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

[Ghuman, Avniel]

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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