(nanmean(pooleposxmat_vrds(:,Offer2LRtime),2)>0);
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- xvrd2LL=vectorise(nanmean(pooleposxmat_vrds(:,Delay2LLtime),2)<0);
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- xvrchLL=vectorise(nanmean(pooleposxmat_vrds(:,ChoiceLLtime),2)<0);
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-
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- pooleposxmat_vrdds=pooleposxmat_vrds;
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- pooleposxmat_vrdds(rmnans(vectorise(pooloffer1sd(:,cumsum(nccs))))==0,:)=...
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- -pooleposxmat_vrdds(rmnans(vectorise(pooloffer1sd(:,cumsum(nccs))))==0,:);
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-
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- xvrdo1LL=vectorise(nanmean(pooleposxmat_vrdds(:,Offer1LLtime),2)<0);
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- xvrdd1LR=vectorise(nanmean(pooleposxmat_vrdds(:,Delay1LRtime),2)>0);
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- xvrdo2LR=vectorise(nanmean(pooleposxmat_vrdds(:,Offer2LRtime),2)>0);
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- xvrdd2LL=vectorise(nanmean(pooleposxmat_vrdds(:,Delay2LLtime),2)<0);
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- xvrdchLL=vectorise(nanmean(pooleposxmat_vrdds(:,ChoiceLLtime),2)<0);
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-
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- xo1LL=vectorise(nanmean(pooleposxmat_vds(:,:,Offer1LLtime),3)<0);
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- xo1LR=vectorise(nanmean(pooleposxmat_vds(:,:,Offer1LLtime),3)>0);
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- xd1LR=vectorise(nanmean(pooleposxmat_vds(:,:,Delay1LRtime),3)>0);
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- xo2LR=vectorise(nanmean(pooleposxmat_vds(:,:,Offer2LRtime),3)>0);
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- xd2LL=vectorise(nanmean(pooleposxmat_vds(:,:,Delay2LLtime),3)<0);
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- vvss=vectorisen(pooleposxmat_vds,1:2);
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- vvrss=(pooleposxmat_vrds);
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- iso1LL=nanmean(pooleposxmat_vds(:,:,Offer1LLtime),3)<0;
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- isd1LR=nanmean(pooleposxmat_vds(:,:,Delay1LRtime),3)>0;
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- iso2LR=nanmean(pooleposxmat_vds(:,:,Offer2LRtime),3)>0;
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- isd2LL=nanmean(pooleposxmat_vds(:,:,Delay2LLtime),3)<0;
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- iso1LLd2LL= iso1LL & isd2LL;
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- iso1LLd1LR= iso1LL &(~isd2LL);
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- iso1LLd1LLd2LL= iso1LL & (~isd1LR) & isd2LL;
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- iso1LLd1LLd2LR= iso1LL & (~isd1LR) &(~isd2LL);
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-
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- iso2LRd2LL= iso2LR & isd2LL;
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- iso2LRd2LR= iso2LR &(~isd2LL);
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- iso2LLd2LL=(~iso2LR)& isd2LL;
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- iso2LLd2LR=(~iso2LR)&(~isd2LL);
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- xebins=linspace(-max(abs(vvss(:))),max(abs(vvss(:))),1e3);
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-
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-
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- firstL =logical(rmnans(vectorise(pooloffer1sd(:,cumsum(nccs))))==1);
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- firstR =logical(rmnans(vectorise(pooloffer1sd(:,cumsum(nccs))))==0);
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- chooseR =logical(rmnans(vectorise(poolofferchR(:,cumsum(nccs))))==1);
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-
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- %%
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- % offer1sd==1 if L; 0 if R.
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- clc
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- fprintf('LookL on offer1 %2.2f%% of the trials where first offer is Left.\n', mean([double(xvrdo1LL(firstL))==1 ])*100);
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- fprintf('LookR on offer1 %2.2f%% of the trials where first offer is Left.\n', mean([double(xvrdo1LL(firstL))==0 ])*100);
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- fprintf('LookL on offer1 %2.2f%% of the trials where first offer is Right.\n', mean([double(xvrdo1LL(firstR))==1 ])*100);
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- fprintf('LookR on offer1 %2.2f%% of the trials where first offer is Right.\n\n',mean([double(xvrdo1LL(firstR))==0 ])*100);
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-
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- fprintf('LookL on delay1 %2.2f%% of the trials where first offer is Left.\n', mean([double(xvrdd1LR(firstL))==0 ])*100);
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- fprintf('LookR on delay1 %2.2f%% of the trials where first offer is Left.\n', mean([double(xvrdd1LR(firstL))==1 ])*100);
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- fprintf('LookL on delay1 %2.2f%% of the trials where first offer is Right.\n', mean([double(xvrdd1LR(firstR))==0 ])*100);
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- fprintf('LookR on delay1 %2.2f%% of the trials where first offer is Right.\n\n',mean([double(xvrdd1LR(firstR))==1 ])*100);
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-
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- fprintf('LookL on offer2 %2.2f%% of the trials where first offer is Left.\n', mean([double(xvrdo2LR(firstL))==0 ])*100);
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- fprintf('LookR on offer2 %2.2f%% of the trials where first offer is Left.\n', mean([double(xvrdo2LR(firstL))==1 ])*100);
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- fprintf('LookL on offer2 %2.2f%% of the trials where first offer is Right.\n', mean([double(xvrdo2LR(firstR))==0 ])*100);
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- fprintf('LookR on offer2 %2.2f%% of the trials where first offer is Right.\n\n',mean([double(xvrdo2LR(firstR))==1 ])*100);
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-
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- fprintf('LookL on delay2 %2.2f%% of the trials where first offer is Left.\n', mean([double(xvrdd2LL(firstL))==1 ])*100);
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- fprintf('LookR on delay2 %2.2f%% of the trials where first offer is Left.\n', mean([double(xvrdd2LL(firstL))==0 ])*100);
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- fprintf('LookL on delay2 %2.2f%% of the trials where first offer is Right.\n', mean([double(xvrdd2LL(firstR))==1 ])*100);
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- fprintf('LookR on delay2 %2.2f%% of the trials where first offer is Right.\n\n',mean([double(xvrdd2LL(firstR))==0 ])*100);
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-
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- fprintf('LookL on choice %2.2f%% of the trials where first offer is Left.\n', mean([double(xvrdchLL(firstL))==1 ])*100);
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- fprintf('LookR on choice %2.2f%% of the trials where first offer is Left.\n', mean([double(xvrdchLL(firstL))==0 ])*100);
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- fprintf('LookL on choice %2.2f%% of the trials where first offer is Right.\n', mean([double(xvrdchLL(firstR))==1 ])*100);
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- fprintf('LookR on choice %2.2f%% of the trials where first offer is Right.\n\n',mean([double(xvrdchLL(firstR))==0 ])*100);
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-
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- %%
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- Fisbest =logical(rmnans(vectorise(pooloffer1ev(:,cumsum(nccs)))) >rmnans(vectorise(pooloffer2ev(:,cumsum(nccs)))));
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- Sisbest =logical(rmnans(vectorise(pooloffer1ev(:,cumsum(nccs)))) <rmnans(vectorise(pooloffer2ev(:,cumsum(nccs)))));
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- FSssame =logical(rmnans(vectorise(pooloffer1ev(:,cumsum(nccs))))==rmnans(vectorise(pooloffer2ev(:,cumsum(nccs)))));
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-
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- Lisbest_reref= logical([Fisbest & firstL; Fisbest & firstR]);
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- Risbest_reref= logical([Sisbest & firstL; Sisbest & firstR]);
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- chR_reref=logical([chooseR==1 & firstL; chooseR==0 & firstR]);
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-
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- clc
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- % LookL and Lis best means LookL(firstL&Fisbest) + LookR(firstR&Risbest)
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- % LL fL fLbest - LL fR fRbest - LL fL SRbest - LL fR SLbest
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- % LL fL fLbest - LL fL fLbest - LR fL fRbest - LL fL
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- fprintf('LookL on offer1 %2.2f%% of the trials where first, left offer is best.\n', mean([double(xvrdo1LL(Fisbest & firstL)==1) double(xvrdo1LL(Fisbest & firstR)==0)])*100);
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- fprintf('LookL on offer1 %2.2f%% of the trials where first, left offer is worse.\n', mean([double(xvrdo1LL(Sisbest & firstL)==1) double(xvrdo1LL(Sisbest & firstR)==0)])*100);
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- fprintf('LookL on offer1 %2.2f%% of the trials where first, left offer is same.\n', mean([double(xvrdo1LL(firstL & FSssame)==1) double(xvrdo1LL(firstR & FSssame)==0)])*100);
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- fprintf('LookR on offer1 %2.2f%% of the trials where first, left offer is best.\n', mean([double(xvrdo1LL(Fisbest & firstL)==0) double(xvrdo1LL(Fisbest & firstR)==1)])*100);
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- fprintf('LookR on offer1 %2.2f%% of the trials where first, left offer is worse.\n', mean([double(xvrdo1LL(Sisbest & firstL)==0) double(xvrdo1LL(Sisbest & firstR)==1)])*100);
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- fprintf('LookR on offer1 %2.2f%% of the trials where first, left offer is same.\n\n',mean([double(xvrdo1LL(firstL & FSssame)==0) double(xvrdo1LL(firstR & FSssame)==1)])*100);
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-
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- fprintf('LookL on delay1 %2.2f%% of the trials where first, left offer is best.\n', mean([double(xvrdd1LR(Fisbest & firstL)==0) double(xvrdd1LR(Fisbest & firstR)==1)])*100);
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- fprintf('LookL on delay1 %2.2f%% of the trials where first, left offer is worse.\n', mean([double(xvrdd1LR(Sisbest & firstL)==0) double(xvrdd1LR(Sisbest & firstR)==1)])*100);
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- fprintf('LookL on delay1 %2.2f%% of the trials where first, left offer is same.\n', mean([double(xvrdd1LR(firstL & FSssame)==0) double(xvrdd1LR(firstR & FSssame)==1)])*100);
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- fprintf('LookR on delay1 %2.2f%% of the trials where first, left offer is best.\n', mean([double(xvrdd1LR(Fisbest & firstL)==1) double(xvrdd1LR(Fisbest & firstR)==0)])*100);
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- fprintf('LookR on delay1 %2.2f%% of the trials where first, left offer is worse.\n', mean([double(xvrdd1LR(Sisbest & firstL)==1) double(xvrdd1LR(Sisbest & firstR)==0)])*100);
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- fprintf('LookR on delay1 %2.2f%% of the trials where first, left offer is same.\n\n',mean([double(xvrdd1LR(firstL & FSssame)==1) double(xvrdd1LR(firstR & FSssame)==0)])*100);
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-
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- fprintf('LookL on offer2 %2.2f%% of the trials where first, left offer is best.\n', mean([double(xvrdo2LR(Fisbest & firstL)==0) double(xvrdo2LR(Fisbest & firstR)==1)])*100);
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- fprintf('LookL on offer2 %2.2f%% of the trials where first, left offer is worse.\n', mean([double(xvrdo2LR(Sisbest & firstL)==0) double(xvrdo2LR(Sisbest & firstR)==1)])*100);
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- fprintf('LookL on offer2 %2.2f%% of the trials where first, left offer is same.\n', mean([double(xvrdo2LR(firstL & FSssame)==0) double(xvrdo2LR(firstR & FSssame)==1)])*100);
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- fprintf('LookR on offer2 %2.2f%% of the trials where first, left offer is best.\n', mean([double(xvrdo2LR(Fisbest & firstL)==1) double(xvrdo2LR(Fisbest & firstR)==0)])*100);
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- fprintf('LookR on offer2 %2.2f%% of the trials where first, left offer is worse.\n', mean([double(xvrdo2LR(Sisbest & firstL)==1) double(xvrdo2LR(Sisbest & firstR)==0)])*100);
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- fprintf('LookR on offer2 %2.2f%% of the trials where first, left offer is same.\n\n',mean([double(xvrdo2LR(firstL & FSssame)==1) double(xvrdo2LR(firstR & FSssame)==0)])*100);
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-
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- fprintf('LookL on delay2 %2.2f%% of the trials where first, left offer is best.\n', mean([double(xvrdd2LL(Fisbest & firstL)==1) double(xvrdd2LL(Fisbest & firstR)==0)])*100);
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- fprintf('LookL on delay2 %2.2f%% of the trials where first, left offer is worse.\n', mean([double(xvrdd2LL(Sisbest & firstL)==1) double(xvrdd2LL(Sisbest & firstR)==0)])*100);
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- fprintf('LookL on delay2 %2.2f%% of the trials where first, left offer is same.\n', mean([double(xvrdd2LL(firstL & FSssame)==1) double(xvrdd2LL(firstR & FSssame)==0)])*100);
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- fprintf('LookR on delay2 %2.2f%% of the trials where first, left offer is best.\n', mean([double(xvrdd2LL(Fisbest & firstL)==0) double(xvrdd2LL(Fisbest & firstR)==1)])*100);
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- fprintf('LookR on delay2 %2.2f%% of the trials where first, left offer is worse.\n', mean([double(xvrdd2LL(Sisbest & firstL)==0) double(xvrdd2LL(Sisbest & firstR)==1)])*100);
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- fprintf('LookR on delay2 %2.2f%% of the trials where first, left offer is same.\n\n',mean([double(xvrdd2LL(firstL & FSssame)==0) double(xvrdd2LL(firstR & FSssame)==1)])*100);
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-
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- fprintf('LookL on choice %2.2f%% of the trials where first, left offer is best.\n', mean([double(xvrdchLL(Fisbest & firstL)==1) double(xvrdchLL(Fisbest & firstR)==0)])*100);
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- fprintf('LookL on choice %2.2f%% of the trials where first, left offer is worse.\n', mean([double(xvrdchLL(Sisbest & firstL)==1) double(xvrdchLL(Sisbest & firstR)==0)])*100);
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- fprintf('LookL on choice %2.2f%% of the trials where first, left offer is same.\n', mean([double(xvrdchLL(firstL & FSssame)==1) double(xvrdchLL(firstR & FSssame)==0)])*100);
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- fprintf('LookR on choice %2.2f%% of the trials where first, left offer is best.\n', mean([double(xvrdchLL(Fisbest & firstL)==0) double(xvrdchLL(Fisbest & firstR)==1)])*100);
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- fprintf('LookR on choice %2.2f%% of the trials where first, left offer is worse.\n', mean([double(xvrdchLL(Sisbest & firstL)==0) double(xvrdchLL(Sisbest & firstR)==1)])*100);
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- fprintf('LookR on choice %2.2f%% of the trials where first, left offer is same.\n\n',mean([double(xvrdchLL(firstL & FSssame)==0) double(xvrdchLL(firstR & FSssame)==1)])*100);
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-
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-
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- %%
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-
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- clc
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- fprintf('LookL on offer1 %2.2f%% of the trials where chosen offer is Left.\n', mean([double(xvrdo1LL(firstL & chooseR==0))==1 double(xvrdo1LL(firstR & chooseR==1))==0])*100);
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- fprintf('LookR on offer1 %2.2f%% of the trials where chosen offer is Left.\n', mean([double(xvrdo1LL(firstL & chooseR==0))==0 double(xvrdo1LL(firstR & chooseR==1))==1])*100);
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- fprintf('LookL on offer1 %2.2f%% of the trials where chosen offer is Right.\n', mean([double(xvrdo1LL(firstL & chooseR==1))==1 double(xvrdo1LL(firstR & chooseR==0))==0])*100);
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- fprintf('LookR on offer1 %2.2f%% of the trials where chosen offer is Right.\n\n',mean([double(xvrdo1LL(firstL & chooseR==1))==0 double(xvrdo1LL(firstR & chooseR==0))==1])*100);
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-
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- fprintf('LookL on delay1 %2.2f%% of the trials where chosen offer is Left.\n', mean([double(xvrdd1LR(firstL & chooseR==0))==0 double(xvrdd1LR(firstR & chooseR==1))==1])*100);
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- fprintf('LookR on delay1 %2.2f%% of the trials where chosen offer is Left.\n', mean([double(xvrdd1LR(firstL & chooseR==0))==1 double(xvrdd1LR(firstR & chooseR==1))==0])*100);
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- fprintf('LookL on delay1 %2.2f%% of the trials where chosen offer is Right.\n', mean([double(xvrdd1LR(firstL & chooseR==1))==0 double(xvrdd1LR(firstR & chooseR==0))==1])*100);
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- fprintf('LookR on delay1 %2.2f%% of the trials where chosen offer is Right.\n\n',mean([double(xvrdd1LR(firstL & chooseR==1))==1 double(xvrdd1LR(firstR & chooseR==0))==0])*100);
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-
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- fprintf('LookL on offer2 %2.2f%% of the trials where chosen offer is Left.\n', mean([double(xvrdo2LR(firstL & chooseR==0))==0 double(xvrdo2LR(firstR & chooseR==1))==1])*100);
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- fprintf('LookR on offer2 %2.2f%% of the trials where chosen offer is Left.\n', mean([double(xvrdo2LR(firstL & chooseR==0))==1 double(xvrdo2LR(firstR & chooseR==1))==0])*100);
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- fprintf('LookL on offer2 %2.2f%% of the trials where chosen offer is Right.\n', mean([double(xvrdo2LR(firstL & chooseR==1))==0 double(xvrdo2LR(firstR & chooseR==0))==1])*100);
|
|
|
- fprintf('LookR on offer2 %2.2f%% of the trials where chosen offer is Right.\n\n',mean([double(xvrdo2LR(firstL & chooseR==1))==1 double(xvrdo2LR(firstR & chooseR==0))==0])*100);
|
|
|
-
|
|
|
- fprintf('LookL on delay2 %2.2f%% of the trials where chosen offer is Left.\n', mean([double(xvrdd2LL(firstL & chooseR==0))==1 double(xvrdd2LL(firstR & chooseR==1))==0])*100);
|
|
|
- fprintf('LookR on delay2 %2.2f%% of the trials where chosen offer is Left.\n', mean([double(xvrdd2LL(firstL & chooseR==0))==0 double(xvrdd2LL(firstR & chooseR==1))==1])*100);
|
|
|
- fprintf('LookL on delay2 %2.2f%% of the trials where chosen offer is Right.\n', mean([double(xvrdd2LL(firstL & chooseR==1))==1 double(xvrdd2LL(firstR & chooseR==0))==0])*100);
|
|
|
- fprintf('LookR on delay2 %2.2f%% of the trials where chosen offer is Right.\n\n',mean([double(xvrdd2LL(firstL & chooseR==1))==0 double(xvrdd2LL(firstR & chooseR==0))==1])*100);
|
|
|
-
|
|
|
- fprintf('LookL on choice %2.2f%% of the trials where chosen offer is Left.\n', mean([double(xvrdchLL(firstL & chooseR==0))==1 double(xvrdchLL(firstR & chooseR==1))==0])*100);
|
|
|
- fprintf('LookR on choice %2.2f%% of the trials where chosen offer is Left.\n', mean([double(xvrdchLL(firstL & chooseR==0))==0 double(xvrdchLL(firstR & chooseR==1))==1])*100);
|
|
|
- fprintf('LookL on choice %2.2f%% of the trials where chosen offer is Right.\n', mean([double(xvrdchLL(firstL & chooseR==1))==1 double(xvrdchLL(firstR & chooseR==0))==0])*100);
|
|
|
- fprintf('LookR on choice %2.2f%% of the trials where chosen offer is Right.\n\n',mean([double(xvrdchLL(firstL & chooseR==1))==0 double(xvrdchLL(firstR & chooseR==0))==1])*100);
|
|
|
-
|
|
|
-
|
|
|
- %%
|
|
|
- fullfig();
|
|
|
- subplot(3,1,1);
|
|
|
- %SUBJECTS1&2
|
|
|
- for tt=1:Nvtps_ds; [hc(:,tt),he]=histcounts(vvrss(:,tt),xebins,'Normalization', 'probability'); end
|
|
|
- imagesc(rtmax_ds,he,hc); colormap(getdivergentcolmap(repmat(1:-.25:0,3,1)',[8 16 32 128])); hold on; view(2)
|
|
|
- for jj=1:8; plot([1 1].*sum(rtmes_ds(1:jj)),get(gca,'YLim'),'k:'); text(sum(rtmes_ds(1:jj-1)),max(get(gca,'YLim')),twLabels{jj}); end
|
|
|
- plot([0 sum(rtmes_ds)],[0 0],'k:');
|
|
|
- xlabel('time bins (10 ms)'); ylabel('eye pos. (<0 is L; >0 is R)');
|
|
|
-
|
|
|
- subplot(3,1,2);
|
|
|
- %SUBJECT1
|
|
|
- for tt=1:Nvtps_ds; [hc(:,tt),he]=histcounts(vectorise(pooleposxmat_vds(:,1:sum(nccs(1:4)),tt)),xebins,'Normalization', 'probability'); end
|
|
|
- imagesc(rtmax_ds,he,hc); colormap(getdivergentcolmap(repmat(1:-.25:0,3,1)',[8 16 32 128])); hold on; view(2)
|
|
|
- for jj=1:8; plot([1 1].*sum(rtmes_ds(1:jj)),get(gca,'YLim'),'k:'); text(sum(rtmes_ds(1:jj-1)),max(get(gca,'YLim')),twLabels{jj}); end
|
|
|
- plot([0 sum(rtmes_ds)],[0 0],'k:');
|
|
|
- xlabel('time bins (10 ms)'); ylabel('eye pos. (<0 is L; >0 is R)');
|
|
|
-
|
|
|
- subplot(3,1,3);
|
|
|
- %SUBJECT2
|
|
|
- for tt=1:Nvtps_ds; [hc(:,tt),he]=histcounts(vectorise(pooleposxmat_vds(:,sum(nccs(1:4))+1:end,tt)),xebins,'Normalization', 'probability'); end
|
|
|
- imagesc(rtmax_ds,he,hc); colormap(getdivergentcolmap(repmat(1:-.25:0,3,1)',[8 16 32 128])); hold on; view(2)
|
|
|
- for jj=1:8; plot([1 1].*sum(rtmes_ds(1:jj)),get(gca,'YLim'),'k:'); text(sum(rtmes_ds(1:jj-1)),max(get(gca,'YLim')),twLabels{jj}); end
|
|
|
- plot([0 sum(rtmes_ds)],[0 0],'k:');
|
|
|
- xlabel('time bins (10 ms)'); ylabel('eye pos. (<0 is L; >0 is R)');
|
|
|
-
|
|
|
-
|
|
|
- %%
|
|
|
- fullfig();
|
|
|
- subplot(3,1,1);
|
|
|
- %SUBJECTS1&2
|
|
|
- for tt=1:Nvtps_ds; [hc(:,tt),he]=histcounts(vectorise(pooleposxmat_vrdds(:,tt)),xebins,'Normalization', 'probability'); end
|
|
|
- imagesc(rtmax_ds,he,hc); colormap(getdivergentcolmap(repmat(1:-.25:0,3,1)',[8 16 32 128])); hold on; view(2)
|
|
|
- for jj=1:8; plot([1 1].*sum(rtmes_ds(1:jj)),get(gca,'YLim'),'k:'); text(sum(rtmes_ds(1:jj-1)),max(get(gca,'YLim')),twLabels{jj}); end
|
|
|
- plot([0 sum(rtmes_ds)],[0 0],'k:');
|
|
|
- xlabel('time bins (10 ms)'); ylabel('eye pos. (<0 is L; >0 is R)');
|
|
|
-
|
|
|
- subplot(3,1,2);
|
|
|
- %SUBJECT1
|
|
|
- for tt=1:Nvtps_ds; [hc(:,tt),he]=histcounts(vectorise(pooleposxmat_vrdds(1:sum(ntrs(1:4)),tt)),xebins,'Normalization', 'probability'); end
|
|
|
- imagesc(rtmax_ds,he,hc); colormap(getdivergentcolmap(repmat(1:-.25:0,3,1)',[8 16 32 128])); hold on; view(2)
|
|
|
- for jj=1:8; plot([1 1].*sum(rtmes_ds(1:jj)),get(gca,'YLim'),'k:'); text(sum(rtmes_ds(1:jj-1)),max(get(gca,'YLim')),twLabels{jj}); end
|
|
|
- plot([0 sum(rtmes_ds)],[0 0],'k:');
|
|
|
- xlabel('time bins (10 ms)'); ylabel('eye pos. (<0 is L; >0 is R)');
|
|
|
-
|
|
|
- subplot(3,1,3);
|
|
|
- %SUBJECT2
|
|
|
- for tt=1:Nvtps_ds; [hc(:,tt),he]=histcounts(vectorise(pooleposxmat_vrdds(sum(ntrs(1:4))+1:end,tt)),xebins,'Normalization', 'probability'); end
|
|
|
- imagesc(rtmax_ds,he,hc); colormap(getdivergentcolmap(repmat(1:-.25:0,3,1)',[8 16 32 128])); hold on; view(2)
|
|
|
- for jj=1:8; plot([1 1].*sum(rtmes_ds(1:jj)),get(gca,'YLim'),'k:'); text(sum(rtmes_ds(1:jj-1)),max(get(gca,'YLim')),twLabels{jj}); end
|
|
|
- plot([0 sum(rtmes_ds)],[0 0],'k:');
|
|
|
- xlabel('time bins (10 ms)'); ylabel('eye pos. (<0 is L; >0 is R)');
|
|
|
-
|
|
|
-
|
|
|
- %%
|
|
|
- fullfig();
|
|
|
- subplot(2,1,1);
|
|
|
- % LOOK LEFT DURING OFFER1
|
|
|
- for tt=1:Nvtps_ds; [hc(:,tt),he]=histcounts(vvrss(xvro1LL,tt),xebins,'Normalization', 'probability'); end
|
|
|
- imagesc(rtmax_ds,he,hc); colormap(getdivergentcolmap(repmat(1:-.25:0,3,1)',[8 16 32 128])); hold on; view(2)
|
|
|
- for jj=1:8; plot([1 1].*sum(rtmes_ds(1:jj)),get(gca,'YLim'),'k:'); text(sum(rtmes_ds(1:jj-1)),max(get(gca,'YLim')),twLabels{jj}); end
|
|
|
- plot([0 sum(rtmes_ds)],[0 0],'k:'); text(Offer1LLtime(1),-10000,sprintf('LookL:%2.2f%%',mean(xvro1LL)*100),'color','r');
|
|
|
- plot([1 1].*Offer1LLtime(1),get(gca,'YLim'),'r:');
|
|
|
- xlabel('time bins (10 ms)'); ylabel('eye pos. (<0 is L; >0 is R)');
|
|
|
-
|
|
|
- subplot(2,1,2);
|
|
|
- %LOOK RIGHT DURING OFFER1
|
|
|
- for tt=1:Nvtps_ds; [hc(:,tt),he]=histcounts(vvrss(~xvro1LL,tt),xebins,'Normalization', 'probability'); end
|
|
|
- imagesc(rtmax_ds,he,hc); colormap(getdivergentcolmap(repmat(1:-.25:0,3,1)',[8 16 32 128])); hold on; view(2)
|
|
|
- for jj=1:8; plot([1 1].*sum(rtmes_ds(1:jj)),get(gca,'YLim'),'k:'); text(sum(rtmes_ds(1:jj-1)),max(get(gca,'YLim')),twLabels{jj}); end
|
|
|
- plot([0 sum(rtmes_ds)],[0 0],'k:'); text(Offer1LLtime(1),+10000,sprintf('LookR:%2.2f%%',mean(~xvro1LL)*100),'color','r');
|
|
|
- plot([1 1].*Offer1LLtime(1),get(gca,'YLim'),'r:');
|
|
|
- xlabel('time bins (10 ms)'); ylabel('eye pos. (<0 is L; >0 is R)');
|
|
|
- supertitle('Compare offer1 side: LookL (top), LookR (bottom)');
|
|
|
- %%
|
|
|
-
|
|
|
- fullfig();
|
|
|
- subplot(2,1,1);
|
|
|
- % LOOK RIGHT DURING DELAY1
|
|
|
- for tt=1:Nvtps_ds; [hc(:,tt),he]=histcounts(vvrss(xvrd1LR,tt),xebins,'Normalization', 'probability'); end
|
|
|
- imagesc(rtmax_ds,he,hc); colormap(getdivergentcolmap(repmat(1:-.25:0,3,1)',[8 16 32 128])); hold on; view(2)
|
|
|
- for jj=1:8; plot([1 1].*sum(rtmes_ds(1:jj)),get(gca,'YLim'),'k:'); text(sum(rtmes_ds(1:jj-1)),max(get(gca,'YLim')),twLabels{jj}); end
|
|
|
- plot([0 sum(rtmes_ds)],[0 0],'k:'); text(Delay1LRtime(1),+10000,sprintf('LookR:%2.2f%%',mean(xvrd1LR)*100),'color','r');
|
|
|
- plot([1 1].*Delay1LRtime(1),get(gca,'YLim'),'r:');
|
|
|
- xlabel('time bins (10 ms)'); ylabel('eye pos. (<0 is L; >0 is R)');
|
|
|
-
|
|
|
- subplot(2,1,2);
|
|
|
- %LOOK LEFT DURING DELAY1
|
|
|
- for tt=1:Nvtps_ds; [hc(:,tt),he]=histcounts(vvrss(~xvrd1LR,tt),xebins,'Normalization', 'probability'); end
|
|
|
- imagesc(rtmax_ds,he,hc); colormap(getdivergentcolmap(repmat(1:-.25:0,3,1)',[8 16 32 128])); hold on; view(2)
|
|
|
- for jj=1:8; plot([1 1].*sum(rtmes_ds(1:jj)),get(gca,'YLim'),'k:'); text(sum(rtmes_ds(1:jj-1)),max(get(gca,'YLim')),twLabels{jj}); end
|
|
|
- plot([0 sum(rtmes_ds)],[0 0],'k:'); text(Delay1LRtime(1),-10000,sprintf('LookL:%2.2f%%',mean(~xvrd1LR)*100),'color','r');
|
|
|
- plot([1 1].*Delay1LRtime(1),get(gca,'YLim'),'r:');
|
|
|
- xlabel('time bins (10 ms)'); ylabel('eye pos. (<0 is L; >0 is R)');
|
|
|
- supertitle('Compare delay1 side: LookR (top), LookL (bottom)');
|
|
|
-
|
|
|
- %%
|
|
|
- fullfig();
|
|
|
- subplot(2,1,1);
|
|
|
- % LOOK LEFT DURING OFFER1 AND LEFT DURING DELAY2
|
|
|
- for tt=1:Nvtps_ds; [hc(:,tt),he]=histcounts(vvrss(xvro1LL&(~xvrd1LR)&xvrd2LL,tt),xebins,'Normalization', 'probability'); end
|
|
|
- imagesc(rtmax_ds,he,hc); colormap(getdivergentcolmap(repmat(1:-.25:0,3,1)',[8 16 32 128])); hold on; view(2)
|
|
|
- for jj=1:8; plot([1 1].*sum(rtmes_ds(1:jj)),get(gca,'YLim'),'k:'); text(sum(rtmes_ds(1:jj-1)),max(get(gca,'YLim')),twLabels{jj}); end
|
|
|
- plot([0 sum(rtmes_ds)],[0 0],'k:'); text(Delay2LLtime(1),-10000,sprintf('LookL:%2.2f%%',mean(xvro1LL&(~xvrd1LR)&xvrd2LL)*100),'color','r');
|
|
|
- plot([1 1].*Offer1LLtime(1),get(gca,'YLim'),'r:');
|
|
|
- plot([1 1].*Delay1LRtime(1),get(gca,'YLim'),'r:');
|
|
|
- plot([1 1].*Delay2LLtime(1),get(gca,'YLim'),'r:');
|
|
|
- xlabel('time bins (10 ms)'); ylabel('eye pos. (<0 is L; >0 is R)');
|
|
|
-
|
|
|
- subplot(2,1,2);
|
|
|
- %LOOK LEFT DURING OFFER1 AND RIGHT DURING DELAY2
|
|
|
- for tt=1:Nvtps_ds; [hc(:,tt),he]=histcounts(vvss(xvro1LL&(~xvrd1LR)&(~xvrd2LL),tt),xebins,'Normalization', 'probability'); end
|
|
|
- imagesc(rtmax_ds,he,hc); colormap(getdivergentcolmap(repmat(1:-.25:0,3,1)',[8 16 32 128])); hold on; view(2)
|
|
|
- for jj=1:8; plot([1 1].*sum(rtmes_ds(1:jj)),get(gca,'YLim'),'k:'); text(sum(rtmes_ds(1:jj-1)),max(get(gca,'YLim')),twLabels{jj}); end
|
|
|
- plot([0 sum(rtmes_ds)],[0 0],'k:'); text(Delay2LLtime(1),+10000,sprintf('LookR:%2.2f%%',mean(xvro1LL&(~xvrd1LR)&(~xvrd2LL))*100),'color','r');
|
|
|
- plot([1 1].*Offer1LLtime(1),get(gca,'YLim'),'r:');
|
|
|
- plot([1 1].*Delay1LRtime(1),get(gca,'YLim'),'r:');
|
|
|
- plot([1 1].*Delay2LLtime(1),get(gca,'YLim'),'r:');
|
|
|
- xlabel('time bins (10 ms)'); ylabel('eye pos. (<0 is L; >0 is R)');
|
|
|
- supertitle('offer1 LookL, delay1 LookL, compare delay2 side: LookL (top), LookR (bottom)');
|
|
|
-
|
|
|
- %%
|
|
|
- Vpl(1,:)=( xvro1LL)&(~xvrd1LR);% offer1=L delay1=L
|
|
|
- Vpl(2,:)=( xvro1LL)&( xvrd1LR);% offer1=L delay1=R
|
|
|
- Vpl(3,:)=(~xvro1LL)&(~xvrd1LR);% offer1=R delay1=L
|
|
|
- Vpl(4,:)=(~xvro1LL)&( xvrd1LR);% offer1=R delay1=R
|
|
|
- Vpl(5,:)=(~xvro2LR)&( xvrd2LL);% offer2=L delay1=L
|
|
|
- Vpl(6,:)=(~xvro2LR)&(~xvrd2LL);% offer2=L delay1=R
|
|
|
- Vpl(7,:)=( xvro2LR)&( xvrd2LL);% offer2=R delay1=L
|
|
|
- Vpl(8,:)=( xvro2LR)&(~xvrd2LL);% offer2=R delay1=R
|
|
|
-
|
|
|
- Spl={'Off1L,Del1L=','Off1L,Del1R=','Off1R,Del1L=','Off1R,Del1R=',...
|
|
|
- 'Off2L,Del2L=','off2L,Del2R=','Off2R,Del2L=','Off2R,Del2R='};
|
|
|
- Ppl=[0 0; 0 1; 1 0; 1 1];
|
|
|
-
|
|
|
- for jj=[1 3 5 7]
|
|
|
- fullfig([Ppl((jj+1)/2,:)*.5 .5 .5]);
|
|
|
- subplot(2,1,1);
|
|
|
- % LOOK RIGHT DURING OFFER2 AND LEFT DURING DELAY2
|
|
|
- for tt=1:Nvtps_ds; [hc(:,tt),he]=histcounts(vvrss(Vpl(jj,:),tt),xebins,'Normalization', 'probability'); end
|
|
|
- imagesc(rtmax_ds,he,hc); colormap(getdivergentcolmap(repmat(1:-.25:0,3,1)',[8 16 32 128])); hold on; view(2)
|
|
|
- for tt=1:8; plot([1 1].*sum(rtmes_ds(1:tt)),get(gca,'YLim'),'k:'); text(sum(rtmes_ds(1:tt-1)),max(get(gca,'YLim')),twLabels{tt}); end
|
|
|
- plot([0 sum(rtmes_ds)],[0 0],'k:'); text(Delay2LLtime(1),-10000,sprintf('%s:%2.2f%%',Spl{jj},mean(Vpl(jj,:))*100),'color','r');
|
|
|
- plot([1 1].*Offer2LRtime(1),get(gca,'YLim'),'r:');
|
|
|
- plot([1 1].*Delay2LLtime(1),get(gca,'YLim'),'r:');
|
|
|
- xlabel('time bins (10 ms)'); ylabel('eye pos. (<0 is L; >0 is R)');
|
|
|
-
|
|
|
- subplot(2,1,2);
|
|
|
- %LOOK RIGHT DURING OFFER2 AND RIGHT DURING DELAY2
|
|
|
- for tt=1:Nvtps_ds; [hc(:,tt),he]=histcounts(vvrss(Vpl(jj+1,:),tt),xebins,'Normalization', 'probability'); end
|
|
|
- imagesc(rtmax_ds,he,hc); colormap(getdivergentcolmap(repmat(1:-.25:0,3,1)',[8 16 32 128])); hold on; view(2)
|
|
|
- for tt=1:8; plot([1 1].*sum(rtmes_ds(1:tt)),get(gca,'YLim'),'k:'); text(sum(rtmes_ds(1:tt-1)),max(get(gca,'YLim')),twLabels{tt}); end
|
|
|
- plot([0 sum(rtmes_ds)],[0 0],'k:'); text(Delay2LLtime(1),+10000,sprintf('%s:%2.2f%%',Spl{jj+1},mean(Vpl(jj+1,:))*100),'color','r');
|
|
|
- plot([1 1].*Offer2LRtime(1),get(gca,'YLim'),'r:');
|
|
|
- plot([1 1].*Delay2LLtime(1),get(gca,'YLim'),'r:');
|
|
|
- xlabel('time bins (10 ms)'); ylabel('eye pos. (<0 is L; >0 is R)');
|
|
|
-
|
|
|
- end
|
|
|
-
|
|
|
-end
|
|
|
|
|
|
%% Regress EV vs Spiking
|
|
|
if recomputelm
|
