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fig1_simCCEPComponents.m
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fig1_simCCEPComponents.m
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%% Figure 1. Create simulated CCEP data and their components
%
% 2023/09/27
%
% If this code is used in a publication, please cite the manuscript:
% "CARLA: Adjusted common average referencing for cortico-cortical evoked potential data"
% by H Huang, G Ojeda Valencia, NM Gregg, GM Osman, MN Montoya,
% GA Worrell, KJ Miller, and D Hermes.
%
% CARLA manuscript package.
% Copyright (C) 2023 Harvey Huang
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your option) any later version.
%
% This program is distributed in the hope that it will be useful,
% but WITHOUT ANY WARRANTY; without even the implied warranty of
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
% GNU General Public License for more details.
%
% You should have received a copy of the GNU General Public License
% along with this program. If not, see <https://www.gnu.org/licenses/>.
%
srate = 4800;
tt = -0.5:1/srate:1-1/srate;
nchs = 10; % number of simulated channels
ntrs = 12; % number of trials
chs = arrayfun(@(x) sprintf('ch%d', x), 1:nchs, 'UniformOutput', false)';
outdir = fullfile('output', 'simComponents');
mkdir(outdir)
%% i) Create data, add stim artifacts
% stores the data
V0 = zeros(length(tt), nchs);
Aart = 50 + rand(nchs, 1)*6; % slightly different artifact amplitudes for each channel
artifact = sin(2*pi*600*tt)';
artifact(tt < 0 | tt > 0.002) = 0;
V0 = V0 + artifact*Aart';
figure('Position', [200, 200, 400, 800]); ieeg_plotTrials(tt, V0, 100);
xlabel('Time (s)'); ylabel('Channels');
%% A) Add unique input signals at a subset of channels
rng(14);
chsResp = 1:4;
A = 100;
% using previous version of signal generator for this illustration to preserve backwards compatibility
sig = genRandSigOrig(tt, length(chsResp), A);
V1 = V0;
V1(:, chsResp) = V0(:, chsResp) + sig;
figure('Position', [200, 200, 400, 800]); ieeg_plotTrials(tt, V1, 100, [], [], 'LineWidth', 1.5);
xlabel('Time (s)'); ylabel('Channels');
%% B) Add a global signal across all chs and trials when present. Here amplitude Aglobal = 0, so no global signal added
rng(10);
Aglobal = 0;
sigGlob = genRandSigOrig(tt, 1, Aglobal);
V2 = V1 + sigGlob;
figure('Position', [200, 200, 400, 800]); ieeg_plotTrials(tt, V2, 100, [], [], 'LineWidth', 1.5);
xlabel('Time (s)'); ylabel('Channels');
%% C) Add noise common to all channels (line noise and some brown noise from reference)
rng('default');
% add trials, so now put V in ch x time x trial format
V3 = repmat(V2', 1, 1, ntrs);
% random line noise phases for each trial, trials x harmonic (60, 120, 180)
phLN = rand(ntrs, 3)*2*pi;
LN = zeros(length(tt), ntrs);
for ii = 1:ntrs
LN(:, ii) = 8*sin(2*pi*60*tt - phLN(ii, 1)) + 2*sin(2*pi*120*tt - phLN(ii, 2)) + 1*sin(2*pi*180*tt - phLN(ii, 3));
end
% brown noise shared across channels (from ref electrode
BN = cumsum(0.4*randn(2*length(tt), ntrs));
BN = ieeg_highpass(BN, srate, true);
BN = BN((0.5*length(tt)+1) : 1.5*length(tt), :);
noiseCommon = LN + BN;
V3 = V3 + shiftdim(noiseCommon, -1);
figure('Position', [200, 200, 600, 400]);
subplot(1, 2, 1); ieeg_plotTrials(tt, V3(:, :, 1)', 100, [], [], 'LineWidth', 1.5);
title('V at one trial');
xlabel('Time (s)'); ylabel('Channels');
subplot(1, 2, 2); ieeg_plotTrials(tt, mean(V3, 3)', 100, [], [], 'LineWidth', 1.5);
title('V across trials');
xlabel('Time (s)'); ylabel('Channels');
%% D) add random brown noise across all channels
rng('default');
noiseRand = cumsum(0.4*randn(nchs, 2*length(tt), ntrs), 2); % give double the number of time points so we can highpass it
for ii = 1:nchs
noiseRand(ii, :, :) = ieeg_highpass(squeeze(noiseRand(ii, :, :)), srate, true);
end
noiseRand = noiseRand(:, (0.5*length(tt)+1) : 1.5*length(tt), :);
V4 = V3 + noiseRand;
figure('Position', [200, 200, 600, 400]);
subplot(1, 2, 1); ieeg_plotTrials(tt, V4(:, :, 1)', 100, [], [], 'LineWidth', 1.5);
title('V at one trial');
xlabel('Time (s)'); ylabel('Channels');
subplot(1, 2, 2); ieeg_plotTrials(tt, mean(V4, 3)', 100, [], [], 'LineWidth', 1.5);
title('V across trials');
xlabel('Time (s)'); ylabel('Channels');
saveas(gcf, fullfile(outdir, 'V4'), 'svg');
saveas(gcf, fullfile(outdir, 'V4'), 'png');
%% Save construction components for channels of interest
% Plot select channels for figure (3 and 8)
chs2Plot = [3, 8];
for ii = 1:length(chs2Plot)
ch = chs2Plot(ii);
ylims = [-120, 120];
% plot full simulation of all trials at data
figure('Position', [200, 200, 600, 300]); hold on
plot(tt, squeeze(V4(ch, :, :)), 'Color', [0.5, 0.5, 0.5]);
plot(tt, mean(squeeze(V4(ch, :, :)), 2), 'k', 'LineWidth', 1.5);
hold off
ylim(ylims);
xlabel('Time (s)'); ylabel('Voltage (\muV)');
saveas(gcf, fullfile(outdir, sprintf('V4_ch%d', ch)), 'png');
saveas(gcf, fullfile(outdir, sprintf('V4_ch%d', ch)), 'svg');
% plot the true signal
figure('Position', [200, 200, 200, 300]);
plot(tt, V1(:, ch), 'k', 'LineWidth', 2);
ylim(ylims); xlim([0, 0.5]);
xlabel('Time (s)'); ylabel('Voltage (\muV)');
saveas(gcf, fullfile(outdir, sprintf('V1_ch%d', ch)), 'png');
saveas(gcf, fullfile(outdir, sprintf('V1_ch%d', ch)), 'svg');
% plot examples of the common noise
figure('Position', [200, 200, 200, 300]);
ieeg_plotTrials(tt, noiseCommon(:, 1:3), 50, [], [0.5, 0.5, 0.5]); % plot at one trial
xlim([0, 0.5]);
xlabel('Time (s)'); ylabel('Voltage (\muV)');
saveas(gcf, fullfile(outdir, 'lineNoise_3trs'), 'png');
saveas(gcf, fullfile(outdir, 'lineNoise_3trs'), 'svg');
% plot the random noise
figure('Position', [200, 200, 200, 300]); hold on
plot(tt, squeeze(noiseRand(ch, :, :)), 'Color', [0.5, 0.5, 0.5]);
hold off
xlim([0, 0.5]); ylim(ylims);
xlabel('Time (s)'); ylabel('Voltage (\muV)');
saveas(gcf, fullfile(outdir, sprintf('randNoise_ch%d', ch)), 'png');
saveas(gcf, fullfile(outdir, sprintf('randNoise_ch%d', ch)), 'svg');
end