% POP_REJCHAN - reject artifacts channels in an EEG dataset using joint
% probability of the recorded electrode.
%
% Usage:
% >> pop_rejchan( INEEG ) % pop-up interactive window mode
% >> [EEG, indelec, measure, com] = ...
% = pop_rejchan( INEEG, 'key', 'val');
%
% Inputs:
% INEEG - input dataset
%
% Optional inputs:
% 'elec' - [n1 n2 ...] electrode number(s) to take into
% consideration for rejection
% 'threshold' - [max] absolute threshold or activity probability
% limit(s) (in std. dev.) if norm is 'on'.
% 'measure' - ['prob'|'kurt'|'spec'] compute probability 'prob', kurtosis 'kurt'
% or spectrum 'spec' for each channel. Default is 'kurt'.
% 'norm' - ['on'|'off'] normalize measure above (using trimmed
% normalization as described in the function JOINTPROB
% and REJKURT. Default is 'off'.
% 'precomp' - [float array] use this array instead of computing the 'prob'
% or 'kurt' measures.
% 'freqrange' - [min max] frequency range for spectrum computation.
% Default is 1 to sampling rate divided by 2. The average
% of the log spectral power is computed over the frequency
% range of interest.
%
% Outputs:
% OUTEEG - output dataset with updated joint probability array
% indelec - indices of rejected electrodes
% measure - measure value for each electrode
% com - executed command
%
% Author: Arnaud Delorme, CERCO, UPS/CNRS, 2008-
%
% See also: JOINTPROB, REJKURT
% Copyright (C) 2008 Arnaud Delorme, CERCO, UPS/CNRS
%
% This file is part of EEGLAB, see http://www.eeglab.org
% for the documentation and details.
%
% Redistribution and use in source and binary forms, with or without
% modification, are permitted provided that the following conditions are met:
%
% 1. Redistributions of source code must retain the above copyright notice,
% this list of conditions and the following disclaimer.
%
% 2. Redistributions in binary form must reproduce the above copyright notice,
% this list of conditions and the following disclaimer in the documentation
% and/or other materials provided with the distribution.
%
% THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
% AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
% IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
% ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
% LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
% CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
% SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
% INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
% CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
% ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF
% THE POSSIBILITY OF SUCH DAMAGE.
function [EEG, indelec, measure, com] = pop_rejchan( EEG, varargin);
com = '';
indelec = [];
measure = [];
freq = [];
if nargin < 1
help pop_rejchan;
return;
end;
if nargin < 2
% which set to save
% -----------------
cb_select = [ 'if get(gcbo, ''value'') == 3,' ...
' set(findobj(gcbf, ''tag'', ''spec''), ''enable'', ''on'');' ...
'else,' ...
' set(findobj(gcbf, ''tag'', ''spec''), ''enable'', ''off'');' ...
'end;' ];
cb_norm = [ 'if get(gcbo, ''value''),' ...
' set(findobj(gcbf, ''tag'', ''normlab''), ''string'', ''Z-score threshold [max] or [min max]'');' ...
'else,' ...
' set(findobj(gcbf, ''tag'', ''normlab''), ''string'', ''Absolute threshold [max] or [min max]'');' ...
'end;' ];
uilist = { { 'style' 'text' 'string' 'Electrode (number(s); Ex: 2 4 5)' } ...
{ 'style' 'edit' 'string' ['1:' int2str(EEG.nbchan)] } ...
{ 'style' 'text' 'string' 'Measure to use' } ...
{ 'style' 'popupmenu' 'string' 'Probability|Kurtosis|Spectrum' 'value' 2 'callback' cb_select } ...
{ 'style' 'text' 'string' 'Normalize measure (check=on)' } ...
{ 'style' 'checkbox' 'string' '' 'value' 1 'callback' cb_norm } { } ...
{ 'style' 'text' 'string' 'Z-score threshold [max] or [min max]' 'tag' 'normlab' } ...
{ 'style' 'edit' 'string' '5' } ...
{ 'style' 'text' 'string' 'Spectrum freq. range' 'enable' 'off' 'tag' 'spec' } ...
{ 'style' 'edit' 'string' num2str([1 EEG.srate/2]) 'enable' 'off' 'tag' 'spec' } }; % 7/16/2014 Ramon
geom = { [2 1.3] [2 1.3] [2 0.4 0.9] [2 1.3] [2 1.3] };
result = inputgui( 'uilist', uilist, 'geometry', geom, 'title', 'Reject channel -- pop_rejchan()', ...
'helpcom', 'pophelp(''pop_rejchan'')');
if isempty(result), return; end
options = { 'elec' eval( [ '[' result{1} ']' ] ) 'threshold' str2num(result{4}) };
if result{3},
options = { options{:} 'norm', 'on' };
else options = { options{:} 'norm', 'off' };
end
if result{2} == 1
options = { options{:} 'measure', 'prob' };
elseif result{2} == 2
options = { options{:} 'measure', 'kurt' };
else
options = { options{:} 'measure', 'spec' };
options = { options{:} 'freqrange', str2num(result{5})};
end
else
options = varargin;
end
opt = finputcheck( options, { 'norm' 'string' { 'on';'off' } 'off';
'verbose' 'string' { 'on';'off' } 'on';
'indexonly' 'string' { 'on';'off' } 'off';
'measure' 'string' { 'prob';'kurt';'spec';'std' } 'kurt';
'precomp' 'real' [] [];
'freqrange' 'real' [] [1 EEG.srate/2];
'elec' 'integer' [] [1:EEG.nbchan];
'threshold' 'real' [] 400 }, 'pop_rejchan');
if ischar(opt), error(opt); end
if strcmpi(opt.verbose, 'on')
myfprintf(1);
else
myfprintf(0);
end
% compute the joint probability
% -----------------------------
if strcmpi(opt.norm, 'on')
normval = 2;
else
normval = 0;
end
if strcmpi(opt.measure, 'prob')
myfprintf('Computing probability for channels...\n');
[ measure, indelec ] = jointprob( reshape(EEG.data(opt.elec,:,:), length(opt.elec), size(EEG.data,2)*size(EEG.data,3)), opt.threshold, opt.precomp, normval);
elseif strcmpi(opt.measure, 'kurt')
myfprintf('Computing kurtosis for channels...\n');
[ measure, indelec ] = rejkurt( reshape(EEG.data(opt.elec,:,:), length(opt.elec), size(EEG.data,2)*size(EEG.data,3)), opt.threshold, opt.precomp, normval);
elseif strcmpi(opt.measure, 'std')
% norm is ignored
measure = std(EEG.data(:,:)');
if length(opt.threshold) > 1
indelec = measure < opt.threshold(1) | measure > opt.threshold(end);
else
indelec = measure > opt.threshold(1);
end
elseif strcmpi(opt.measure, 'spec')
myfprintf('Computing spectrum for channels...\n');
if ~isempty(opt.precomp)
measure = opt.precomp;
else
[measure, freq] = pop_spectopo(EEG, 1, [], 'EEG' , 'plot','off');
measure = measure(opt.elec,:); % selecting channels
% select frequency range
if ~isempty(opt.freqrange)
[~, fBeg] = min(abs(freq-opt.freqrange(1)));
[~, fEnd] = min(abs(freq-opt.freqrange(2)));
measure = measure(:, fBeg:fEnd);
end
end
% consider that data below 20 db has been filtered and remove it
indFiltered = find(mean(measure) < -20);
if ~isempty(indFiltered) && indFiltered(1) > 11,
measure = measure(:,1:indFiltered(1)-10);
myfprintf('Removing spectrum data below -20dB (most likely filtered out)\n');
end
meanSpec = mean(measure);
stdSpec = std( measure);
% for indChan = 1:size(measure,1)
% if any(measure(indChan,:) > meanSpec+stdSpec*opt.threshold), indelec(indChan) = 1; end
% end
if strcmpi(opt.norm, 'on')
measure1 = max(bsxfun(@rdivide, bsxfun(@minus, measure, meanSpec), stdSpec),[],2);
if length(opt.threshold) > 1
measure2 = min(bsxfun(@rdivide, bsxfun(@minus, measure, meanSpec), stdSpec),[],2);
indelec = measure2 < opt.threshold(1) | measure1 > opt.threshold(end);
myfprintf('Selecting minimum and maximum normalized power over the frequency range\n');
else
indelec = measure1 > opt.threshold(1);
myfprintf('Selecting maximum normalized power over the frequency range\n');
end
else
measure1 = max(measure,[],2);
if length(opt.threshold) > 1
measure2 = min(measure,[],2);
indelec = measure2 < opt.threshold(1) | measure1 > opt.threshold(end);
myfprintf('Selecting minimum and maximum power over the frequency range\n');
else
indelec = measure1 > opt.threshold(1);
myfprintf('Selecting maximum power over the frequency range\n');
end
end
measure = measure1;
end
colors = cell(1,length(opt.elec)); colors(:) = { 'k' };
colors(find(indelec)) = { 'r' }; colors = colors(end:-1:1);
myfprintf('%d electrodes labeled for rejection\n', length(find(indelec)));
% output variables
indelec = find(indelec)';
tmpchanlocs = EEG.chanlocs;
if ~isempty(EEG.chanlocs), tmplocs = EEG.chanlocs(opt.elec); tmpelec = { tmpchanlocs(opt.elec).labels }';
else tmplocs = []; tmpelec = mattocell([opt.elec]'); % tmpelec = mattocell([1:EEG.nbchan]');%Ramon on 8/7/2014
end
if exist('measure2', 'var')
myfprintf('#\tElec.\t[min]\t[max]\n');
tmpelec(:,3) = mattocell(measure2);
tmpelec(:,4) = mattocell(measure);
else
myfprintf('#\tElec.\tMeasure\n');
tmpelec(:,3) = mattocell(measure);
end
tmpelec(:,2) = tmpelec(:,1);
tmpelec(:,1) = mattocell([1:length(measure)]');
for index = 1:size(tmpelec,1)
if exist('measure2', 'var')
myfprintf('%d\t%s\t%3.2f\t%3.2f', tmpelec{index,1}, tmpelec{index,2}, tmpelec{index,3}, tmpelec{index,4});
elseif ~isempty(EEG.chanlocs)
myfprintf('%d\t%s\t%3.2f' , tmpelec{index,1}, tmpelec{index,2}, tmpelec{index,3});
else % Ramon on 8/7/2014
myfprintf('%d\t%d\t%3.2f' , tmpelec{index,1}, tmpelec{index,2}, tmpelec{index,3});
end
if any(indelec == index), myfprintf('\t*Bad*\n');
else myfprintf('\n');
end
end
if isempty(indelec), return; end
com = sprintf('EEG = pop_rejchan(EEG, %s);', vararg2str(options));
if nargin < 2
tmpcom = [ 'EEGTMP = pop_select(EEG, ''nochannel'', [' num2str(opt.elec(indelec)) ']);' ];
tmpcom = [ tmpcom ...
'LASTCOM = ' vararg2str(com) ';' ...
'[ALLEEG EEG CURRENTSET tmpcom] = pop_newset(ALLEEG, EEGTMP, CURRENTSET);' ...
' if ~isempty(tmpcom),' ...
' EEG = eegh(LASTCOM, EEG);' ...
' eegh(tmpcom);' ...
' eeglab(''redraw'');' ...
' end; clear EEGTMP tmpcom;' ];
eegplot(EEG.data(opt.elec,:,:), 'srate', EEG.srate, 'title', 'Scroll component activities -- eegplot()', ...
'limits', [EEG.xmin EEG.xmax]*1000, 'color', colors(end:-1:1), 'eloc_file', tmplocs, 'command', tmpcom);
else
if ~strcmpi(opt.indexonly, 'on')
EEG = pop_select(EEG, 'nochannel', opt.elec(indelec));
end
end
function myfprintf(varargin)
persistent verbose;
if isnumeric(varargin{1})
verbose = varargin{1};
return;
end
if verbose
fprintf(varargin{:});
end
return;
Datasets
Models
