[FieldTrip] MNE Source Reconstruction Sanity Check

[E688205]

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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