[FieldTrip] Projection from sensors space to segmented brain surface

andrea brovelli andrea.brovelli at univ-amu.fr
Wed Jun 20 18:56:58 CEST 2012

Thank you very much for your quick reply, Eelke and Johanna.

Yes, I would like only to visualise the data on a cortical surface and  
I am aware of the potential misinterpretation of such visualisation.

I would like to use it as an intermediate step between the ft_topoplot  
on 2D layout and proper source localisation. It would serve as an  
exploratory tool to decide at which frequency, say, I would do a  
beamforming and to have a very rough idea of the number and location  
of cortical sources.

However, it is not very clear to me how I could do this using the  
example in the beamforming tutorial. Could you be a bit more explicit  
? Should I need to do source reconstruction for visualisation ?

Thanks a lot


----- Messaggio da johanna.zumer at donders.ru.nl ---------
     Data: Wed, 20 Jun 2012 18:22:48 +0200
     Da: Johanna Zumer <johanna.zumer at donders.ru.nl>
Rispondi-A: FieldTrip discussion list <fieldtrip at science.ru.nl>
  Oggetto: Re: [FieldTrip] Projection from sensors space to segmented  
brain surface
       A: FieldTrip discussion list <fieldtrip at science.ru.nl>

> Dear Andrea,
> I would like to further clarify the options for this question.    Perhaps
> could you suggest which inverse algorithm you had in mind?
> For example, it is possible to use beamforming limited only to voxels
> defined as lying on the cortical sheet (i.e. restrict .inside to be only
> the gray matter).   This is possible, but you might miss out on the spatial
> peak of the source lying just 5mm away to the inside a bit.   Thus, it
> would be better to do as Eelke suggested and apply beamforming to the whole
> inside of the brain, and then project those values to the surface for
> visualisation (which is easily done with the cfg.method='surface' option in
> ft_sourceplot).
> Alternatively, you can use a min-norm type of inverse method (e.g. sLORETA
> or MNE) which are commonly used to reconstruct onto cortical surface voxels
> only.  This works because the min-norm algorithms force all activity to lie
> in the region over which you select to reconstruct.  Thus, a source 5mm
> inside of the surface will automatically get projected to the surface.
> I also agree with Eelke you should not just project sensors to surface
> without doing a specific type of inverse method.
> Cheers,
> Johanna
> 2012/6/20 Eelke Spaak <eelke.spaak at donders.ru.nl>
>> Dear Andrea,
>> If I understand your question correctly, you just want to *visualise*
>> sensor space activity on a brain surface, without doing source
>> reconstruction first? I would advise against this. Time-frequency
>> power values of your planar gradient data reflect the spectral
>> characteristics of the magnetic gradient at the location of your
>> sensors. These sensors are not located at the surface of the brain,
>> but quite some centimeters away from it. Therefore, visualising the
>> data as if it were actually recorded on the brain surface, without
>> doing a proper transformation, is potentially misleading. It is true
>> that people tend to display all sorts of data in a 'topoplot' fashion,
>> but in that case it is clear to the audience that you are looking at a
>> representation in sensor-space. Have a look at ft_topoplotTFR for this
>> approach, if you're not already familiar with it.
>> If you want to display your time-frequency activity on a cortical
>> surface (which is of course a perfectly valid thing to want to do),
>> you first should map the sensor activity to source space. This mapping
>> is non-trivial and can be done by e.g. beamforming. See
>> http://fieldtrip.fcdonders.nl/tutorial/beamformer for a tutorial on
>> this. That tutorial ends with a surface plot.
>> Hope this helps!
>> Best,
>> Eelke
>> On 20 June 2012 17:26, andrea brovelli <andrea.brovelli at univ-amu.fr>
>> wrote:
>> >
>> > Dear Fieldtrip users and developpers,
>> >
>> > I would like to project and visualise time-frequency power values
>> computed
>> > on planar gradient data at the sensors level onto the brain surface
>> > segmentated from the anatomial MRI of the subject.
>> >
>> > Can anyone suggest me how to do it in Fieldtrip ? Can anyone share the
>> > scripts ?
>> >
>> > Does anyone see any inconvenient to this visualisation ?
>> >
>> > Thanks a lot for you help.
>> >
>> > Andrea
>> >
>> >
>> >
>> > --
>> >
>> >  NEW EMAIL: andrea.brovelli at univ-amu.fr
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