Re: [HCP-Users] CIFTI and NIFTI -parcellating rfMRI

[Joelle Zimmermann]

Hi Michael and Tim,

Thanks for your help. Does the HCP have its own parcellations that are
surface based, or do you have any recommendations?

Are you familiar with the Freesurfer Desikan Killiany cortical atlas  - it
seems that it for example respects the cortical surface?: "The FreeSurfer
utilities mris_ca_train and mris_ca_label together implement a technique
for automatically assigning a neuroanatomical label to each location on a
cortical surface model based on probabilistic information estimated from a
manually labeled training set." (
https://surfer.nmr.mgh.harvard.edu/fswiki/CorticalParcellation).

My ultimate goal is to get a region-wise FC matrix. After parcellating the
cifti into my chosen parcellation atlas, I will be left with region-wise
time series, is that correct? After that, could I just convert the cifti to
nifti and work with that? I presume at that point I wouldn't need the
spatial info (actually Im not actually sure what kind of spatial info this
is?)

Thanks,
Joelle

On Wed, Nov 25, 2015 at 5:21 PM, Timothy Coalson  wrote:

> Because the surface data in our Cifti files is mapped from the volume
> using subject-specific surfaces, it avoids mixing csf and white matter data
> into the cortical signal.  With a volume parcellation, in order to do
> something similar, you would need to parcellate each individual somehow, or
> have an overly generous parcellation and mask it with the per-subject
> cortical segmentation.
>
> Indeed, putting surface and volume data into one file is the main feature
> of the Cifti format (though it also has additional mapping types, notably
> being able to represent a parcellated file in a way that is easy to use for
> visualization).  Cifti also allows the exclusion of vertices and voxels
> that we aren't interested in (medial wall, white matter, csf, skull, air,
> etc), which means that some translation is needed in order to use spatial
> relationships between elements.  If you want the gory details, suitable for
> those implementing their own reader/writer for cifti in other programming
> languages, see the NITRC page:
>
> http://www.nitrc.org/projects/cifti/
>
> The good news is, if you have a parcellation you want to use, and can get
> it into a cifti label file (see -volume-label-to-surface-mapping
> and -cifti-create-label), then you can easily parcellate a cifti file with
> the "wb_command -cifti-parcellate" command.
>
> Tim
>
>
> On Wed, Nov 25, 2015 at 2:53 PM, Harms, Michael  wrote:
>
>>
>> If you want connectivity matrices based on a parcellation that respects
>> the cortical surface, then you'll need to use the CIFTI data, and you'll
>> need a parcellation to go along with it that is also based on the surfaces
>> (for the cortical grayordinates).  We would definitely suggest that you go
>> this route, since much of the HCP effort, from acquisition through
>> processing, is designed around surface-based analyses of the cortical data.
>>
>> Also, you probably want to use the "FIX" cleaned data, which has
>> "*clean*" in the file name, rather than just the minimally pre-processed
>> .dtseries.nii.
>>
>> I think the basic file types are well documented in the release
>> documentation.
>>
>> cheers,
>> -MH
>>
>> --
>> Michael Harms, Ph.D.
>> ---
>> Conte Center for the Neuroscience of Mental Disorders
>> Washington University School of Medicine
>> Department of Psychiatry, Box 8134
>> 660 South Euclid Ave. Tel: 314-747-6173
>> St. Louis, MO  63110 Email: mha...@wustl.edu
>>
>> From: Joelle Zimmermann 
>> Date: Wednesday, November 25, 2015 2:40 PM
>> To: Timothy Coalson 
>> Cc: "hcp-users@humanconnectome.org" 
>> Subject: Re: [HCP-Users] CIFTI and NIFTI -parcellating rfMRI
>>
>> Hi Tim,
>>
>> Thanks for your response. Within the Resting State fMRI 1 preprocessed
>> in the 500 Subjects + MEG2, I see the rfMRI_REST1_LR.nii.gz, which I
>> presume is the Nifti-1 data. And then I see an
>> rfMRI_REST1_LR_Atlas.dtseries.nii  - Is that the dtseries.nii Cifti you
>> refer to? Could you explain a bit more about what's special about the Cifti
>> file? I understand it Cifti is able to handle  surface vertices and
>> subcortical voxels in one file (i.e. gray ordinates).
>>
>> My ultimate goal is to parcellate the brain into cortical regions of
>> interest, in order to ultimately look at regional functional connectivity
>> matrices. Do I need the dtseries.nii cifti for that? It seems like the
>> advantage of that is having surface vertices (i.e. knowing the precise
>> shape of the surface of the brain) - which I don't think I need for a
>> standard FC matrix...
>>
>> Thanks,
>> Joelle
>>
>> On Tue, Nov 24, 2015 at 6:16 PM, Timothy Coalson  wrote:
>>
>>> The .nii.gz files are nifti-1 volumes, while the .dtseries.nii files are
>>> Cifti files.  If you need spatial information, 

Re: [HCP-Users] CIFTI and NIFTI -parcellating rfMRI

[Glasser, Matthew]

Coming soon…

Peace,

Matt.

From: 
>
 on behalf of Joelle Zimmermann 
>
Date: Thursday, November 26, 2015 at 12:03 PM
To: Timothy Coalson >
Cc: "hcp-users@humanconnectome.org" 
>
Subject: Re: [HCP-Users] CIFTI and NIFTI -parcellating rfMRI

Hi Michael and Tim,

Thanks for your help. Does the HCP have its own parcellations that are surface 
based, or do you have any recommendations?

Are you familiar with the Freesurfer Desikan Killiany cortical atlas  - it 
seems that it for example respects the cortical surface?: "The FreeSurfer 
utilities mris_ca_train and mris_ca_label together implement a technique for 
automatically assigning a neuroanatomical label to each location on a cortical 
surface model based on probabilistic information estimated from a manually 
labeled training set." 
(https://surfer.nmr.mgh.harvard.edu/fswiki/CorticalParcellation).

My ultimate goal is to get a region-wise FC matrix. After parcellating the 
cifti into my chosen parcellation atlas, I will be left with region-wise time 
series, is that correct? After that, could I just convert the cifti to nifti 
and work with that? I presume at that point I wouldn't need the spatial info 
(actually Im not actually sure what kind of spatial info this is?)

Thanks,
Joelle

On Wed, Nov 25, 2015 at 5:21 PM, Timothy Coalson 
> wrote:
Because the surface data in our Cifti files is mapped from the volume using 
subject-specific surfaces, it avoids mixing csf and white matter data into the 
cortical signal.  With a volume parcellation, in order to do something similar, 
you would need to parcellate each individual somehow, or have an overly 
generous parcellation and mask it with the per-subject cortical segmentation.

Indeed, putting surface and volume data into one file is the main feature of 
the Cifti format (though it also has additional mapping types, notably being 
able to represent a parcellated file in a way that is easy to use for 
visualization).  Cifti also allows the exclusion of vertices and voxels that we 
aren't interested in (medial wall, white matter, csf, skull, air, etc), which 
means that some translation is needed in order to use spatial relationships 
between elements.  If you want the gory details, suitable for those 
implementing their own reader/writer for cifti in other programming languages, 
see the NITRC page:

http://www.nitrc.org/projects/cifti/

The good news is, if you have a parcellation you want to use, and can get it 
into a cifti label file (see -volume-label-to-surface-mapping and 
-cifti-create-label), then you can easily parcellate a cifti file with the 
"wb_command -cifti-parcellate" command.

Tim


On Wed, Nov 25, 2015 at 2:53 PM, Harms, Michael 
> wrote:

If you want connectivity matrices based on a parcellation that respects the 
cortical surface, then you'll need to use the CIFTI data, and you'll need a 
parcellation to go along with it that is also based on the surfaces (for the 
cortical grayordinates).  We would definitely suggest that you go this route, 
since much of the HCP effort, from acquisition through processing, is designed 
around surface-based analyses of the cortical data.

Also, you probably want to use the "FIX" cleaned data, which has "*clean*" in 
the file name, rather than just the minimally pre-processed .dtseries.nii.

I think the basic file types are well documented in the release documentation.

cheers,
-MH

--
Michael Harms, Ph.D.
---
Conte Center for the Neuroscience of Mental Disorders
Washington University School of Medicine
Department of Psychiatry, Box 8134
660 South Euclid Ave. Tel: 314-747-6173
St. Louis, MO  63110 Email: mha...@wustl.edu

From: Joelle Zimmermann 
>
Date: Wednesday, November 25, 2015 2:40 PM
To: Timothy Coalson >
Cc: "hcp-users@humanconnectome.org" 
>
Subject: Re: [HCP-Users] CIFTI and NIFTI -parcellating rfMRI

Hi Tim,

Thanks for your response. Within the Resting State fMRI 1 preprocessed in the 
500 Subjects + MEG2, I see the rfMRI_REST1_LR.nii.gz, which I presume is the 
Nifti-1 data. And then I see an rfMRI_REST1_LR_Atlas.dtseries.nii  - Is that 
the dtseries.nii Cifti you refer to? Could you explain a bit more about what's 
special about the Cifti file? I understand it Cifti is able to handle  surface 
vertices and subcortical voxels in one file (i.e. gray ordinates).

My ultimate goal is to