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% checksync() - estimate quality of the data synchronization between
% eye-tracker and EEG by computing the crosscorrelation between the
% (horizontal) gaze position signal and the electro-oculogram (or other
% lateral frontal EEG channels that receive strong corneoretinal artifacts).
% Since both signals reflect the rotation of the eye ball, there should be
% virtually no time lag between both signals, that is, the cross
% correlation should peak at a lag of zero. This function computes the
% crosscorrelation between gaze and EOG, plots it, and stores the results
% in the field "EEG.misc.xcorr_EEG_ET" of the EEG structure.
%
% Usage:
% >> EEG = pop_checksync(EEG,eye_x,heog_l,heog_r,plotfig)
%
% Required inputs:
% EEG - [string] EEG struct, also containing synchronized eye
% tracking data (see pop_importeyetracker)
% gaze_x - [one channel index],
% specify channel index of the X-component (horizontal)
% gaze position signal of the eye tracker. If you recorded
% from both eyes (binocular), you can also enter a *vector*
% with two entries (x of left and right eye)
% heog_l - [channel index], index of EOG channel on LEFT side of
% the head/face. If no proper EOG electrode was placed
% near the eye (bad idea!), use a lateral EEG channel that
% is as close to the eye as possible
% heog_r - [channel index], index of EOG channel on RIGHT side of
% the head/face. If no proper EOG electrode was placed
% near the eye (bad idea!), use a lateral EEG channel that
% is as close to the eye as possible
% plotfig - show a plot with result of the crosscorrelation function
%
% Outputs:
% EEG - EEG structure with cross-correlation info added to the
% field EEG.misc.xcorr_EEG_ET
%
% See also: pop_checksync, pop_importeyetracker, synchronize
%
%
% An example call of the function might look like this:
% >> EEG = pop_checksync(EEG,65,1,2,1)
%
% In this example, the horizontal gaze position of the left eye from the
% eye tracker is stored in channel 65 of the synchronized EEG/ET dataset.
% The signal of the horizontal EOG electrodes, placed on the left and right
% canthus of each eye, is stored in channels 1 and 2, respectively.
% The last input indicates that EYE-EEG should plot a figure showing the
% cross-correlation function between the ET channels and the, in this case,
% bipolar-referenced (left minus right EOG electrode) EOG.
% If the synchronization is good, the time lag of the maximum (peak) of the
% cross-correlation should be near zero.
%
% IMPORTANT NOTE: To get clean results, you should first remove
% bad or missing data from the eye tracking channels, e.g. due to
% eye blinks, using method pop_rej_eyecontin(). Otherwise, the cross-corr.
% function will be distorted by this missing data. In some cases, it might
% also be necessary to remove intervals with very bad EOG recordings, but
% in our experience, some bad EOG data is not much of a problem.
%
% Note that this method was first applied in Dimigen et al., 2011, JEP:GEN.
% Please cite this paper when using this method. Thanks!
%
% Author: od
% Copyright (C) 2009-2017 Olaf Dimigen, HU Berlin
% olaf.dimigen@hu-berlin.de
% 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, write to the Free Software
% Foundation, 51 Franklin Street, Boston, MA 02110-1301, USA
function [EEG] = checksync(EEG, chan_gaze_x, chan_heog_l, chan_heog_r, plotfig)
fprintf('\n%s(): Computing cross correlation function between eye tracker and EOG channels...',mfilename);
fprintf('\n\nNote: it is usually necessary to first reject intervals with bad or missing ET data (e.g. blinks)');
fprintf('\nbefore computing the cross-correlation function with the EOG. Otherwise the results will be distorted.');
fprintf(sprintf('\nYou can do this by clicking: \"Reject data based on eye tracker\" > \"Reject bad contin. data\"'));
MAXLAG = 100; % compute cross-corr. up to max. lag of MAXLAG samples
%% warning if data were already epoched
if size(EEG.data,3)>1
warning(sprintf('This function was designed to run on continuous (not epoched) data.\nIt may produce unreliable results if the time series are too short!'))
end
%% get data for cross-correlation
gaze_x = mean(EEG.data(chan_gaze_x,:),1); % "mean", because user can also input several channels
if chan_heog_l == chan_heog_r
fprintf('\n\n%s(): Same channel number was provided for the left and right HEOG electrode!',mfilename);
fprintf('\nTherefore, it is assumed that either (1) the HEOG was already recorded in a bipolar montage as one channel (e.g., L vs. R)');
fprintf('\nor (2) that only one EOG electrode was placed near the eyes (e.g. only at left but not at right canthus).');
fprintf('\nCross-correlation function will therefore be based on this one EOG channel.');
heog = EEG.data(chan_heog_l,:);
else
fprintf('\n%s(): Computing one bipolar EOG channel from both EOG electrodes...',mfilename);
% subtract right minus left EOG channels to obtain *positive* correlations with hor. ET
heog = EEG.data(chan_heog_r,:)-EEG.data(chan_heog_l,:);
end
%% compute cross correlation
% based on entire recording (may include artifacts & loss of tracking!)
[xc,lags] = xcorr(gaze_x,heog,MAXLAG); % get cross-correlation
[maxvalue,ix] = max(abs(xc)); % find maximum xc
sampleDiff = lags(ix); % find lag with maximum xc
%% user feedback
if sampleDiff < 0
fprintf('\n\n-- Maximum cross-correlation is observed at lag of %i samples (= %.2f ms):',sampleDiff,sampleDiff*(1000/EEG.srate));
fprintf('\n-- The eye tracker signal leads the EOG signal');
elseif sampleDiff > 0
fprintf('\n\n-- Maximum cross-correlation is observed at lag of %i samples (= %.2f ms):',sampleDiff,sampleDiff*(1000/EEG.srate));
fprintf('\n-- The eye tracker signal lags behind the EOG signal');
else
fprintf('\n\n-- Maximum cross-correlation is observed at lag of %i samples (= %.2f ms):',sampleDiff,sampleDiff*(1000/EEG.srate));
fprintf('\n-- Gaze and EOG seem perfectly aligned');
end
%% also report correlation coefficient (r) of the two full time series (at lag 0)
r = corrcoef(gaze_x,heog);
fprintf('\n-- At a lag of zero, the Pearson correlation coefficient between both signals is r = %.2f',r(1,2));
%% write values to "EEG.etc" so they are stored with the dataset
fprintf('\n\nThe cross-correlation function is stored in the field \"EEG.etc.xcorr_eyeeeg\".');
EEG.etc.xcorr_eyeeeg = [xc; lags]; % first row: xc-values, second row: lags
%% show figure with cross-correlation function
if plotfig
fprintf('\n%s(): Plotting cross-correlation function... ',mfilename);
figure('Name','synccheck: ET/EOG cross-correlation');
%% plot cross-correlations between -MAXLAGS and +MAXLAGS
subplot(1,2,1); hold on;
title({'Cross-correlation Eye-tracker & EOG';'\fontsize{8}'});
plot(lags,xc,'k.-','markersize',4) % plot xc function
% highlight lag zero and lag with maximum absolute cross-correlation
ylimits = ylim;
%ylimits(2) = ylimits(2)+0.1*ylimits(2);
h1 = plot([0 0],[ylimits(1) ylimits(2)],'color',[0.6 0.6 0.6],'linewidth',2.0,'linestyle',':'); % lag zero
h2 = plot([lags(ix) lags(ix)],[ylimits(1) xc(ix)],'r','linewidth',1.2); % lag with max xc
% xlabel, also explain what pos./neg. lag means
l = legend([h1 h2],{'lag zero','max. absolute cross-corr.'},'Location','Best','box','on');
%xlabel({'\fontsize{10}Lag (in samples)',['\fontsize{8}ET leads EOG '
%char(8592) ' 0 ' char(8594) ' ET lags EOG']}); % arrows do not work in R2012
xlabel({'\fontsize{10}Lag (in samples)',['\fontsize{8}ET leads EOG <-- 0 --> ET lags EOG']});
ylabel('Cross-correlation value')
ylim(ylimits)
axis square, box on
%% zoom in: plot cross-correlation between lag -5 and 5 only
subplot(1,2,2); hold on;
%title(sprintf('Cross-correlation ET and EOG (zoom)'),'fontweight','bold')
title({'Cross-correlation Eye-tracker & EOG';'\fontsize{8}(zoom)'});
xlim([-5 5]);
plot(lags,xc,'k.-','markersize',6) % plot xc function
% highlight lag zero and lag with maximum absolute cross-correlation
ylimits = ylim;
h3 = plot([0 0], [ylimits(1) ylimits(2)],'color',[0.6 0.6 0.6],'linewidth',2.0,'linestyle',':'); % lag zero
h4 = plot([lags(ix) lags(ix)],[ylimits(1) xc(ix)],'r','linewidth',1.2); % lag with max xc
% legend
%xlabel({'\fontsize{10}Lag (in samples)',['\fontsize{8}ET leads EOG ' char(8592) ' 0 ' char(8594) ' ET lags EOG']});
xlabel({'\fontsize{10}Lag (in samples)',['\fontsize{8}ET leads EOG <-- 0 --> ET lags EOG']});
ylabel('Cross-correlation value')
ylim(ylimits)
axis square, box on
fprintf('Done.\n');
end