I meant the volume to surface mapping, so it sounds like your plan should work 
fine.

Peace,

Matt.

From: Claude Bajada <c.baj...@fz-juelich.de<mailto:c.baj...@fz-juelich.de>>
Date: Friday, August 4, 2017 at 5:17 AM
To: Matt Glasser <glass...@wustl.edu<mailto:glass...@wustl.edu>>, Timothy 
Coalson <tsc...@mst.edu<mailto:tsc...@mst.edu>>
Cc: "hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>" 
<hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] Follow-up to: Obtaining the MNI coordinates of cluster 
peaks in the melodic_IC.dscalar.nii ICA maps


Thanks for the reply Matt.

I didn't quite understand what you mean by: " I would do your mapping in 
individual subjects."

In case it was not clear, the tractography is of course performed in individual 
subject space using the MSMAll surfaces in the subject directory of the T1w 
folders. My result is data associated with those surfaces and I was planning on 
averaging the data across participants.

Claude

On 04.08.2017 00:28, Glasser, Matthew wrote:
Tractography has quite strong folding-related biases.  Using MSMAll might 
attenuate those some and focus more on the parts of tractography that aren’t 
biased by folding.  I would do your mapping in individual subjects.

Peace,

Matt.

From: 
<hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>>
 on behalf of Claude Bajada 
<c.baj...@fz-juelich.de<mailto:c.baj...@fz-juelich.de>>
Date: Thursday, August 3, 2017 at 4:54 PM
To: Timothy Coalson <tsc...@mst.edu<mailto:tsc...@mst.edu>>
Cc: "hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>" 
<hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] Follow-up to: Obtaining the MNI coordinates of cluster 
peaks in the melodic_IC.dscalar.nii ICA maps


Thanks Tim and Michael,

I am thinking about doing some work with some statistics derived from 
tractography (starting from the vertices on gray white matter interface and 
then projecting those statistics onto their respective vertices) My thought 
however, is whether the MSMAll (or functional registration) is the most 
appropriate registration for working with what is essentially structure. I 
suppose that one could argue that tracts should be more aligned to function 
than gyral anatomy but it is not obviously true. Would you recommend using a 
more "anatomical" group registration in this case (eg the 
${subject}.${side}.32k_fs_LR.surf.gii files over the MSMAll)?

Claude

On 03.08.2017 21:46, Timothy Coalson wrote:
On Thu, Aug 3, 2017 at 9:03 AM, Claude Bajada 
<c.baj...@fz-juelich.de<mailto:c.baj...@fz-juelich.de>> wrote:

Hi all,

I am starting a new thread because while my question is related to the one ask, 
it is tangential.

Can I confirm that what you mean by not averaging surfaces is that one should 
not average the vertex points across gifti surfaces to create a so-called 
"average surface"

Can I ask then, is averaging the data associated with vertices from individual 
subjects and plotting the result on a template surface (eg colin or a just 
using an individual as a template) also problematic?

Ah, I missed this question on my first read.  You make a good point, that 
individual surfaces have some bias away from the group.  With a good 
registration, doing this could tell you interesting things about the subject 
(the relative size of a particular group-identified feature on this 
individual).  Strictly speaking, though, it will cause some bias in the display 
of group results, in terms of the size of features.

Displaying on group average surfaces may actually have some bias too - 
different regions will lose different amounts of folding detail (because of 
differences in variability), which also means losing surface area (and 
therefore features in high variability regions may *look* smaller than they 
should on group surfaces).  For processing group-average data, we compensate 
for this surface area loss with the use of vertex areas.  I'm not entirely sure 
whether the surface inflation method we use tries to keep the vertex areas 
relatively undistorted, but if so, then the group very_inflated surfaces may 
have the least bias from this effect (less folding present in the surfaces 
before averaging, so less surface area lost due to averaging).  Note that this 
bias would be only in visual size, not in intensity or sampling density.

Back on the single-subject template topic, as a practical matter, we can't yet 
segment individual cerebellums into surfaces reliably, so carefully acquired 
and processed single subjects such as colin are the best we can do at present 
for displaying the cerebellum as a surface.
Regards,
Claude

On 03.08.2017 02:05, Timothy Coalson wrote:
On Wed, Aug 2, 2017 at 6:02 PM, James Morrow 
<james.mor...@monash.edu<mailto:james.mor...@monash.edu>> wrote:
Thanks Tim and Matt for the detailed responses.

I agree that mapping to volumes is sub-optimal. Our goal is to identify coords 
to be used as targets for brain stimulation with TMS. We need MNI coords for 
neuronavigation. Given the extent of the TMS field, we have some tolerance for 
imprecisions in the mapping.

I see.  We generally get asked these questions in the context of fMRI analysis, 
hence our reluctance.

How does the neuronavigation go from MNI coordinates to subject coordinates, do 
you happen to have a reasonable T1w MRI scan of your subjects?  I don't know 
how big the TMS field is, and I hadn't looked at the distance from subject to 
group average surfaces before, but in one of the HCP subjects, I got a maximum 
of 2cm distance from the group average surface (using midthickness surfaces), 
which occurred in a few specific locations, while 90% of the surface was 1cm 
distance or less.

Can I clarify – was the ICA run on the volumes and then later mapped on to 
surfaces, or was it performed on the surface data? If the former, are the 
original volumetric results for the ICA of each subject available anywhere in 
.nii format?

Cheers,
James

James Morrow
Research assistant
Brain & Mental Health Laboratory

Monash Institute of Cognitive and Clinical Neurosciences
School of Psychological Sciences
Monash University
c/o MBI, 770 Blackburn Road
Clayton VIC 3800
Australia

T: 03 9902 9768
E: james.mor...@monash.edu<mailto:amy.al...@monash.edu>
www.med.monash.edu.au/psych/bmh/<http://www.med.monash.edu.au/psych/bmh/>

[http://www.med.monash.edu.au/assets/images/psych/bmh/bannerbmh.jpg]<http://www.med.monash.edu.au/psych/bmh/>
[http://med.monash.edu.au/psych/email-sig/miccn-email-sig.jpg]<http://www.monash.edu/neuro-institute/>

On 3 August 2017 at 07:00, Timothy Coalson 
<tsc...@mst.edu<mailto:tsc...@mst.edu>> wrote:
As Matt said, "MNI coordinates" of functionally-aligned cortical surface 
features don't have much meaning, similar to how T1w-aligned MNI space volumes 
don't have good cortical functional alignment (except in a few low-variability 
regions).  We have shown that group average surface coordinates do not follow 
the MNI cortical ribbon (see attached image that simply shows the average white 
and pial contours on top of the MNI nonlinear template).  The ICA maps 
themselves are also more informative than just the vertices at their peaks.

Surface group results should not be turned into volumetric files, group average 
surfaces do not have much folding left in them, and as such they do not match 
the MNI template anymore - this is due to folding incompatibilities between 
subjects, but also due to using functional surface registration instead of 
folding patterns.  Using the individual surfaces to map to the volume and then 
averaging across them would spread your data out just as badly as doing 
volume-based analysis of cortex, so this is also highly discouraged.

Despite strongly advising you not to do what you outlined, I will tell you what 
commands you would need.  The -cifti-extrema command will output a map with 1s 
and -1s at each local extrema.  The surface it uses is for neighbor information 
and distance computation - this isn't as critical as coordinates are, as it 
merely sets the maximum possible density of extrema (what you could get from a 
very noisy map).  You will need to use a threshold or other method to exclude 
local extrema that are outside the high-valued area.  We use midthickness 
surfaces for this kind of thing (and when doing some important spatial 
operation, we use corrected vertex areas to compensate for the loss of folding 
in group average surfaces, see -metric-smoothing).

You can extract the coordinates of a surface file with 
-surface-coordinates-to-metric, and you can use -cifti-separate on the 
-cifti-extrema result to get those as metric files, so that the indices will 
match, so that you can use them in matlab or some other tool for ad-hoc 
analysis (alternatively, use -cifti-create-dense-from-template to put the 
surface coordinates into a cifti file).  Since we advise not to do this with 
any group data, you are on your own here (finding the coordinates in a bunch of 
individuals and averaging those will give exactly the same bad answer, 
reflecting the fact that many/most functional areas have notably different MNI 
coordinates in each individual).

Tim


On Tue, Aug 1, 2017 at 7:46 PM, James Morrow 
<james.mor...@monash.edu<mailto:james.mor...@monash.edu>> wrote:
Hi,

We have recently downloaded the HCP900 Parcellation + Timeseries + Netmats (820 
Subjects) dataset.

We would like to obtain the MNI coordinates of cluster peaks in the 
melodic_IC.dscalar.nii ICA maps.

Is there any way to do this?

Is the –cifti-extrema function of wb_command the correct command? It requires a 
surface file, but I’m not sure which would be most appropriate for the group 
ICA results.

Alternatively, would there be a way to convert the dscalar file into a standard 
volumetric nii so that I can use standard FSL tools?

Thanks

James Morrow


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