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Hi Jan-Mathijs<br>
<br>
thanks for quick response. I was actually thinking of this and thought
particularly because of the existence of the multi-dipole beamformer
that it should be fairly straightforward to implement a
multi-dipole-fit.<br>
<br>
The answer is, no I haven't used it, cause except in very few subjects
the beamformer didn't give meaningful results for the first source to
start with (which you obviously need for doing it properly)<br>
Of course one could use the information from a dipole localization to
apply in a beamformer, but my concern is that I invest effort to do
this and then the reviewer tells me that if the localization with
method A fails then one should not use method A as spatial filters, but
rather the more robust method B (which doesn't seem that robust
either). <br>
<br>
So, I am not sure whether it is really worth the effort (for now). The
more complicated the methods, the more critical usually the reviewers
and want to finsih this finally.<br>
I may reconsider though for the future and might ask for advice....<br>
<br>
cheers<br>
Markus<br>
<br>
<br>
<blockquote
cite="mid:CB97F8E9-39A1-4DAD-81B8-206D6C446321@psy.gla.ac.uk"
type="cite">Hi Markus,
<div><br>
</div>
<div>Did you consider trying out the beamforming algorithm with
multiple dipoles as a source model?</div>
<div>As opposed to the dipole-fitting (which pinv'es the concatenated
leadfields), the beamformer actually tries to suppress contributions of
the other guys (provided they are not too much correlated in time).
Obviously, the suppression will be more robust against violations of
the temporal uncorrelation-assumption, when the leadfield-columns are
less correlated. However, I would guess it's worth a try, and it's
exactly what you try to achieve: to avoid mixing up correlated
leadfield components. But perhaps I did not grasp the problem
completely... ;o)</div>
<div><br>
</div>
<div>Yours,</div>
<div><br>
</div>
<div>JM</div>
<div><br>
<div>
<div>On May 28, 2008, at 4:00 PM, Markus Bauer wrote:</div>
<br class="Apple-interchange-newline">
<blockquote type="cite"> <br>
Hi fieldtrippers (in particular probably Robert)<br>
<br>
I have a few slightly more advanced questions regarding the use of
dipoles as spatial filters and the creation of multi-dipole models with
fieldtrip (questions in bold)<br>
I know that the functionality of fieldtrip is not designed for
multi-dipole models, but neither Beamformer nor MNE worked somewhat
reliably (only worked in rather few subjects and then was usually
pretty smeared still), as often is the case...(for evoked fields in
this case). So I finally decided to once go back to the "gold standard"
of somatosensory EEG/MEG research<br>
<br>
I have used a serial fit-procedure to fit components of the SEP to EEG
data. The early components (50 and 80 ms post response) are largely
determined by two single dipoles, plus a symmetric dipole later for
bilateral S2. So it is kind of ok to fit simple dipoles to those
(though clearly not ideal)<br>
<br>
My first question: <br>
<b>Are there plans to extend the functionality of dipolefitting to
allow for proper serial fit (i.e. adding to be fitted dipoles to
existing ones) ? I guess it would not be that much rewriting to include
a fixed dipole and only fit the parameters of the other?<br>
</b><br>
Anyway, in order to create spatial filters I have then fitted the
orientation of each dipole (estimated from the moments) and thereby
reduced the leadfield to a onedimensional one.<br>
In order to get to the sourcewaveforms, I have concatenated the (one
dimensional) leadfields associated with each source into a common
leadfield matrix (4 sources corresponding to 4 rows and 124 columns for
each channel) and then took the pseudoinverse of this combined
leadfield matrix - for use as spatial filters to obtain sourcewaveforms
- for the "complete solution".<br>
<br>
When I looked at those filters obtained, however, I realized that it
did not work that nicely, since the filters looked for at least two
components very similar - more similar than the respective leadfields!!
(which is contra-intuitive)<br>
The topographies of the peaks where I fitted dipoles to are beautiful
single dipolar topographies and so are the single leadfield matrices,
but the filters are anything else than clean. It is clear that they
will represent a mixture between the sources - mutually "supressing"
each other. But at least for two of them (the early sources for 50 and
80 ms with clearly distinct topos, presumably area3b and area1) they
pretty much mixed up. I was surprised about this cause the
topoghraphies look so distinct and I would have assumed this should
come out nicely (also considering all the Hari-studies)<br>
<br>
Anyway, a look at the correlation matrix of the leadfields showed that
despite the topographies of those dipoles had quite a different
orientation they were correlated at 0.77 (weights over channels). So I
guess what happens is identical to a suppressor effect in multiple
regresion - when the predictors are too correlated their weights get
mixed up.... <br>
<br>
I tend to use the individual spatial filters now - not the
pseudoinverse of the combined source model (consisting of only four,
well identifiable sources).<br>
My question:<br>
<br>
<b>Is this justified - to take individual filters when having a
multi-dipole model ? </b><i><br>
</i><br>
I also realized that when I only included the first two sources (the
ones described above), and take the pseudoinverse the separation
succeeds much better.<br>
<br>
<b>- Might prior regularization of the leadfield help ?<br>
- Are there any standards about this - when to still use a combined
leadfield model ? I guess should be the same as in multiple regression
cause formulas more or less identical...? But I guess nobody publishing
sourcewaveforms from multidipole model cares about it...<br>
</b><br>
I was a bit "shocked" to see how much this can falsify the results (the
waveforms), I also wouldn't have expected the leadfields (and
filters...) of such rather different sources to be that strongly
correlated. I assume it will be not much different in MEG, cause they
were both tangential dipoles, looking almost identical as in MEG (apart
from 90deg rotation due to field geometry).<br>
My strategy is therefore to either use individual filters of single
dipoles or reduce the dipolar model...any other suggestions ??<br>
It seems it is really a very ill-posed problem that we're spending our
time with....<br>
<br>
<br>
thanks and best wishes <br>
Markus <br>
<p>----------------------------------</p>
<p>The aim of this list is to facilitate the discussion between
users of the FieldTrip toolbox, to share experiences and to discuss new
ideas for MEG and EEG analysis.</p>
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</blockquote>
</div>
<br>
</div>
<p>----------------------------------</p>
<p>The aim of this list is to facilitate the discussion between users
of the FieldTrip toolbox, to share experiences and to discuss new ideas
for MEG and EEG analysis.</p>
<p> <a class="moz-txt-link-freetext" href="http://listserv.surfnet.nl/archives/fieldtrip.html">http://listserv.surfnet.nl/archives/fieldtrip.html</a></p>
<p> <a class="moz-txt-link-freetext" href="http://www.ru.nl/fcdonders/fieldtrip/">http://www.ru.nl/fcdonders/fieldtrip/</a></p>
</blockquote>
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<p>The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis.</p>
<p> http://listserv.surfnet.nl/archives/fieldtrip.html</p>
<p> http://www.ru.nl/fcdonders/fieldtrip/</p>