[Mne_analysis] GSoC Update: dSPM source reconstruction for the right amygdala in the SPM dataset

Tue May 27 13:34:03 EDT 2014

Thanks everyone for the feedback. I've put up the current code as a pull
request, with the understanding that there will be major changes before its
merged.

On Mon, May 26, 2014 at 11:47 PM, Alexandre Gramfort <
alexandre.gramfort at telecom-paristech.fr> wrote:

> hi everyone,
>
> I agree with that have been said. We're at the beginning
> of the GSOC and our first objective is to have the machinery
> working. Then we'll do the science right.
>
> @sheraz : When I said we need the cortical surface in the source
> space to not just estimate the sources on the amygdala it
> is precisely because I had in mind the issue you raised.
>
> Alan please continue to assemble the machinery, maybe next time
> avoid the stats at the end ( :-) ) as it is certainly not a good
> conclusion.
>
> cheers,
> Alex
>
> PS : with all this interest on this topic, it looks like we're going
> to have a lot of early adopters to test :)
>
> On Tue, May 27, 2014 at 12:30 AM, Hari Bharadwaj
> <hari at nmr.mgh.harvard.edu> wrote:
> > I would add that the issue of having the software machinery to
> potentially
> > try localizing deep sources is a separate issue from trusting the
> obtained
> > solution..Thus, for the purposes of demos and code development,
> localizing
> > simulated deep source activity might be the best scenario where the
> ground
> > truth is known..
> >
> > If real data demos are really desired, something like the ABR might be a
> > potentially safer candidate...
> >
> >
> >
> > "Ghuman, Avniel" <ghumana at upmc.edu> wrote:
> >>
> >> I should say though, things like Hippocampus and cerebellum might be
> more
> >> feasible.
> >>
> >>> On May 26, 2014, at 5:33 PM, "Ghuman, Avniel" <ghumana at upmc.edu>
> wrote:
> >>>
> >>> It also might be a reasonable time to discuss a bit of the physics and
> >>> physiology of what MEG is and is not sensitive to. MEG is not
> particularly
> >>> sensitive to four things:
> >>>
> >>> 1. Radial sources
> >>> 2. Deep sources
> >>> 3. Sources where the neurons are not aligned
> >>> 4. Even worse are sources with randomly aligned neurons that are
> >>> relatively spherical (and small)
> >>>
> >>> The amygdala strikes out on the bottom three. Thus, in my opinion, it
> is
> >>> fairly unlikely that MEG can pick up activity from the amygdala. I
> would
> >>> love to hear other opinions.
> >>>
> >>> Best wishes,
> >>> Avniel
> >>>
> >>> Avniel Ghuman, Ph.D.
> >>> Director of MEG Research
> >>> Assistant Professor of Neurological Surgery, Neurobiology, and
> Psychiatry
> >>> Faculty in the Center for the Neural Basis of Cognition
> >>> University of Pittsburgh
> >>>
> >>> ________________________________
> >>>
> >>> From: mne_analysis-bounces at nmr.mgh.harvard.edu
> >>> [mne_analysis-bounces at nmr.mgh.harvard.edu] on behalf of
> >>> sheraz at nmr.mgh.harvard.edu [sheraz at nmr.mgh.harvard.edu]
> >>> Sent: Monday, May 26, 2014 5:13 PM
> >>> To: Discussion and support forum for the users of MNE Software
> >>> Subject: Re: [Mne_analysis] GSoC Update: dSPM source reconstruction for
> >>> the right amygdala in the SPM dataset
> >>>
> >>> hi Alex,
> >>>
> >>> my 2 cents, if you look at the waveform carefully, the responses
> follows
> >>> the same time course as the cortical responses. Putting this example
> will
> >>> give very wrong impression about MEG and deep sources.
> >>>
> >>> Putting premature examples might not be great idea :)
> >>>
> >>> Sheraz
> >>>
> >>> hi Alan,
> >>>
> >>> if the demo aims to demonstrate inverse modeling with deep structures
> >>> I would put it in examples/inverse
> >>>
> >>> Alex
> >>>
> >>>
> >>>> On Mon, May 26, 2014 at 9:00 PM, Alan <leggitta3 at gmail.com> wrote:
> >>>> Hi Alex,
> >>>>
> >>>> Thanks. I will make that my next step. Where in the mne code structure
> >>>> should I put this? I was thinking in under examples/datasets.
> >>>>
> >>>> Alan
> >>>>
> >>>>
> >>>> On Sat, May 24, 2014 at 5:43 AM, Alexandre Gramfort
> >>>> <alexandre.gramfort at telecom-paristech.fr> wrote:
> >>>>
> >>>>> hi Alan,
> >>>>>
> >>>>> nice work !
> >>>>>
> >>>>> I have a few comments to make on the code so a PR
> >>>>>  on
> >>>>> github would allow
> >>>>> me to comment inline.
> >>>>>
> >>>>> Regarding the approach, it does what it is supposed to do in a pretty
> >>>>> elegant way, but
> >>>>> it is dangerous to only run the inverse method on such a tiny
> >>>>> source space. An activation from the cortex would necessarily be
> >>>>> projected
> >>>>> to the amygdala. My hunch, is that an LCMV beamformer would suffer
> >>>>> less from this.
> >>>>>
> >>>>> I think the next step would be to be able to combine a surface source
> >>>>> space
> >>>>> and the deep volume source space you create.
> >>>>>
> >>>>> best,
> >>>>> Alex
> >>>>>
> >>>>>
> >>>>>> On Sat, May 24, 2014 at 1:10 AM, Alan <leggitta3 at gmail.com> wrote:
> >>>>>> Hello,
> >>>>>>
> >>>>>> I worked through creating a discrete source space of the right
> >>>>>
> >>>>> amygdala
> >>>>>>
> >>>>>> and
> >>>>>> performing dSPM source reconstruction in the SPM dataset. My code is
> >>>>>> available on my GSoC blog.
> >>>>>>
> >>>>>>
> >>>>>>
> >>>>>>
> http://misterbrainley.blogspot.com/2014/05/day-5-putting-it-together.html
> >>>>>>
> >>>>>> I've attached a copy of the results for data filtered between 1-45
> >>>>>
> >>>>> hz.
> >>>>>>
> >>>>>> The
> >>>>>> grey region indicates statistical significance using an independent
> >>>>>> t-test
> >>>>>> with fdr correction.
> >>>>>>
> >>>>>> I would greatly appreciate any feedback you could offer.
> >>>>>>
> >>>>>> Thanks!
> >>>>>> Alan
> >>>>>>
> >>>>>>
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