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Supplementary_4_brain_networks.m
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Supplementary_4_brain_networks.m
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% Copyright (c) 2024 Mohammad Al-Sa'd
%
% Permission is hereby granted, free of charge, to any person obtaining a
% copy of this software and associated documentation files (the "Software"),
% to deal in the Software without restriction, including without limitation
% the rights to use, copy, modify, merge, publish, distribute, sublicense,
% and/or sell copies of the Software, and to permit persons to whom the
% Software is furnished to do so, subject to the following conditions:
%
% The above copyright notice and this permission notice shall be included
% in all copies or substantial portions of the Software.
%
% THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS
% OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
% FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
% THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
% LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
% FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
% DEALINGS IN THE SOFTWARE.
%
% Email: mohammad.al-sad@helsinki.fi, alsad.mohamed@gmail.com
%
% The following reference should be cited whenever this script is used:
% Al‐Sa'd, M., Vanhatalo, S. and Tokariev, A., 2024. Multiplex dynamic
% networks in the newborn brain disclose latent links with neurobehavioral
% phenotypes. Human Brain Mapping, 45(2), https://doi.org/10.1002/hbm.26610
%
% Last Modification: 12-February-2024
%
% Description:
% This script generates Figs. 4-7 in the supplementary material.
%% Initialization
clear; close all; clc;
addpath(genpath('Functions'));
%% Parameters
corr_dir = '+'; % Correlation direction +/-
fdr_thr = 0.025; % 5% false discovery rate +/- threshold
%% Load all requirements
load('Head Model\FidelityOperator.mat');
load('Head Model\Atlas.mat');
load('Head Model\surfaces\cortex_smoothed.mat');
load('Head Model\MyAtlas_n58.mat');
mask = logical(FidelityOperator);
mask = unfold_upper_matrix(mask);
%% Load results
X_hc = []; D_hc = []; X_ad = []; D_ad = [];
for subset = 1:2
if(strcmp(corr_dir,'+'))
load(['Results\HC\Selection\subset_' num2str(subset) '_selected'],'x_pos','K_pos');
X_hc = cat(2,X_hc,x_pos); D_hc = cat(2,D_hc,K_pos);
load(['Results\AED\Selection\subset_' num2str(subset) '_selected'],'x_pos','K_pos');
X_ad = cat(2,X_ad,x_pos); D_ad = cat(2,D_ad,K_pos);
else
load(['Results\HC\Selection\subset_' num2str(subset) '_selected'],'x_neg','K_neg');
X_hc = cat(2,X_hc,x_neg); D_hc = cat(2,D_hc,K_neg);
load(['Results\AED\Selection\subset_' num2str(subset) '_selected'],'x_neg','K_neg');
X_ad = cat(2,X_ad,x_neg); D_ad = cat(2,D_ad,K_neg);
end
end
%% Get brain network
mask_hc = cell(1,length(X_hc));
mask_ad = cell(1,length(X_hc));
for i = 1:length(X_hc)
mask_hc{i} = abs(D_hc{i}) >= fdr_thr;
mask_ad{i} = abs(D_ad{i}) >= fdr_thr;
XX = squeeze(mean(X_hc{i},2,'omitnan')); % average the subjects connections
XX = (XX - min(XX(:)))./(max(XX(:))-min(XX(:))); % Standardize to be from 0 to 1
XX(isnan(XX)) = 0; % remove connections with insignificant correlations
X_hc{i} = XX.^2; % Improve visualization by squaring
XX = squeeze(mean(X_ad{i},2,'omitnan')); % average the subjects connections
XX = (XX - min(XX(:)))./(max(XX(:))-min(XX(:))); % Standardize to be from 0 to 1
XX(isnan(XX)) = 0; % remove connections with insignificant correlations
X_ad{i} = XX.^2; % Improve visualization by squaring
end
%% Plotting
ccc = [0 0.447 0.741; 0.85 0.325 0.098; 0.466 0.674 0.188; 0.494 0.184 0.556; 0.929 0.694 0.125];
N = 101; dx = 1.05; t = linspace(0, 1, N);
Band_str = {'low-$\delta$','high-$\delta$','$\theta$','$\alpha$','$\beta$'};
Score_str{1} = 'Neurological Score (C1)';
Score_str{2} = 'Neurological Score (C2)';
Score_str{3} = 'Cognition';
Score_str{4} = 'Language Comprehension';
Score_str{5} = 'Language Production';
Score_str{6} = 'Fine Motor Skills';
Score_str{7} = 'Gross Motor Skills';
for n = 1:length(X_hc)
figure('Color',[1,1,1],'Position',[20 100 1400 500]); hold on;
for f = 1:size(X_hc{n},1)
if(mask_hc{n}(f))
[~, y] = fold_connectivity(X_hc{n}(f,:), mask, 0);
for i = 1:length(MyAtlas.Parcels)
for j = i+1:length(MyAtlas.Parcels)
if y(i, j) ~= 0 % skip zeros (no connections)
pts = kron((1-t).^2, MyAtlas.Circular_xy(i, :)') + ...
kron(2*(1-t).^t, [0; 0]) + kron(t.^2, MyAtlas.Circular_xy(j, :)');
plot3(pts(1,:)+(f-1)*dx, pts(2,:)+1.1, repelem(0,1,N), ...
'Color', [ccc(f,:) y(i,j)], 'Linewidth', 1);
end
end
end
% Nodes
scatter3(MyAtlas.Circular_xy(cell2mat(MyAtlas.Areas) == 'O', 1)+(f-1)*dx, ...
MyAtlas.Circular_xy(cell2mat(MyAtlas.Areas) == 'O', 2)+1.075, 0, 40, ...
'MarkerFaceColor', [0.00 0.00 0.00], 'MarkerEdgeColor', 'none');
scatter3(MyAtlas.Circular_xy(cell2mat(MyAtlas.Areas) == 'C', 1)+(f-1)*dx, ...
MyAtlas.Circular_xy(cell2mat(MyAtlas.Areas) == 'C', 2)+1.075, 0, 40, ...
'MarkerFaceColor', [1.00 0.00 1.00], 'MarkerEdgeColor', 'none');
scatter3(MyAtlas.Circular_xy(cell2mat(MyAtlas.Areas) == 'F', 1)+(f-1)*dx, ...
MyAtlas.Circular_xy(cell2mat(MyAtlas.Areas) == 'F', 2)+1.075, 0, 40, ...
'MarkerFaceColor', [0.93 0.69 0.13], 'MarkerEdgeColor', 'none');
scatter3(MyAtlas.Circular_xy(cell2mat(MyAtlas.Areas) == 'T', 1)+(f-1)*dx, ...
MyAtlas.Circular_xy(cell2mat(MyAtlas.Areas) == 'T', 2)+1.075, 0, 40, ...
'MarkerFaceColor', [0.20 0.60 0.00], 'MarkerEdgeColor', 'none');
else
annotation(gcf,'textbox',...
[0.12+(0.156)*(f-1) 0.525 0.45*(2/5) 0.425],...
'VerticalAlignment','middle',...
'String','n.s.',...
'Interpreter','latex',...
'HorizontalAlignment','center',...
'FontSize',40,...
'FitBoxToText','off',...
'EdgeColor','none');
% Nodes
scatter3(MyAtlas.Circular_xy(cell2mat(MyAtlas.Areas) == 'O', 1)+(f-1)*dx, ...
MyAtlas.Circular_xy(cell2mat(MyAtlas.Areas) == 'O', 2)+1.075, 0, 40, ...
'MarkerFaceColor', [0.75 0.75 0.75], 'MarkerEdgeColor', 'none');
scatter3(MyAtlas.Circular_xy(cell2mat(MyAtlas.Areas) == 'C', 1)+(f-1)*dx, ...
MyAtlas.Circular_xy(cell2mat(MyAtlas.Areas) == 'C', 2)+1.075, 0, 40, ...
'MarkerFaceColor', [0.75 0.75 0.75], 'MarkerEdgeColor', 'none');
scatter3(MyAtlas.Circular_xy(cell2mat(MyAtlas.Areas) == 'F', 1)+(f-1)*dx, ...
MyAtlas.Circular_xy(cell2mat(MyAtlas.Areas) == 'F', 2)+1.075, 0, 40, ...
'MarkerFaceColor', [0.75 0.75 0.75], 'MarkerEdgeColor', 'none');
scatter3(MyAtlas.Circular_xy(cell2mat(MyAtlas.Areas) == 'T', 1)+(f-1)*dx, ...
MyAtlas.Circular_xy(cell2mat(MyAtlas.Areas) == 'T', 2)+1.075, 0, 40, ...
'MarkerFaceColor', [0.75 0.75 0.75], 'MarkerEdgeColor', 'none');
end
if(mask_ad{n}(f))
[~, y] = fold_connectivity(X_ad{n}(f,:), mask, 0);
for i = 1:length(MyAtlas.Parcels)
for j = i+1:length(MyAtlas.Parcels)
if y(i, j) ~= 0 % skip zeros (no connections)
pts = kron((1-t).^2, MyAtlas.Circular_xy(i, :)') + ...
kron(2*(1-t).^t, [0; 0]) + kron(t.^2, MyAtlas.Circular_xy(j, :)');
plot3(pts(1,:)+(f-1)*dx, pts(2,:), repelem(0,1,N), ...
'Color', [ccc(f,:) y(i,j)], 'Linewidth', 1);
end
end
end
% Nodes
scatter3(MyAtlas.Circular_xy(cell2mat(MyAtlas.Areas) == 'O', 1)+(f-1)*dx, ...
MyAtlas.Circular_xy(cell2mat(MyAtlas.Areas) == 'O', 2), 0, 40, ...
'MarkerFaceColor', [0.00 0.00 0.00], 'MarkerEdgeColor', 'none');
scatter3(MyAtlas.Circular_xy(cell2mat(MyAtlas.Areas) == 'C', 1)+(f-1)*dx, ...
MyAtlas.Circular_xy(cell2mat(MyAtlas.Areas) == 'C', 2), 0, 40, ...
'MarkerFaceColor', [1.00 0.00 1.00], 'MarkerEdgeColor', 'none');
scatter3(MyAtlas.Circular_xy(cell2mat(MyAtlas.Areas) == 'F', 1)+(f-1)*dx, ...
MyAtlas.Circular_xy(cell2mat(MyAtlas.Areas) == 'F', 2), 0, 40, ...
'MarkerFaceColor', [0.93 0.69 0.13], 'MarkerEdgeColor', 'none');
scatter3(MyAtlas.Circular_xy(cell2mat(MyAtlas.Areas) == 'T', 1)+(f-1)*dx, ...
MyAtlas.Circular_xy(cell2mat(MyAtlas.Areas) == 'T', 2), 0, 40, ...
'MarkerFaceColor', [0.20 0.60 0.00], 'MarkerEdgeColor', 'none');
else
annotation(gcf,'textbox',...
[0.12+(0.156)*(f-1) 0.1 0.45*(2/5) 0.425],...
'VerticalAlignment','middle',...
'String','n.s.',...
'Interpreter','latex',...
'HorizontalAlignment','center',...
'FontSize',40,...
'FitBoxToText','off',...
'EdgeColor','none');
% Nodes
scatter3(MyAtlas.Circular_xy(cell2mat(MyAtlas.Areas) == 'O', 1)+(f-1)*dx, ...
MyAtlas.Circular_xy(cell2mat(MyAtlas.Areas) == 'O', 2), 0, 40, ...
'MarkerFaceColor', [0.75 0.75 0.75], 'MarkerEdgeColor', 'none');
scatter3(MyAtlas.Circular_xy(cell2mat(MyAtlas.Areas) == 'C', 1)+(f-1)*dx, ...
MyAtlas.Circular_xy(cell2mat(MyAtlas.Areas) == 'C', 2), 0, 40, ...
'MarkerFaceColor', [0.75 0.75 0.75], 'MarkerEdgeColor', 'none');
scatter3(MyAtlas.Circular_xy(cell2mat(MyAtlas.Areas) == 'F', 1)+(f-1)*dx, ...
MyAtlas.Circular_xy(cell2mat(MyAtlas.Areas) == 'F', 2), 0, 40, ...
'MarkerFaceColor', [0.75 0.75 0.75], 'MarkerEdgeColor', 'none');
scatter3(MyAtlas.Circular_xy(cell2mat(MyAtlas.Areas) == 'T', 1)+(f-1)*dx, ...
MyAtlas.Circular_xy(cell2mat(MyAtlas.Areas) == 'T', 2), 0, 40, ...
'MarkerFaceColor', [0.75 0.75 0.75], 'MarkerEdgeColor', 'none');
end
if(n == 1 || n == 3)
annotation(gcf,'textbox',[0.12+(0.156)*(f-1) 0.75 0.45*(2/5) 0.425],'VerticalAlignment', ...
'middle','String',Band_str{f},'Interpreter','latex','HorizontalAlignment', ...
'center','FontSize',24,'FitBoxToText','off','EdgeColor','none');
elseif(n == 2 || n == 7)
annotation(gcf,'textbox',[0.12+(0.156)*(f-1) 0 0.45*(2/5) 0.1],'VerticalAlignment', ...
'middle','String',Band_str{f},'Interpreter','latex','HorizontalAlignment', ...
'center','FontSize',24,'FitBoxToText','off','EdgeColor','none');
end
end
annotation(gcf,'textbox',[0.1 0.155 0.25 0.2],'VerticalAlignment', ...
'middle','String',Score_str{n},'Interpreter','latex','HorizontalAlignment', ...
'center','FontSize',38,'FitBoxToText','off','EdgeColor','none','rotation',90);
annotation(gcf,'textbox',[0.77 0.625 0.35 0.2],'VerticalAlignment', ...
'middle','String','HC','Interpreter','latex','HorizontalAlignment', ...
'center','FontSize',24,'FitBoxToText','off','EdgeColor','none');
annotation(gcf,'textbox',[0.77 0.2 0.35 0.2],'VerticalAlignment', ...
'middle','String','AED','Interpreter','latex','HorizontalAlignment', ...
'center','FontSize',24,'FitBoxToText','off','EdgeColor','none');
xlim([-0.5 0.5+(size(X_hc{1},1)-1)*dx]); ylim([-0.5 1.6]); axis off;
set(gcf,'Units','inches'); screenposition = get(gcf,'Position');
set(gcf,'PaperPosition',[0 0 screenposition(3:4)],'PaperSize',screenposition(3:4));
end
%% Saving
opt = input('Do you want to save results (Y/N)\n','s');
if(opt == 'y' || opt == 'Y')
for n = 1:length(X_hc)
if(strcmp(corr_dir,'+'))
if(n <= 2)
print(n,['Results\Figures\Supp_Fig_4_brain_network_' num2str(n)],'-dpdf','-r400');
else
print(n,['Results\Figures\Supp_Fig_6_brain_network_' num2str(n-2)],'-dpdf','-r400');
end
else
if(n <= 2)
print(n,['Results\Figures\Supp_Fig_5_brain_network_' num2str(n)],'-dpdf','-r400');
else
print(n,['Results\Figures\Supp_Fig_7_brain_network_' num2str(n-2)],'-dpdf','-r400');
end
end
end
end