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iclabel.m
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iclabel.m
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function EEG = iclabel(EEG, version)
%ICLABEL Function for EEG IC labeling
% Label independent components using ICLabel. Go to
% https://sccn.ucsd.edu/wiki/ICLabel for a tutorial on this plug-in. Go
% to labeling.ucsd.edu/tutorial/about for more information. To report a
% bug or issue, please create an "Issue" post on the GitHub page at
% https://github.com/sccn/ICLabel/issues or send an email to
%
% Inputs:
% EEG: EEGLAB EEG structure. Must have an attached ICA decomposition.
% version (optional): Version of ICLabel to use. Default
% (recommended) version is used if passed 'default', '', or left
% empty. Pass 'lite' to use ICLabelLite or 'beta' to use the original
% beta version of ICLabel (only recommended for replicating old
% results).
%
% Results are stored in EEG.etc.ic_classifications.ICLabel. The matrix of
% label vectors is stored under "classifications" and the cell array of
% class names are stored under "classes". The version if ICLabel used is
% stored under The matrix stored under "version". "classifications" is
% organized with each column matching to the equivalent element in
% "classes" and each row matching to the equivalent IC. For example, if
% you want to see what percent ICLabel attributes IC 7 to the class
% "eye", you would look at:
% EEG.etc.ic_classifications.ICLabel.classifications(7, 3)
% since EEG.etc.ic_classifications.ICLabel.classes{3} is "eye".
% check inputs
if ~exist('version', 'var') || isempty(version)
version = 'default';
else
version = lower(version);
end
assert(any(strcmp(version, {'default', 'lite', 'beta'})), ...
['Invalid network version choice. ' ...
'Version must be one of the following: ' ...
'''default'', ''lite'', or ''beta''.'])
if any(strcmpi(version, {'', 'default'}))
flag_autocorr = true;
else
flag_autocorr = false;
end
% check for ica
assert(isfield(EEG, 'icawinv') && ~isempty(EEG.icawinv), ...
'You must have an ICA decomposition to use ICLabel')
if EEG.srate < 100
error('ICLabel requires a sampling frequency of at least 100 Hz')
end
% extract features
disp 'ICLabel: extracting features...'
features = ICL_feature_extractor(EEG, flag_autocorr);
% run ICL
disp 'ICLabel: calculating labels...'
labels = run_ICL(version, features{:});
% save into EEG
disp 'ICLabel: saving results...'
EEG.etc.ic_classification.ICLabel.classes = ...
{'Brain', 'Muscle', 'Eye', 'Heart', ...
'Line Noise', 'Channel Noise', 'Other'};
EEG.etc.ic_classification.ICLabel.classifications = labels;
EEG.etc.ic_classification.ICLabel.version = version;