[Mne_analysis] mne-python lcmv

Jon Houck jhouck at mrn.org
Mon Mar 11 19:38:20 EDT 2013
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Hi Alex,

That fixed it, thanks!  The change cleared up the boundaries, and the dSPM
& LCMV solutions are now fairly similar.

I did run into one other thing with read_source_estimate
and save_stc_as_volume.  A volume source estimate read with
read_source_estimate is interpreted as a surface by is_surface, and so
can't be saved as a volume.  The this seems to happen because vertno is a
1-dimensional array with N elements, rather than a 2-dimensional 1xN array.
 My workaround after loading a volume stc has just been to reshape
stc.vertno [e.g., stc.vertno = stc.vertno.reshape(1,len(stc.vertno)) ].
 There's probably a better way, but my attempts to change
source_estimate.py have have broken too many other things downstream.

Jon




On Mon, Mar 11, 2013 at 2:58 PM, Alexandre Gramfort <
gramfort at nmr.mgh.harvard.edu> wrote:

> hi Jon,
>
> let me know if this :
>
>
> https://github.com/mne-tools/mne-python/commit/da303d3e1bbe013fd76819b26586949315bcf1c0
>
> fixes the problem
>
> Thanks for the bug report.
>
> Alex
>
> On Mon, Mar 11, 2013 at 4:39 PM, Martin Luessi
> <mluessi at nmr.mgh.harvard.edu> wrote:
> > Hi Jon,
> >
> > I can see distinct boundaries as well, so they do not seem to be caused
> by
> > your setup. I'm not sure what is causing this and we have to investigate
> why
> > the boundaries occur. The beamformer does correctly localize the
> activity,
> > have a look at the screenshot below (frame 61 in the nifit file,
> > corresponding to 100ms).
> >
> > As noted in the documentation, our LCMV code has not been heavily
> tested, so
> > the boundaries might indeed be caused by an error in the code.
> >
> > Note that the dSPM volume inverse (link below) does not show these
> > boundaries and also correctly localizes the bilateral activity. If it is
> an
> > option for you, you could use this method instead of LCMV.
> >
> > Best,
> >
> > Martin
> >
> >
> >
> http://martinos.org/mne/auto_examples/inverse/plot_compute_mne_inverse_volume.html#example-inverse-plot-compute-mne-inverse-volume-py
> >
> >
> >
> >
> > On 03/10/13 19:39, Jon Houck wrote:
> >>
> >> Hi all,
> >>
> >> I'm consistently seeing distinct boundaries within my lcmv estimates,
> >> and am wondering what might be wrong with my setup.  The images below
> >> are axial and coronal slices from the nifti file produced by the lcmv
> >> example with the sample data
> >>
> >> (
> http://martinos.org/mne/auto_examples/inverse/plot_lcmv_beamformer_volume.html
> ).
> >>    These boundaries are consistent throughout the timecourse (on
> >> Dropbox, see link below).
> >>
> >> I've re-run the volume data tutorial and the lcmv inverse example, but
> >> still see this effect. The slice and timecourse figures that I get from
> >> the example script look identical to the output on the website, so it
> >> may be something specific to the final step.  I'm using 0.6 of
> >> mne-python (downloaded this week) with EPD, and a recent nightly build
> >> of MNE.  Any ideas on what might be happening?
> >>
> >> Inline image 3Inline image 4
> >>
> >> https://www.dropbox.com/s/nkvw9mn4hio5yp7/lcmv_inverse.nii.gz
> >>
> >> Thanks,
> >>
> >> Jon
> >>
> >>
> >> _______________________________________________
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> >> Mne_analysis at nmr.mgh.harvard.edu
> >> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis
> >>
> >
> >
> > --
> > Martin Luessi, Ph.D.
> >
> > Research Fellow
> >
> > Department of Radiology
> > Athinoula A. Martinos Center for Biomedical Imaging
> > Massachusetts General Hospital
> > Harvard Medical School
> > 149 13th Street
> > Charlestown, MA 02129
> >
> > Fax: +1 617 726-7422
> >
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