[Mne_analysis] pick orientation, MNE, dSPM and group analyses

dgw dgwakeman at gmail.com
Fri Aug 8 09:38:21 EDT 2014
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On Fri, Aug 8, 2014 at 9:34 AM, Denis-Alexander Engemann
<denis.engemann at gmail.com> wrote:
> Thanks Dan,
>
> On Fri, Aug 8, 2014 at 3:27 PM, dgw <dgwakeman at gmail.com> wrote:
>>
>> IMO, oct-6 is severely decimated (only 2.75% of the points in the
>> source space originally).
>
>
> I agree. But what's the alternative? Do you compute inverse solutions on the
> entire source space?

I often do, but you could always try with ico 5 (higher numbers than
that make more work, by breaking morphing), to keep it simple and
still have morphing.

>
>>
>> I'm not sure that --loose 0.2 will
>> accurately capture the range of orientations (especially dangerous if
>> not using the cps). Plus by morphing on top of this coarse spacing
>> with 20 smooth steps that ends up smoothing the result a lot. If you
>> want to keep the analysis in the time domain, I would first explore
>> the timecourses of the labels within the individuals to see what sort
>> of pattern emerges (particularly with respect to their individual
>> anatomy).
>
>
> I was feeling that this is probably the way to go.
>
>>
>> As I said before it could be anatomical variability, but you
>> may be able to correct for this if the whole label actually has a
>> consistent orientation across participants (the current decimation (in
>> combination with your other parameters), could be causing the sign
>> flipping you are seeing). In that case simply adding cps "should"
>> improve the situation.
>
>
> I feel we should handle CPS a bit more verbosely, e.g. log whether it's used
> or not when computing / applying inverse.
>
>>
>> Of course one "easy fix" is to just pick the peak frequency in the
>> region/time you are interested in and average the power in that band
>> (this will save you from the flipping issues, by removing phase).
>>
>
> indeed.
>
>>
>> HTH,
>> D
>>
>> Aside:
>> What would be "explicit" decimation? To me reducing the source space
>> to oct-6 is decimation (how else could one decimate?).
>>
>
> forget about the wording. I simply expressed the fact that these are
> parameters we normally don't touch.
>
>
>>
>> On Fri, Aug 8, 2014 at 9:06 AM, Denis-Alexander Engemann
>> <denis.engemann at gmail.com> wrote:
>> >
>> >
>> >
>> > On Fri, Aug 8, 2014 at 3:01 PM, dgw <dgwakeman at gmail.com> wrote:
>> >>
>> >> On Fri, Aug 8, 2014 at 8:26 AM, Denis-Alexander Engemann
>> >> <denis.engemann at gmail.com> wrote:
>> >> > Hi Dan,
>> >> >
>> >> >
>> >> > On Thu, Aug 7, 2014 at 9:45 PM, dgw <dgwakeman at gmail.com> wrote:
>> >> >>
>> >> >> Hi Denis,
>> >> >>
>> >> >> This effect can be influenced by a lot of variables. I would say
>> >> >> anatomical variability is a huge one but there are tons of factors
>> >> >> which affect just that:
>> >> >>
>> >> >> Did you decimate? (I guess you must have to morph, but how severely
>> >> >> did you decimate?)
>> >> >
>> >> >
>> >> > I think I did not explicitlly decimate. Simply a 20 steps morpch from
>> >> > subject to fsaverage.
>> >>
>> >> How did you map the full ~300,000 vertices from each participant to
>> >> fsaverage without decimating?
>> >>
>> >
>> > As I said, not *explcitly*, it's the an oct 6 source space that we
>> > usually
>> > recommend as default.
>> >
>> >>
>> >>
>> >> >
>> >> >>
>> >> >> Are you using --loose, or --loosevar
>> >> >> What parameters with those
>> >> >
>> >> >
>> >> > our default, loose=0.2
>> >> >
>> >> >>
>> >> >> Did you use cps?
>> >> >>
>> >> >
>> >> > I'm actually not sure whether Python takes the cps into account /
>> >> > where
>> >> > /
>> >> > when /
>> >> >
>> >> >>
>> >> >> I suspect the morphing will also influence this, but that is easy to
>> >> >> check (and wise to do see how the labels morph back on the
>> >> >> individual's surface?).
>> >> >
>> >> >
>> >> > Yeah, or compute the grand ave time series based on time courses
>> >> > extracted
>> >> > from unorphed stcs.
>> >> >
>> >> >>
>> >> >> Though as long as you have FreeSurfer quality
>> >> >> scans, I don't expect the segmentation to be an issue. What if any
>> >> >> smoothing did you do (at each stage)?
>> >> >>
>> >> >
>> >> > see above
>> >> >
>> >> >>
>> >> >> HTH,
>> >> >> D
>> >> >>
>> >> >
>> >> > more imporatanlty, does all this actually matter at all if the SNR
>> >> > seems
>> >> > to
>> >> > be ok.
>> >> >
>> >> > Denis
>> >> >
>> >> >>
>> >> >> On Thu, Aug 7, 2014 at 11:25 AM, Denis-Alexander Engemann
>> >> >> <denis.engemann at gmail.com> wrote:
>> >> >> > Dear list,
>> >> >> >
>> >> >> > I'm currently comparing group grand averages in a set of
>> >> >> > functional
>> >> >> > labels
>> >> >> > which are derived from the PALS B12 Brodmann parcellation. These
>> >> >> > were
>> >> >> > then
>> >> >> > used with subjects' stcs after morphing to fsaverage.
>> >> >> > Now I'm really struck that with surface orientation AND mean
>> >> >> > flipping
>> >> >> > the
>> >> >> > minima and maxima, even for dSPM shrink to values below 1 while
>> >> >> > the
>> >> >> > expected
>> >> >> > temporal dynamics are preserved. In the 'wild', that is, *before*
>> >> >> > averaging,
>> >> >> > the signed dSPMS are between -7 and 8, just as the
>> >> >> > free-orientation
>> >> >> > dSPM
>> >> >> > maxima are around 8 --- *after*  --- averaging.
>> >> >> >
>> >> >> > I'm wondering whether this could be a result of the morphing, the
>> >> >> > anatomical
>> >> >> > variability, or even the segmentation quality.
>> >> >> >
>> >> >> > Any hint would be appreciated.
>> >> >> >
>> >> >> > Denis
>> >> >> >
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