[FieldTrip] Leadfield computation generates NaNs

[Topkan, Tugberk]

Dear Fieldtrip experts,


I am currently trying to carry out source localization of EEG oscillations of a dataset. Although computation of leadfields of some participants seems fine, the computations of most participants generate only NaNs in leadfield matrices. I took a look at the previous messages and saw that many researchers also experienced the same problem, but could not find any relevant solution.


I would really appreciate it, if the experts with more experience on it could guide me to solve this problem.


Here is the code I currently use.


ft_defaults;
mri = ft_read_mri('f73.nii');

ft_determine_coordsys(mri)
cfg = [];
cfg.method = 'interactive'
[mri] = ft_volumerealign(cfg, mri);
save mri mri


cfg           = [];
cfg.output    = {'brain','skull','scalp'};
cfg.scalpthreshold = 0.05;
segmentedmri  = ft_volumesegment(cfg, mri);
save segmentedmri segmentedmri

cfg = [];
cfg.tissue = {'brain','skull','scalp'};
cfg.numvertices = [3000 2000 1000];
bnd = ft_prepare_mesh(cfg,segmentedmri);
save bnd bnd

cfg        = [];
cfg.method = 'bemcp';
vol        = ft_prepare_headmodel(cfg, bnd);
save vol vol

cfg = [];
cfg.tissue      = 'scalp';
cfg.numvertices = 10000;
scalp = ft_prepare_mesh(cfg, segmentedmri);
save scalp scalp

%get elec info
load(fullfile(current_dir,'elec_template.mat'));
elec = ft_determine_coordsys(elec)

% markerpos = table2cell(readtable(['load(fullfile('C:\Users\......',['elec_template.mat']));marker_positions_' subj '.csv']));
% markerpos = table2cell(readtable(['marker_positions_P30.csv']));
markerpos = table2cell(readtable(['D:......\',[subj '.csv']]));
%%% align the electrodes %%%
for i = 1:length(markerpos)
    elec.label{i} = char(markerpos{i,2});
    elec.elecpos(i,:) = cell2mat(markerpos(i,3:5));
    elec.chanunit{i} = 'V';
    elec.chantype{i} = 'eeg';
end
elec.chanpos = elec.elecpos;


nas = mri.cfg.fiducial.nas;
lpa = mri.cfg.fiducial.lpa;
rpa = mri.cfg.fiducial.rpa;

transm = mri.transform;

nas = ft_warp_apply(transm,nas, 'homogenous');
lpa = ft_warp_apply(transm,lpa, 'homogenous');
rpa = ft_warp_apply(transm,rpa, 'homogenous');

% create a structure similar to a template set of electrodes
fid.elecpos       = [nas; lpa; rpa];       % ctf-coordinates of fiducials
fid.label         = {'nasion','Left Tragus','Right Tragus'};    % same labels as in elec
fid.unit          = 'mm';                  % same units as mri

% alignment
cfg               = [];
cfg.method        = 'fiducial';
cfg.target        = fid;                   % see above
cfg.elec          = elec;
cfg.headshape     = vol; %scalp
cfg.fiducial      = {'nasion','Left Tragus','Right Tragus'};  % labels of fiducials in fid and in elec
elec_aligned      = ft_electroderealign(cfg);

cfg           = [];
cfg.method    = 'interactive';
cfg.elec      = elec_aligned;
cfg.headshape = vol.bnd(3);
elec_aligned  = ft_electroderealign(cfg);

save elec_aligned elec_aligned

% Create the sourcemodel
cfg = [];
cfg.resolution = 7.5;
cfg.threshold = 0.1;
cfg.smooth = 5;
cfg.headmodel = vol;
sourcemodel = ft_prepare_sourcemodel(cfg);

% Compute the leadfield
cfg = [];
cfg.sourcemodel     = sourcemodel;
cfg.headmodel       = vol;
cfg.elec            = elec_aligned;
cfg.channel         = {'all','-AFz','-M1','-M2','-nasion','-Left Eye','-Right Eye','-Left Tragus','-Right Tragus','-nose tip','-chin tip'};
cfg.reducerank      = 3;
grid                = ft_prepare_leadfield(cfg);

Thanks in advance,
Andac Topkan
University of Leipzig

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