LORETA to Fieldtrip

Vladimir Litvak litvak at TECHUNIX.TECHNION.AC.IL
Mon Mar 27 15:15:30 CEST 2006


Hi Robert,

I tried reading the SPM MRI file (single_subj_T1.mnc - is this the one you
meant?) but in the grid variables there are just indices in the matrix. So
how do I know the correspondence to LORETA voxels? Is there a way to put the
MNI grid there?

Thanks,

Vladimir

-----Original Message-----
From: Robert Oostenveld [mailto:r.oostenveld at fcdonders.ru.nl] 
Sent: Monday, March 27, 2006 2:43 PM
To: Vladimir Litvak
Subject: Re: Clusterrandanalysis

> The question is - can we build a gateway for reading LORETA files  
> in FT and
> applying the same statistics as you use for the beamformer? 
> This
> shouldn't be something very complicated I think. The only problem  
> is that
> LORETA uses a grid of 2394 voxels which are only in the gray matter  
> (so
> there are some holes there) and it would probably be necessary to  
> do some
> smoothing. Also one must write a routine for transforming from  
> LORETA grid
> to your grid (based on Tailarach coordinates of the voxels).

I once started with implementing LORETA myself in sourceanalysis, but  
never finished it. I don't consider LORETA to be too interesting for  
MEG, although I do appreciate it's usefullness for EEG. I have been  
in contact a couple of times with Roberto Pasqual-Marqui, and he told  
me some of the details.

LORETA is using plain SPM/MNI coordinates, which can also be used in  
FT. The holes can be dealt with in FT by specifying NaNs as  
source.avg.pow, [] as source.avg.mom, and by specifying the right  
source.inside and source.outside vector (those are indices specifying  
which voxels are inside the brain, or inside the gray matter if you  
wish).

Writing a LORETA importer should be trivial, but I am not going to do  
it myself. Please point the grad student to
   http://www2.ru.nl/fcdonders/fieldtrip/doku.php? 
id=fieldtrip:documentation:frequently_asked_questions#how_is_anatomical_ 
functional_or_statistical_volume_data_described
and tell him to use volume.inside and volume.outside to "fill" the  
non-gray matter so that the data fits into a 3D box.

Also do
   addpath spm2
   volume = read_fcdc_mri(filename)
with filename being the canonical MRI from SPM (the collin27 one).  
That should belp in getting it alligned with the proper  
transformation matrix.

Once you can read a single LORETA volume into FT, then you can repeat  
it for all subjects and do your statistics. Please address further  
questions regarding this topic to the mailing list.

Robert

PS I don't think that you want to smooth, our source clustering is  
aware of the grey/white matter differences (given the correct inside/ 
outside specification).



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