<div dir="ltr">I can't think of anything offhand, it's been a bit too long since I've touched that bit of code.<div><br></div><div>Eric</div><div><br></div></div><div class="gmail_extra"><br><div class="gmail_quote">On Fri, Apr 24, 2015 at 4:56 AM, Matthias Treder <span dir="ltr"><<a href="mailto:matthias.treder@gmail.com" target="_blank">matthias.treder@gmail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr"><div><div><div>I tried following your recipe but got stuck. First of all I create 2 structures looking like that<br></div><br> tmin: 0<br> tstep: 1<br> vertices: [4098x1 uint32]<br> data: [4098x4098 double]<br><br></div>for left and right hemispheres separately. I took the vertices field (vertex numbers) from the oct-6-src.fif file, for each hemisphere. I export the files as "tmp_diagfile-lh.stc" and "tmp_diagfile-rh.stc" using mne_write_stc_file. <br><br></div>I then run "mne_make_movie --stcin $MYPATH/tmp_diagfile --subject CC110033 --morph fsaverage --smooth 5 --stc outfile" on the command line. It works for quite a bit and then gets stuck. It stops with the error "Overlay does not match the loaded surfaces", any ideas what is going wrong?<br><div><div><br></div><div>This is the full output:<br></div><div><br><br>Create movies and tif, rgb, jpeg, png, or w files using a precomputed inverse operator decomposition<br><br>stc input file : /imaging/dp01/freesurfer700/CC110033/bem/tmp_diagfile<br>stc file output : outfile<br> The input stc file will be assumed to contain current expectation value data<br>Subject : CC110033<br>Morph to : fsaverage<br>Visualization surface : inflated<br> Process both hemispheres<br><br>-------------------------------------------------------------------<br><br>read stc file /imaging/dp01/freesurfer700/CC110033/bem/tmp_diagfile-lh.stc<br>read stc file /imaging/dp01/freesurfer700/CC110033/bem/tmp_diagfile-rh.stc<br><br>-------------------------------------------------------------------<br>Loading inflated surfaces for subject CC110033...<br><br>Triangle file : created by dp01 on Mon Mar 30 05:39:51 2015 nvert = 136702 ntri = 273400<br> Triangle and vertex normals and neighboring triangles...[done]<br> Vertex neighbors...[done]<br> Distances between neighboring vertices...[820200 distances done]<br>Triangle file : created by dp01 on Mon Mar 30 08:24:03 2015 nvert = 140152 ntri = 280300<br> Triangle and vertex normals and neighboring triangles...[done]<br> Vertex neighbors...[done]<br> Distances between neighboring vertices...[840900 distances done]<br><br>-------------------------------------------------------------------<br><br><br>Loading inflated surfaces for morph destination fsaverage...<br><br>Triangle file : created by nicks on Wed Aug 15 21:20:39 2007 nvert = 163842 ntri = 327680<br> Triangle and vertex normals and neighboring triangles...[done]<br> Vertex neighbors...[done]<br> Distances between neighboring vertices...[983040 distances done]<br>Triangle file : created by nicks on Wed Aug 15 21:20:57 2007 nvert = 163842 ntri = 327680<br> Triangle and vertex normals and neighboring triangles...[done]<br> Vertex neighbors...[done]<br> Distances between neighboring vertices...[983040 distances done]<br>Adding morphing data...<br>Precomputed morphing maps successfully loaded.<br>-------------------------------------------------------------------<br><br>Parameters set.<br><br>-------------------------------------------------------------------<br><br>Movie production selected (from stc files)...<br>Loading geometry from /imaging/dp01/freesurfer700/fsaverage/surf/lh.sphere.reg...<br>Triangle file : created by greve on Thu Jun 8 19:17:51 2006 nvert = 163842 ntri = 327680<br> Triangle and vertex normals and neighboring triangles...[done]<br> Vertex neighbors...[done]<br> Distances between neighboring vertices...[61440 distances done]<br>Mapping lh fsaverage -> ico (5) ...[done]<br>Initialized outfile-lh.stc...<br>Loading geometry from /imaging/dp01/freesurfer700/fsaverage/surf/rh.sphere.reg...<br>Triangle file : created by greve on Thu Jun 8 19:17:51 2006 nvert = 163842 ntri = 327680<br> Triangle and vertex normals and neighboring triangles...[done]<br> Vertex neighbors...[done]<br> Distances between neighboring vertices...[61440 distances done]<br>Mapping rh fsaverage -> ico (5) ...[done]<br>Initialized outfile-rh.stc...<br>MNE at 0.00 ms...Overlay does not match the loaded surfaces<br><br><br><br><br><br><br><br></div></div></div><div class="HOEnZb"><div class="h5"><div class="gmail_extra"><br><div class="gmail_quote">2015-04-23 17:58 GMT+01:00 Matthias Treder <span dir="ltr"><<a href="mailto:matthias.treder@gmail.com" target="_blank">matthias.treder@gmail.com</a>></span>:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr">Great I will give it a go!<br></div><div><div><div class="gmail_extra"><br><div class="gmail_quote">2015-04-23 17:48 GMT+01:00 Eric Larson <span dir="ltr"><<a href="mailto:larson.eric.d@gmail.com" target="_blank">larson.eric.d@gmail.com</a>></span>:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr">Oh boy, I have no idea where that code lives anymore :) But it's a fairly simple procedure. The MNE-MATLAB toolbox allows you to construct your own source estimates, I believe, and if you can't I think it's just a struct with a few fields. The procedure to get the morph matrix from subject_a to fsaverage would be:<div><br></div><div>1. Make the .data property an identity matrix</div><div>2. Make the .vertno two arrays with the vertices equal to those from the "from" subject's decimated space. Be careful about 1- versus 0-indexing here.</div><div>3. Make .tmin and .tstep whatever is sensible, e.g. 0 and 1.</div><div>4. Save the source estimate to disk as a `.stc` file, e.g. "diagfile".</div><div>5. Use mne_make_movie with the following parametrs: --stcin diagfile, --subject subject_a, --morph fsaverage, --smooth n_steps, --stc outfile (see help for descriptions).</div><div>6. Read "outfile" in MATLAB -- the .data parameter should be the smoothing matrix.</div><span><font color="#888888"><div><br></div><div>Eric</div><div><br></div></font></span></div><div><div><div class="gmail_extra"><br><div class="gmail_quote">On Thu, Apr 23, 2015 at 9:39 AM, Matthias Treder <span dir="ltr"><<a href="mailto:matthias.treder@gmail.com" target="_blank">matthias.treder@gmail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr"><div>You've got a point here. MNE-Python is a great piece of software, but I have a Matlab/Bash processing pipeline and it would be a hassle to add Python. But regarding the second option, you said "A long time ago I used a diagonal matrix in an STC file to get the same
transformation using the mne-C tools, which you could presumably also
still do."<br><br></div><div>Frankly speaking, I don't know how to create this STC file with a diagonal matrix to obtain the transformation matrix. Do you have any code that you'd be willing to post?<span><font color="#888888"><br><br></font></span></div><span><font color="#888888"><div>Matthias<br></div></font></span></div><div><div><div class="gmail_extra"><br><div class="gmail_quote">2015-04-23 17:24 GMT+01:00 Eric Larson <span dir="ltr"><<a href="mailto:larson.eric.d@gmail.com" target="_blank">larson.eric.d@gmail.com</a>></span>:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr">I can't think of any problem offhand with doing that -- I'm unsure what advantages (or disadvantages) it would have over the existing data smoothing procedure, though. One advantage to using the existing data smoothing procedure is that AFAIK it is widely used, so any drawbacks or bugs are likely to have been found and fixed already.<span><font color="#888888"><div><br></div><div>Eric</div></font></span><div><div><div><br></div><div class="gmail_extra"><br><div class="gmail_quote">On Thu, Apr 23, 2015 at 9:15 AM, Matthias Treder <span dir="ltr"><<a href="mailto:matthias.treder@gmail.com" target="_blank">matthias.treder@gmail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr">@Rezvan: Follow up to your question, in case this was not clear from the previous posts: Since both inverse modelling and morphing are linear operations you can exchange them. <br>However, connectivity analysis is usually not linear, e.g. power envelope correlation. So you cannot simply linearly combine your nonlinear estimates, this is why everything else has to be done before you calculate your connectivity matrix.<br></div><div><div><div class="gmail_extra"><br><div class="gmail_quote">2015-04-23 12:33 GMT+01:00 Rezvan Farahi <span dir="ltr"><<a href="mailto:rezvan.farahi@gmail.com" target="_blank">rezvan.farahi@gmail.com</a>></span>:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr">Hi,<div><br></div><div>One question following Eric's explanations regarding data morphing.</div><div>So far in my analyses, my understanding was that I can do morphing just before group analysis (i.e. after computing connectivity). And as Eric said since morphing procedure is something linear I assumed there is no difference if I first morph source signals then compute connectivity or the other way around</div><div><br></div><div>But both Denis and Matthias suggested data morphing before connectivity. Does it mean that it would introduce any biases if I compute it the other way around?</div><div><br></div><div>Many thanks,</div><div>Rezvan</div></div><div><div><div class="gmail_extra"><br><div class="gmail_quote">On Thu, Apr 23, 2015 at 1:53 AM, Eric Larson <span dir="ltr"><<a href="mailto:larson.eric.d@gmail.com" target="_blank">larson.eric.d@gmail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr">Hey Per,<div><br></div><div>There are two different "morph" operations being talked about.</div><div><br></div><div>I have never morphed source spaces, but this is my understanding of how it works. Morphing source spaces means taking the subset of vertices from subject's A's brain mesh (typically white) that are in that subject's existing source space, and finding the vertices for subject B that are as close as possible based on A and B's spherical coregistration / morph map. In other words, the source space for subject B is created by subsampling subject B's high density cortical mesh vertices using the spherical-morphing correspondence of subject A's subsampled mesh. In physical space, the vertices from subject A could thus be in very different positions from their counterparts for subject B, but conceptually each vertex from subject A is intended to be in an equivalent anatomical location in subject B. Since subject A's source space was originally subdivided in a way that to some extent evenly subsampled its physical space, the differences in cortical folding between subjects A and B may result in subject B's (morphed) source space vertices having a spacing that is less uniform than a source space that was created for subject B directly. In this scheme, data does not need to be morphed between one subject and another, because the vertices in their source spaces are the same, anatomically speaking.</div><div><br></div><div>The other type of morphing is the one I talked about, data morphing. This is required when subject A has some source space created for it using any subsampling, and subject B has a source space created for it with any subsampling independently. The vertices from subject A were created independently from those in subject B (e.g., vertex 1 in A might map to 1093 in B, and 1093 in A might map to 5921 in B, etc.) There is a morphing procedure that allows you to map activity (i.e., source estimates) from subject A to subject B or vice-versa via a linear transformation. This transformation also makes use of the morph maps / spherical anatomical alignment of A and B, but it uses a smudging-like procedure to effectively push data from one subsampled mesh onto the other. This is also detailed in the manual somewhere. This is the procedure I am most familiar with -- create source space for each subject, arrive at source estimates for each subject in their own space, and for group analyses, use mne-python or MNE-C to morph all subjects' data to fsaverage's ico-5 source space for analysis.</div><div><br></div><div>Cheers,</div><div>Eric</div><div><br></div></div><div><div><div class="gmail_extra"><br><div class="gmail_quote">On Wed, Apr 22, 2015 at 4:40 PM, Denis-Alexander Engemann <span dir="ltr"><<a href="mailto:denis.engemann@gmail.com" target="_blank">denis.engemann@gmail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr">To elaborate on my note, this is what I do exactly to deal with this:<div><br></div><div><a href="https://gist.github.com/dengemann/f90cf354816273fe87eb" target="_blank">https://gist.github.com/dengemann/f90cf354816273fe87eb</a><br></div><div><br></div><div>It's a genarator function that you can pass to `mne.connectivity.spectral_connectivity`</div><div><br></div><div>Hope this is useful for you,</div><div><br></div><div>Denis</div><div><div>
<div class="gmail_extra"><br><div class="gmail_quote">2015-04-23 0:30 GMT+02:00 Per Arnold Lysne <span dir="ltr"><<a href="mailto:lysne@unm.edu" target="_blank">lysne@unm.edu</a>></span>:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">Hello All,<br>
<br>
Apologies for belaboring this thread - and thanks for everyone's useful comments. It appears that I may not understand the morphing option in mne_setup_source_space as well as I thought.<br>
<br>
I understand Matthias' original point of wanting to analyze individual subjects' in a common, "canonical" source space. I had assumed that, when morphing was done in mne_setup_source_space (i.e. --subject MySubject --morph fsaverage), a common space would be the result (the fsaverage space) and that the forward and inverse operators would be adjusted to compensate for the changed cortical surface. In other words, there would be no loss of accuracy and that fsaverage would be the new, common source space. Am I missing something?<br>
<br>
In reviewing the 2.7.3 manual I see a comment, "The drawback of this approach is that the spacing between source locations in the “morph” subject is not going to be as uniform as it would be without morphing" (under --morph, p22). Does this mean that the original subject's vertices are not being translated directly to those on fsaverage? In other words, although the new morphed surface may match fsaverage, there is not a common set of vertices shared between them?<br>
<br>
(This complicates things for me because I am working on a group localization and am expecting the morphed individual subjects to have a common number of vertices in comparable locations.)<br>
<br>
Thanks again,<br>
<span><br>
Per Lysne<br>
University of New Mexico<br>
<br>
</span>________________________________________<br>
From: <a href="mailto:mne_analysis-bounces@nmr.mgh.harvard.edu" target="_blank">mne_analysis-bounces@nmr.mgh.harvard.edu</a> <<a href="mailto:mne_analysis-bounces@nmr.mgh.harvard.edu" target="_blank">mne_analysis-bounces@nmr.mgh.harvard.edu</a>> on behalf of Alexandre Gramfort <<a href="mailto:alexandre.gramfort@telecom-paristech.fr" target="_blank">alexandre.gramfort@telecom-paristech.fr</a>><br>
Sent: Wednesday, April 22, 2015 7:48 AM<br>
To: Discussion and support forum for the users of MNE Software<br>
Subject: Re: [Mne_analysis] mne_setup_source_space with --morph option => morphing fsaverage onto subject<br>
<div><div><br>
hi Matthias,<br>
<br>
what you do makes sense and I would do the same.<br>
<br>
Not sure what's going wrong here. Maybe somebody has time<br>
to look at this problem with the triangles.<br>
<br>
Alex<br>
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