[Mne_analysis] extracting ROI sources using mne_compute_raw_inverse

[Matt Panichello]

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
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