% POP_LIMO - prepare and convert EEGLAB data and structure to be
% processed by LIMO.
%
% Usage:
% >> STUDY = pop_limo( STUDY, ALLEEG, 'key', val)
% >> STUDY = pop_limo( STUDY, ALLEEG, 'dat', 'key', val)
% >> STUDY = pop_limo( STUDY, ALLEEG, 'ica', 'key', val)
%
% Inputs:
% STUDY - an EEGLAB STUDY set of loaded EEG structures
% ALLEEG - ALLEEG vector of one or more loaded EEG dataset structures
% 'dat'|'ica' - show the interface for data channels or for ICA. The
% default is to use data.
%
% Optional inputs: same as STD_LIMO
%
% Graphical interface:
% "See GLM factors" - [push button] See all the GLM factors or columns in
% the design matrix. This list depends on your study
% design. Adding contrast will change this list. In
% practice, it is important to understand that every
% single factor will be fitted by the GLM, and the choice
% of these factors is critical. It is recommended to
% include as many factors as possible, especially because
% this allows you to define new contrast later on without
% having to recompute the GLM on each subject (as long as
% these new contrast do not involve new factors).
%
% "Interaction model for categorical indep. var." - When using more than
% one categorical variable, clicking this option forces
% to have factors which are the conjunction of the
% different independent var. values. This is useful only
% if you want to calculate interactions at the subject.
% The 'best' option is typically to have a design with
% all conditions (no factors) and create factors at the
% group level.
%
% "Split regressions (continuous indep. var.)" - This options allows to
% split continuous variables for the different
% categorical variables. This is useful to compute
% interaction between continuous and categorical
% variables.
%
% "Input data to use for the GLM" - [pop up menu] measure to use as input
% for the GLM. Currently, only "ERP" and "spectrum" are
% supported.
%
% "Optimization method" - [pop up menu] may be Ordinary Least Squares (OLS),
% Weighted Least Squares (WLS), or Iterative Reweighted Least
% Squares. WTS should be used as it is more robust to trials
% with different time course. OLS is a standard solution and
% WLS/IRLS are solution that automatically weight down outliers
% (trials/data point).
%
% "Options" - [edit box] additional options. These are given
% directly as input to the std_limo.m function. They may
% be ['freqlim', value] frequency trimming in Hz or
% ['timelim', value] time trimming in millisecond. These
% allow to speed up computation by not including all the
% data as input. Example: 'timelim', [-50 650] only
% include data within the -50 ms and 650 ms for ERPs.
%
% "Erase previous model" - [checkbox] erase previous model for this
% measure.
%
% Outputs:
% STUDY - an EEGLAB STUDY set of loaded EEG structures
%
% Author: Arnaud Delorme, SCCN, UCSD, 2015-
% Cyril Pernet, LIMO Team - edit info and defaults
%
% See also: STD_LIMO
% Copyright (C) Arnaud Delorme
%
% 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 [STUDY,com,limofiles] = pop_limo(STUDY, ALLEEG, measureflag, varargin)
if nargin < 2
help pop_limo;
return;
end
com = '';
if nargin > 2
if strcmpi(measureflag,'dat')
measureflagindx = 1;
elseif strcmpi(measureflag,'ica')
measureflagindx = 2;
else
varargin = { measureflag varargin{:} };
measureflagindx = 1;
end
else
measureflagindx = 1;
end
% check for empty relative paths
for iSet = 1:length(STUDY.datasetinfo)
if isempty(STUDY.datasetinfo(iSet).filepath)
STUDY.datasetinfo(iSet).filepath = STUDY.filepath;
ALLEEG(iSet).filepath = STUDY.filepath;
end
end
% check that channel location are present
ALLEEG = eeg_checkset(ALLEEG, 'chanloc');
if isfield(STUDY, 'group') && length(STUDY.group) > 1
warndlg2([ 'Your STUDY have groups of subjects. This will only be relevant' 10 ...
'for 2nd-level LIMO analysis and will be ignored at the 1st' 10 ...
'(single subject) level.'] );
end
if nargin < 4
dataMeasures = { 'ERP' 'Spectrum' 'ERSP'};
fileMeasures = { 'daterp' 'datspec' 'dattimef'; 'icaerp' 'icaspec' 'icatimef'};
methods = { 'WLS' 'OLS' 'IRLS'};
cb_measure = [ 'if get(gcbo, ''value'') == 1,' ...
' set(findobj(gcbf, ''tag'', ''options''), ''string'', '''');' ...
'else,' ...
' set(findobj(gcbf, ''tag'', ''options''), ''string'', ''''''freqlim'''', [1 25]'');' ...
'end;' ];
cb_listfactors = [ 'pop_listfactors(STUDY.design(STUDY.currentdesign), ''gui'', ''on'', ' ...
'''level'', ''both'',' ...
'''splitreg'' , fastif(get(findobj(gcbf, ''tag'', ''splitreg'' ), ''value''), ''on'', ''off''),' ...
'''interaction'', fastif(get(findobj(gcbf, ''tag'', ''interaction''), ''value''), ''on'', ''off''));' ];
uilist = { ...
{'style' 'text' 'string' 'LInear MOdeling of EEG data' 'fontweight' 'bold' 'fontsize', 12} ...
{'style' 'pushbutton' 'string' 'See GLM variables' 'callback' cb_listfactors } ...
{'style' 'checkbox' 'string' 'Split regressions (continuous indep. var.)' 'tag' 'splitreg' } {} ...
{'style' 'text' 'string' 'Input data to use for the GLM' } ...
{'style' 'popupmenu' 'string' dataMeasures 'tag' 'measure' 'callback' cb_measure} ...
{'style' 'text' 'string' 'Estimation method' } ...
{'style' 'popupmenu' 'string' methods 'tag' 'method' } ...
{'style' 'text' 'string' 'Options' } ...
{'style' 'edit' 'string' '' 'tag' 'options' } ...
{'style' 'checkbox' 'string' 'Erase previous model' 'tag' 'erase' 'value' true } ...
};
cline = [1.1 0.8];
geometry = { [1.6 1] 1 1 cline cline cline 1 };
geomvert = [ 1 1 1 1 1 1 1 ];
[out_param userdat tmp res] = inputgui( 'geometry' , geometry, 'uilist', uilist, 'geomvert', geomvert, ...
'title', 'LInear MOdeling of EEG data -- pop_limo()', 'helpcom', 'pophelp(''pop_limo'');');
if isempty(res), return; end
opttmp = eval( [ '{ ' res.options ' }' ]);
if length(opttmp) > 0 && isnumeric(opttmp{1})
error([ 'Wrong options. Options must be in the format' 10 '''key'', val. For example ''timelim'', [-100 600]' ]);
end
options = { 'method' methods{res.method} 'measure' fileMeasures{measureflagindx,res.measure} opttmp{:} ...
'erase' fastif(res.erase, 'on', 'off') ...
'splitreg' fastif(res.splitreg, 'on', 'off') };
else
options = varargin;
end
[STUDY,limofiles] = std_limo(STUDY, ALLEEG, options{:});
com = sprintf('pop_limo(STUDY, ALLEEG, %s);', vararg2str(options));
Datasets
Models
