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ft_artifact_tms.m
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function [cfg, artifact] = ft_artifact_tms(cfg, data)
% FT_ARTIFACT_TMS reads the data segments of interest from file and identifies artefacts in
% EEG recordings that were done during TMS stimulation.
%
% Use as
% [cfg, artifact] = ft_artifact_tms(cfg)
% with the configuration options
% cfg.dataset = string with the filename
% or
% cfg.headerfile = string with the filename
% cfg.datafile = string with the filename
% and optionally
% cfg.headerformat
% cfg.dataformat
%
% Alternatively you can use it as
% [cfg, artifact] = ft_artifact_tms(cfg, data)
% where the input data is a structure as obtained from FT_PREPROCESSING.
%
% In both cases the configuration should also contain
% cfg.trl = structure that defines the data segments of interest. See FT_DEFINETRIAL
% cfg.continuous = 'yes' or 'no' whether the file contains continuous data (default = 'yes')
% and
% cfg.method = 'detect' or 'marker', see below.
% markers written in the EEG.
% cfg.prestim = scalar, time in seconds prior to onset of detected
% event to mark as artifactual (default = 0.005 seconds)
% cfg.poststim = scalar, time in seconds post onset of detected even to
% mark as artifactual (default = 0.010 seconds)
%
% METHOD SPECIFIC OPTIONS AND DESCRIPTIONS
%
% With cfg.method='detect', TMS-artifacts are detected by preprocessing the data to be
% sensitive to transient high gradients, typical for TMS-pulses. The data is preprocessed
% (again) with the following configuration parameters, which are optimal for identifying tms
% artifacts. This acts as a wrapper around ft_artifact_zvalue
% cfg.artfctdef.tms.derivative = 'yes'
% Artifacts are identified by means of thresholding the z-transformed value
% of the preprocessed data.
% cfg.artfctdef.tms.channel = Nx1 cell-array with selection of channels, see FT_CHANNELSELECTION for details
% cfg.artfctdef.tms.cutoff = z-value at which to threshold (default = 4)
% cfg.artfctdef.tms.trlpadding = 0.1
% cfg.artfctdef.tms.fltpadding = 0.1
% cfg.artfctdef.tms.artpadding = 0.01
% Be aware that if one artifact falls within this specified range of another artifact, both
% artifact will be counted as one. Depending on cfg.prestim and cfg.poststim you may not mark
% enough data as artifactual.)
%
% With cfg.method='marker', TMS-artifact onset and offsets are based on markers/triggers that
% are written into the EEG dataset. This method acts as a wrapper around FT_DEFINETRIAL to
% determine on- and offsets of TMS pulses by reading markers in the EEG.
% cfg.trialfun = function name, see below (default = 'ft_trialfun_general')
% cfg.trialdef.eventtype = 'string'
% cfg.trialdef.eventvalue = number, string or list with numbers or strings
% The cfg.trialfun option is a string containing the name of a function that you wrote
% yourself and that FT_ARTIFACT_TMS will call. The function should take the cfg-structure as
% input and should give a NxM matrix with M equal to or larger than 3) in the same format as
% "trl" as the output. You can add extra custom fields to the configuration structure to
% pass as arguments to your own trialfun. Furthermore, inside the trialfun you can use the
% FT_READ_EVENT function to get the event information from your data file.
%
% The output argument "artifact" is a Nx2 matrix comparable to the
% "trl" matrix of FT_DEFINETRIAL. The first column of which specifying the
% beginsamples of an artifact period, the second column contains the
% endsamples of the artifactperiods.
%
% To facilitate data-handling and distributed computing with the peer-to-peer
% module, this function has the following option:
% cfg.inputfile = ...
% If you specify this option the input data will be read from a *.mat
% file on disk. This mat files should contain only a single variable named 'data',
% corresponding to the input structure.
%
% See also FT_REJECTARTIFACT, FT_ARTIFACT_CLIP, FT_ARTIFACT_ECG, FT_ARTIFACT_EOG,
% FT_ARTIFACT_JUMP, FT_ARTIFACT_MUSCLE, FT_ARTIFACT_THRESHOLD, FT_ARTIFACT_ZVALUE
% Copyright (C) 2003-2011, Jan-Mathijs Schoffelen & Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.fieldtriptoolbox.org
% for the documentation and details.
%
% FieldTrip 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.
%
% FieldTrip 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 FieldTrip. If not, see <http://www.gnu.org/licenses/>.
%
% $Id$
% these are used by the ft_preamble/ft_postamble function and scripts
ft_revision = '$Id$';
ft_nargin = nargin;
ft_nargout = nargout;
% do the general setup of the function
ft_defaults
ft_preamble init
% ft_preamble provenance is not needed because just a call to ft_artifact_zvalue
% ft_preamble loadvar data is not needed because ft_artifact_zvalue will do this
% check if the input cfg is valid for this function
cfg = ft_checkconfig(cfg, 'renamed', {'datatype', 'continuous'});
cfg = ft_checkconfig(cfg, 'renamedval', {'continuous', 'continuous', 'yes'});
cfg = ft_checkconfig(cfg, 'required', 'method');
cfg = ft_checkconfig(cfg, 'allowedval', {'method', 'detect', 'marker'});
% set default rejection parameters
if ~isfield(cfg, 'artfctdef'), cfg.artfctdef = []; end
if ~isfield(cfg, 'method'), cfg.method = 'detect'; end
if ~isfield(cfg.artfctdef, 'tms'), cfg.artfctdef.tms = []; end
if ~isfield(cfg, 'prestim'), cfg.prestim = 0.005; end
if ~isfield(cfg, 'poststim'), cfg.poststim = 0.010; end
if isfield(cfg.artfctdef.tms, 'artifact')
fprintf('tms artifact detection has already been done, retaining artifacts\n');
artifact = cfg.artfctdef.tms.artifact;
return
end
switch cfg.method
case 'detect'
% settings for preprocessing
if ~isfield(cfg.artfctdef.tms, 'derivative'), cfg.artfctdef.tms.derivative = 'yes'; end
% settings for the zvalue subfunction
if ~isfield(cfg.artfctdef.tms, 'method'), cfg.artfctdef.tms.method = 'zvalue'; end
if ~isfield(cfg.artfctdef.tms, 'channel'), cfg.artfctdef.tms.channel = 'all'; end
if ~isfield(cfg.artfctdef.tms, 'trlpadding'), cfg.artfctdef.tms.trlpadding = 0.1; end
if ~isfield(cfg.artfctdef.tms, 'fltpadding'), cfg.artfctdef.tms.fltpadding = 0.1; end
if ~isfield(cfg.artfctdef.tms, 'artpadding'), cfg.artfctdef.tms.artpadding = 0.01; end
if ~isfield(cfg.artfctdef.tms, 'cutoff'), cfg.artfctdef.tms.cutoff = 4; end
% construct a temporary configuration that can be passed onto artifact_zvalue
tmpcfg = [];
tmpcfg.trl = cfg.trl;
tmpcfg.artfctdef.zvalue = cfg.artfctdef.tms;
if isfield(cfg, 'continuous'), tmpcfg.continuous = cfg.continuous; end
if isfield(cfg, 'dataformat'), tmpcfg.dataformat = cfg.dataformat; end
if isfield(cfg, 'headerformat'), tmpcfg.headerformat = cfg.headerformat; end
% call the zvalue artifact detection function
% the data is either passed into the function by the user or read from file with cfg.inputfile
hasdata = exist('data', 'var');
if hasdata
% read the header
cfg = ft_checkconfig(cfg, 'forbidden', {'dataset', 'headerfile', 'datafile'});
fsample = data.fsample;
[tmpcfg, artifact] = ft_artifact_zvalue(tmpcfg, data);
else
cfg = ft_checkconfig(cfg, 'dataset2files', 'yes');
cfg = ft_checkconfig(cfg, 'required', {'headerfile', 'datafile'});
hdr = ft_read_header(cfg.headerfile);
fsample = hdr.Fs;
tmpcfg.datafile = cfg.datafile;
tmpcfg.headerfile = cfg.headerfile;
[tmpcfg, artifact] = ft_artifact_zvalue(tmpcfg);
end
cfg.artfctdef.tms = tmpcfg.artfctdef.zvalue;
% adjust artifact definition so that Nx2 matrix contains detected TMS
% events with user-specified pre- and post stimulus period included.
% The reason for this is that ft_artifact_zvalue centers the period
% marked as artifactual around the detected event. In the case of a TMS
% pulse the window you would like to mark as artifactual is not
% symmetrical around the onset of the pulse.
% get values and express in samples
prestim = round(cfg.prestim * fsample);
poststim = round(cfg.poststim * fsample);
% adjust Nx2 artifact matrix to be centered non-symmetrically around
% detected TMS-pulse
artifact(:,1) = (artifact(:,1)+artifact(:,2))./2 - prestim;
artifact(:,2) = artifact(:,1) + poststim;
cfg.artfctdef.tms.artifact = artifact;
case 'marker'
% Check if the cfg is correct for this method
cfg = ft_checkconfig(cfg, 'dataset2files', 'yes');
ft_checkconfig(cfg, 'required', 'trialdef');
cfg.trialfun = ft_getopt(cfg, 'trialfun', 'ft_trialfun_general');
trialdef = cfg.trialdef;
trialdef.prestim = cfg.prestim;
trialdef.poststim = cfg.poststim;
cfg.trialdef = ft_checkconfig(trialdef, 'required', {'eventvalue', 'eventtype'});
% Get the trialfun
cfg.trialfun = ft_getuserfun(cfg.trialfun, 'trialfun');
% Evaluate the trialfun
fprintf('evaluating trialfunction ''%s''\n', func2str(cfg.trialfun));
trl = feval(cfg.trialfun, cfg);
% Prepare the found events for output
artifact = trl(:,1:2);
cfg.artfctdef.tms.artifact = artifact;
fprintf('found %d events\n', size(artifact,1));
otherwise
ft_error('unsupported method'); % This should be redundant as ft_checkconfig does not allow other methods than the supported ones.
end
cfg = rmfield(cfg, 'method'); % FIXME - not removing this causes problems when passing to ft_preprocessing