[FieldTrip] MNE Source Reconstruction Sanity Check

Fri Jul 25 09:29:55 CEST 2014

Hi Roey,

Since you do not have the subject’s anatomical MRI and are using the colin27 
standard brain, you can just use the template BEM headmodel in 
fieldtrip/template/headmodel (see for example, 
http://fieldtrip.fcdonders.nl/template/headmodel) . This head model is based 
on the colin27 brain.

Best,

Jim

From: fieldtrip-bounces at science.ru.nl 
[mailto:fieldtrip-bounces at science.ru.nl] On Behalf Of Roey Schurr
Sent: donderdag 24 juli 2014 20:50
To: FieldTrip discussion list
Subject: Re: [FieldTrip] MNE Source Reconstruction Sanity Check

Dear Jim,

Thank you for drawing my attention to this problem. I have actually tried 
building a realistic head model using OPENMEG but encountered some 
compitability problems since our lab does not use Linux. This is indeed one 
of the most important (short) future tasks - being able to use such 
realistic head models.

Best,

roey

On Thu, Jul 24, 2014 at 6:34 PM, E688205 <j.herring at fcdonders.ru.nl> wrote:

Dear Roey,

To add to Diego's comments, since you are dealing with EEG data a single 
sphere headmodel is not a good idea because it does not take into account 
the differences in conductivity between the skull, scalp, and brain. This is 
not a problem for MEG but is important for EEG. Therefore it is better to 
use, for example, a BEM head model.

Best,

Jim

On 23 jul. 2014, at 16:38, "Lozano Soldevilla, D. (Diego)" 
<d.lozanosoldevilla at fcdonders.ru.nl> wrote:

Dear Roey,

In my opinion it's definitely not a good idea to compute MNE using 19 
sensors. There are studies that have found a drastic localization precision 
from 31 to 63 electrodes and further improvements till 123:

http://www.ncbi.nlm.nih.gov/pubmed/15351361 (see figure 1)
http://www.ncbi.nlm.nih.gov/pubmed/12495765

Although it's very difficult to know the "minimum" number of electrodes 
needed to accurately localize a given source (it depends on the strength of 
the source you want to localize, source reconstruction algorithm, data 
noise...), 19 electrodes are too low to trust the results you can get.

best,

Diego

  _____

>From roeysc at gmail.com  Mon Jul 21 11:21:32 2014
From: roeysc at gmail.com (Roey Schurr)
Date: Mon, 21 Jul 2014 12:21:32 +0300
Subject: [FieldTrip] MNE Source Reconstruction Sanity Check
Message-ID: 
<CAHm4wZBRYo4fV63EL9yXaAQ_W43cHF_8J2b+rNyzd55x4aRviw at mail.gmail.com>

Dear fieldtrippers,

I want to do a sanity check on mne source reconstruction.

I'm working on continuous EEG recordings (19 electrodes), estimating the
source reconstruction activity using the *mne* (minimum norm estimate)
method, a *template MRI* (Colin27) and a *singlesphere* headmodel. As a
sanity check for the source reconstruction itself, I wanted to compare
conditions in which I could estimate the loci of significant changes, e.g.:
rest vs movement of the hand, moving the right hand vs the left hand, etc.
I have about 60 seconds of recording for each condition.

What I did was:

1) Segment the recording of each condition into many "trials" of 2 seconds
each.

2) For each trial, average the activity in each of the 90 ROIs of the aal
atlas (I excluded the cerebellum from the source reconstruction).

I was wondering what comparison would be best in this case. Since this is
not Evoked Responses data, I find it hard to find relevant ideas, and would
like to hear your thoughts.

1) I did a frequency analysis (mtmfft) in conventional bands of interest
and ran ft_freqstatistics on the resulting structures (using ttest2 and the
bonferoni correction for the multiple comparison problem). This gave some
results, however for most conditions they are not very encouraging (the
ROIs that showed significant differences were not close to those that I
have assumed).

*QUESTION 1*: do you think this is a proper method? Note that I did not use
a frequency based source reconstruction in the first place, because I'm
ultimately interested in the time course in the source space.

2) I was wondering if a cluster based permutation test is impossible to use
here, since this is a continuous recording, so clustering according to time
adjacency seems irrelevant.

*QUESTION 2*: is it possible to use a cluster based statistical test here?
If so, it could be better than a-priori averaging the source activity in
the atlas ROIs, which could mask some of the effects, if they are located
in a small area.

3) Another possibility is looking at the data itself. Unfortunately I
encountered some problems using ft_sourcemovie, though this is a subject
for a different thread.

Any thoughts and advice are highly appreciated!

Thank you for taking the time,

roey

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