Re: [HCP-Users] mapping HCP data into 7 functional networks (using Thomas Yeo parcellation)

[Glasser, Matthew]

There are folks working on this.  The Yeo parcellation was made using differing 
surface registration, and also it is a “winner take all” clustering 
parcellation, rather than a gradient-based parcellation.  This means that 
relatively subtle differences in fc could occur on either side of some borders. 
 The parcellation agrees with the resting state gradients found in HCP data 
however (i.e. parcels do not cross regions of strongly differing functional 
connectivity).

Peace,

Matt.

From: David Hartman <dhartman1...@gmail.com<mailto:dhartman1...@gmail.com>>
Date: Tuesday, July 18, 2017 at 6:45 PM
To: Matt Glasser <glass...@wustl.edu<mailto:glass...@wustl.edu>>
Cc: "hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>" 
<hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] mapping HCP data into 7 functional networks (using 
Thomas Yeo parcellation)

I noticed that the parcellation of the nodes into 360 ROIs (Glasser 2016) does 
not "fit" well into networks (ie, Yeo parcellation). There are nodes in a given 
ROI that belong to multiple networks. Are you aware of any work that has tried 
to bridge your ROI parcellation with some of the network parcellations or is 
this something any of the folks at HCP have explored?

Thank you,
David Hartman

On Mon, Jul 17, 2017 at 7:55 PM, Timothy Coalson 
<tsc...@mst.edu<mailto:tsc...@mst.edu>> wrote:
As Matt says, 32k is used to roughly match the acquisition resolution.  The 7T 
data at 1.6mm is on a 59k mesh for the same reasons.  If you want to resample 
them, see the -cifti-resample command (or -metric-resample for a simpler 
command that does the same surface operation on a different format).

Side note though, in order to get the data onto 32k or 59k, we do in fact first 
map the volume data to the native freesurfer mesh for the subject (~140k if 
memory serves), in order to use the surfaces that contain the original folding 
detail (even though 32k surfaces still have very good folding detail).  After 
that, we downsample them on the surface to the more sensible resolution.

Tim


On Mon, Jul 17, 2017 at 6:44 PM, Glasser, Matthew 
<glass...@wustl.edu<mailto:glass...@wustl.edu>> wrote:
No that would be a massive oversampling of the data.  The data are acquired at 
2mm isotropic, which is roughly the vertex spacing of the 32k mesh.  164k files 
would be much larger for no benefit.  If you want to upsample particular maps 
to 164k (or downsample something to 32k) that is trivial to do.

Peace,

Matt.

From: 
<hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>>
 on behalf of David Hartman 
<dhartman1...@gmail.com<mailto:dhartman1...@gmail.com>>
Date: Monday, July 17, 2017 at 6:24 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] mapping HCP data into 7 functional networks (using 
Thomas Yeo parcellation)

Yes it does seem the first of four columns has 8 distinct numbers.

As a side note, is there any released HCP resting state data on a 164k mesh or 
are they all 32k mesh?

Thank you,
David Hartman

On Mon, Jul 17, 2017 at 6:19 PM, Timothy Coalson 
<tsc...@mst.edu<mailto:tsc...@mst.edu>> wrote:
You can get a text file containing the label names and keys for a map by using 
-cifti-label-export-table.  It appears that this will have extraneous labels in 
it due to how the file was generated, but you can ignore the key values that 
aren't used.

If you count the number of unique values in one column of the cifti file you 
opened, you will probably get the number you are expecting.  It is simply that 
the values are not 1-7, but an arbitrary set of integers.

The -cifti-parcellate command will automatically use the first map in the label 
file to compute within-label averages for its labels.  It is probably not what 
you want to use to simply examine the label map.  I'm not sure why it ended up 
with 8 rather than 7 parcels, though.  As a side effect, you could use 
"wb_command -cifti-parcel-mapping-to-label" to generate a label file that 
should be much less cluttered, but we may have better advice on this soon...

Tim


On Mon, Jul 17, 2017 at 4:51 PM, David Hartman 
<dhartman1...@gmail.com<mailto:dhartman1...@gmail.com>> wrote:

Since calling in MATLAB: 
“ciftiopen('RSN-networks.32k_fs_LR.dlabel.nii','workbench\bin_windows64\wb_command.exe')”
 gives me a matrix with 4 columns whose range is beyond the 17 or 7 
corresponding to their functional grouping, I have resorted to using wb-command 
hoping to get right labelling.



Question: Which wb-command should I use to read the labels and see for the 32k 
mesh which networ

Re: [HCP-Users] mapping HCP data into 7 functional networks (using Thomas Yeo parcellation)

[David Hartman]

I noticed that the parcellation of the nodes into 360 ROIs (Glasser 2016)
does not "fit" well into networks (ie, Yeo parcellation). There are nodes
in a given ROI that belong to multiple networks. Are you aware of any work
that has tried to bridge your ROI parcellation with some of the network
parcellations or is this something any of the folks at HCP have explored?

Thank you,
David Hartman

On Mon, Jul 17, 2017 at 7:55 PM, Timothy Coalson <tsc...@mst.edu> wrote:

> As Matt says, 32k is used to roughly match the acquisition resolution.
> The 7T data at 1.6mm is on a 59k mesh for the same reasons.  If you want to
> resample them, see the -cifti-resample command (or -metric-resample for a
> simpler command that does the same surface operation on a different format).
>
> Side note though, in order to get the data onto 32k or 59k, we do in fact
> first map the volume data to the native freesurfer mesh for the subject
> (~140k if memory serves), in order to use the surfaces that contain the
> original folding detail (even though 32k surfaces still have very good
> folding detail).  After that, we downsample them on the surface to the more
> sensible resolution.
>
> Tim
>
>
> On Mon, Jul 17, 2017 at 6:44 PM, Glasser, Matthew <glass...@wustl.edu>
> wrote:
>
>> No that would be a massive oversampling of the data.  The data are
>> acquired at 2mm isotropic, which is roughly the vertex spacing of the 32k
>> mesh.  164k files would be much larger for no benefit.  If you want to
>> upsample particular maps to 164k (or downsample something to 32k) that is
>> trivial to do.
>>
>> Peace,
>>
>> Matt.
>>
>> From: <hcp-users-boun...@humanconnectome.org> on behalf of David Hartman
>> <dhartman1...@gmail.com>
>> Date: Monday, July 17, 2017 at 6:24 PM
>> To: Timothy Coalson <tsc...@mst.edu>
>> Cc: "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org>
>> Subject: Re: [HCP-Users] mapping HCP data into 7 functional networks
>> (using Thomas Yeo parcellation)
>>
>> Yes it does seem the first of four columns has 8 distinct numbers.
>>
>> As a side note, is there any released HCP resting state data on a 164k
>> mesh or are they all 32k mesh?
>>
>> Thank you,
>> David Hartman
>>
>> On Mon, Jul 17, 2017 at 6:19 PM, Timothy Coalson <tsc...@mst.edu> wrote:
>>
>>> You can get a text file containing the label names and keys for a map by
>>> using -cifti-label-export-table.  It appears that this will have extraneous
>>> labels in it due to how the file was generated, but you can ignore the key
>>> values that aren't used.
>>>
>>> If you count the number of unique values in one column of the cifti file
>>> you opened, you will probably get the number you are expecting.  It is
>>> simply that the values are not 1-7, but an arbitrary set of integers.
>>>
>>> The -cifti-parcellate command will automatically use the first map in
>>> the label file to compute within-label averages for its labels.  It is
>>> probably not what you want to use to simply examine the label map.  I'm not
>>> sure why it ended up with 8 rather than 7 parcels, though.  As a side
>>> effect, you could use "wb_command -cifti-parcel-mapping-to-label" to
>>> generate a label file that should be much less cluttered, but we may have
>>> better advice on this soon...
>>>
>>> Tim
>>>
>>>
>>> On Mon, Jul 17, 2017 at 4:51 PM, David Hartman <dhartman1...@gmail.com>
>>> wrote:
>>>
>>>> Since calling in MATLAB: “ciftiopen('RSN-networks.32k_fs_LR.dlabel.nii'
>>>> ,'workbench\bin_windows64\wb_command.exe')” gives me a matrix with 4
>>>> columns whose range is beyond the 17 or 7 corresponding to their functional
>>>> grouping, I have resorted to using wb-command hoping to get right
>>>> labelling.
>>>>
>>>>
>>>>
>>>> *Question:* Which wb-command should I use to read the labels and see
>>>> for the 32k mesh which networks the nodes belong to (ie. 1 to 7)?
>>>>
>>>>
>>>>
>>>> I tried using wb_command -cifti-parcellate
>>>> rfMRI_REST1_LR_Atlas_MSMAll.dtseries.nii
>>>> RSN-networks.32k_fs_LR.dlabel.nii COLUMN out.ptseries.nii, but
>>>> out.ptseries.nii returns a matrix 8×1200. But I am hoping for something
>>>> 32k×1 for the correct labelling, where each row is a number between 1
>>>> and 7 or 17 corresponding to the group the node belongs to.
>>>

Re: [HCP-Users] mapping HCP data into 7 functional networks (using Thomas Yeo parcellation)

[Glasser, Matthew]

Please use our CIFTI tool for now (option 2B): 
https://wiki.humanconnectome.org/display/PublicData/HCP+Users+FAQ

We are planning to modify the CIFTI tools that were originally written for 
field trip to work better with brain imaging data in the future.

Peace,

Matt.

From: David Hartman <dhartman1...@gmail.com<mailto:dhartman1...@gmail.com>>
Date: Tuesday, July 18, 2017 at 12:05 PM
To: Timothy Coalson <tsc...@mst.edu<mailto:tsc...@mst.edu>>
Cc: Matt Glasser <glass...@wustl.edu<mailto:glass...@wustl.edu>>, 
"hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>" 
<hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] mapping HCP data into 7 functional networks (using 
Thomas Yeo parcellation)

Thank you for your responses. My data is indeed in a 32k (per hemisphere) mesh. 
My question pertains to what counts as a medial wall? My impression (but please 
correct me if I am wrong) is that  when using the MATLAB command ciftiopen, 
there are 64.9k vertices (32k per hemisphere). and when using the MATLAB 
command ft_read_cifti, there are ~59.5k vertices.  The results from the 
ft_read_cifti produce around 5.5k NANS corresponding to the discrepancy between 
ciftiopen and ft_read_cifti. My impression is that these ~5.5k NANS are the 
medial wall vertices.

On the other hand,  when using the "RSN-networks.32k_fs_LR.dlabel.nii”, there 
are 8 distinct numbers.
 From workbench (cifti-label-export-table) I notice that one of these numbers 
corresponds to FreeSurfer_Defined_Medial_Wall, while the other 7 to  
7Networks_X.

The NANS and the FreeSurferDefined_Medial_Wall vertices match up mostly. 
However, there is a gap. There is only a ~5k overlap between the ~5.5k NANs and 
the vertices corresponding to the group: FreeSurfer_Defined_Medial_Wall.   Any 
ideas why the groups would be slightly different (mismatch of 500 vertices) 
between the NANS and the FreeSurfer_Defined_Medial_Wall?

Thank you,
David Hartman

On Mon, Jul 17, 2017 at 7:55 PM, Timothy Coalson 
<tsc...@mst.edu<mailto:tsc...@mst.edu>> wrote:
As Matt says, 32k is used to roughly match the acquisition resolution.  The 7T 
data at 1.6mm is on a 59k mesh for the same reasons.  If you want to resample 
them, see the -cifti-resample command (or -metric-resample for a simpler 
command that does the same surface operation on a different format).

Side note though, in order to get the data onto 32k or 59k, we do in fact first 
map the volume data to the native freesurfer mesh for the subject (~140k if 
memory serves), in order to use the surfaces that contain the original folding 
detail (even though 32k surfaces still have very good folding detail).  After 
that, we downsample them on the surface to the more sensible resolution.

Tim


On Mon, Jul 17, 2017 at 6:44 PM, Glasser, Matthew 
<glass...@wustl.edu<mailto:glass...@wustl.edu>> wrote:
No that would be a massive oversampling of the data.  The data are acquired at 
2mm isotropic, which is roughly the vertex spacing of the 32k mesh.  164k files 
would be much larger for no benefit.  If you want to upsample particular maps 
to 164k (or downsample something to 32k) that is trivial to do.

Peace,

Matt.

From: 
<hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>>
 on behalf of David Hartman 
<dhartman1...@gmail.com<mailto:dhartman1...@gmail.com>>
Date: Monday, July 17, 2017 at 6:24 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] mapping HCP data into 7 functional networks (using 
Thomas Yeo parcellation)

Yes it does seem the first of four columns has 8 distinct numbers.

As a side note, is there any released HCP resting state data on a 164k mesh or 
are they all 32k mesh?

Thank you,
David Hartman

On Mon, Jul 17, 2017 at 6:19 PM, Timothy Coalson 
<tsc...@mst.edu<mailto:tsc...@mst.edu>> wrote:
You can get a text file containing the label names and keys for a map by using 
-cifti-label-export-table.  It appears that this will have extraneous labels in 
it due to how the file was generated, but you can ignore the key values that 
aren't used.

If you count the number of unique values in one column of the cifti file you 
opened, you will probably get the number you are expecting.  It is simply that 
the values are not 1-7, but an arbitrary set of integers.

The -cifti-parcellate command will automatically use the first map in the label 
file to compute within-label averages for its labels.  It is probably not what 
you want to use to simply examine the label map.  I'm not sure why it ended up 
with 8 rather than 7 parcels, though.  As a side effect, you could use 
"wb_c

Re: [HCP-Users] mapping HCP data into 7 functional networks (using Thomas Yeo parcellation)

[David Hartman]

Thank you for your responses. My data is indeed in a 32k (per hemisphere)
mesh. My question pertains to what counts as a medial wall? My impression
(but please correct me if I am wrong) is that  when using the MATLAB
command ciftiopen, there are 64.9k vertices (32k per hemisphere). and when
using the MATLAB command ft_read_cifti, there are ~59.5k vertices.  The
results from the ft_read_cifti produce around 5.5k NANS corresponding to
the discrepancy between ciftiopen and ft_read_cifti. My impression is that
these ~5.5k NANS are the medial wall vertices.

On the other hand,  when using the "RSN-networks.32k_fs_LR.dlabel.nii”,
there are 8 distinct numbers.
 From workbench (cifti-label-export-table) I notice that one of these
numbers corresponds to FreeSurfer_Defined_Medial_Wall, while the other 7 to
 7Networks_X.

The NANS and the FreeSurferDefined_Medial_Wall vertices match up mostly.
However, there is a gap. There is only a ~5k overlap between the ~5.5k NANs
and the vertices corresponding to the group: FreeSurfer_Defined_Medial_Wall.
Any ideas why the groups would be slightly different (mismatch of 500
vertices) between the NANS and the FreeSurfer_Defined_Medial_Wall?

Thank you,
David Hartman

On Mon, Jul 17, 2017 at 7:55 PM, Timothy Coalson <tsc...@mst.edu> wrote:

> As Matt says, 32k is used to roughly match the acquisition resolution.
> The 7T data at 1.6mm is on a 59k mesh for the same reasons.  If you want to
> resample them, see the -cifti-resample command (or -metric-resample for a
> simpler command that does the same surface operation on a different format).
>
> Side note though, in order to get the data onto 32k or 59k, we do in fact
> first map the volume data to the native freesurfer mesh for the subject
> (~140k if memory serves), in order to use the surfaces that contain the
> original folding detail (even though 32k surfaces still have very good
> folding detail).  After that, we downsample them on the surface to the more
> sensible resolution.
>
> Tim
>
>
> On Mon, Jul 17, 2017 at 6:44 PM, Glasser, Matthew <glass...@wustl.edu>
> wrote:
>
>> No that would be a massive oversampling of the data.  The data are
>> acquired at 2mm isotropic, which is roughly the vertex spacing of the 32k
>> mesh.  164k files would be much larger for no benefit.  If you want to
>> upsample particular maps to 164k (or downsample something to 32k) that is
>> trivial to do.
>>
>> Peace,
>>
>> Matt.
>>
>> From: <hcp-users-boun...@humanconnectome.org> on behalf of David Hartman
>> <dhartman1...@gmail.com>
>> Date: Monday, July 17, 2017 at 6:24 PM
>> To: Timothy Coalson <tsc...@mst.edu>
>> Cc: "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org>
>> Subject: Re: [HCP-Users] mapping HCP data into 7 functional networks
>> (using Thomas Yeo parcellation)
>>
>> Yes it does seem the first of four columns has 8 distinct numbers.
>>
>> As a side note, is there any released HCP resting state data on a 164k
>> mesh or are they all 32k mesh?
>>
>> Thank you,
>> David Hartman
>>
>> On Mon, Jul 17, 2017 at 6:19 PM, Timothy Coalson <tsc...@mst.edu> wrote:
>>
>>> You can get a text file containing the label names and keys for a map by
>>> using -cifti-label-export-table.  It appears that this will have extraneous
>>> labels in it due to how the file was generated, but you can ignore the key
>>> values that aren't used.
>>>
>>> If you count the number of unique values in one column of the cifti file
>>> you opened, you will probably get the number you are expecting.  It is
>>> simply that the values are not 1-7, but an arbitrary set of integers.
>>>
>>> The -cifti-parcellate command will automatically use the first map in
>>> the label file to compute within-label averages for its labels.  It is
>>> probably not what you want to use to simply examine the label map.  I'm not
>>> sure why it ended up with 8 rather than 7 parcels, though.  As a side
>>> effect, you could use "wb_command -cifti-parcel-mapping-to-label" to
>>> generate a label file that should be much less cluttered, but we may have
>>> better advice on this soon...
>>>
>>> Tim
>>>
>>>
>>> On Mon, Jul 17, 2017 at 4:51 PM, David Hartman <dhartman1...@gmail.com>
>>> wrote:
>>>
>>>> Since calling in MATLAB: “ciftiopen('RSN-networks.32k_fs_LR.dlabel.nii'
>>>> ,'workbench\bin_windows64\wb_command.exe')” gives me a matrix with 4
>>>> columns whose range is beyond the 17 or 7 corresponding to their functional
>>>> grouping, 

Re: [HCP-Users] mapping HCP data into 7 functional networks (using Thomas Yeo parcellation)

[Timothy Coalson]

As Matt says, 32k is used to roughly match the acquisition resolution.  The
7T data at 1.6mm is on a 59k mesh for the same reasons.  If you want to
resample them, see the -cifti-resample command (or -metric-resample for a
simpler command that does the same surface operation on a different format).

Side note though, in order to get the data onto 32k or 59k, we do in fact
first map the volume data to the native freesurfer mesh for the subject
(~140k if memory serves), in order to use the surfaces that contain the
original folding detail (even though 32k surfaces still have very good
folding detail).  After that, we downsample them on the surface to the more
sensible resolution.

Tim


On Mon, Jul 17, 2017 at 6:44 PM, Glasser, Matthew <glass...@wustl.edu>
wrote:

> No that would be a massive oversampling of the data.  The data are
> acquired at 2mm isotropic, which is roughly the vertex spacing of the 32k
> mesh.  164k files would be much larger for no benefit.  If you want to
> upsample particular maps to 164k (or downsample something to 32k) that is
> trivial to do.
>
> Peace,
>
> Matt.
>
> From: <hcp-users-boun...@humanconnectome.org> on behalf of David Hartman <
> dhartman1...@gmail.com>
> Date: Monday, July 17, 2017 at 6:24 PM
> To: Timothy Coalson <tsc...@mst.edu>
> Cc: "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org>
> Subject: Re: [HCP-Users] mapping HCP data into 7 functional networks
> (using Thomas Yeo parcellation)
>
> Yes it does seem the first of four columns has 8 distinct numbers.
>
> As a side note, is there any released HCP resting state data on a 164k
> mesh or are they all 32k mesh?
>
> Thank you,
> David Hartman
>
> On Mon, Jul 17, 2017 at 6:19 PM, Timothy Coalson <tsc...@mst.edu> wrote:
>
>> You can get a text file containing the label names and keys for a map by
>> using -cifti-label-export-table.  It appears that this will have extraneous
>> labels in it due to how the file was generated, but you can ignore the key
>> values that aren't used.
>>
>> If you count the number of unique values in one column of the cifti file
>> you opened, you will probably get the number you are expecting.  It is
>> simply that the values are not 1-7, but an arbitrary set of integers.
>>
>> The -cifti-parcellate command will automatically use the first map in the
>> label file to compute within-label averages for its labels.  It is probably
>> not what you want to use to simply examine the label map.  I'm not sure why
>> it ended up with 8 rather than 7 parcels, though.  As a side effect, you
>> could use "wb_command -cifti-parcel-mapping-to-label" to generate a
>> label file that should be much less cluttered, but we may have better
>> advice on this soon...
>>
>> Tim
>>
>>
>> On Mon, Jul 17, 2017 at 4:51 PM, David Hartman <dhartman1...@gmail.com>
>> wrote:
>>
>>> Since calling in MATLAB: “ciftiopen('RSN-networks.32k_fs_LR.dlabel.nii',
>>> 'workbench\bin_windows64\wb_command.exe')” gives me a matrix with 4
>>> columns whose range is beyond the 17 or 7 corresponding to their functional
>>> grouping, I have resorted to using wb-command hoping to get right
>>> labelling.
>>>
>>>
>>>
>>> *Question:* Which wb-command should I use to read the labels and see
>>> for the 32k mesh which networks the nodes belong to (ie. 1 to 7)?
>>>
>>>
>>>
>>> I tried using wb_command -cifti-parcellate
>>> rfMRI_REST1_LR_Atlas_MSMAll.dtseries.nii  RSN-networks.32k_fs_LR.dlabel.nii
>>> COLUMN out.ptseries.nii, but out.ptseries.nii returns a matrix 8×1200.
>>> But I am hoping for something  32k×1 for the correct labelling, where
>>> each row is a number between 1 and 7 or 17 corresponding to the group the
>>> node belongs to.
>>>
>>>
>>>
>>>
>>>
>>> Hope it is not too confusing.
>>>
>>>
>>>
>>> Thank you,
>>>
>>> David Hartman
>>>
>>> On Mon, Jul 17, 2017 at 3:09 PM, Harms, Michael <mha...@wustl.edu>
>>> wrote:
>>>
>>>>
>>>> Hi,
>>>> There are actually 4 different maps in that file.  If you load it into
>>>> Workbench, the name associated with each map tells you what each map is.
>>>>
>>>> cheers,
>>>> -MH
>>>>
>>>> --
>>>> Michael Harms, Ph.D.
>>>> ---
>>>> Conte Center for the Neuroscience of Mental Disorders
>>&g

Re: [HCP-Users] mapping HCP data into 7 functional networks (using Thomas Yeo parcellation)

[David Hartman]

Yes it does seem the first of four columns has 8 distinct numbers.

As a side note, is there any released HCP resting state data on a 164k mesh
or are they all 32k mesh?

Thank you,
David Hartman

On Mon, Jul 17, 2017 at 6:19 PM, Timothy Coalson <tsc...@mst.edu> wrote:

> You can get a text file containing the label names and keys for a map by
> using -cifti-label-export-table.  It appears that this will have extraneous
> labels in it due to how the file was generated, but you can ignore the key
> values that aren't used.
>
> If you count the number of unique values in one column of the cifti file
> you opened, you will probably get the number you are expecting.  It is
> simply that the values are not 1-7, but an arbitrary set of integers.
>
> The -cifti-parcellate command will automatically use the first map in the
> label file to compute within-label averages for its labels.  It is probably
> not what you want to use to simply examine the label map.  I'm not sure why
> it ended up with 8 rather than 7 parcels, though.  As a side effect, you
> could use "wb_command -cifti-parcel-mapping-to-label" to generate a label
> file that should be much less cluttered, but we may have better advice on
> this soon...
>
> Tim
>
>
> On Mon, Jul 17, 2017 at 4:51 PM, David Hartman <dhartman1...@gmail.com>
> wrote:
>
>> Since calling in MATLAB: “ciftiopen('RSN-networks.32k_fs_LR.dlabel.nii',
>> 'workbench\bin_windows64\wb_command.exe')” gives me a matrix with 4
>> columns whose range is beyond the 17 or 7 corresponding to their functional
>> grouping, I have resorted to using wb-command hoping to get right
>> labelling.
>>
>>
>>
>> *Question:* Which wb-command should I use to read the labels and see for
>> the 32k mesh which networks the nodes belong to (ie. 1 to 7)?
>>
>>
>>
>> I tried using wb_command -cifti-parcellate rfMRI_REST1_LR_Atlas_MSMAll.dt
>> series.nii  RSN-networks.32k_fs_LR.dlabel.nii COLUMN out.ptseries.nii,
>> but out.ptseries.nii returns a matrix 8×1200. But I am hoping for
>> something  32k×1 for the correct labelling, where each row is a number
>> between 1 and 7 or 17 corresponding to the group the node belongs to.
>>
>>
>>
>>
>>
>> Hope it is not too confusing.
>>
>>
>>
>> Thank you,
>>
>> David Hartman
>>
>> On Mon, Jul 17, 2017 at 3:09 PM, Harms, Michael <mha...@wustl.edu> wrote:
>>
>>>
>>> Hi,
>>> There are actually 4 different maps in that file.  If you load it into
>>> Workbench, the name associated with each map tells you what each map is.
>>>
>>> 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 <(314)%20747-6173>
>>> St. Louis, MO  63110 Email: mha...@wustl.edu
>>>
>>> From: <hcp-users-boun...@humanconnectome.org> on behalf of David
>>> Hartman <dhartman1...@gmail.com>
>>> Date: Monday, July 17, 2017 at 12:21 PM
>>> To: "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org>
>>> Subject: Re: [HCP-Users] mapping HCP data into 7 functional networks
>>> (using Thomas Yeo parcellation)
>>>
>>> Hi,
>>>
>>>
>>>
>>> *Background:*
>>>
>>> Regarding the labels file, “RSN-networks.32k_fs_LR.dlabel.nii” which I
>>> thought should contain the 7 and 17 network parcellation, this file has a
>>> matrix of size 64984×4. What do the numbers in the 4 columns represent (ie.
>>> 1st column has a max of 44 and 4th column a max of 26). I was expecting
>>> a single column that took values from 1 to 17 or 1 to 7 mapping each vertex
>>> to its grouping in the functional networks.
>>>
>>>
>>>
>>>
>>>
>>> *Question:*
>>>
>>> How should I understand these 4 columns and their connection to
>>> functional network parcellation?
>>>
>>>
>>>
>>> Thank you,
>>>
>>> David Hartman
>>>
>>> On Fri, Jul 14, 2017 at 2:27 PM, David Hartman <dhartman1...@gmail.com>
>>> wrote:
>>>
>>>> Hi,
>>>>
>>>>
>>>>
>>>> *Background:*
>>>>
>>>> Regarding the parcellation of the cortex into 

Re: [HCP-Users] mapping HCP data into 7 functional networks (using Thomas Yeo parcellation)

[David Hartman]

Since calling in MATLAB: “ciftiopen('RSN-networks.32k_fs_LR.dlabel.nii',
'workbench\bin_windows64\wb_command.exe')” gives me a matrix with 4 columns
whose range is beyond the 17 or 7 corresponding to their functional
grouping, I have resorted to using wb-command hoping to get right
labelling.



*Question:* Which wb-command should I use to read the labels and see for
the 32k mesh which networks the nodes belong to (ie. 1 to 7)?



I tried using wb_command -cifti-parcellate
rfMRI_REST1_LR_Atlas_MSMAll.dtseries.nii  RSN-networks.32k_fs_LR.dlabel.nii
COLUMN out.ptseries.nii, but out.ptseries.nii returns a matrix 8×1200. But
I am hoping for something  32k×1 for the correct labelling, where each row
is a number between 1 and 7 or 17 corresponding to the group the node
belongs to.





Hope it is not too confusing.



Thank you,

David Hartman

On Mon, Jul 17, 2017 at 3:09 PM, Harms, Michael <mha...@wustl.edu> wrote:

>
> Hi,
> There are actually 4 different maps in that file.  If you load it into
> Workbench, the name associated with each map tells you what each map is.
>
> 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 <(314)%20747-6173>
> St. Louis, MO  63110 Email: mha...@wustl.edu
>
> From: <hcp-users-boun...@humanconnectome.org> on behalf of David Hartman <
> dhartman1...@gmail.com>
> Date: Monday, July 17, 2017 at 12:21 PM
> To: "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org>
> Subject: Re: [HCP-Users] mapping HCP data into 7 functional networks
> (using Thomas Yeo parcellation)
>
> Hi,
>
>
>
> *Background:*
>
> Regarding the labels file, “RSN-networks.32k_fs_LR.dlabel.nii” which I
> thought should contain the 7 and 17 network parcellation, this file has a
> matrix of size 64984×4. What do the numbers in the 4 columns represent (ie.
> 1st column has a max of 44 and 4th column a max of 26). I was expecting a
> single column that took values from 1 to 17 or 1 to 7 mapping each vertex
> to its grouping in the functional networks.
>
>
>
>
>
> *Question:*
>
> How should I understand these 4 columns and their connection to functional
> network parcellation?
>
>
>
> Thank you,
>
> David Hartman
>
> On Fri, Jul 14, 2017 at 2:27 PM, David Hartman <dhartman1...@gmail.com>
> wrote:
>
>> Hi,
>>
>>
>>
>> *Background:*
>>
>> Regarding the parcellation of the cortex into functional networks (“The
>> organization of the human cerebral cortex estimated by intrinsic functional
>> connectivity,” Yeo et al.) Yeo breaks up the cortex into 7 networks.
>> However, his cortical data has 163842 vertices, while the HCP data only has
>> 59412 vertices.
>>
>>
>>
>> *Question:*
>>
>> I am looking to map the HCP data into these 7 networks, but I don’t see a
>> way to get the data into the same format as Yeo’s data (ie. 163842
>> vertices) to use his mapping.
>>
>> 1.  Does anyone know of a way to convert HCP data into the same format
>> as Yeo’s data to use his mapping or a direct way to map the HCP data to 7
>> networks?
>>
>>
>>
>> Any help would be much appreciated.
>>
>>
>>
>> Thank you,
>>
>> David Hartman
>>
>>
> ___
> 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] mapping HCP data into 7 functional networks (using Thomas Yeo parcellation)

[Harms, Michael]

Hi,
There are actually 4 different maps in that file.  If you load it into 
Workbench, the name associated with each map tells you what each map is.

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: 
<hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>>
 on behalf of David Hartman 
<dhartman1...@gmail.com<mailto:dhartman1...@gmail.com>>
Date: Monday, July 17, 2017 at 12:21 PM
To: "hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>" 
<hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] mapping HCP data into 7 functional networks (using 
Thomas Yeo parcellation)


Hi,



Background:

Regarding the labels file, “RSN-networks.32k_fs_LR.dlabel.nii” which I thought 
should contain the 7 and 17 network parcellation, this file has a matrix of 
size 64984×4. What do the numbers in the 4 columns represent (ie. 1st column 
has a max of 44 and 4th column a max of 26). I was expecting a single column 
that took values from 1 to 17 or 1 to 7 mapping each vertex to its grouping in 
the functional networks.





Question:

How should I understand these 4 columns and their connection to functional 
network parcellation?



Thank you,

David Hartman

On Fri, Jul 14, 2017 at 2:27 PM, David Hartman 
<dhartman1...@gmail.com<mailto:dhartman1...@gmail.com>> wrote:

Hi,



Background:

Regarding the parcellation of the cortex into functional networks (“The 
organization of the human cerebral cortex estimated by intrinsic functional 
connectivity,” Yeo et al.) Yeo breaks up the cortex into 7 networks. However, 
his cortical data has 163842 vertices, while the HCP data only has 59412 
vertices.



Question:

I am looking to map the HCP data into these 7 networks, but I don’t see a way 
to get the data into the same format as Yeo’s data (ie. 163842 vertices) to use 
his mapping.

1.  Does anyone know of a way to convert HCP data into the same format as Yeo’s 
data to use his mapping or a direct way to map the HCP data to 7 networks?



Any help would be much appreciated.



Thank you,

David Hartman



___
HCP-Users mailing list
HCP-Users@humanconnectome.org<mailto: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] mapping HCP data into 7 functional networks (using Thomas Yeo parcellation)

[Glasser, Matthew]

Also you shouldn’t be using the HCP 7T fMRI data at this time.  See the message 
about this on the list.

Peace,

Matt.

From: 
<hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>>
 on behalf of Timothy Coalson <tsc...@mst.edu<mailto:tsc...@mst.edu>>
Date: Friday, July 14, 2017 at 2:57 PM
To: David Hartman <dhartman1...@gmail.com<mailto:dhartman1...@gmail.com>>
Cc: "hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>" 
<hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] mapping HCP data into 7 functional networks (using 
Thomas Yeo parcellation)

As for the 59k vertices you mentioned, I'm guessing you were looking at a cifti 
file that contains both hemispheres, and excludes the medial wall - if so, this 
actually uses surfaces with 32k vertices.  Unfortunately, our 1.6mm 7T data was 
processed with a mesh that happens to use 59k-vertex surfaces for each 
hemisphere, so there is some potential for confusion here.  You may want to 
read this for an explanation of the cifti format:

http://www.humanconnectome.org/software/workbench-command/-cifti-help

The file containing the 17-network version on balsa also contains the 7-network 
version as the first map:

https://balsa.wustl.edu/file/show/Q2xn

Tim


On Fri, Jul 14, 2017 at 2:42 PM, Timothy Coalson 
<tsc...@mst.edu<mailto:tsc...@mst.edu>> wrote:
We have a version of the 17-network Yeo parcellation here:

https://balsa.wustl.edu/W8wK

163842 sounds like a freesurfer resolution.  If the version you have is on the 
freesurfer atlas, then you can resample it to ours (or resample our 
parcellation to freesurfer's atlas) following these instructions:

https://wiki.humanconnectome.org/display/PublicData/HCP+Users+FAQ#HCPUsersFAQ-9.HowdoImapdatabetweenFreeSurferandHCP?

FAQ 9, "How do I map data between FreeSurfer and HCP?"

Note that if you want the left and right portions of each network separated, or 
want each contiguous piece to be a separate entity, more work is required.  We 
have a script somewhere that does these things...

Tim


On Fri, Jul 14, 2017 at 1:27 PM, David Hartman 
<dhartman1...@gmail.com<mailto:dhartman1...@gmail.com>> wrote:

Hi,



Background:

Regarding the parcellation of the cortex into functional networks (“The 
organization of the human cerebral cortex estimated by intrinsic functional 
connectivity,” Yeo et al.) Yeo breaks up the cortex into 7 networks. However, 
his cortical data has 163842 vertices, while the HCP data only has 59412 
vertices.



Question:

I am looking to map the HCP data into these 7 networks, but I don’t see a way 
to get the data into the same format as Yeo’s data (ie. 163842 vertices) to use 
his mapping.

1.  Does anyone know of a way to convert HCP data into the same format as Yeo’s 
data to use his mapping or a direct way to map the HCP data to 7 networks?



Any help would be much appreciated.



Thank you,

David Hartman


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



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

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

Re: [HCP-Users] mapping HCP data into 7 functional networks (using Thomas Yeo parcellation)

[Glasser, Matthew]

Most of the released HCP data are on a 32k mesh.  You can find the Yeo 
parcellation on the 32k mesh here: https://balsa.wustl.edu/study/show/WG33

Peace,

Matt.

From: 
>
 on behalf of David Hartman 
>
Date: Friday, July 14, 2017 at 1:27 PM
To: "hcp-users@humanconnectome.org" 
>
Subject: [HCP-Users] mapping HCP data into 7 functional networks (using Thomas 
Yeo parcellation)


Hi,



Background:

Regarding the parcellation of the cortex into functional networks (“The 
organization of the human cerebral cortex estimated by intrinsic functional 
connectivity,” Yeo et al.) Yeo breaks up the cortex into 7 networks. However, 
his cortical data has 163842 vertices, while the HCP data only has 59412 
vertices.



Question:

I am looking to map the HCP data into these 7 networks, but I don’t see a way 
to get the data into the same format as Yeo’s data (ie. 163842 vertices) to use 
his mapping.

1.  Does anyone know of a way to convert HCP data into the same format as Yeo’s 
data to use his mapping or a direct way to map the HCP data to 7 networks?



Any help would be much appreciated.



Thank you,

David Hartman


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

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

Re: [HCP-Users] mapping HCP data into 7 functional networks (using Thomas Yeo parcellation)

[Timothy Coalson]

As for the 59k vertices you mentioned, I'm guessing you were looking at a
cifti file that contains both hemispheres, and excludes the medial wall -
if so, this actually uses surfaces with 32k vertices.  Unfortunately, our
1.6mm 7T data was processed with a mesh that happens to use 59k-vertex
surfaces for each hemisphere, so there is some potential for confusion
here.  You may want to read this for an explanation of the cifti format:

http://www.humanconnectome.org/software/workbench-command/-cifti-help

The file containing the 17-network version on balsa also contains the
7-network version as the first map:

https://balsa.wustl.edu/file/show/Q2xn

Tim


On Fri, Jul 14, 2017 at 2:42 PM, Timothy Coalson  wrote:

> We have a version of the 17-network Yeo parcellation here:
>
> https://balsa.wustl.edu/W8wK
>
> 163842 sounds like a freesurfer resolution.  If the version you have is on
> the freesurfer atlas, then you can resample it to ours (or resample our
> parcellation to freesurfer's atlas) following these instructions:
>
> https://wiki.humanconnectome.org/display/PublicData/HCP+
> Users+FAQ#HCPUsersFAQ-9.HowdoImapdatabetweenFreeSurferandHCP?
>
> FAQ 9, "How do I map data between FreeSurfer and HCP?"
>
> Note that if you want the left and right portions of each network
> separated, or want each contiguous piece to be a separate entity, more work
> is required.  We have a script somewhere that does these things...
>
> Tim
>
>
> On Fri, Jul 14, 2017 at 1:27 PM, David Hartman 
> wrote:
>
>> Hi,
>>
>>
>>
>> *Background:*
>>
>> Regarding the parcellation of the cortex into functional networks (“The
>> organization of the human cerebral cortex estimated by intrinsic functional
>> connectivity,” Yeo et al.) Yeo breaks up the cortex into 7 networks.
>> However, his cortical data has 163842 vertices, while the HCP data only has
>> 59412 vertices.
>>
>>
>>
>> *Question:*
>>
>> I am looking to map the HCP data into these 7 networks, but I don’t see a
>> way to get the data into the same format as Yeo’s data (ie. 163842
>> vertices) to use his mapping.
>>
>> 1.  Does anyone know of a way to convert HCP data into the same format
>> as Yeo’s data to use his mapping or a direct way to map the HCP data to 7
>> networks?
>>
>>
>>
>> Any help would be much appreciated.
>>
>>
>>
>> Thank you,
>>
>> David Hartman
>>
>> ___
>> HCP-Users mailing list
>> HCP-Users@humanconnectome.org
>> http://lists.humanconnectome.org/mailman/listinfo/hcp-users
>>
>
>

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

Re: [HCP-Users] mapping HCP data into 7 functional networks (using Thomas Yeo parcellation)

[Elam, Jennifer]

Hi David,

With 59k vertices, it sounds like you are using the versions of the HCP 
individual data that was preprocessed at 1.6mm resolution for use with the 7T 
data contained in the "Structural Preprocessed for 7T (1.6mm/59k mesh)" package 
in ConnectomeDB. The 3T "Structural Preprocessed" package contains both 164k 
and 32k resolution Conte69-registered standard mesh cortical surfaces in MNI 
space in the {Subject_ID}/MNINonLinear/ and 
{Subject_ID}/MNINonLinear/fsaverage_32k directories, respectively.


In addition, 32k versions of the 7 and 17 Network versions of the Yeo et al. 
2011 parcellation are included in the RSN-networks.32k_fs_LR.dlabel.nii CIFTI 
file that is included in the 900 Subjects group average dataset available in 
ConnectomeDB: https://db.humanconnectome.org/data/projects/HCP_1200


Tim Coalson can give you more info on using wb_command to do surface resampling 
if you want to do that as well.


Best,

Jenn

Jennifer Elam, Ph.D.
Scientific Outreach, Human Connectome Project
Washington University School of Medicine
Department of Neuroscience, Box 8108
660 South Euclid Avenue
St. Louis, MO 63110
314-362-9387
e...@wustl.edu
www.humanconnectome.org



From: hcp-users-boun...@humanconnectome.org 
 on behalf of David Hartman 

Sent: Friday, July 14, 2017 1:27:09 PM
To: hcp-users@humanconnectome.org
Subject: [HCP-Users] mapping HCP data into 7 functional networks (using Thomas 
Yeo parcellation)


Hi,



Background:

Regarding the parcellation of the cortex into functional networks (“The 
organization of the human cerebral cortex estimated by intrinsic functional 
connectivity,” Yeo et al.) Yeo breaks up the cortex into 7 networks. However, 
his cortical data has 163842 vertices, while the HCP data only has 59412 
vertices.



Question:

I am looking to map the HCP data into these 7 networks, but I don’t see a way 
to get the data into the same format as Yeo’s data (ie. 163842 vertices) to use 
his mapping.

1.  Does anyone know of a way to convert HCP data into the same format as Yeo’s 
data to use his mapping or a direct way to map the HCP data to 7 networks?



Any help would be much appreciated.



Thank you,

David Hartman


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

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