Dear Donna and Tim,

thank you very much for your replies and insights. Yes, flatmaps is 
exactly what I was looking for!

For now, I was just taking the xyz positions on the sphere, converting 
to polar coordinates, interpolating and resampling the myelin on a 
regular grid along the two angular coordinates, hence resulting in a 2D 
image.

 From you explanation I understand that this would preserve topological 
neighborhood relationships between scalar values but not so much real 
(geodesic) distances, right?

Thanks a lot!

Nicola

On 3/29/2017 9:29 PM, Dierker, Donna wrote:
> Nicola,
>
> It is possible to generate a grid on a spherical surface like Alex Cohen did 
> in this paper:
>
> https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2705206/
>
> … and then fold those coordinates back up into midthickness configuration.
>
> The 164k_fs_LR vertex-wise correspondence is as good as can be expected, 
> given anatomical variability across subjects.
> Just having trouble understanding how you are using x,y,z coords with the 
> myelin scalars.
>
> Donna
>
>
>> On Mar 29, 2017, at 12:22 PM, Timothy Coalson <[email protected]> wrote:
>>
>> If by 2D images you mean pixel-based (like .png), then the spatial 
>> relationships can't be preserved very well.  In order to make flatmaps with 
>> moderate distortion, we have to add cuts to the cortical surface, which 
>> leaves connected parts of cortex separated by many blank pixels.  Our flat 
>> surfaces are intended for visualization, and we do not use them for 
>> processing.
>>
>> I would suggest doing as much of the spatial processing as you can with 
>> wb_command - we have smoothing, gradient, dilation, and a few other things - 
>> if you want it identical across subjects, rather than based on the cortical 
>> distances in each subject, you can use a group average surface along with 
>> the corresponding vertex area metric files - this is because group average 
>> surfaces have much less folding than individual subjects, and as such, 
>> geodesic distances along the cortical surfaces are much shorter than they 
>> should be.
>>
>> As your earlier emails implied use of matlab, you should note that you can 
>> load the gifti surface files into matlab, which contain vertex neighbor 
>> information, by using the gifti toolbox 
>> (https://www.artefact.tk/software/matlab/gifti/).  The easiest way to get 
>> vertex correspondence to the data in matlab is currently to use wb_command 
>> -cifti-separate to convert the surface data to gifti metric (.func.gii) 
>> files, and then load them instead.
>>
>> Tim
>>
>>
>> On Wed, Mar 29, 2017 at 9:24 AM, Nicola Toschi <[email protected]> 
>> wrote:
>> Hi,
>>
>> I'd like to arrive at a set of 2D images (e.g. 'unraveled' myelin maps 
>> obtained by cutting and stretching out the sphere), with     anatomical 
>> correspondence across subjects, which can be used as inputs to external 
>> proprietary algorithms (e.g. classification), so I'm pretty sure I'll need 
>> to step out of the Workbench.
>>
>> Thanks!
>>
>> Nicola
>>
>>
>>
>> On 03/29/2017 04:18 PM, Glasser, Matthew wrote:
>>> What operations beyond smoothing do you need?  There is wb_command 
>>> -cifti-smoothing.
>>>
>>> Peace,
>>>
>>> Matt.
>>>
>>> From: Nicola Toschi <[email protected]>
>>> Date: Wednesday, March 29, 2017 at 9:09 AM
>>> To: Matt Glasser <[email protected]>, "[email protected]" 
>>> <[email protected]>
>>> Subject: Re: [HCP-Users] Position of vertices in myelin maps and 164k sphere
>>>
>>> Hi Matt,
>>>
>>> thank you for your quick answer! That makes sense.
>>>
>>> I would like to do some spatial operations on the sphere that exploit 
>>> spatial neighborhood information (e.g. even simple smoothing or filtering 
>>> on the 2D surface), and have these operations be consistent across subjects.
>>>
>>> What would be the best way to go about this do you think? Incorporate the 
>>> exact vertex locations for each subject anyway, or ignore them and 
>>> (somehow) just use the fact that vertex n has the same neuroanatomical 
>>> meaning in every subject?
>>>
>>> Thanks again,
>>>
>>> Nicola
>>>
>>> On 03/29/2017 04:02 PM, Glasser, Matthew wrote:
>>>> We don¹t recommend using the ft_ tools with MRI data.  Instead use
>>>> ciftiopen/ciftisave/
>>>> ciftisavereset:
>>>>
>>>>
>>>> https://wiki.humanconnectome.org/display/PublicData/HCP+Users+FAQ
>>>>   item 2B
>>>>
>>>> As for your other question, the vertex indices have neuroanatomical
>>>> correspondence across subjects, but that often does not equate to having
>>>> the same 3D coordinates (as volumetric registration is not able to align
>>>> cortical areas across subjects).
>>>>
>>>> Peace,
>>>>
>>>> Matt.
>>>>
>>>> On 3/29/17, 8:41 AM,
>>>> "hcp-users-bounces@
>>>> humanconnectome.org on behalf of
>>>> Nicola Toschi"
>>>>   <hcp-users-bounces@
>>>> humanconnectome.org on behalf of
>>>> [email protected]>
>>>>   wrote:
>>>>
>>>>
>>>>> Dear List,
>>>>>
>>>>> I am trying to do some postprocessing on myelin and thickness maps (164k
>>>>> versions) contained in the MNINonLinear Directory of the Structural
>>>>> dataset (e.g. ${subject}.corrThickness_
>>>>> MSMAll.164k_fs_LR.dscalar.nii and
>>>>> ${subject}.MyelinMap_BC_
>>>>> MSMAll.164k_fs_LR.dscalar.nii)
>>>>> .
>>>>>
>>>>> I thought these data would all be in the same atlas space across
>>>>> subjects, hence I was expecting to find the same vertex coordinates for
>>>>> all subjects. Instead, when reading the data into matlab (
>>>>> 'ft_cifti_read' and gifti') every subject seems to have their own
>>>>> distinct vertex locations. Also, the spherical gifti surfaces appear to
>>>>> be sampled at different coordinates across subjects.
>>>>>
>>>>> Can I assume that, nonetheless, anatomical correspondence is preserved
>>>>> across subjects? Could I, for example, take the vertex locations from
>>>>> ${subject}.R.sphere.164k_fs_
>>>>> LR.surf.gii, associate the scalar values in
>>>>> ${subject}.MyelinMap_BC_
>>>>> MSMAll.164k_fs_LR.dscalar.nii to each vertex,
>>>>> interpolate on the sphere and assume that I can superimpose the results
>>>>> of this procedure across subjects?
>>>>>
>>>>> Thanks very much in advance!
>>>>>
>>>>> Nicola
>>>>>
>>>>>
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