[FieldTrip] warping from MNI to individual subjects

[Meike Schweisfurth]

 Dear Fieldtrippers!
As newbie I have another question, now concerning the warping from MNI to
individual subjects.
Using the below code (the first part almost entirely from
http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_space),
I get first the template and then apply the grid to the individual
subjects.
However, in later on analysis step it turned out that while the subjects
where nicely similar positioned, the template position is entirely
different, as it is was even axes were exchanged...
Does anybody know what could be the reason and how to change it?
Thanks for any suggestions!
Best, Meike


% NOTE: the path to the template file is user-specific
template =
ft_read_mri('fieldtrip/fieldtrip-20140316/external/spm8/templates/T1.nii');
template.coordsys = 'spm'; % so that FieldTrip knows how to interpret the
coordinate system

% segment the template brain and construct a volume conduction model (i.e.
head model): this is needed
% for the inside/outside detection of voxels.
cfg          = [];
template_seg = ft_volumesegment(cfg, template);

cfg          = [];
cfg.method   = 'singleshell';
template_vol = ft_prepare_headmodel(cfg, template_seg);
template_vol = ft_convert_units(template_vol, 'cm'); % Convert the vol to
cm, since the grid will also be expressed in cm

% construct the dipole grid in the template brain coordinates
% the source units are in cm
% the negative inwardshift means an outward shift of the brain surface for
inside/outside detection
cfg = [];
cfg.grid.xgrid  = -20:1:20;
cfg.grid.ygrid  = -20:1:20;
cfg.grid.zgrid  = -20:1:20;
cfg.grid.unit   = 'cm';
cfg.grid.tight  = 'yes';
cfg.inwardshift = -1.5;
cfg.vol        = template_vol;
template_grid  = ft_prepare_sourcemodel(cfg);
save('../analysis/MEG/source_analysis/MNI','template_grid','template_vol','template_seg','template')

% make a figure with the template head model and dipole grid
figure
hold on
ft_plot_vol(template_vol, 'facecolor', 'cortex', 'edgecolor', 'none');alpha
0.5; camlight;
ft_plot_mesh(template_grid.pos(template_grid.inside,:));
else
load('../analysis/MEG/source_analysis/MNI','template_grid','template_vol','template_seg','template')


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

     SUBJECTS={    'VP02'    'VP03'    'VP04'    'VP05'    'VP06' 'VP07'
'VP08'    'VP09'    'VP11'    'VP12'    'VP13' 'VP14'    'VP15'
'VP16'    'VP17'    'VP18'}

for SUBJI=SUBJECTS
    SUBJ=SUBJI{1};
% read the single subject anatomical MRI
load(['..*/analysis/MEG/source_analysis/*',SUBJ,'/mri']);  %Has been
processed to CFT coordinates before
load(['..*/analysis/MEG/source_analysis/*',SUBJ,'/segmentedmri']);


cfg = [];
cfg.method = 'singleshell';
vol = ft_prepare_headmodel(cfg, segmentedmri);

% create the subject specific grid, using the template grid that has just
been created
cfg = [];
cfg.grid.warpmni   = 'yes';
cfg.grid.template  = template_grid;
cfg.grid.nonlinear = 'yes'; % use non-linear normalization
cfg.mri            = mri_ra;
grid               = ft_prepare_sourcemodel(cfg);

% make a figure of the single subject headmodel, and grid positions
figure;
ft_plot_vol(vol, 'edgecolor', 'none'); alpha 0.4; %camlight
ft_plot_mesh(grid.pos(grid.inside,:));

save(['..*/analysis/MEG/source_analysis/*',SUBJ,'/MNIgrid'],'grid','vol')
end
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