Microstim_FF-FB/SCRIPTS/FUNCTIONS/FB_FIGURES.m

%% Generate the FEEDBACK MS figure panels ===============================
fprintf('== GENERATING FEEDBACK MS EFFECT FIGURES ==================\n')

% Effect Windows
EffWin.V1toV4.Exc = [0 0.050];
EffWin.V1toV4.Sup = [0.050 0.120];
EffWin.V4toV1.Exc = [0 0.030];
EffWin.V4toV1.Sup = [0.030 0.150];

% FEEDBACK V4 to V1 
EffectWindow.exc = EffWin.V4toV1.Exc;
EffectWindow.sup = EffWin.V4toV1.Sup;

fprintf(['Calculating V1 effect sizes in the following post-stimulation windows:\n'...
    'Excitation: ' num2str(EffectWindow.exc(1)*1e3) ' to ' num2str(EffectWindow.exc(2)*1e3) ' ms\n'...
    'Suppression: ' num2str(EffectWindow.sup(1)*1e3) ' to ' num2str(EffectWindow.sup(2)*1e3) ' ms\n']);

V4MS = preProcessV4MS(V4MS,EffectWindow);

%% FIGURE 6C - EXAMPLE UNIT V1 ==========================================
fprintf('\n -- FIGURE 6C ----------\n');

INDS = find(V4MS.RFDATA(:,5)>-1);
indCH = 36;

V4MS.META.S = 1;
soa = 3;
S = 8;

BL_EX = smooth(V4MS.CLEAN.UNITS(:,INDS(indCH),1),S );
MAX = nanmax(BL_EX); BL_EX = BL_EX/MAX;
MS_EX = smooth(V4MS.CLEAN.UNITS(:,INDS(indCH),soa+1),S )/MAX;
FSZ = 12;

figure (44);clf; hold all;
set(gca,'FontSize',FSZ)
xlim([-0.1 0.35])
ylim([-0.15 1.05])

YL = ylim;p = patch([0.15 0.15 0.15+0.025 0.15+0.025],...
    [YL(1) YL(2) YL(2) YL(1)],0.8*[1 1 1],'EdgeColor','none',...
    'FaceColor',[230 220 110]/255);
hms = plot(V4MS.TIME,smooth(MS_EX,1),'Color',...
    V4MS.META.COLS(soa+1,:),'LineWidth',2);
hbl = plot(V4MS.TIME,smooth(BL_EX,1),'Color',...
    0*V4MS.META.COLS(1,:),'LineWidth',2);

legend([hbl hms],{'no MS' 'MS'})
xlabel('Time [s]'); ylabel('MUA')

print_figure('figure6C',[0 0 7 7],fullfile(fld.figs,'FIG_6'),save_figs)
cd(fld.scripts);

%% FIGURE 6B - Make RF figure FB ========================================
fprintf('\n -- FIGURE 6B ----------\n');
load(fullfile(fld.data,'MAPPINGS','RF_B.mat'));

figure(17);
set(gca,'FontSize',FSZ)
V4Lims=[0 9; -9 0];
NV1RFs=[3]; % Say how many V1 RF there are.
v1ch = 3; % Say which one do you want to plot
% (if you want only RF 1 and 3 for example you can use v1ch=[1 3] )
NV4CH=19; % Set the V4 channel that you want to plot.
YTicks=[-9:2:0];
XTicks=[0:2:9];
[X,Y]=meshgrid(V4Lims(1,1):V4Lims(1,2),V4Lims(2,1):V4Lims(2,2));

ST=0.01;
[XI,YI]=meshgrid([V4Lims(1,1):ST:V4Lims(1,2)],[V4Lims(2,1):ST:V4Lims(2,2)]);

SM=3; count=0;

wh=[0.5 0.5];
POS=[0.5 1; 1 1; 0.5 0.5; 1 0.5];
count=count+1;

TEMP=squeeze(RESPMATV4(NV4CH,:,:));
if SM~=0
    TEMP3=TEMP;
    for j=1:size(TEMP,1)
        TEMP3(j,:)=smooth(TEMP(j,:),SM);
    end
    for i=1:size(TEMP3,2)
        TEMP3(:,i)=smooth(TEMP3(:,i),SM);
    end
else
    TEMP3=TEMP;
end


Z=interp2(X,Y,TEMP3,XI,YI);

colormap('default')
imagesc(V4Lims(1,:),V4Lims(2,:),Z/max(max(Z)));
set(gca,'YDir','normal')
hold on
axis('square')
COLORS=[159/255, 29/255, 53/255; 0 128/255 0; ...
    125/255, 249/255, 1; 244/255, 196/255, 48/255];
for v1=v1ch
    TEMP=DATAV1(v1);
    
    DAT=TEMP.DAT;
    sampf=TEMP.Sampf;
    MP=TEMP.MP;
    DegperS=TEMP.DegperS;
    OFF.rho=TEMP.RFPecc;
    OFF.angle=TEMP.RFPangle;
    
    RF_INFO(v1)= RFpos(DAT, sampf, MP, DegperS, OFF);
    
    Mid=RF_INFO(v1).Mid;
    WH=RF_INFO(v1).WH;
    clr=RF_INFO(v1).clr;
    Ic=RF_INFO(v1).Ic;
    if v1==1;channs=[2 3 4 7 10 11 12 14];
    elseif v1==2;channs=[1 2 3 4 6 11 12 14 15];
    elseif v1==3;channs=[2];
    end
    for chan = channs
        M = [Mid.x(chan) Mid.y(chan)];
        P = patch([Mid.x(chan)-WH(chan).w2 Mid.x(chan)+WH(chan).w2 Mid.x(chan)+WH(chan).w2 Mid.x(chan)-WH(chan).w2], ...
            [Mid.y(chan)-WH(chan).h2 Mid.y(chan)-WH(chan).h2 Mid.y(chan)+WH(chan).h2 Mid.y(chan)+WH(chan).h2],COLORS(v1,:), ...
            'EdgeColor', 'w','LineWidth',4); % COLORS(v1,1:3)
        set(P,'FaceColor','none')
    end
end

plot(xlim,[0 0],'w:')
plot([0 0], ylim,'w:')
scatter(0,0,[],[0 0 0],'Filled')
set(gca,'XAxisLocation','top')
set(gca,'Color',[0 0 1])
xlabel('Horizontal Position [deg]')
ylabel('Vertical Position [deg]')

print_figure('figure6B',[0 0 7 7],fullfile(fld.figs,'FIG_6'),save_figs)
cd(fld.scripts);

%% FIGURE 4C - RF overlap vs Supp effect ================================ 
fprintf('\n -- FIGURE 4C ----------\n');

OVER = V4MS.RFDATA(:,5);
EFFE  = 50*V4MS.EFFECT(3,:);
AMP = V4MS.RFDATA(:,12);

OVER_SIG = OVER(logical(V4MS.CLEAN.UNITSIND) & ~isnan(OVER));
EFFE_SIG = EFFE(logical(V4MS.CLEAN.UNITSIND) & ~isnan(OVER));
AMP_SIG  = AMP(logical(V4MS.CLEAN.UNITSIND) & ~isnan(OVER));

OVER = OVER(~isnan(OVER));
EFFE = EFFE(~isnan(OVER));
AMP = AMP(~isnan(OVER));

eff = EFFE./AMP';
over = OVER;

iNAN = isnan(eff);
eff(iNAN) = [];
over(iNAN) = [];
X = [ones(length(eff),1) over];
y = eff';
[b,bint,r,rint,stats] = regress(y,X);

[r,n,p,t] = regressionTTest(y,stats);
    disp(['R = ' num2str(r)])
    disp(['N = ' num2str(n)])
    disp(['P = ' num2str(p)])
    disp(['T = ' num2str(t)])

figure(100);clf;hold all
set(gca,'FontSize',10)
scatter(OVER,EFFE./AMP',60,[0.75 0.75 0.9],'filled','LineWidth',1)
scatter(OVER_SIG,EFFE_SIG./AMP_SIG',60,V4MS.META.COLS(4,:),'filled','LineWidth',1)
plot([0.1 0.95],b(2)*[0.15 0.99]+b(1),'Color',0*V4MS.META.COLS(2,:))
xlim([0 1])
ylabel('Effect Size')
set(gca,'XTick',[0 0.5 1])

plot(xlim,[0 0],'k:','LineWidth',2)
xlabel('RFs Overlap')
print_figure('figure4C',[0 0 7 7],fullfile(fld.figs,'FIG_4'),save_figs)
cd(fld.scripts);

%% FIGURE 6D SOA both monkeys ===========================================
fprintf('\n -- FIGURE 6D ----------\n');

S = 10;
SS = [-0.02 0.05 .15];
figure;clf;
for soa = 1:3
    subplot(1,3,soa);hold all;
    set(gca,'FontSize',FSZ)
    xlim([-0.1 0.35]); ylim([-0.15 1.05]); YL = ylim;
    p = patch([SS(soa) SS(soa) SS(soa)+0.025 SS(soa)+0.025],...
        [YL(1) YL(2) YL(2) YL(1)],0.8*[1 1 1],...
        'EdgeColor','none','FaceColor',[230 220 110]/255);
    hms = plot(V4MS.TIME,smooth(V4MS.CLEAN.AVE(:,soa+1)/...
        nanmax(smooth(V4MS.CLEAN.AVE(:,1),S)),S),...
        'Color',V4MS.META.COLS(soa+1,:), 'LineWidth',1);
    hbl = plot(V4MS.TIME,smooth(V4MS.CLEAN.AVE(:,1),S)/...
        nanmax(smooth(V4MS.CLEAN.AVE(:,1),S)),...
        'Color',0*V4MS.META.COLS(1,:),'LineWidth',1);
    legend([hbl hms],{'no MS' 'MS'})
    xlabel('Time [s]')
    title(['SOA ' num2str(SS(soa)*1000) ' ms']);
end
fprintf(['N = ' num2str(sum(V4MS.CLEAN.UNITSIND)) '\n']);

print_figure('figure6D',[0 0 21 7],fullfile(fld.figs,'FIG_6'),save_figs)
cd(fld.scripts);

%% FIGURE S3B SOA per MONKEY ============================================
fprintf('\n -- SUPP FIGURE 3B ----------\n');

MS = {'B' 'C'};
for m = 1:2
    S = 10;
    SS = [-0.02 0.05 .15];  
    temp = nanmean(nanmean(V4MS.CLEAN.UNITS(:,strcmp(V4MS.MONKEY,MS{m}),:),3),1);
    fprintf(['Monkey ' MS{m} ', n = ' num2str(sum(~isnan(temp))) '\n'])  
    AVS = squeeze(nanmean(V4MS.CLEAN.UNITS(:,strcmp(V4MS.MONKEY,MS{m}),:),2));
    
    figure (m+400*m);clf;
    for soa = 1:3
        subplot(1,3,soa);hold all;
        set(gca,'FontSize',FSZ)
        xlim([-0.1 0.35])
        ylim([-0.2 1.05])
        YL = ylim;p = patch([SS(soa) SS(soa) SS(soa)+0.025 SS(soa)+0.025],...
            [YL(1) YL(2) YL(2) YL(1)],0.8*[1 1 1],'EdgeColor','none',...
            'FaceColor',[230 220 110]/255);
        hms = plot(V4MS.TIME,smooth(AVS(:,soa+1)/nanmax(smooth(AVS(:,1),S)),S),...
            'Color',V4MS.META.COLS(soa+1,:), 'LineWidth',1);
        hbl = plot(V4MS.TIME,smooth(AVS(:,1),S)/nanmax(smooth(AVS(:,1),S)),...
            'Color',V4MS.META.COLS(1,:)*0,'LineWidth',1);
        
        legend([hbl hms],{'no MS' 'MS'})
        xlabel('Time [s]')
    end
    print_figure(['suppfigure3B_Monkey' MS{m}],[0 0 21 7],...
        fullfile(fld.figs,'SUPPFIG_3'),save_figs);
    cd(fld.scripts);
end

%% FIGURE 6E - Diff MUA by SOA, triggered on MS ========================= 
fprintf('\n -- FIGURE 6E ----------\n');

figure (8);clf;hold all;
set(gca,'FontSize',FSZ)
ylim([-0.15 0.06])
YL = ylim;p = patch([0 0 0.025 0.025],[YL(1) YL(2) YL(2) YL(1)],...
    0.8*[1 1 1],'EdgeColor','none','FaceColor',[230 220 110]/255);
S = 10;
SAOS = [-0.02 0.05 0.15];
hds = [];
for soa = 1:3
    hds(end+1) = plot(V4MS.TIME-SAOS(soa),...
        smooth(-V4MS.CLEAN.AVE(:,1)+V4MS.CLEAN.AVE(:,soa+1),S)/...
        nanmax(smooth(V4MS.CLEAN.AVE(:,1),S)),...
        'Color',V4MS.META.COLS(soa+1,:),'LineWidth',1);
    xlim([-0.1 0.2])
end

plot(xlim,[0 0],'k:')
set(gca,'YTick',[-0.1:0.05:0.05]);
set(gca,'XTick',[-0.1:0.1:0.1]);
legend(hds,{'-20ms' '50ms' '150ms'},'Location','SouthWest')
ylabel('MS - no MS');
xlabel('Time [s]')
print_figure('figure6E',[0 0 13 5.5],fullfile(fld.figs,'FIG_6'),save_figs)
cd(fld.scripts);

%% FIGURE S3C - Supressive effect per monkey ============================
fprintf('\n -- SUPP FIGURE 3C ----------\n');

for m = 1:2
    figure (856+m);clf;hold all;
    set(gca,'FontSize',FSZ)
    ylim([-0.2 0.1])
    YL = ylim;p = patch([0 0 0.025 0.025],[YL(1) YL(2) YL(2) YL(1)],...
        0.8*[1 1 1],'EdgeColor','none','FaceColor',[230 220 110]/255);
    S = 10;
    SAOS = [-0.02 0.05 0.15];
    
    AVS = squeeze(nanmean(V4MS.CLEAN.UNITS(:,strcmp(V4MS.MONKEY,MS{m}),:),2));
    
    hds = [];
    for soa = 1:3
        hds(end+1) = plot(V4MS.TIME-SAOS(soa),smooth(-AVS(:,1)+AVS(:,soa+1),S)/...
            nanmax(smooth(AVS(:,1),S)),'Color',V4MS.META.COLS(soa+1,:),'LineWidth',1);
        xlim([-0.1 0.2])
    end

    plot(xlim,[0 0],'k:')
    legend(hds,{'-20ms' '50ms' '150ms'},'Location','SouthWest')
    ylabel('MS - no MS'); xlabel('Time [s]');
    print_figure(['suppfigure3C_Monkey' MS{m}],[0 0 7 7],...
        fullfile(fld.figs,'SUPPFIG_3'),save_figs);
    cd(fld.scripts);
end

%% FIGURE 6F - Average Effect Sizes per SOA =============================
fprintf('\n -- FIGURE 6F ----------\n');

ANOVA_DATA= [];ANOVA_DATA2= [];
OVER = V4MS.RFDATA(:,5);

figure(103);clf;hold all

subplot(1,2,2);hold on;
set(gca,'FontSize',FSZ)
for soa = 1:3
    EFFE  = V4MS.EFFECT(soa,:);
    EFFE_SIG = EFFE(~isnan(nanmean(V4MS.CLEAN.UNITS(:,:,1),1)))/...
        nanmax(smooth(V4MS.CLEAN.AVE(:,1),10));;
    mEFF    = nanmean(EFFE_SIG);
    sEFF    = nanstd(EFFE_SIG)/sqrt(sum(~isnan(EFFE_SIG)));
    errorbar(soa,mEFF,sEFF,'sk','LineWidth',2);
    bar(soa,mEFF,'FaceColor',V4MS.META.COLS(soa+1,:))
    
    ANOVA_DATA = [ANOVA_DATA EFFE_SIG'];
end
ylim([-0.07 0.032])
xlim([0.5 3.5])
set(gca,'XTick',[1 2 3],'XTickLabel',{'-20' '50' '150'})
ylabel('Mean Difference')
% plot(xlim,[0 0],'k:','LineWidth',2)
xlabel('SOA [ms]')
title('Suppression')

subplot(1,2,1);hold on;
set(gca,'FontSize',FSZ)
for soa = 1:3
    EFFE2  = V4MS.EXCIT_EFFECT(soa,:);
    EFFE_SIG2 = EFFE2(~isnan(nanmean(V4MS.CLEAN.UNITS(:,:,1),1)))/...
        nanmax(smooth(V4MS.CLEAN.AVE(:,1),10));;
    mEFF2    = nanmean(EFFE_SIG2);
    sEFF2    = nanstd(EFFE_SIG2)/sqrt(sum(~isnan(EFFE_SIG2)));
    errorbar(soa,mEFF2,sEFF2,'sk','LineWidth',2);
    bar(soa,mEFF2,'FaceColor',V4MS.META.COLS(soa+1,:))
    
    ANOVA_DATA2 = [ANOVA_DATA2 EFFE_SIG2'];
end
ylim([-0.07 0.032])
xlim([0.5 3.5])
set(gca,'XTick',[1 2 3],'XTickLabel',{'-20' '50' '150'})
ylabel('Mean Difference')
% plot(xlim,[0 0],'k:','LineWidth',2)
xlabel('SOA [ms]')
title('Excitation')

print_figure('figure6F',[0 0 7 7],fullfile(fld.figs,'FIG_6'),save_figs)
cd(fld.scripts);

%% STATS for FiG 6F =====================================================
fprintf('Statistics for FIG 6F\n');

fprintf('- Excitation -\n');
anova_data2 = ANOVA_DATA2;
anova_data2(isnan(ANOVA_DATA2(:,1)),:) = [];
[P2,ANOVATAB2,STATS2] = anova1(anova_data2);
[c2,m2,h2,names2] = multcompare(STATS2,'Alpha',10^-15,'CType','tukey-kramer');

for s=1:3
    [h_soa{s},p_soa{s}] = ttest(anova_data2(:,s));
    fprintf(['SOA ' num2str(c2(s,1)) ' vs ' num2str(c2(s,2)) ': p = ' ...
        num2str(c2(s,6)) '\n']);
end

fprintf('- Suppression -\n');
anova_data = ANOVA_DATA;
anova_data(isnan(ANOVA_DATA(:,1)),:) = [];
[P,ANOVATAB,STATS] = anova1(anova_data);
[c,m,h,names] = multcompare(STATS,'Alpha',10^-15,'CType','tukey-kramer');

for i=1:3
    fprintf(['SOA ' num2str(c(i,1)) ' vs ' num2str(c(i,2)) ': p = ' ...
        num2str(c(i,6)) '\n']);
end

%% FIGURE 4D - Suppression effect size vs MUA ===========================
fprintf('\n -- FIGURE 4D ----------\n');

S = 10; SS = [-0.05 0.05 .15];

% Compute activity during blank trials.
BASES = nan(size(V4MS.CLEAN.UNITS,2),3);
for soa = 1:3
    indT = V4MS.TIME > (SS(soa)+0.025) & V4MS.TIME < (SS(soa)+0.125);
    BASES(:,soa) = squeeze(nanmean(V4MS.UNITS(indT,:,1),1));
end

EFFS = nan(size(V4MS.CLEAN.UNITS,2),3);
for soa = 1:3
    EFFE  = V4MS.EFFECT(soa,:);
    EFFS(:,soa) = EFFE;
end

figure(105);clf;hold on
set(gca,'FontSize',FSZ)
xlim([-0.45 0.45])

for soa = 3 % only the 150 ms SOA
    scatter(BASES(:,soa),EFFS(:,soa),60,[0.75 0.75 0.9],'filled','LineWidth',1),
    scatter(BASES(logical(V4MS.CLEAN.UNITSIND),soa),...
        EFFS(logical(V4MS.CLEAN.UNITSIND),soa),60,...
        V4MS.META.COLS(soa+1,:),'filled','LineWidth',1);
    
    % compute regressions
    indM = logical(V4MS.CLEAN.UNITSIND);
    eff = EFFS(indM,soa);
    over = BASES(indM,soa);
    
    iNAN = isnan(mean([eff over],2));
    
    eff(iNAN) = [];
    over(iNAN) = [];
    
    X = [ones(length(eff),1) over];
    y = eff';
    [b,bint,r,rint,stats] = regress(y',X);
    
    [r,n,p,t] = regressionTTest(y,stats);
    disp(['R = ' num2str(r)])
    disp(['N = ' num2str(n)])
    disp(['P = ' num2str(p)])
    disp(['T = ' num2str(t)])
end
h = lsline;
xlim([-0.45 0.4])
set(h(1),'Color','k','LineStyle','--')
set(h(2),'LineStyle','none');
xlabel('Average MUA')
ylabel('Effect Size')

print_figure('figure4D' ,[0 0 7 7],fullfile(fld.figs,'FIG_4'),save_figs);
cd(fld.scripts);