[Mne_analysis] extracting ROI sources using mne_compute_raw_inverse

[Matt Panichello]

Hi Hari,

Your hunch about the source orientation was correct. I took a look at the
individual traces at each vertex that were used in calculating the evoked
average for the label; even with the --align_z option the polarity wasn't
consistent across all of the vertices. I baseline corrected the traces to
zero and took their absolute value before averaging, and now the evoked
response looks fine. Thanks for pointing out the problem to me; this had
been a big headache.

Thanks,

Matt


On Wed, Oct 19, 2011 at 12:48 PM, Hari Bharadwaj
<hari at nmr.mgh.harvard.edu>wrote:

> Hi Matt,
>   I'm not sure if the implementation of mne_compute_raw_inverse ignores
> the --align_z flag if (1) --picknormalcomp is used and/or if (2) Your
> source space contains sources of fixed orientation... So unfortunately,
> I don't have a better suggestion than to try leaving out the
> picknormalcomp option or if you are using a fixed orientation solution
> try loose..
>
> I can share python code (that's not tested much) that works with a fixed
> orientation inverse operator if you are interested in playing with it..
>
> Regards,
> Hari
>
>
>
> On Wed, October 19, 2011 12:09 pm, Matt Panichello wrote:
> > Hi Hari,
> >
> > Thanks for your response. I had included the --align_z flag with
> > mne_compute_raw inverse, so unfortunately I don't think this is the
> issue.
> > Do any other possibilities come to mind?
> >
> > This is a shot in the dark on my part, but the script I inherited for
> this
> > analysis also included the --picknormalcomp flag with
> > mne_compute_raw_inverse. Could this be causing trouble for any reason?
> >
> > Thanks again,
> >
> > Matt
> >
> >
> > On Tue, Oct 18, 2011 at 6:24 PM, Hari Bharadwaj
> > <hari at nmr.mgh.harvard.edu>wrote:
> >
> >> Hi Matt,
> >>   This is just a hunch.. So in viewing using mne_analyze, for the
> >> options
> >> you have selected you are averaging the absolute value of the signal
> >> across vertices.. On the other hand when using mne_compute_raw_inverse,
> >> you seem to be doing a signed averaging (Which is the correct thing to
> >> do given you want to do frequency analysis). What happens when you
> >> average the signed signal across vertices is that since the orientation
> >> of the sources is not the same and the MNE spreads, some vertices have
> >> positive polarity deflections and some have negative polarity
> >> deflection and they cancel.. The avoid this cancellation there is a
> >> --align_z option  in mne_compute_raw_inverse that you could use which
> >> is described in the manual.
> >>
> >> Hope it helps,
> >>
> >>
> >> Regards,
> >> Hari
> >>
> >>
> >> On Tue, October 18, 2011 6:02 pm, Matt Panichello wrote:
> >> > Hi everyone,
> >> >
> >> > I am trying extract the sources from a series of functional-anatomical
> >> > rois
> >> > for frequency analysis, but am having some trouble getting good
> >> quality
> >> > data. I'm using mne_compute_raw_inverse to extract the data before
> >> loading
> >> > it into matlab.
> >> >
> >> > Subjects completed an object recognition task during recording. To
> >> check
> >> > the
> >> > quality of the extracted data, I've been averaging the timecourses in
> >> an
> >> > early visual ROI across all vertices and visualizing the evoked
> >> response.
> >> > For some of the subjects (e.g., S003-a, attached), the evoked response
> >> > looks
> >> > normal. The evoked response for many subjects, however, looks like
> >> > senseless
> >> > noise (S007-a) or shows an unexpected negative deflection (S010-a).
> >> >
> >> > I don't think these problems are solely due to the labels I've drawn,
> >> or
> >> > to
> >> > the intrinsic quality of the raw data. This is because when I average
> >> the
> >> > raw data for each subject using mne_process_raw, and then view the
> >> average
> >> > of the vertices inside the same ROIs using mne_analyze, the evoked
> >> > responses
> >> > all look as expected, often very different from the averages produced
> >> from
> >> > my mne_compute_raw_inverse pipeline (see S007-b and S010-b).
> >> >
> >> > Does anyone have an idea what the problem might be? Are there any
> >> special
> >> > considerations to take in account when using mne_compute_raw_inverse
> >> to
> >> > extract sources from ROIs? Why might the label averages using the two
> >> > different methods described look so different?
> >> >
> >> > Thanks in advance for any help,
> >> >
> >> > Matt
> >> > _______________________________________________
> >> > Mne_analysis mailing list
> >> > Mne_analysis at nmr.mgh.harvard.edu
> >> > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis
> >>
> >>
> >> --
> >> Hari Bharadwaj
> >>
> >>
> >>
> >>
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> >
> >
> > --
> > Matthew Panichello
> > Research Coordinator, Bar Group
> > Massachusetts General Hospital
> > Phone: 617-726-9034
> >
>
>
> --
> Hari Bharadwaj
>
>
>


-- 
Matthew Panichello
Research Coordinator, Bar Group
Massachusetts General Hospital
Phone: 617-726-9034
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