/
exvivoRGC_RF_Analysis_plotting.m
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exvivoRGC_RF_Analysis_plotting.m
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%Tested on Matlab 2019b
%requires:
% panel (from Matlab file exchange)
% othercolor (from Matlab file exchange)
load("./exvivo_RFs.mat");
addpath("./utils");
%%
fprintf("Flipping ON rfs to OFF\n");
spatial_unsigned_all = flip_on_rfs(spatial_all);
clear spatial_all; %save RAM
%% Fig 3a. Binned Spatial RFs from one retina (retina 5)
f = figure;
idx_ret = find(ret_number == 5);
idx_map = bin_2d(centroids(idx_ret,:), 'binsize', 300, 'mincount',5);
counts = plot_binned_rfs(idx_map, spatial_unsigned_all(:,:,idx_ret));
sgtitle(sprintf("Fig 3a: Cell count = %.1f ± %.1f", mean(counts), std(counts)));
f.Position = [0 0 750 750]; %ensure figure is square for proper alignment
%% Extended Data Fig 5. Binned Spatial RFs from all sopsin retinas
f = figure;
idx_ret = find(sopsin_gt);
idx_map = bin_2d(centroids(idx_ret,:), 'binsize', 300, 'mincount',5);
counts = plot_binned_rfs(idx_map, spatial_unsigned_all(:,:,idx_ret));
sgtitle(sprintf("Extended Fig 5: Cell count = %.1f ± %.1f", mean(counts), std(counts)));
f.Position = [0 0 750 750]; %ensure figure is square for proper alignment
%% Fig 3b. Mean RFs from below, at and above horizon
figure;
cond = sopsin_gt; %only use sopsin retinas
as = [-1500, -900, 500]; bs = [-1000, -700, 600]; %bin limits in um
for i = 1:3
subplot(2,3,3+i);
a = as(i); b = bs(i);
idx = centroids(:,2) > a & centroids(:,2) < b & cond;
spatial = squeeze(mean(spatial_unsigned_all(:,:,idx), 3));
plot_spatial(spatial, sprintf("N = %d", nnz(idx)));
title(sprintf("[%d, %d] µm", a, b));
end
sgtitle("Fig 3b");
%% Fig 3c. Radial RF profiles (same bins as above)
fprintf("computing radial profiles of all rfs, ~2mins\n");
radial_all = zeros(size(spatial_unsigned_all,3), 50);
for i = 1:size(spatial_unsigned_all,3)
radial_all(i,:) = radial_profile(spatial_unsigned_all(:,:,i));
end
%%
for i = 1:3
a = as(i); b = bs(i);
idx = centroids(:,2) > a & centroids(:,2) < b & cond;
radials = radial_all(idx,:);
avg_rad(i,:) = mean(radials,1);
caption{i} = sprintf("[%d, %d] µm, n = %d", a, b, nnz(idx));
end
figure;
subplot(2,1,2);
plot(linspace(0,500,size(radials,2)),avg_rad', 'LineWidth', 3);
yline(0, 'LineStyle', '--');
legend(caption,'Location', 'southeastoutside');
xlabel("Radius (um)");
ylabel("RF Profile Weight");
ylim([-.1 .1]);
yticks([-.1 0 .1]);
xticks([0 500]);
xlim([0 500]);
colorv = [144 25 28]/255;
colorh = [184 72 38]/255;
colord = [231 138 36]/255;
colororder([colord;colorh;colorv]);
sgtitle("Fig 3c");
%% Fig 3d-i RF Properties binned in 1D or 2D
% and extended Data Fig. 7
clear cond;
cond{1} = find(sopsin_gt);
cond{2} = find(~sopsin_gt);
for c = 1:2
idx = cond{c};
idx_map = bin_2d(centroids(idx,:), 'binsize', 100);
colors = {flipud(othercolor('PRGn7')), flipud(othercolor('PRGn7')), othercolor('BrBG11')};
titles = ["Relative Surround Strength", "Center Size", "Vertical Surround Asymmetry"];
params{1} = scRatio(idx);
params{2} = centSize(idx);
params{3} = rfAsymm(idx);
figure;
if c == 1; sgtitle("Fig 3d-i"); else sgtitle("Extended Fig. 7"); end
for i = 1:3
% 2D Bins
subplot(2,3,i);
output = propertyMap(idx_map, params{i});
nz = output(output~=0);
mini = quantile(nz(:), .05); %remove extremes from dynamic range
maxi = quantile(nz(:), .95);
title(titles(i));
imAlpha = ones(size(output));
imAlpha(isnan(output)) = 0;
hold on;
if i~=3
imagesc(output, 'AlphaData', imAlpha, [mini, maxi]);
else
imagesc(output, 'AlphaData', imAlpha, [-1,1]);
end
xticks([]); yticks([]);
colorbar;
ax = imgca();
axis image; axis xy;
colormap(ax, colors{i});
mid = size(output,1)/2;
plot(mid,mid, '+');
% 1D Bins (per retina)
subplot(2,3,3+i);
pts = plot_trend_by_group(centroids(idx,:), params{i}, ret_number(idx));
ylabel(titles(i));
if i~=3; legend('hide'); end
dors = pts(:,1) < 0;
[~,pval] = kstest2(pts(dors,2), pts(~dors,2));
title(sprintf("Pvalue: %e", pval));
end
end
%% Fig. 3j (Example surround orientations from retina 9)
figure;
colors = [colorv;colorh;colord];
for i = 1:3
subplot(3,1,i);
orts = [gprops_all(idxs{i}).orientation_centers_of_mass_data_masks];
alpha = wrapTo180(sopsin_dorsal(9)-90);
orts = wrapToPi(-deg2rad(alpha) - orts);
histogram(orts, 20,'Normalization', 'probability', 'FaceColor', colors(i,:), 'EdgeAlpha', 0);
ylim([0 .5]);
hold on;
xlim([-pi pi]);
xticks(linspace(-pi,pi, 5));
xticklabels(["T", "D", "N", "V", "T"]);
end
sgtitle("Fig. 3j");
%% Fig. 3k (Surround asymmetry in sinusoidal projection of visual space)
alpha0 = deg2rad(22); %final coordinates of optical axis = resting position of mouse eye
theta0 = deg2rad(64);
cents = polar_to_visual(polar_coords, alpha0, theta0);
minlim = min(cents, [], 'all'); maxlim = max(cents, [], 'all');
lims = [minlim maxlim];
binsize = (maxlim - minlim)/40; %divide into 40 bins
idx_map = bin_2d(cents, 'binsize', binsize, 'lims', lims, 'mincount', 0);
map = propertyMap(idx_map, rfAsymm);
figure;
colormap(othercolor('BrBG11'));
imAlpha = ones(size(map));
imAlpha(isnan(map)) = 0;
image('CData', map, 'XData', lims, 'YData', lims,'CDataMapping','scaled', 'AlphaData', imAlpha);
caxis([-1 1]);
colorbar;
hold on;
plotGrid();
axis equal
% Also plot the rim of a retina
phiRim = zeros(1,100)'; %latitude = 0 defines the equator in retinal coords
lambdaRim = linspace(-pi,pi,100)'; % make a line passing through all longitudes
cent_rim = polar_to_visual([lambdaRim phiRim], alpha0, theta0);
x = cent_rim(:,1); y = cent_rim(:,2);
kink = find(abs(diff(x)) > 2);
x = circshift(x,-kink);
y = circshift(y, -kink);
plot(x,y, 'LineWidth', 2, 'Color', 'k');
title("Surround Asymmetry in Visual Coordinates");
xticks([-pi 0 pi]);
xticklabels({'-180', 'Front', '180'});
yticks([-pi/2 0 pi/2]);
yticklabels({'ground', 'horizon', 'sky'});
xlabel("Azimuth");
ylabel("Elevation");
%% Fig 4a
k = numel(unique(group_idx));
temps = temporal_all./max(abs(temporal_all), [], 2); %normalize
nCellsPerClust = zeros(k,1);
for i = 1:k
nCellsPerClust(i) = nnz(group_idx == i);
end
inds = zeros(length(group_idx), 1);
idxPic = zeros(length(group_idx), 1);
ccmap = jet(k);
cnt = 0;
for cluster_id = 1:k
cnt1 = cnt + sum(group_idx == cluster_id);
inds(cnt+1:cnt1) = find(group_idx == cluster_id);
idxPic(cnt+1:cnt1) = cluster_id;
cnt = cnt1;
end
figure;
ax_cluster = subplot(1, 12, 1);
imagesc(idxPic);
ylabel('Cluster ID');
xlabel('');
set(gca, 'YTickLabels', {''}, 'YTick', []);
colormap(ax_cluster, jet)
ax_data = subplot(1, 12, 2:12);
imagesc(temps(inds,:), [-1.5,1.5]);
colormap(flipud(othercolor('RdBu11')));
xticks([1 size(temps,2)]);
xticklabels({0 num2str(25*size(temps,2))});
title('Temporal RFs');
xlabel('Time (ms)');
sgtitle("Fig 4a");
figure;
for id = 1:k
subplot(5,2,id);
idx = group_idx == id;
traces = temps(idx,:);
avg = mean(traces, 1)';
stds = std(traces, 0, 1)';
hold on;
plot(avg-stds, 'Color', 'k', 'LineWidth', 1);
plot(avg+stds, 'Color', 'k', 'LineWidth', 1);
plot(avg, 'LineWidth', 2, 'Color', "k");
title(sprintf("cluster %d, n = %d", id,nnz(group_idx == id)));
ylim([-1.2 1.2]);
xlim([1, size(temps, 2)]);
xticks([1 size(temps,2)]);
xticklabels({0 num2str(25*size(temps,2))});
end
sgtitle("Fig 4a");
%% Fig 4c-e 1D Bins of properties, within each cluster
idx = find(sopsin_gt);
titles = ["Relative Surround Strength", "Center Size", "Vertical Surround Asymmetry"];
params{1} = scRatio(idx);
params{2} = centSize(idx);
params{3} = rfAsymm(idx);
figure;
for i = 1:3
subplot(1,3,i);
pts = plot_trend_by_group(centroids(idx,:), params{i}, group_idx(idx));
ylabel(titles(i));
if i~=3; legend('hide'); end
dors = pts(:,1) < 0;
[~,pval] = kstest2(pts(dors,2), pts(~dors,2));
title(sprintf("Pvalue: %e", pval));
end
%% Helper functions
function unsigned = flip_on_rfs(signed)
unsigned = signed;
mid = ceil(size(signed,1)/2);
onrfs = signed(mid,mid,:) > 0;
unsigned(:,:,onrfs) = -signed(:,:,onrfs);
end