r.oostenveld at FCDONDERS.RU.NL
Wed Oct 4 14:36:09 CEST 2006
On 4 Oct 2006, at 12:38, Mikhail Zvyagintsev wrote:
> I am using 4 D Neuroimaging mashine (BTi), and, therefore, I had to
> change the routine a bit - at least change settings, concerning the
> sensors name.
Yes, I can imagine that, since it is using some pre-defined sensor
names to construct the averaged template helmet position. Could you
send me the change (private mail), then I will include it in FT.
> (I actually attached a picture regarding sensors' position's
> difference derived from Matlab, but probably it is not so easy to
> recognize what is what on this picture - points are sensors and
> different colors - positions in different sessions, the view is
> from front).
There is an option in MEGREALIGN that you can use for plotting
something similar (cfg.plot3d=yes)
> And later in this routine I use the approach based on calculation
> of brain surface from headshape. As a headshape we use here points
> from bridge (of nose) to nape (of the neck).
You should ensure that the points, when shifted inwards with
cfg.inwardshift (units are the same as your units of the volume an
dgradiometer system, in case of CTF that is in cm), that they more or
less ly in the gray matter, i.e. approx 0.5-1cm inward from the brain
surafce. If your head surface includes ears and a nose, you will have
weird effects. You could change teh plot3d option in such a way that
the dipole grid positions are also plotted (you should plot the pos
> I get 644 dipoles from it 'prunedinv' subfunction gives me 'pruning
> 49 out of 148 singular values' (so, we use 148 channels mashine).
That seems a rather large reduction. The issue here is that you need
148 sources (i.e. a dipole onsists of an x, y and z source, and in
case of a spherical headmodel the radial component will be zero) to
be able to completely describe the data. But if there is noise (a
small and spatially shart amplitude contribution), then that noise
will also project to teh sourcespace. Hence, the noise will also
project outward again to the new sensor array. By "pruning" the
leadfield matrix, the N spatially strongest components are selected,
where a component is then not a dipole any more, but a combination of
dipoles. I.e. a SVD is done on the leadfield, and the smallest
contributing components are removed. By default all source components
smaller than 0.001 times the largest component will be removed (note
that this is independent of data). In your case there are 49 of the
148 removed. You have 644 sources, each with 3 orientations -> those
are compressed into 148-49=99 spatial topographies.
> After calculation of realign matrix and applying it for 'realigning
> trial' the residual variance (RV) which I get for one trial is
> arround 30%. I have a feelling that it is rather to much, or might
> be it's normal, becouse difference between sensors is rather big one.
> Because in case 'mean distance towards template gradiometers' was
> 6.48 mm - residual variances were arround 5-6%.
> distance RV
> 6.48 mm 5-6%
> 25.45 mm ~30%.
> My question is - is such RV difference correspondent to the
> difference distance I have and how many points should be like a
> 'control value' for 'prunedinv' routine?
The RV is not the incorrectness of the projection, but the difference
between the original and realigned data (i.e. before and after). If
it were zero, then realigning would not have an effect. So "RV" is
not a good name, it is "before-after difference". A large helmet
shift probably fits with a large before-after difference. Various
differences can be shown, i.e. "original->brain->original" and
"original->brain->template", and also "original->brain->template-
>brain->original". I hope that these numbers are now more clear.
I cannot tell you what a good value is for the cfg.pruneration
option. You can set it between 0 (no pruning) and 1 (all except the
largest component will be pruned/removed). Perhaps other people on
the FT list can tell you about their experience with this setting.
More information about the fieldtrip