[FieldTrip] Pipeline for sourceanalysis with individualize grid.

[Olga Sysoeva]

Dear Simon,

Thank you very much for the answer, but I think that this code should
"create the subject specific grid, using the template grid" as specified in
tutorial here http://www.fieldtriptoolbox.org/tutorial/sourcemodel.
"

% create the subject specific grid, using the template grid that has
just been created
cfg                = [];
cfg.grid <http://www.mathworks.com/access/helpdesk/help/techdoc/ref/grid.html>.warpmni
  = 'yes';
cfg.grid <http://www.mathworks.com/access/helpdesk/help/techdoc/ref/grid.html>.template
 = template_grid;
cfg.grid <http://www.mathworks.com/access/helpdesk/help/techdoc/ref/grid.html>.nonlinear
= 'yes'; % use non-linear normalization
cfg.mri            = mri;
cfg.grid <http://www.mathworks.com/access/helpdesk/help/techdoc/ref/grid.html>.unit
     ='mm';grid
<http://www.mathworks.com/access/helpdesk/help/techdoc/ref/grid.html>
             = ft_prepare_sourcemodel(cfg);

I believe it "align/project" the template grid with individual mri using
non-linear transformation.

Correct me if I'm wrong.
I'll be more than happy to get more comments on this.

Best Regards,
Olga.

On Wed, Mar 9, 2016 at 2:43 PM, Simon Homolle <s.homolle at donders.ru.nl>
wrote:

> Dear Olga,
>
> Should I use template or subject-specific headmodel with “projected to
> template grid individualized grid”?
>
>
> I would use the individual head model based on the MRI as it provides more
> information for your source analysis. This should provide more accurate
> results.
>
> Actually I tried both ways for one subject and did not notice any
> difference in the results.
>
>
> It seems to that this is due to this line of code, but I’m not quite sure
> about that:
>
> cfg = [];
>
> cfg.grid.warpmni = 'yes';
>
> cfg.grid.template = template_grid;
>
> cfg.grid.nonlinear = 'yes'; % use non-linear normalization
>
> cfg.mri = mri_cm{Subj_i};
>
> grid_ind{Subj_i} = ft_prepare_sourcemodel(cfg);
>
>
> I think with this configuration the source model that is prepared is only
> based on the cfg.grid.template, and completely ignores the MRI (which you
> are interested in). This might explain why you see no difference.
>
> Bests,
>
> Simon Homölle
> PhD Candidate
> Donders Institute for Brain, Cognition and Behaviour
> Centre for Cognitive Neuroimaging
> Radboud University Nijmegen
> Phone: +31-(0)24-36-65059
>
> On 09 Mar 2016, at 11:57, Olga Sysoeva <olga.v.sysoeva at gmail.com> wrote:
>
> Pipeline for sourceanalysis with individualize grip
>
>
>
> Dear field trippers,
>
>
> I have a question related to pipeline for sourceanalysis with
> individualize grid.
>
> Should I use template or subject-specific headmodel with “projected to
> template grid individualized grid”? Below is my pipeline with details of
> what I mean. Actually I tried both ways for one subject and did not notice
> any difference in the results. Does it mean that I do not need to constract
> headmodel for each subject? That's indeed save a lot of time, but I'd like
> to get your green light on this.
>
> Best Regards,
>
> Olga.
>
>
> % 1. load template grid, e.g.
>
>
> load(
> '/net/server/mnt/programs/olgas/fieldtrip-20160119/template/sourcemodel/standard_sourcemodel3d10mm.mat'
> );
>
> template_grid = sourcemodel;
>
>
> %2. Make the individual subjects' grid
>
> %a) Load individual subject mri, e.g.
>
>
> [mri{Subj_i}] = ft_read_mri(path_MRI{Subj_i});
>
> mri_cm{Subj_i} = ft_convert_units(mri{Subj_i}, 'cm');
>
>
> %b) construct individual grid by projecting to template grid
>
>
> cfg = [];
>
> cfg.grid.warpmni = 'yes';
>
> cfg.grid.template = template_grid;
>
> cfg.grid.nonlinear = 'yes'; % use non-linear normalization
>
> cfg.mri = mri_cm{Subj_i};
>
> grid_ind{Subj_i} = ft_prepare_sourcemodel(cfg);
>
>
> % 3. Make source reconstruction, using individualized grid and* template?
> or individual headmodel*
>
> %a) load template volume
> load('/net/server/data/programs/olgas/fieldtrip-20160119/template/headmodel/standard_singleshell.mat');
>
> template_vol = vol;
>
>
> cfg = [];
>
> cfg.grid = grid_ind{Subj_i};
>
> *cfg.vol = vol_K0012_cm; **% **individual* *or template **vol???*
>
> cfg.channel = {'MEG'};
>
> cfg.grad = freq_cmb{Subj_i}.grad;
>
> sourcemodel_lf_K0012 = ft_prepare_leadfield(cfg, freq_cmb{Subj_i});
>
>
> cfg = [];
>
> cfg.frequency = freq_cmb{Subj_i}.freq;
>
> cfg.grad = freq_cmb{Subj_i}.grad;
>
> cfg.method = 'dics';
>
> cfg.keeptrials = 'yes';
>
> *cfg.grid = sourcemodel_lf{Subj_i}; % **sourcemodel after leadfield with
> individual or template headmodel?*
>
> *cfg.vol = vol_K0012_cm; **% individual or template vol???*
>
> cfg.keeptrials = 'yes';
>
> cfg.dics.lambda = '5%';
>
> cfg.dics.keepfilter = 'yes';
>
> cfg.dics.fixedori = 'yes';
>
> cfg.dics.realfilter = 'yes';
>
> source_K0012 = ft_sourceanalysis(cfg, freq_cmb{Subj_i});
>
>
>
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