[FieldTrip] Defining cfg.neighbourdist at source level

Pomper, Ulrich Ulrich.Pomper at charite.de
Wed Feb 1 14:44:44 CET 2012

Dear Robert and Stephan,
Thank you for your replies.
I guess I use what Robert called the 'regular' 3D grid, but I'm not quite sure.

The structures of my headmodel and leadfield matrix are the following (based on data from a BEM standard file):

vol =

     bnd: [1x3 struct]
    cond: [0.3300 0.0041 0.3300]
     mat: [3000x3000 double]
    type: 'dipoli'

ldf =

        xgrid: [-65 -58 -51 -44 -37 -30 -23 -16 -9 -2 5 12 19 26 33 40 47 54 61 68]
        ygrid: [-107 -100 -93 -86 -79 -72 -65 -58 -51 -44 -37 -30 -23 -16 -9 -2 5 12 19 26 33 40 47 54 61 68 75]
        zgrid: [-52 -45 -38 -31 -24 -17 -10 -3 4 11 18 25 32 39 46 53 60 67 74 81]
          dim: [20 27 20]
          pos: [10800x3 double]
       inside: [1x5739 double]
      outside: [1x5061 double]
    leadfield: {1x10800 cell}
          cfg: [1x1 struct]

In any case, I still don't quite understand how to calculate the neighbours to each voxel.
By saying that the "neighbours are trivial to find and you do not have to specify a structure", do you mean that I don't need to define the cfg.neighbours property at all (given that I do use a regular 3D grid)?

Thanks again for your help, cheers,

On 31.01.2012 21:48, smoratti at psi.ucm.es<mailto:smoratti at psi.ucm.es> wrote:
Dear Robert,

To do clustering on a 3D source surface I always had to "trick" field trip and squeezed the 3D source surface data into a ERF structure treating the 3D surface points as sensors. Then by triangulation I found the neighbors. However, if there is a more elegant method implemented in ft_sourcestatistc, I would be very interested to know how to do it. Where can I find some hints on that?



Stephan Moratti, PhD

see also: http://web.me.com/smoratti/

Universidad Complutense de Madrid
Facultad de Psicología
Departamento de Psicología Básica I
Campus de Somosaguas
28223 Pozuelo de Alarcón (Madrid)


Center for Biomedical Technology
Laboratory for Cognitive and Computational Neuroscience
Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
Campus Montegancedo
28223 Pozuelo de Alarcón (Madrid)

email: smoratti at psi.ucm.es<mailto:smoratti at psi.ucm.es>
Tel.:    +34 679219982

El 31/01/2012, a las 15:37, Robert Oostenveld escribió:

Dear Ulrich

If your source locations are defined on a regular 3D grid that can be represented as volume, then the neighbours are trivial to find and you do not have to specify a structure for the neighbours.

If you have done source reconstruction on a 3D folded cortical sheet that is defined by a triangulated surface, then it is also possible to cluster along the surface. I don't know the details for the cortical sheet clustering from the top of my head, if you are interested please let me know and I'll look them up.


On 30 Jan 2012, at 16:58, Pomper, Ulrich wrote:

Dear Jörn,
Thanks for you reply. I did mean source-level, so like you said, I am trying to define the neighbouring voxels for each voxel.
As far as I understand, leaving cfg.neighbours blank means that the clustering is done over the time and frequency dimensions only, not over space.
The FT help reads:
%If you specify an empty neighbourhood structure, clustering will only be done in frequency and time (if available) and not over neighbouring channels.

Has anybody done clustering in source space using all three dimensions and could explain how this works?

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