Re: [HCP-Users] Position of vertices in myelin maps and 164k sphere

[Timothy Coalson]

On Wed, Mar 29, 2017 at 3:47 PM, Nicola Toschi 
wrote:

> 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?
>

Mostly correct, though wheverever the "poles" happen to land will be
stretched out immensely, and any 2D smoothing applied naively will not only
result in much less smoothing near these poles, but it will also be highly
directional (anisotropic).  Additionally, if the spatial processing doesn't
"wrap around" and process the 2D image as if it were a tube, then it will
have a "seam" vertically on the sphere that data doesn't interact across.
Any other spatial processing that takes a naive 2D regularly spaced grid
approach will have similar biases.

Distances on the sphere surface are merely similar to real cortical
distances, but even using the sphere will be more consistent across the
surface than what you describe.  This is why I recommend doing any
smoothing or gradient steps in wb_command (or any other things it can do).

You mentioned a classifier, which often doesn't need spatial information,
or at least not fully regular structure - gifti or cifti files would work
just fine for a spatially-agnostic process, and even if it needs spatial
information, if it can be freeform associations rather than 2D regular
grid, then it is possible to do it without this resampling.

Tim



> 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  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/softw
>>> are/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 
>>> 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 
 Date: Wednesday, March 29, 2017 at 9:09 AM
 To: Matt Glasser , "hcp-users@humanconnectome.org"
 
 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 

Re: [HCP-Users] Position of vertices in myelin maps and 164k sphere

[Nicola Toschi]

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  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  
>> 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 
>>> Date: Wednesday, March 29, 2017 at 9:09 AM
>>> To: Matt Glasser , "hcp-users@humanconnectome.org" 
>>> 
>>> 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"
   
   wrote:


> Dear List,
>
> I am trying to do some 

Re: [HCP-Users] Position of vertices in myelin maps and 164k sphere

[Dierker, Donna]

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  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  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 
>> Date: Wednesday, March 29, 2017 at 9:09 AM
>> To: Matt Glasser , "hcp-users@humanconnectome.org" 
>> 
>> 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"
>>>  >> humanconnectome.org on behalf of
>>> tos...@med.uniroma2.it>
>>>  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 

Re: [HCP-Users] Position of vertices in myelin maps and 164k sphere

[Timothy Coalson]

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 
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 
> Date: Wednesday, March 29, 2017 at 9:09 AM
> To: Matt Glasser < glass...@wustl.edu>, "
> hcp-users@humanconnectome.org" 
> 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-boun...@humanconnectome.org on behalf of
> Nicola Toschi"  
>  tos...@med.uniroma2.it> 
>  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
>
>
> ___
> HCP-Users mailing 
> listHCP-Users@humanconnectome.orghttp://lists.humanconnectome.org/mailman/listinfo/hcp-users
>
> 

Re: [HCP-Users] Position of vertices in myelin maps and 164k sphere

[Nicola Toschi]

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 >

Date: Wednesday, March 29, 2017 at 9:09 AM
To: Matt Glasser >, 
"hcp-users@humanconnectome.org " 
>
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-boun...@humanconnectome.org on behalf of Nicola Toschi"    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


___
HCP-Users mailing list
HCP-Users@humanconnectome.orghttp://lists.humanconnectome.org/mailman/listinfo/hcp-users


The materials in this message are private and may contain Protected Healthcare 
Information or other information of a sensitive nature. If you are not the 
intended recipient, be advised that any unauthorized use, disclosure, copying 
or the taking of any action in reliance on the contents of this information is 
strictly prohibited. If you have received this email in error, please 
immediately notify the sender via telephone or return mail.




The materials in this message are private and may contain Protected 
Healthcare Information or other information of a sensitive nature. If 
you are not the intended recipient, be advised that any unauthorized 
use, disclosure, copying or the taking of any action in reliance on 
the contents of this information is strictly prohibited. If you have 
received this email in error, please immediately notify the sender via 
telephone or return mail.





___
HCP-Users mailing list
HCP-Users@humanconnectome.org
http://lists.humanconnectome.org/mailman/listinfo/hcp-users

Re: [HCP-Users] Position of vertices in myelin maps and 164k sphere

[Glasser, Matthew]

What operations beyond smoothing do you need?  There is wb_command 
-cifti-smoothing.

Peace,

Matt.

From: Nicola Toschi >
Date: Wednesday, March 29, 2017 at 9:09 AM
To: Matt Glasser >, 
"hcp-users@humanconnectome.org" 
>
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-boun...@humanconnectome.org on behalf of
Nicola 
Toschi" 

 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


___
HCP-Users mailing list
HCP-Users@humanconnectome.orghttp://lists.humanconnectome.org/mailman/listinfo/hcp-users


The materials in this message are private and may contain Protected Healthcare 
Information or other information of a sensitive nature. If you are not the 
intended recipient, be advised that any unauthorized use, disclosure, copying 
or the taking of any action in reliance on the contents of this information is 
strictly prohibited. If you have received this email in error, please 
immediately notify the sender via telephone or return mail.




The materials in this message are private and may contain Protected Healthcare 
Information or other information of a sensitive nature. If you are not the 
intended recipient, be advised that any unauthorized use, disclosure, copying 
or the taking of any action in reliance on the contents of this information is 
strictly prohibited. If you have received this email in error, please 
immediately notify the sender via telephone or return mail.

___
HCP-Users mailing list
HCP-Users@humanconnectome.org
http://lists.humanconnectome.org/mailman/listinfo/hcp-users

Re: [HCP-Users] Position of vertices in myelin maps and 164k sphere

[Nicola Toschi]

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-boun...@humanconnectome.org on behalf of
Nicola Toschi"  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


___
HCP-Users mailing list
HCP-Users@humanconnectome.org
http://lists.humanconnectome.org/mailman/listinfo/hcp-users



The materials in this message are private and may contain Protected Healthcare 
Information or other information of a sensitive nature. If you are not the 
intended recipient, be advised that any unauthorized use, disclosure, copying 
or the taking of any action in reliance on the contents of this information is 
strictly prohibited. If you have received this email in error, please 
immediately notify the sender via telephone or return mail.



___
HCP-Users mailing list
HCP-Users@humanconnectome.org
http://lists.humanconnectome.org/mailman/listinfo/hcp-users

Re: [HCP-Users] Position of vertices in myelin maps and 164k sphere

[Glasser, Matthew]

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-boun...@humanconnectome.org on behalf of
Nicola Toschi"  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
>
>
>___
>HCP-Users mailing list
>HCP-Users@humanconnectome.org
>http://lists.humanconnectome.org/mailman/listinfo/hcp-users



The materials in this message are private and may contain Protected Healthcare 
Information or other information of a sensitive nature. If you are not the 
intended recipient, be advised that any unauthorized use, disclosure, copying 
or the taking of any action in reliance on the contents of this information is 
strictly prohibited. If you have received this email in error, please 
immediately notify the sender via telephone or return mail.

___
HCP-Users mailing list
HCP-Users@humanconnectome.org
http://lists.humanconnectome.org/mailman/listinfo/hcp-users

[HCP-Users] Position of vertices in myelin maps and 164k sphere

[Nicola Toschi]

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


___
HCP-Users mailing list
HCP-Users@humanconnectome.org
http://lists.humanconnectome.org/mailman/listinfo/hcp-users