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

Fri Aug 8 09:47:47 EDT 2014

On Fri, Aug 8, 2014 at 3:38 PM, dgw <dgwakeman at gmail.com> wrote:

> 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.
>
>
If only all this wouldn't be that impractical wrt to resources consumption
...

>  >
> >>
> >> 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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