[FieldTrip] Antw: Re: MNE surface data: normalising and averaging?

jan-mathijs schoffelen jan.schoffelen at donders.ru.nl
Tue Mar 5 10:24:51 CET 2013


Hi Gregor,

To follow up on this: I guess what Jörn meant is that you could use the irregular 3D grids, as the target grids onto which the surface data will be interpolated. This makes the interpolated 3D-grid data directly averageable.

JM

On Mar 5, 2013, at 9:03 AM, Gregor Volberg wrote:

> Hi Jörn,
> 
> thank you for your fast response! I wasn't aware that this approach also works with irregularly spaced surface grids as input. I will try it this way.
> 
> Thanks again,
> Gregor
> 
> 
> 
> 
> -- 
> Dr. rer. nat. Gregor Volberg <gregor.volberg at psychologie.uni-regensburg.de> ( mailto:gregor.volberg at psychologie.uni-regensburg.de )
> University of Regensburg
> Institute for Experimental Psychology
> 93040 Regensburg, Germany
> Tel: +49 941 943 3862 
> Fax: +49 941 943 3233
> http://www.psychologie.uni-regensburg.de/Greenlee/team/volberg/volberg.html
> 
> 
> >>> "Jörn M. Horschig"<jm.horschig at donders.ru.nl> 3/4/2013 10:01 PM >>>
> Hi Gregor,
> 
> would there be any reason why the following approach might not work?
> http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_space?s[]=warp
> 
> The specific steps are in more detail explained in this (new) tutorial:
> http://fieldtrip.fcdonders.nl/development/beamformingextended
> 
> Best,
> Jörn
> 
> On 3/4/2013 6:45 PM, Gregor Volberg wrote:
>> Dear Fieldtrippers,
>>  
>> I need to ask for a helpful hint on MNE source reconstructions. Following this tutorial http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate I obtained nice individual cortical meshes and source points; the MNE forward and inverse solution for the individuals all work well. I would now like to normalize the individual grids to a template brain in order to do statistics and averaging for plotting. I figured out that I could use ft_sourceinterpolate to tranform the grid into a volumetric representation, and then use ft_volumenormalise to normalise to a standard brain.  But this did not work too well for source structures containing time series (like 'mne'-stcutures) where the computational load gets very high. I also tried to use a grid of one subject as a template for the other subject's grids with ft_sourceinterpolate and cfg.interpmethod = 'smudge', but this seems to require two grids with the same number of source points as input(?).
>> Is there a way to do a normalisation directly on brain triangulations / source grids ? Thanks for any help!
>> Best regards,
>> Gregor   
>>  
>> --
>> Dr. rer. nat. Gregor Volberg <gregor.volberg at psychologie.uni-regensburg.de> ( mailto:gregor.volberg at psychologie.uni-regensburg.de )
>> University of Regensburg
>> Institute for Experimental Psychology
>> 93040 Regensburg, Germany
>> Tel: +49 941 943 3862
>> Fax: +49 941 943 3233
>> http://www.psychologie.uni-regensburg.de/Greenlee/team/volberg/volberg.html
>> 
>> 
>> 
>> 
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>> 
> 
> 
> 
> -- 
> 
> Jörn M. Horschig
> 
> PhD Student
> 
> Donders Institute for Brain, Cognition and Behaviour 
> 
> Centre for Cognitive Neuroimaging
> 
> Radboud University Nijmegen 
> 
> Neuronal Oscillations Group
> 
> FieldTrip Development Team
> 
> 
> 
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> 
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Jan-Mathijs Schoffelen, MD PhD 

Donders Institute for Brain, Cognition and Behaviour, 
Centre for Cognitive Neuroimaging,
Radboud University Nijmegen, The Netherlands

Max Planck Institute for Psycholinguistics,
Nijmegen, The Netherlands

J.Schoffelen at donders.ru.nl
Telephone: +31-24-3614793

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