Positions to mri mapping

[Robert Oostenveld]

Hi Marie

On 15 Dec 2006, at 16:46, Marie Smith wrote:
> I have performed an lcmv beamformer analysis to estimate the single
> time course at a regular grid of points within the brain space. At
> each point inside the space (from source.inside) i computed the
> reverse correlation with the bubbles stimuli to establish the
> information sensitivity of that point. I would now like to go from
> these points in a regular array to a more interpretable brain
> space. I have been trying to do this myself looking at your
> sourceinterpolate and prepare_dipole_grid functions to establish
> what the x, y and z co-ordinates correspond to in terms of the
> brain orientations but I am getting lost in the functions.  Would
> you be able to tell me? I am assuming z - is the vertical direction
> from chin to scalp, but x and y?

The dipole grid as constructed with fieldtrip/private/
prepare_dipole_grid is aligned with the x, y and z-axis of the head
coordinate system.That means for CTF that the  x-ax is going to the
nose, and the y-axis to the left ear.  The default is to make a 3D
box with positions that encompases the brain. Hence some positions
are inside the brain, and other positions are outside. The dipole
positions that are in the brain are coded in

source.pos(source.inside,:)

The positions are coded linearly, with the x as the fastest changing
index, then y, and then z.

For plotting the 3D volume, it is more convenient to have all the
positions in the 3D box, including the outside positions. So if you
compute a value "val" at all inside positions, you could do

tmp = zeros(source.dim);
tmp(source.inside)  = val;
tmp(source.outside) = 0;

and you would have a 3D array with the values all at the right
position. The source2full function is needed if you ghave a sparse
source representation, since in that case only the inside grid points
are retained, which makes inside=1:Ndipoles. Hence in a sparse source
representation the inside and outside in the sparse structure cannot
be used as above, but the original inside and outside first have to
be reconstructed (using the sparse positions in source.pos and the x/
y/zgrid fields).

> The other solution that I thought off was to replace the energy
> values coming out of sourceanalysis with a score for the
> correlation of the classification image at that point with a given
> facial feature (e.g. left eye). Could I then put that in
> source2full and sourceinterpolate along with the mri to establish
> illustrate the sensitivity to that feature overlayed on the mri?

For interpolating the values on the regular grid in headcoordinates
(i.e. the source grid) onto the regular grid in MRI coordinates, I
indeed would suggest to use the SOURCEINTERPOLATE function. In the
MRI the axis are not aligned to the head-coordinate axes (i.e. the
first dimension of the MRI 3D volume is not equal to x). The MRI uses
a homogenous transformation matrix to attach a head-coordinate
position to each MRI voxel, and the inverted transformation matrix
can be used to assign each head coortdinate point to a MRI voxel:
that is how sourceinterpolate works (except that sourceinterploate
also tries to do it in a memory efficient manner, which makes the
code more difficult to read).

I hope this helps,
Robert


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