Re: [HCP-Users] Convert subject-specific ICA node maps to volumetric space?

[Nicola Toschi]

Hi Tim,

thanks a lot for your detailed answer and insight!

Best

Nicola


On 11/13/2018 9:06 PM, Timothy Coalson wrote:
-cifti-convert does not do this, it only dumps the matrix into 
different file formats as-is, the spatial relationships are not 
accessible from its output.


If you are only interested in subcortical/cerebellum data, that is 
trivial to extract from cifti as a volumetric nifti using 
-cifti-separate with -volume-all.  In the future, when resolution 
increases sufficiently, we hope to move the cerebellum data to surface 
representation also.


Group volume-registered space has significant drawbacks, in that it 
does not align cortical functional areas to the degree that 
surface/cifti processing can.  This is because much of the cortex has 
variable folding between subjects, which volume registration can't 
unfold to try to match, and because functional areas vary somewhat in 
their position relative to these folds.  See our recent paper:


https://www.ncbi.nlm.nih.gov/pubmed/29925602

This actually means that mapping the cifti data back into the volume 
should have better cross-subject functional correspondence than 
computing group maps from the original volumetric data - the drawback, 
however, is that the folding patterns can't be preserved (since they 
are different across subjects), and you will end up with a much less 
folded cortical ribbon with oddly sharp boundaries (and perfect 
correlation along the normal vector of the surface). Processing the 
data in cifti format will use less memory, be more correct to the 
nature of the data, and make it more obvious that you aren't really 
using a volumetric processing stream.  Matlab and python both have 
support for reading and writing cifti files (though in matlab there 
isn't good support for spatial relationships), as well as a few other 
languages (the cifti code from workbench has been made into a c++ 
library, though you will also need a gifti library to make full use of 
spatial relationships).  wb_command can do several types of spatial 
processing operations on cifti, and -cifti-convert will allow you to 
feed the data through virtually any tool that doesn't use spatial 
neighborhood information.


Tim


On Tue, Nov 13, 2018 at 10:45 AM, Nicola Toschi 
mailto:tos...@med.uniroma2.it>> wrote:


Thank you Steve,

I was hoping to get them out of the CIFTI versions (also so I
don't have to reprocess the 4D FIX data for all subjects). Maybe
with cifti-convert? The brain would not be fully covered here i
realise but much better than nothing.

Alternatively, do you think there is a chance of obtaining them
somehow (since they have been calculated by you guys anyway)? Can
i put in a request somewhere maybe?

Thank you in advance!

Nicola


On 11/13/2018 5:13 PM, Steve Smith wrote:

Hi - we calculated them in order to estimate the volumetric group
maps. However AFAIK we didn't bundle them in the PTN release.
You can easily get them though by regressing node timeseries into
4D FIX-cleaned data.

Cheers.



On 13 Nov 2018, at 16:09, Nicola Toschi mailto:tos...@med.uniroma2.it>> wrote:

Dear HCP list and experts,

I was wondering if the subject-specific node maps from the
latest PTN
release (which are available in CIFTI format) are also available in
volumetric space (which would aid the specific analysis we are
running).

Or if not, maybe a pointer on how to convert them?

Thank you very much in advance!

nicola

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FMRIB, JR Hospital, Headington, Oxford  OX3 9DU, UK
+44 (0) 1865 610470
st...@fmrib.ox.ac.uk 
http://www.fmrib.ox.ac.uk/~steve 
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Re: [HCP-Users] Convert subject-specific ICA node maps to volumetric space?

[Timothy Coalson]

-cifti-convert does not do this, it only dumps the matrix into different
file formats as-is, the spatial relationships are not accessible from its
output.

If you are only interested in subcortical/cerebellum data, that is trivial
to extract from cifti as a volumetric nifti using -cifti-separate with
-volume-all.  In the future, when resolution increases sufficiently, we
hope to move the cerebellum data to surface representation also.

Group volume-registered space has significant drawbacks, in that it does
not align cortical functional areas to the degree that surface/cifti
processing can.  This is because much of the cortex has variable folding
between subjects, which volume registration can't unfold to try to match,
and because functional areas vary somewhat in their position relative to
these folds.  See our recent paper:

https://www.ncbi.nlm.nih.gov/pubmed/29925602

This actually means that mapping the cifti data back into the volume should
have better cross-subject functional correspondence than computing group
maps from the original volumetric data - the drawback, however, is that the
folding patterns can't be preserved (since they are different across
subjects), and you will end up with a much less folded cortical ribbon with
oddly sharp boundaries (and perfect correlation along the normal vector of
the surface).  Processing the data in cifti format will use less memory, be
more correct to the nature of the data, and make it more obvious that you
aren't really using a volumetric processing stream.  Matlab and python both
have support for reading and writing cifti files (though in matlab there
isn't good support for spatial relationships), as well as a few other
languages (the cifti code from workbench has been made into a c++ library,
though you will also need a gifti library to make full use of spatial
relationships).  wb_command can do several types of spatial processing
operations on cifti, and -cifti-convert will allow you to feed the data
through virtually any tool that doesn't use spatial neighborhood
information.

Tim


On Tue, Nov 13, 2018 at 10:45 AM, Nicola Toschi 
wrote:

> Thank you Steve,
>
> I was hoping to get them out of the CIFTI versions (also so I don't have
> to reprocess the 4D FIX data for all subjects). Maybe with cifti-convert?
> The brain would not be fully covered here i realise but much better than
> nothing.
>
> Alternatively, do you think there is a chance of obtaining them somehow
> (since they have been calculated by you guys anyway)? Can i put in a
> request somewhere maybe?
>
> Thank you in advance!
>
> Nicola
>
>
> On 11/13/2018 5:13 PM, Steve Smith wrote:
>
> Hi - we calculated them in order to estimate the volumetric group maps.
> However AFAIK we didn't bundle them in the PTN release.
> You can easily get them though by regressing node timeseries into 4D
> FIX-cleaned data.
>
> Cheers.
>
>
> On 13 Nov 2018, at 16:09, Nicola Toschi  wrote:
>
> Dear HCP list and experts,
>
> I was wondering if the subject-specific node maps from the latest PTN
> release (which are available in CIFTI format) are also available in
> volumetric space (which would aid the specific analysis we are running).
>
> Or if not, maybe a pointer on how to convert them?
>
> Thank you very much in advance!
>
> nicola
>
> ---
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>
>
> 
> ---
> Stephen M. Smith, Professor of Biomedical Engineering
> Head of Analysis,  WIN (FMRIB) Oxford
>
> FMRIB, JR Hospital, Headington, Oxford  OX3 9DU, UK
> +44 (0) 1865 610470
> st...@fmrib.ox.ac.ukhttp://www.fmrib.ox.ac.uk/~steve
> 
> ---
>
> Stop the cultural destruction of Tibet 
>
>
>
>
>
>
>
>
>
>
>
> 
>  Virus-free.
> www.avast.com
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Re: [HCP-Users] Convert subject-specific ICA node maps to volumetric space?

[Nicola Toschi]

Thank you Steve,

I was hoping to get them out of the CIFTI versions (also so I don't have 
to reprocess the 4D FIX data for all subjects). Maybe with 
cifti-convert? The brain would not be fully covered here i realise but 
much better than nothing.


Alternatively, do you think there is a chance of obtaining them somehow 
(since they have been calculated by you guys anyway)? Can i put in a 
request somewhere maybe?


Thank you in advance!

Nicola


On 11/13/2018 5:13 PM, Steve Smith wrote:
Hi - we calculated them in order to estimate the volumetric group 
maps.  However AFAIK we didn't bundle them in the PTN release.
You can easily get them though by regressing node timeseries into 4D 
FIX-cleaned data.


Cheers.


On 13 Nov 2018, at 16:09, Nicola Toschi > wrote:


Dear HCP list and experts,

I was wondering if the subject-specific node maps from the latest PTN
release (which are available in CIFTI format) are also available in
volumetric space (which would aid the specific analysis we are running).

Or if not, maybe a pointer on how to convert them?

Thank you very much in advance!

nicola

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---
Stephen M. Smith, Professor of Biomedical Engineering
Head of Analysis,  WIN (FMRIB) Oxford

FMRIB, JR Hospital, Headington, Oxford  OX3 9DU, UK
+44 (0) 1865 610470
st...@fmrib.ox.ac.uk  
http://www.fmrib.ox.ac.uk/~steve 

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Re: [HCP-Users] Convert subject-specific ICA node maps to volumetric space?

[Steve Smith]

Hi - we calculated them in order to estimate the volumetric group maps.  
However AFAIK we didn't bundle them in the PTN release.  
You can easily get them though by regressing node timeseries into 4D 
FIX-cleaned data.

Cheers.


> On 13 Nov 2018, at 16:09, Nicola Toschi  wrote:
> 
> Dear HCP list and experts,
> 
> I was wondering if the subject-specific node maps from the latest PTN 
> release (which are available in CIFTI format) are also available in 
> volumetric space (which would aid the specific analysis we are running).
> 
> Or if not, maybe a pointer on how to convert them?
> 
> Thank you very much in advance!
> 
> nicola
> 
> ---
> This email has been checked for viruses by Avast antivirus software.
> https://www.avast.com/antivirus
> 
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> http://lists.humanconnectome.org/mailman/listinfo/hcp-users


---
Stephen M. Smith, Professor of Biomedical Engineering
Head of Analysis,  WIN (FMRIB) Oxford

FMRIB, JR Hospital, Headington, Oxford  OX3 9DU, UK
+44 (0) 1865 610470
st...@fmrib.ox.ac.ukhttp://www.fmrib.ox.ac.uk/~steve 

---

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[HCP-Users] Convert subject-specific ICA node maps to volumetric space?

[Nicola Toschi]

Dear HCP list and experts,

I was wondering if the subject-specific node maps from the latest PTN 
release (which are available in CIFTI format) are also available in 
volumetric space (which would aid the specific analysis we are running).

Or if not, maybe a pointer on how to convert them?

Thank you very much in advance!

nicola

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Re: [HCP-Users] (no subject)

[Glasser, Matthew]

I was recommending CIFTI files not NIFTI files.  You would want to use a CIFTI 
atlas so that brain areas are aligned.

Peace,

Matt.

From: HERACLES PANAGIOTIDES <he...@uw.edu<mailto:he...@uw.edu>>
Date: Thursday, January 4, 2018 at 11:54 AM
To: Matt Glasser <glass...@wustl.edu<mailto:glass...@wustl.edu>>
Subject: Re: [HCP-Users] (no subject)

Hello again, Matt.

Happy New Year!

Thank you so much for the detailed processing steps.

What I downloaded so far was the Resting State fMRI  FIX-Denoised (Extended) 
series.  I assumed that this was the most processed series (denoised, alined, 
etc).  My next assumption was that (1) I could take these NIFTI files, (2) 
demean, variance normilize (i.e., z-transform them), and then (3) extract ROIs 
using standard atlases.   Should I include some of the steps you outlined in 
your email, or is what I am doing sufficient?  Sorry about these simple minded 
questions.

Best,
Heracles

From: Glasser, Matthew
Sent: Monday, January 01, 2018 4:30 PM
To: HERACLES PANAGIOTIDES ; hcp-users@humanconnectome.org
Subject: Re: [HCP-Users] (no subject)

>From previous post:

There are four rfMRI runs per subject.  LR vs RL refers to the phase encoding 
direction and 1 and 2 refers to the session each run was acquired in.  You 
should use balanced amounts of RL and LR data ideally, as the phase encoding 
direction does create some asymmetry in the data.  You want to use the 
MSMAll_hp2000_clean dtseries file, as this file has its cortical areas aligned 
across subjects.  If you wish to concatenate across runs, you should remove the 
mean image.  You could also variance normalize the data with by multiplying by 
the bias field and dividing by the variance normalization map though these maps 
would need to be resampled into MSMAll alignment as the currently distributed 
files are in MSMSulc alignment.  This can be done using:

#Create spheres for resampling from MSMSulc to MSMAll on the 32k mesh
wb_command -surface-project-unproject 
${StudyFolder}/${Subject}/MNINonLinear/fsaverage_LR32k/${Subject}.L.sphere.32k_fs_LR.surf.gii
 
${StudyFolder}/${Subject}/MNINonLinear/Native/${Subject}.L.sphere.MSMSulc.native.surf.gii
 
${StudyFolder}/${Subject}/MNINonLinear/Native/${Subject}.L.sphere.MSMAll.native.surf.gii
 
${StudyFolder}/${Subject}/MNINonLinear/fsaverage_LR32k/${Subject}.L.sphere.MSMSulc_MSMAll.32k_fs_LR.surf.gii
wb_command -surface-project-unproject 
${StudyFolder}/${Subject}/MNINonLinear/fsaverage_LR32k/${Subject}.R.sphere.32k_fs_LR.surf.gii
 
${StudyFolder}/${Subject}/MNINonLinear/Native/${Subject}.R.sphere.MSMSulc.native.surf.gii
 
${StudyFolder}/${Subject}/MNINonLinear/Native/${Subject}.R.sphere.MSMAll.native.surf.gii
 
${StudyFolder}/${Subject}/MNINonLinear/fsaverage_LR32k/${Subject}.R.sphere.MSMSulc_MSMAll.32k_fs_LR.surf.gii

#Resample Variance Normalization Map
wb_command -cifti-resample 
${StudyFolder}/${Subject}/MNINonLinear/Results/${fMRIName}/${fMRIName}_Atlas_hp2000_clean_vn.dscalar.nii
 COLUMN 
${StudyFolder}/${Subject}/MNINonLinear/Results/${fMRIName}/${fMRIName}_Atlas_hp2000_clean_vn.dscalar.nii
 COLUMN ADAP_BARY_AREA ENCLOSING_VOXEL 
${StudyFolder}/${Subject}/MNINonLinear/Results/${fMRIName}/${fMRIName}_Atlas_MSMAll_hp2000_clean_vn.dscalar.nii
 -surface-postdilate 30 -nearest -left-spheres 
${StudyFolder}/${Subject}/MNINonLinear/fsaverage_LR32k/${Subject}.L.sphere.MSMSulc_MSMAll.32k_fs_LR.surf.gii
 
${StudyFolder}/${Subject}/MNINonLinear/fsaverage_LR32k/${Subject}.L.sphere.32k_fs_LR.surf.gii
 -left-area-surfs 
${StudyFolder}/${Subject}/T1w/fsaverage_LR32k/${Subject}.L.midthickness.32k_fs_LR.surf.gii
 
${StudyFolder}/${Subject}/T1w/fsaverage_LR32k/${Subject}.L.midthickness_MSMAll.32k_fs_LR.surf.gii
 -right-spheres 
${StudyFolder}/${Subject}/MNINonLinear/fsaverage_LR32k/${Subject}.R.sphere.MSMSulc_MSMAll.32k_fs_LR.surf.gii
 
${StudyFolder}/${Subject}/MNINonLinear/fsaverage_LR32k/${Subject}.R.sphere.32k_fs_LR.surf.gii
 -right-area-surfs 
${StudyFolder}/${Subject}/T1w/fsaverage_LR32k/${Subject}.R.midthickness.32k_fs_LR.surf.gii
 
${StudyFolder}/${Subject}/T1w/fsaverage_LR32k/${Subject}.R.midthickness_MSMAll.32k_fs_LR.surf.gii

#Resample Bias Field Map
wb_command -cifti-resample 
${StudyFolder}/${Subject}/MNINonLinear/Results/${fMRIName}/${fMRIName}_Atlas_hp2000_clean_bias.dscalar.nii
 COLUMN 
${StudyFolder}/${Subject}/MNINonLinear/Results/${fMRIName}/${fMRIName}_Atlas_hp2000_clean_bias.dscalar.nii
 COLUMN ADAP_BARY_AREA ENCLOSING_VOXEL 
${StudyFolder}/${Subject}/MNINonLinear/Results/${fMRIName}/${fMRIName}_Atlas_MSMAll_hp2000_clean_bias.dscalar.nii
 -surface-postdilate 30 -nearest -left-spheres 
${StudyFolder}/${Subject}/MNINonLinear/fsaverage_LR32k/${Subject}.L.sphere.MSMSulc_MSMAll.32k_fs_LR.surf.gii
 
${StudyFolder}/${Subject}/MNINonLinear/fsaverage_LR32k/${Subject}.L.sphere.32k_fs_LR.surf.gii
 -left-area-surfs 
${StudyFolder}/${Subject}/T1w/fsaverage_LR32k/${Subject}.L.midthickness.32k_fs_LR.surf.gii
 
${StudyFolder}/${Subject}/T1

Re: [HCP-Users] (no subject)

[Glasser, Matthew]

ion)
wb_command -cifti-math “((TCS - Mean) * Bias) / VN” 
${StudyFolder}/${Subject}/MNINonLinear/Results/${fMRIName}/${fMRIName}_Atlas_MSMAll_hp2000_clean_nobias_vn.dtseries.nii
 -var TCS 
${StudyFolder}/${Subject}/MNINonLinear/Results/${fMRIName}/${fMRIName}_Atlas_MSMAll_hp2000_clean.dtseries.nii
 -var Mean 
${StudyFolder}/${Subject}/MNINonLinear/Results/${fMRIName}/${fMRIName}_Atlas_MSMAll_hp2000_clean_mean.dscalar.nii
 -var Bias 
${StudyFolder}/${Subject}/MNINonLinear/Results/${fMRIName}/${fMRIName}_Atlas_MSMAll_hp2000_clean_bias.dscalar.nii
 -var VN 
${StudyFolder}/${Subject}/MNINonLinear/Results/${fMRIName}/${fMRIName}_Atlas_MSMAll_hp2000_clean_vn.dscalar.nii

Peace,

Matt.

From: HERACLES PANAGIOTIDES <he...@uw.edu<mailto:he...@uw.edu>>
Date: Monday, January 1, 2018 at 6:26 PM
To: Matt Glasser <glass...@wustl.edu<mailto:glass...@wustl.edu>>
Subject: Re: [HCP-Users] (no subject)

Hi Matt and Happy New Year.

Is the processing already done and available on the site?  If o, what are the 
processed files called?

Thanks,
Heracles

From: Glasser, Matthew
Sent: Sunday, December 31, 2017 9:35 AM
To: hcp-users@humanconnectome.org
Cc: HERACLES PANAGIOTIDES
Subject: Re: [HCP-Users] (no subject)

The variance normalization is per timeseries.  We prefer to use the _vn files 
provided by the RestingStateStats pipeline so that this is equalizing the 
unstructured noise.

Peace,

Matt.

From: HERACLES PANAGIOTIDES <he...@uw.edu>
Date: Saturday, December 30, 2017 at 2:05 PM
To: Matt Glasser <glass...@wustl.edu>
Subject: Re: [HCP-Users] (no subject)

Hello Matt,

I am getting ready to launch a group analysis of rfMRI files using Matlab.  I 
want to make sure that I am not making any fundamental errors in preprocessing. 
 I would be deeply appreciative, if I could (phone?) consult with you or anyone 
else, to make sure that I am not making any gross mistakes.  At this point, I 
am following your instructions about mean and and variance normalization before 
ROI extraction.  For example, is this equivalent to a z-score transformation?  
If so, is this done to the entire 4D volume or to the individual voxel time 
series?

At any rate, these are some of my questions.

Thank you for being so kind.

Heracles


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Re: [HCP-Users] (no subject)

[Glasser, Matthew]

The variance normalization is per timeseries.  We prefer to use the _vn files 
provided by the RestingStateStats pipeline so that this is equalizing the 
unstructured noise.

Peace,

Matt.

From: HERACLES PANAGIOTIDES <he...@uw.edu<mailto:he...@uw.edu>>
Date: Saturday, December 30, 2017 at 2:05 PM
To: Matt Glasser <glass...@wustl.edu<mailto:glass...@wustl.edu>>
Subject: Re: [HCP-Users] (no subject)

Hello Matt,

I am getting ready to launch a group analysis of rfMRI files using Matlab.  I 
want to make sure that I am not making any fundamental errors in preprocessing. 
 I would be deeply appreciative, if I could (phone?) consult with you or anyone 
else, to make sure that I am not making any gross mistakes.  At this point, I 
am following your instructions about mean and and variance normalization before 
ROI extraction.  For example, is this equivalent to a z-score transformation?  
If so, is this done to the entire 4D volume or to the individual voxel time 
series?

At any rate, these are some of my questions.

Thank you for being so kind.

Heracles


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Re: [HCP-Users] (no subject)

[Glasser, Matthew]

I don’t know what the maximum capacity is.

Peace,

Matt.

From: hercp <he...@uw.edu<mailto:he...@uw.edu>>
Date: Friday, December 1, 2017 at 5:19 PM
To: Matt Glasser <glass...@wustl.edu<mailto:glass...@wustl.edu>>
Subject: Re: [HCP-Users] (no subject)

Thanks, Matt.  I am in the Seattle area and plan to upgrade my speed to 1 GBit. 
 Is this too fast for the server?

Heracles Panagiotides, PhD



From: Glasser, Matthew
Sent: Friday, December 01, 2017 1:49 PM
To: hercp ; HUMAN CONNECTOME
Subject: Re: [HCP-Users] (no subject)

1.  Depends on your internet connection and how far you are from us.

2.  The nucleus accumbens is segmented by FreeSurfer.  Dunno about the others.

Peace,

Matt.

From: <hcp-users-boun...@humanconnectome.org> on behalf of hercp <he...@uw.edu>
Date: Friday, December 1, 2017 at 12:58 PM
To: HUMAN CONNECTOME <hcp-users@humanconnectome.org>
Subject: [HCP-Users] (no subject)

Two questions:

1.  What is the speed limit for downloading.  I am planning to upgrade my 
internet.

2.  Does anyone know of a good ROI atlases that might include regions as the 
substantia nigra, the nucleus accumbens, subdivisions of the hypothalamus, etc.

Heracles Panagiotides, PhD



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Re: [HCP-Users] (no subject)

[Glasser, Matthew]

1.  Depends on your internet connection and how far you are from us.

2.  The nucleus accumbens is segmented by FreeSurfer.  Dunno about the others.

Peace,

Matt.

From: 
<hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>>
 on behalf of hercp <he...@uw.edu<mailto:he...@uw.edu>>
Date: Friday, December 1, 2017 at 12:58 PM
To: HUMAN CONNECTOME 
<hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>
Subject: [HCP-Users] (no subject)

Two questions:

1.  What is the speed limit for downloading.  I am planning to upgrade my 
internet.

2.  Does anyone know of a good ROI atlases that might include regions as the 
substantia nigra, the nucleus accumbens, subdivisions of the hypothalamus, etc.

Heracles Panagiotides, PhD



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[HCP-Users] (no subject)

[hercp]

Two questions:

1.  What is the speed limit for downloading.  I am planning to upgrade my 
internet.

2.  Does anyone know of a good ROI atlases that might include regions as the 
substantia nigra, the nucleus accumbens, subdivisions of the hypothalamus, etc. 
 

Heracles Panagiotides, PhD



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Re: [HCP-Users] (no subject)

[Glasser, Matthew]

Also there is a -volume-reduce command if you want to do reduce operations on 
NIFTI volumes.

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: Monday, October 23, 2017 at 4:23 PM
To: hercp <he...@uw.edu<mailto:he...@uw.edu>>
Cc: HUMAN CONNECTOME 
<hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] (no subject)

rfMRI_REST1_LR_hp2000_clean.nii.gz is a volume file, not a cifti file.  Cifti 
files end in things like .dtseries.nii.  See wb_command -cifti-help:

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

Tim


On Mon, Oct 23, 2017 at 4:17 PM, hercp <he...@uw.edu<mailto:he...@uw.edu>> 
wrote:
I am running the command

wb_command -cifti-reduce rfMRI_REST1_LR_hp2000_clean.nii.gz MEAN 
mean.rfMRI_REST1_LR_hp2000_clean.nii.gz

and I get this error returned:

ERROR: no cifti extension found in file C:/rfMRI_REST1_LR_hp2000_clean.nii.gz

Am I missing a step?

Thanks for your help,
Heracles Panagiotides, PhD



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Re: [HCP-Users] (no subject)

[Timothy Coalson]

rfMRI_REST1_LR_hp2000_clean.nii.gz is a volume file, not a cifti file.
Cifti files end in things like .dtseries.nii.  See wb_command -cifti-help:

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

Tim


On Mon, Oct 23, 2017 at 4:17 PM, hercp  wrote:

> I am running the command
>
>
> wb_command -cifti-reduce rfMRI_REST1_LR_hp2000_clean.nii.gz MEAN mean.
> rfMRI_REST1_LR_hp2000_clean.nii.gz
>
>
>
> and I get this error returned:
>
>
>
> ERROR: no cifti extension found in file C:/rfMRI_REST1_LR_hp2000_
> clean.nii.gz
>
>
>
> Am I missing a step?
>
>
>
> Thanks for your help,
> Heracles Panagiotides, PhD
>
>
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Re: [HCP-Users] (no subject) -> amygdala atlas

[Antonin Skoch]

Dear Heracles,

the development version of FreeSurfer now contains probabilistic labeling of 
nuclei of Amygdala:

https://surfer.nmr.mgh.harvard.edu/fswiki/HippocampalSubfieldsAndNucleiOfAmygdala

Regards,

Antonin Skoch


Hi Heracles, 
 
There?s a very nice parcellated amygdala atlas based on HCP data published by 
Tyszka and Pauli (https://www.ncbi.nlm.nih.gov/pubmed/27354150).  The atlas 
dataset is accessible via http://evendim.caltech.edu/amygdala-atlas/ in various 
spaces (MNI152 1mm and 700um and CIT168 700um) in both Nifti-1 format and Cifti 
dlabels. 
 
David 
 
> On Sep 12, 2017, at 4:55 PM, hercp  wrote: 
>  
> Does anyone know if there any atlases of amygdala subdivisions? 
>   
> Heracles Panagiotides, PhD 
>  
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Re: [HCP-Users] (no subject) -> amygdala atlas

[Alexander J. Shackman]

The CalTech Atlas is an important step forward, but does have a few
limitations. Reading the paper is highly recommended. It is based on only
one hemisphere. Given how it was constructed, you may wish to
diffeomorphically warp to mni152 via ANTS or 3dQwarp. Take care when
decimating to EPI resolution, if applicable.

Hth,
Alex

On Sep 12, 2017 7:20 PM, "David Van Essen"  wrote:

> Hi Heracles,
>
> There’s a very nice parcellated amygdala atlas based on HCP data published
> by Tyszka and Pauli (https://www.ncbi.nlm.nih.gov/pubmed/27354150).  The
> atlas dataset is accessible via http://evendim.caltech.edu/amygdala-atlas/
> in various spaces (MNI152 1mm and 700um and CIT168 700um) in both Nifti-1
> format and Cifti dlabels.
>
> David
>
> On Sep 12, 2017, at 4:55 PM, hercp  wrote:
>
> Does anyone know if there any atlases of amygdala subdivisions?
>
> Heracles Panagiotides, PhD
>
>
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Re: [HCP-Users] (no subject) -> amygdala atlas

[David Van Essen]

Hi Heracles,

There’s a very nice parcellated amygdala atlas based on HCP data published by 
Tyszka and Pauli (https://www.ncbi.nlm.nih.gov/pubmed/27354150).  The atlas 
dataset is accessible via http://evendim.caltech.edu/amygdala-atlas/ in various 
spaces (MNI152 1mm and 700um and CIT168 700um) in both Nifti-1 format and Cifti 
dlabels.

David

> On Sep 12, 2017, at 4:55 PM, hercp  wrote:
> 
> Does anyone know if there any atlases of amygdala subdivisions?
>  
> Heracles Panagiotides, PhD
> 
> 
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[HCP-Users] (no subject)

[hercp]

Does anyone know if there any atlases of amygdala subdivisions?

Heracles Panagiotides, PhD



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Re: [HCP-Users] Single Subject Parcellation

[Elam, Jennifer]

Hi Nicolò,

Matt Glasser did have a lecture on applying his multimodal group parcellation 
MMP1.0

(see https://balsa.wustl.edu/study/show/RVVG)
to individual subjects at the HCP Course. We intend to make a pipeline that 
does this and run it on all HCP subjects, but it is in a long list of 
priorities for the HCP as we are also gearing up to process data being 
collected for HCP-Development and HCP-Aging.


You can download the group parcellation from the BALSA database linked above if 
that can work for your purposes now.


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<mailto:e...@wustl.edu>
www.humanconnectome.org<http://www.humanconnectome.org/>



From: hcp-users-boun...@humanconnectome.org 
<hcp-users-boun...@humanconnectome.org> on behalf of Nicolo Biagi 
<n.bi...@pgr.reading.ac.uk>
Sent: Thursday, July 13, 2017 11:38:27 AM
To: hcp-users@humanconnectome.org
Subject: [HCP-Users] Single Subject Parcellation


Hi,

I am Nicolò Biagi, a PhD student at the University of Reading (UK).


I am writing to you because I've seen that you presented the Single Subject 
Parcellation at the 2017 HCP Course: "Exploring the Human Connectome", held in 
June in Vancouver, and I'd like to ask you if is now possible to use it and 
where I can find it.


Thank you very much for your time.


Best regards,


Nicolò Biagi
PhD Student
School of Psychology and Clinical Language Sciences
University of Reading

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[HCP-Users] Single Subject Parcellation

[Nicolo Biagi]

Hi,

I am Nicolò Biagi, a PhD student at the University of Reading (UK).


I am writing to you because I've seen that you presented the Single Subject 
Parcellation at the 2017 HCP Course: "Exploring the Human Connectome", held in 
June in Vancouver, and I'd like to ask you if is now possible to use it and 
where I can find it.


Thank you very much for your time.


Best regards,


Nicolò Biagi
PhD Student
School of Psychology and Clinical Language Sciences
University of Reading

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Re: [HCP-Users] (no subject)

[Harms, Michael]

Hi Ariana,
If you were referring to asymmetry in the ventricles, I passed an image on to 
our radiologist, and he confirmed that the ventricular asymmetry is within 
normal variability.

If there was something else that you were referring to, please let us know off 
the list.

thanks,
-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 "Reid, Erin" <e...@wustl.edu<mailto:e...@wustl.edu>>
Date: Wednesday, May 24, 2017 at 1:10 PM
To: Ariana Cahn <ac...@ualberta.ca<mailto:ac...@ualberta.ca>>
Cc: "hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>" 
<hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] (no subject)

I see asymmetries in the ventricles.  Is this what you are referring to?  Our 
Radiologist looked at all of our subjects’ scans and didn’t note any issue.

Erin

On May 24, 2017, at 12:46 PM, Ariana Cahn 
<ac...@ualberta.ca<mailto:ac...@ualberta.ca>> wrote:

The brain is very asymmetric, so I was wondering if this has been noted by the 
HCP team.

On Wed, May 24, 2017 at 11:43 AM, Reid, Erin 
<e...@wustl.edu<mailto:e...@wustl.edu>> wrote:
I do not have any flags for this subject from structural scan or surface QC 
measures.  What are you referring to specifically?

Erin

On May 24, 2017, at 11:44 AM, Ariana Cahn 
<ac...@ualberta.ca<mailto:ac...@ualberta.ca>> wrote:

Hello,

I was wondering if subject 130619 has been flagged in any way previously.

Thanks,

--
Ariana Cahn
BSc (Hons), Neuroscience

ac...@ualberta.ca<mailto:ac...@ualberta.ca>

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--
Ariana Cahn
BSc (Hons), Neuroscience

ac...@ualberta.ca<mailto:ac...@ualberta.ca>


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The materials in this message are private and may contain Protected Healthcare 
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Re: [HCP-Users] (no subject)

[Reid, Erin]

I see asymmetries in the ventricles.  Is this what you are referring to?  Our 
Radiologist looked at all of our subjects’ scans and didn’t note any issue.

Erin

On May 24, 2017, at 12:46 PM, Ariana Cahn 
> wrote:

The brain is very asymmetric, so I was wondering if this has been noted by the 
HCP team.

On Wed, May 24, 2017 at 11:43 AM, Reid, Erin 
> wrote:
I do not have any flags for this subject from structural scan or surface QC 
measures.  What are you referring to specifically?

Erin

On May 24, 2017, at 11:44 AM, Ariana Cahn 
> wrote:

Hello,

I was wondering if subject 130619 has been flagged in any way previously.

Thanks,

--
Ariana Cahn
BSc (Hons), Neuroscience

ac...@ualberta.ca

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--
Ariana Cahn
BSc (Hons), Neuroscience

ac...@ualberta.ca


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Re: [HCP-Users] (no subject)

[Reid, Erin]

I do not have any flags for this subject from structural scan or surface QC 
measures.  What are you referring to specifically?

Erin

On May 24, 2017, at 11:44 AM, Ariana Cahn 
> wrote:

Hello,

I was wondering if subject 130619 has been flagged in any way previously.

Thanks,

--
Ariana Cahn
BSc (Hons), Neuroscience

ac...@ualberta.ca

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[HCP-Users] (no subject)

[Ariana Cahn]

Hello,

I was wondering if subject 130619 has been flagged in any way previously.

Thanks,

-- 
*Ariana Cahn*
*BSc (Hons), *Neuroscience

*ac...@ualberta.ca *

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Re: [HCP-Users] Single Subject Pipelines

[Glasser, Matthew]

Not yet.  There are still several things ahead of them in the queue.

Peace,

Matt.

From: 
<hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>>
 on behalf of Nicolo Biagi 
<n.bi...@pgr.reading.ac.uk<mailto:n.bi...@pgr.reading.ac.uk>>
Date: Friday, March 24, 2017 at 5:04 AM
To: "hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>" 
<hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>
Subject: [HCP-Users] Single Subject Pipelines


Hello everyone,


sorry for bothering you, but I'd like to ask if the pipelines for the single 
subject parcellation have been released yet?


If not, is there a raw idea of when they will be released?


Thank you very much.


Best regards,


Nicolò Biagi
PhD Student
School of Psychology and Clinical Language Sciences
University of Reading

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The materials in this message are private and may contain Protected Healthcare 
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[HCP-Users] Single Subject Pipelines

[Nicolo Biagi]

Hello everyone,


sorry for bothering you, but I'd like to ask if the pipelines for the single 
subject parcellation have been released yet?


If not, is there a raw idea of when they will be released?


Thank you very much.


Best regards,


Nicolò Biagi
PhD Student
School of Psychology and Clinical Language Sciences
University of Reading

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Re: [HCP-Users] 1200-subject release on AWS

[Benjamin Risk]

Okay, thank you.

On Tue, Mar 21, 2017 at 4:23 PM, Elam, Jennifer <e...@wustl.edu> wrote:

> It is looking like it will be at least a month before S1200 data will be
> available on Amazon S3.
>
>
> Sorry for the delay due to competing priorities for the staff involved.
>
> 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 <hcp-users-bounces@
> humanconnectome.org> on behalf of Benjamin Risk <bb...@cornell.edu>
> *Sent:* Tuesday, March 21, 2017 1:35:39 PM
> *To:* hcp-users@humanconnectome.org
> *Subject:* [HCP-Users] 1200-subject release on AWS
>
> Hello HCP experts,
>
> If I understand correctly, the 1200-subject release is not yet on Amazon
> S3. Do you have any information about when it will be available?
>
> Thank you!
> Ben
>
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Re: [HCP-Users] 1200-subject release on AWS

[Elam, Jennifer]

It is looking like it will be at least a month before S1200 data will be 
available on Amazon S3.


Sorry for the delay due to competing priorities for the staff involved.

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<mailto:e...@wustl.edu>
www.humanconnectome.org<http://www.humanconnectome.org/>



From: hcp-users-boun...@humanconnectome.org 
<hcp-users-boun...@humanconnectome.org> on behalf of Benjamin Risk 
<bb...@cornell.edu>
Sent: Tuesday, March 21, 2017 1:35:39 PM
To: hcp-users@humanconnectome.org
Subject: [HCP-Users] 1200-subject release on AWS

Hello HCP experts,

If I understand correctly, the 1200-subject release is not yet on Amazon S3. Do 
you have any information about when it will be available?

Thank you!
Ben

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[HCP-Users] 1200-subject release on AWS

[Benjamin Risk]

Hello HCP experts,

If I understand correctly, the 1200-subject release is not yet on Amazon
S3. Do you have any information about when it will be available?

Thank you!
Ben

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Re: [HCP-Users] (no subject)

[Burgess, Gregory]

Hi Ferdaus,

It doesn’t appear that you’re using FIX data, but I think you should seriously 
consider doing so. To be clear, we believe that using FIX-denoised timeseries 
data is a replacement for / better alternative to: 1) regression of head motion 
estimates, 2) frame censoring / scrubbing of high motion timepoints, and 3) 
bandpass filtering.

Other regressors, such as WM/CSF/GS regressors may need special handling to use 
in the context of FIX-denoised data. I believe those steps have been covered in 
other posts to the HCP mailing list.

--Greg


Greg Burgess, Ph.D.
Staff Scientist, Human Connectome Project
Washington University School of Medicine
Department of Psychiatry
Phone: 314-362-7864
Email: gburg...@wustl.edu

> On Oct 25, 2016, at 5:21 PM, Glasser, Matthew <glass...@wustl.edu> wrote:
>
> We don’t recommend doing bandpass filtering on HCP data, however if you must, 
> you can convert the file to a fake NIFTI with wb_command -cifti-convert, run 
> fslmaths on it, and then convert it back to CIFTI.
>
> Peace,
>
> Matt.
>
> From: Ferdaus Kawsar <ferdaus.kaw...@gmail.com>
> Date: Tuesday, October 25, 2016 at 10:17 AM
> To: Matt Glasser <glass...@wustl.edu>
> Subject: Re: [HCP-Users] (no subject)
>
> Hi Matt,
>This is how I am removing noise from Volume file. Following is a 
> AFNI command.
> 3dTproject -input rfMRI_REST1_AP.nii.gz -prefix rfMRI_REST1_AP_cleaned.nii.gz 
> -ort  rfMRI_REST1_AP_WM_Timecourse.1D -ort rfMRI_REST1_AP_CSF_Timecourse.1D 
> -ort rfMRI_REST1_AP_GS_Timecourse.1D -polort 2 -passband 0.01 0.1
>
> However, this only removes "noise" from the voxels in the volume file. How do 
> I clean the surface data in a similar process? I want to create a cifti file 
> by using -cifti-create-dense-timeseries
> and use the cleaned volume data and cleaned surafce data for input of this 
> command.
>
> Best regards
> -Ferdaus
>
>
> On Tue, Oct 25, 2016 at 4:01 AM, Glasser, Matthew <glass...@wustl.edu> wrote:
>> We don’t support using ft_read_cifti for MRI data, as it currently has some 
>> bugs.  Also I am not sure what you mean by “remove noise.”
>>
>> Peace,
>>
>> Matt.
>>
>> From: <hcp-users-boun...@humanconnectome.org> on behalf of Ferdaus Kawsar 
>> <ferdaus.kaw...@gmail.com>
>> Date: Tuesday, October 25, 2016 at 12:31 AM
>> To: "hcp-users@humanconnectome.org" <HCP-Users@humanconnectome.org>
>> Subject: [HCP-Users] (no subject)
>>
>> Hi HCP Experts,
>>   I need some help with  resting analysis of my data. I 
>> have extracted average time course for each sub-cortical parcels. I have 
>> also extracted average time course for each cortical parcels (BA, aparc, 
>> aparc.2009 and Glasser parcellation). For this I used  -cifti-parcellate 
>> command from workbench. However, to remove noise I used 3dTproject command 
>> of Afni on the volume file. My plan was to use 
>> -cifti-create-dense-timeseries to convert the volume data into dtseries.nii 
>> format so that I can read it into matlab using ft_read_cifti. However, I 
>> think 3dTproject only removed noise from volume file (sub-cortical areas?). 
>> How do I remove noise from cortical data?
>>
>> Thanks in advance.
>>
>> Best
>> -Ferdaus
>>
>>
>> Ferdaus A. Kawsar, PhD
>> Research Scientist II
>> Department of Neurology
>> Medical College of Wisconsin
>> Milwaukee, WI
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>>
>>
>> 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.
>
>
>
> --
> Ferdaus A. Kawsar, PhD
> Research Scientist II
> Department of Neurology
> Medical College of Wisconsin
> Milwaukee, WI
>
>
> 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 
&g

Re: [HCP-Users] (no subject)

[Glasser, Matthew]

We don't recommend doing bandpass filtering on HCP data, however if you must, 
you can convert the file to a fake NIFTI with wb_command -cifti-convert, run 
fslmaths on it, and then convert it back to CIFTI.

Peace,

Matt.

From: Ferdaus Kawsar <ferdaus.kaw...@gmail.com<mailto:ferdaus.kaw...@gmail.com>>
Date: Tuesday, October 25, 2016 at 10:17 AM
To: Matt Glasser <glass...@wustl.edu<mailto:glass...@wustl.edu>>
Subject: Re: [HCP-Users] (no subject)

Hi Matt,
   This is how I am removing noise from Volume file. Following is a 
AFNI command.
3dTproject -input rfMRI_REST1_AP.nii.gz -prefix rfMRI_REST1_AP_cleaned.nii.gz 
-ort  rfMRI_REST1_AP_WM_Timecourse.1D -ort rfMRI_REST1_AP_CSF_Timecourse.1D 
-ort rfMRI_REST1_AP_GS_Timecourse.1D -polort 2 -passband 0.01 0.1

However, this only removes "noise" from the voxels in the volume file. How do I 
clean the surface data in a similar process? I want to create a cifti file by 
using -cifti-create-dense-timeseries
and use the cleaned volume data and cleaned surafce data for input of this 
command.

Best regards
-Ferdaus


On Tue, Oct 25, 2016 at 4:01 AM, Glasser, Matthew 
<glass...@wustl.edu<mailto:glass...@wustl.edu>> wrote:
We don't support using ft_read_cifti for MRI data, as it currently has some 
bugs.  Also I am not sure what you mean by "remove noise."

Peace,

Matt.

From: 
<hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>>
 on behalf of Ferdaus Kawsar 
<ferdaus.kaw...@gmail.com<mailto:ferdaus.kaw...@gmail.com>>
Date: Tuesday, October 25, 2016 at 12:31 AM
To: "hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>" 
<HCP-Users@humanconnectome.org<mailto:HCP-Users@humanconnectome.org>>
Subject: [HCP-Users] (no subject)

Hi HCP Experts,
  I need some help with  resting analysis of my data. I 
have extracted average time course for each sub-cortical parcels. I have also 
extracted average time course for each cortical parcels (BA, aparc, aparc.2009 
and Glasser parcellation). For this I used  -cifti-parcellate command from 
workbench. However, to remove noise I used 3dTproject command of Afni on the 
volume file. My plan was to use -cifti-create-dense-timeseries to convert the 
volume data into dtseries.nii format so that I can read it into matlab using 
ft_read_cifti. However, I think 3dTproject only removed noise from volume file 
(sub-cortical areas?). How do I remove noise from cortical data?

Thanks in advance.

Best
-Ferdaus


Ferdaus A. Kawsar, PhD
Research Scientist II
Department of Neurology
Medical College of Wisconsin
Milwaukee, WI

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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.



--
Ferdaus A. Kawsar, PhD
Research Scientist II
Department of Neurology
Medical College of Wisconsin
Milwaukee, WI


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 
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[HCP-Users] (no subject)

[Ferdaus Kawsar]

Hi HCP Experts,
  I need some help with  resting analysis of my data. I
have extracted average time course for each sub-cortical parcels. I have
also extracted average time course for each cortical parcels (BA, aparc,
aparc.2009 and Glasser parcellation). For this I used
-cifti-parcellate command
from workbench. However, to remove noise I used 3dTproject command of Afni
on the volume file. My plan was to use -cifti-create-dense-timeseries to
convert the volume data into dtseries.nii format so that I can read it into
matlab using *ft_read_cifti. *However, I think 3dTproject only removed
noise from volume file (sub-cortical areas?). How do I remove noise from
cortical data?

Thanks in advance.

Best
-Ferdaus


Ferdaus A. Kawsar, PhD
Research Scientist II
Department of Neurology
Medical College of Wisconsin
Milwaukee, WI

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[HCP-Users] (no subject)

[Maryam Abaei]

Hi,
I am wondering if I can have the gradient table that HCP uses for dMRI?

Thank you in advance,
Best wishes,
Maryam

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[HCP-Users] (no subject)

[gelindo.castellarin]

Inviato da Samsung Mobile.
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Re: [HCP-Users] (no subject)

[ARCHANA S]

I am facing problems while uploading brain images onto 3D Slicer software. As
  i try to load the image,the image gets inverted. Mapping is not
  possible. KIndly provide me assistance.
  Thank you

On 8/11/16, ARCHANA S  wrote:
> I am facing problems while uploading brain images onto 3D software. As
>  i try to load the image,the image gets inverted. Mapping is not
>  possible. KIndly provide me assistance.
>  Thank you
> ___
> HCP-Users mailing list
> HCP-Users@humanconnectome.org
> http://lists.humanconnectome.org/mailman/listinfo/hcp-users
>
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[HCP-Users] (no subject)

[ARCHANA S]

I am facing problems while uploading brain images onto 3D software. As
 i try to load the image,the image gets inverted. Mapping is not
 possible. KIndly provide me assistance.
 Thank you
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Re: [HCP-Users] One subject information missing

[Elam, Jennifer]

Subject 599065 is Male. We will correct this info in ConnectomeDB.


Thanks,

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<mailto:e...@wustl.edu>
www.humanconnectome.org<http://www.humanconnectome.org/>



From: hcp-users-boun...@humanconnectome.org 
<hcp-users-boun...@humanconnectome.org> on behalf of Aaron C 
<aaroncr...@outlook.com>
Sent: Thursday, June 16, 2016 12:25:09 PM
To: hcp-users@humanconnectome.org
Subject: [HCP-Users] One subject information missing

Dear HCP experts,

I noticed that subject #599065's gender information is missing. Could anyone 
please provide this information? Thank you.

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[HCP-Users] One subject information missing

[Aaron C]

Dear HCP experts,

I noticed that subject #599065's gender information is missing. Could anyone 
please provide this information? Thank you.
  
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Re: [HCP-Users] (no subject)

[Donna Dierker]

I don't know the name of the package, but it might be something like 
"structural extended" -- one of them has the subject's freesurfer directory in 
it.


On Dec 27, 2015, at 7:08 PM, A-reum Min  wrote:

> hello 
> my name is areum.
> i have some question to you.
> a few days ago i was down load HCP(human connectom project) s900 data. --> 3T 
> imaging protocol completed True ver.
> but.. how can i use these HCP format.
> i use a freesurfer software.
> i have never seen before these format(fig.1.png) like a .gii , nii..
> I want to see HCP data subjects's average cortical thickness using qdec or 
> freeview.
> how can i to do? 
> plz answer me  
> ___
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> HCP-Users@humanconnectome.org
> http://lists.humanconnectome.org/mailman/listinfo/hcp-users
> 
> 


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Re: [HCP-Users] (no subject)

[Donna Dierker]

Jenn wrote:
> output from the HCP pipelines that toy ate unfamiliar worth is available

Auto-complete run amok or typing while nursing? ;-)

A-reum, if you have the structural extended package, you'll find the freesurfer 
subject directory here:

> /MyDataPath/subjectID/T1w/subjectID

Qdec should be happy with the stuff in there.

I'm not sure which tools in the Freesurfer distribution can read CIFTI (e.g., 
*.dscalar.nii, *.dtseries.nii).  I know some tools can read GIFTI (*.surf.gii) 
files.  But whether all utilities do equally isn't clear to me.

If you want to do statistical analyses with these files, I'd like to point you 
to PALM:

https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/PALM/UserGuide

There is a bit of preprocessing to be done going into PALM, but it handles 
family structure and so much more. 


On Dec 28, 2015, at 11:44 AM, Jennifer Elam  wrote:

> Yes, the preprocessed "Structural Extended" package for each subject has the 
> Freesurfer outputs that are intermediates in the HCP preprocessing pipelines.
> More info about the files output from the HCP pipelines that toy ate 
> unfamiliar worth is available in the HCP Reference Manual for the 900 
> Subjects release, on the HCP wiki,  and in various posts to the HCP-users 
> list (searchable in the archive). Links to these are all at 
> humanconnectome.org
> 
> Best, 
> Jenn
> 
> On Dec 28, 2015 10:06 AM, "Donna Dierker"  wrote:
> I don't know the name of the package, but it might be something like 
> "structural extended" -- one of them has the subject's freesurfer directory 
> in it.
> 
> 
> On Dec 27, 2015, at 7:08 PM, A-reum Min  wrote:
> 
>> hello
>> my name is areum.
>> i have some question to you.
>> a few days ago i was down load HCP(human connectom project) s900 data. --> 
>> 3T imaging protocol completed True ver.
>> but.. how can i use these HCP format.
>> i use a freesurfer software.
>> i have never seen before these format(fig.1.png) like a .gii , nii..
>> I want to see HCP data subjects's average cortical thickness using qdec or 
>> freeview.
>> how can i to do?
>> plz answer me
>> ___
>> HCP-Users mailing list
>> HCP-Users@humanconnectome.org
>> http://lists.humanconnectome.org/mailman/listinfo/hcp-users
>> 
>> 
> 
> 
> ___
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> http://lists.humanconnectome.org/mailman/listinfo/hcp-users


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Re: [HCP-Users] (no subject)

[Jennifer Elam]

Yes, the preprocessed "Structural Extended" package for each subject has
the Freesurfer outputs that are intermediates in the HCP preprocessing
pipelines.
More info about the files output from the HCP pipelines that toy ate
unfamiliar worth is available in the HCP Reference Manual for the 900
Subjects release, on the HCP wiki,  and in various posts to the HCP-users
list (searchable in the archive). Links to these are all at
humanconnectome.org

Best,
Jenn
On Dec 28, 2015 10:06 AM, "Donna Dierker"  wrote:

> I don't know the name of the package, but it might be something like
> "structural extended" -- one of them has the subject's freesurfer directory
> in it.
>
>
> On Dec 27, 2015, at 7:08 PM, A-reum Min  wrote:
>
> > hello
> > my name is areum.
> > i have some question to you.
> > a few days ago i was down load HCP(human connectom project) s900 data.
> --> 3T imaging protocol completed True ver.
> > but.. how can i use these HCP format.
> > i use a freesurfer software.
> > i have never seen before these format(fig.1.png) like a .gii , nii..
> > I want to see HCP data subjects's average cortical thickness using qdec
> or freeview.
> > how can i to do?
> > plz answer me
> > ___
> > 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
>

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[HCP-Users] (no subject)

[A-reum Min]

hello
my name is areum.
i have some question to you.
a few days ago i was down load HCP(human connectom project) s900 data. -->
3T imaging protocol completed True ver.
but.. how can i use these HCP format.
i use a freesurfer software.
i have never seen before these format(fig.1.png) like a .gii , nii..
I want to see HCP data subjects's average cortical thickness using qdec or
freeview.
how can i to do?
plz answer me

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Re: [HCP-Users] Inter-subject vertex:voxel correspondence

[Matthew George Liptrot]

Hi again,

Many thanks Matt, Carl and Tim for such quick replies! A few follow-up 
questions are in-line below:

http://about.me/matthewliptrot


I am a novice at handling surfaces, and at using the Connectome 
Workbench/commandline, so apologies if the following is obvious.

We want to be able to perform connectivity analysis of subjects (both HCP and 
our own) using diffusion tractography. In order to directly compare the 
resultant (voxel-to-voxel) connectivity matrices across subjects, we would like 
to have a one-to-one correspondence between the tractography seed voxels in 
each subject. I presume that the best way to do this would be to first select 
the desired set of (inter-subject matched) seed points upon the aligned surface 
meshes already provided (BIG thanks!) by the HCP and then convert them to the 
(nearest) voxel? (I realise that this may be a surjective mapping). Are there 
functions/commands within the Connectome Workbench that can do this? Or are 
there more sensible approaches to achieving this?

We don't seed cortex tractography from voxels, we seed from surfaces. FSL 
tractography supports this:

http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FDT/UserGuide#Using_surfaces

Great!
Qn 1: Is the recommended approach to perform tractography seeded from the ’32K 
registered surface mesh in native volume space’ (the final surface generated by 
the PostFreeSurfer pipeline)?
Qn 2: Are these surfaces stored in what FSL calls the ‘caret’ convention?

Then we use workbench commands to convert the outputs as needed for viewing in 
workbench, and to stitch the two cortex pieces and any volume pieces together 
into one file, etc.

Also, in [1], it states that the ‘standard grayordinate space’ (in CIFTI 
format) is used for achieving bijective inter-subject correspondence of the WM 
surface vertices and the subcortical voxels. However, I’m a bit confused how 
this bijective correspondence is maintained during the resampling from the 164K 
to the 32K meshes i.e. does the adaptive barycentric surface resampling method 
guarantee that the 32K-to-32K mappings are also bijective?

The resampling of an individual surface from one atlas mesh to another uses the 
atlas spheres, not the subject spheres, so you get the same mesh and vertex 
correspondence every time.  Also, we do surface resampling with barycentric, 
not adaptive barycentric area resampling, because signal loss doesn't really 
apply to coordinate data - barycentric resampling doesn't add smoothness when 
downsampling, so it stays closer to the original anatomical contours in areas 
with curvature.

Thanks for the clarification.
Qn 3: Do you have any references/citations for the barycentric resampling 
methods that were implemented?

Cheers,

M@
--
Matthew George Liptrot

http://about.me/matthewliptrot
Department of Computer Science
University of Copenhagen

Section for Cognitive Systems
Department of Applied Mathematics and Computer Science
Technical University of Denmark

http://about.me/matthewliptrot


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Re: [HCP-Users] Inter-subject vertex:voxel correspondence

[Glasser, Matthew]

Yes to the first two questions. There is some discussion of the more advanced adaptive barycentric resampling method in the HCP Pipelines paper. 


Peace,


Matt.




From: Matthew George Liptrot matthew.lipt...@di.ku.dk
Date: Friday, September 26, 2014 at 1:18 AM
To: hcp-users@humanconnectome.org hcp-users@humanconnectome.org
Subject: Re: [HCP-Users] Inter-subject vertex:voxel correspondence







Hi again,


Many thanks Matt, Carl and Tim for such quick replies! A few follow-up questions are in-line below:





































I am a novice at handling surfaces, and at using the Connectome Workbench/commandline, so apologies if the following is obvious.


We want to be able to perform connectivity analysis of subjects (both HCP and our own) using diffusion tractography. In order to directly compare the resultant (voxel-to-voxel) connectivity matrices across subjects, we would like to have a one-to-one correspondence
 between the tractography seed voxels in each subject. I presume that the best way to do this would be to first select the desired set of (inter-subject matched) seed points upon the aligned surface meshes already provided (BIG thanks!) by the HCP and then
 convert them to the (nearest) voxel? (I realise that this may be a surjective mapping). Are there functions/commands within the Connectome Workbench that can do this? Or are there more sensible approaches to achieving this?




We don't seed cortex tractography from voxels, we seed from surfaces. FSL tractography supports this:


http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FDT/UserGuide#Using_surfaces







Great!
Qn 1: Is the recommended approach to perform tractography seeded from the ’32K registered surface mesh in native volume space’ (the final surface generated by the PostFreeSurfer pipeline)?
Qn 2: Are these surfaces stored in what FSL calls the ‘caret’ convention?







Then we use workbench commands to convert the outputs as needed for viewing in workbench, and to stitch the two cortex pieces and any volume pieces together into one file, etc.




Also, in [1], it states that the ‘standard grayordinate space’ (in CIFTI format) is used for achieving bijective inter-subject correspondence of the WM surface vertices and the subcortical voxels. However, I’m a bit confused how this bijective correspondence
 is maintained during the resampling from the 164K to the 32K meshes i.e. does the adaptive barycentric surface resampling method guarantee that the 32K-to-32K mappings are also bijective?




The resampling of an individual surface from one atlas mesh to another uses the atlas spheres, not the subject spheres, so you get the same mesh and vertex correspondence every time. Also, we do surface resampling with barycentric, not adaptive barycentric
 area resampling, because signal loss doesn't really apply to coordinate data - barycentric resampling doesn't add smoothness when downsampling, so it stays closer to the original anatomical contours in areas with curvature.







Thanks for the clarification.
Qn 3: Do you have any references/citations for the barycentric resampling methods that were implemented?


Cheers,


M@








--




Matthew George Liptrot











Department of Computer Science

University of Copenhagen



Section for Cognitive Systems



Department of Applied Mathematics and Computer Science

Technical University of Denmark




http://about.me/matthewliptrot















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 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.
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[HCP-Users] Inter-subject vertex:voxel correspondence

[Matthew George Liptrot]

Hi,

I am a novice at handling surfaces, and at using the Connectome 
Workbench/commandline, so apologies if the following is obvious.

We want to be able to perform connectivity analysis of subjects (both HCP and 
our own) using diffusion tractography. In order to directly compare the 
resultant (voxel-to-voxel) connectivity matrices across subjects, we would like 
to have a one-to-one correspondence between the tractography seed voxels in 
each subject. I presume that the best way to do this would be to first select 
the desired set of (inter-subject matched) seed points upon the aligned surface 
meshes already provided (BIG thanks!) by the HCP and then convert them to the 
(nearest) voxel? (I realise that this may be a surjective mapping). Are there 
functions/commands within the Connectome Workbench that can do this? Or are 
there more sensible approaches to achieving this?

Also, in [1], it states that the ‘standard grayordinate space’ (in CIFTI 
format) is used for achieving bijective inter-subject correspondence of the WM 
surface vertices and the subcortical voxels. However, I’m a bit confused how 
this bijective correspondence is maintained during the resampling from the 164K 
to the 32K meshes i.e. does the adaptive barycentric surface resampling method 
guarantee that the 32K-to-32K mappings are also bijective?

1. Glasser MF, Sotiropoulos SN, Wilson JA, Coalson TS, Fischl B, et al. (2013) 
The minimal preprocessing pipelines for the Human Connectome Project. 
NeuroImage 80: 105–124. doi:10.1016/j.neuroimage.2013.04.127.

Cheers,

M@
--
Matthew George Liptrot

http://about.me/matthewliptrot
Department of Computer Science
University of Copenhagen

Section for Cognitive Systems
Department of Applied Mathematics and Computer Science
Technical University of Denmark

http://about.me/matthewliptrot

http://about.me/matthewliptrot


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Re: [HCP-Users] Inter-subject vertex:voxel correspondence

[Hacker, Carl]

Yes, the resampling and registration guarantees a bijective mapping. However, like Matt said, the correctness of the mapping (that the same vertex index corresponds to the same
 gyral feature across subjects) is of course dependent on the quality of the surface registration.


Carl


From: hcp-users-boun...@humanconnectome.org [hcp-users-boun...@humanconnectome.org] on behalf of Glasser, Matthew [glass...@wusm.wustl.edu]
Sent: Thursday, September 25, 2014 9:19 AM
To: Matthew George Liptrot; hcp-users@humanconnectome.org
Subject: Re: [HCP-Users] Inter-subject vertex:voxel correspondence




As one goes from subcortical to cortical structures, it progressively becomes more difficult to achieve an accurate volume-based alignment, which is why we don’t try to and instead use surface models (where the alignment problem is easier). On the surface,
 we use a standard mesh approach so that a given vertex number is aligned by the registration to correspond to the same neuroanatomical location across subjects (and the accuracy of this depends on the information made available to the registration algorithm).
 


I’m not sure I understand the rest of your question (because I don’t know what surjective and bijective mean). Perhaps you can restate the question a little more plainly?


Thanks,


Matt.




From: Matthew George Liptrot matthew.lipt...@di.ku.dk
Date: Thursday, September 25, 2014 at 9:00 AM
To: hcp-users@humanconnectome.org hcp-users@humanconnectome.org
Subject: [HCP-Users] Inter-subject vertex:voxel correspondence





Hi,


I am a novice at handling surfaces, and at using the Connectome Workbench/commandline, so apologies if the following is obvious.


We want to be able to perform connectivity analysis of subjects (both HCP and our own) using diffusion tractography. In order to directly compare the resultant (voxel-to-voxel) connectivity matrices across subjects, we would like to have a one-to-one correspondence
 between the tractography seed voxels in each subject. I presume that the best way to do this would be to first select the desired set of (inter-subject matched) seed points upon the aligned surface meshes already provided (BIG thanks!) by the HCP and then
 convert them to the (nearest) voxel? (I realise that this may be a surjective mapping). Are there functions/commands within the Connectome Workbench that can do this? Or are there more sensible approaches to achieving this?


Also, in [1], it states that the ‘standard grayordinate space’ (in CIFTI format) is used for achieving bijective inter-subject correspondence of the WM surface vertices and the subcortical voxels. However, I’m a bit confused how this bijective correspondence
 is maintained during the resampling from the 164K to the 32K meshes i.e. does the adaptive barycentric surface resampling method guarantee that the 32K-to-32K mappings are also bijective?


1.Glasser
 MF, Sotiropoulos SN, Wilson JA, Coalson TS, Fischl B, et al. (2013) The minimal preprocessing pipelines for the Human Connectome Project. NeuroImage 80: 105–124. doi:10.1016/j.neuroimage.2013.04.127.


Cheers,


M@

--



Matthew George Liptrot









Department of Computer Science
University of Copenhagen

Section for Cognitive Systems





Department of Applied Mathematics and Computer Science

Technical University of Denmark




http://about.me/matthewliptrot




















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 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.
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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.
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Re: [HCP-Users] Inter-subject vertex:voxel correspondence

[Timothy Coalson]

On Thu, Sep 25, 2014 at 9:00 AM, Matthew George Liptrot 
matthew.lipt...@di.ku.dk wrote:

  Hi,

  I am a novice at handling surfaces, and at using the Connectome
 Workbench/commandline, so apologies if the following is obvious.

  We want to be able to perform connectivity analysis of subjects (both
 HCP and our own) using diffusion tractography. In order to directly compare
 the resultant (voxel-to-voxel) connectivity matrices across subjects, we
 would like to have a one-to-one correspondence between the tractography
 seed voxels in each subject. I presume that the best way to do this would
 be to first select the desired set of (inter-subject matched) seed points
 upon the aligned surface meshes already provided (BIG thanks!) by the HCP
 and then convert them to the (nearest) voxel? (I realise that this may be a
 surjective mapping). Are there functions/commands within the Connectome
 Workbench that can do this? Or are there more sensible approaches to
 achieving this?


We don't seed cortex tractography from voxels, we seed from surfaces.  FSL
tractography supports this:

http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FDT/UserGuide#Using_surfaces

Then we use workbench commands to convert the outputs as needed for viewing
in workbench, and to stitch the two cortex pieces and any volume pieces
together into one file, etc.

Also, in [1], it states that the ‘standard grayordinate space’ (in CIFTI
 format) is used for achieving bijective inter-subject correspondence of the
 WM surface vertices and the subcortical voxels. However, I’m a bit confused
 how this bijective correspondence is maintained during the resampling from
 the 164K to the 32K meshes i.e. does the adaptive barycentric surface
 resampling method guarantee that the 32K-to-32K mappings are also bijective?


The resampling of an individual surface from one atlas mesh to another uses
the atlas spheres, not the subject spheres, so you get the same mesh and
vertex correspondence every time.  Also, we do surface resampling with
barycentric, not adaptive barycentric area resampling, because signal
loss doesn't really apply to coordinate data - barycentric resampling
doesn't add smoothness when downsampling, so it stays closer to the
original anatomical contours in areas with curvature.

Tim

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Re: [HCP-Users] multi-subject tfMRI analysis

[Glasser, Matthew]

The LR and RL phase encoding directions were more favorable than the AP/PA phase encoding directions for our scanner. They are counterbalanced because of the hemispheric asymmetry, but can be directly combined across without the below concerns, as cortical
 areas are not expected to move within a subject. That being said, I would still not recommend smoothing the data in the volume, as you wouldn't get the benefits from the high resolution acquisition if you did that. 


Peace,


Matt.




From: Yan, Shulin shu.ya...@imperial.ac.uk
Date: Monday, September 16, 2013 5:38 AM
To: Matt Glasser glass...@wusm.wustl.edu
Cc: hcp-users@humanconnectome.org hcp-users@humanconnectome.org
Subject: RE: [HCP-Users] multi-subject tfMRI analysis





thanks, its very useful.

I have another question: I find for each individual, it has both RL and LR phase encoding images. what the purpose for doing this?and can I combine them two for analysis or it has the same problem as cross-subject analysis?


Best Shulin



From: Glasser, Matthew [glass...@wusm.wustl.edu]
Sent: 14 September 2013 23:20
To: Yan, Shulin; hcp-users@humanconnectome.org
Subject: Re: [HCP-Users] multi-subject tfMRI analysis




Not worry if you haven't done much fMRI analysis before, that means you'll be in an excellent position with a fresh perspective to learn about how to best do these analyses!


My understanding is that it is generally best to do mixed (rather than fixed) effects group analyses (where subjects are treated as a random effects), but I admit to not knowing all the details on when each type of analysis is best in different statistical
 scenarios. 


The fMRI volume data are all nonlinearly registered to MNI volume standard space. This means that the overall brains will be largely the same size, shape, and position. This does not mean that functionally homologous regions of the cerebral cortex will
 be well aligned across subjects. Volume-based registration using T1w images (or, to a lesser extent, surface-based registration with cortical folding patterns) are not very good in achieving these kind of correspondences in many cortical brain areas. 


The volume timeseries for each fMRI run is called ${SubjectID}/MNINonLinear/Results/${fMRIName}/${fMRIName}.nii.gz. 


As I said above, it's my opinion not to recommend combining across subjects using volume-based registration for the cerebral cortex. There is no guarantee that functionally homologous regions of the cortex will be aligned with volume-based registration.
 We are actively working on making better (than folding-based) areal-feature-based surface registrations of the cerebral cortex available, but this will take some time yet before it is publicly available. Before that, we will have grayordinates-based versions
 of the task analyses that use FreeSurfer folding-based registration for cerebral cortical surfaces and nonlinear volume registration for subcortical structures.  We'll have individual analyses and group mean analyses for two groups available for download
 in the next data release (hopefully sometime next week). These group averages will continue to improve with time as we improve the cross-subject alignments on the surface with areal features. 


To learn about the new combined surface and volume coordinate system, grayordinates, see this paper:


http://www.sciencedirect.com/science/article/pii/S1053811913005053


Peace,


Matt.




From: Yan, Shulin shu.ya...@imperial.ac.uk
Date: Thursday, September 12, 2013 5:06 PM
To: hcp-users@humanconnectome.org hcp-users@humanconnectome.org
Subject: [HCP-Users] multi-subject tfMRI analysis





I am beginner of fMRI volume based analysis. I found connectome provides a
minimal preprocessed fMRI volume data which has been normalized and
registered to a reference structure (T1W?) for each individual. Activation
detection can be directly proceed on this data.
My questions are:


1. if I want to do a fixed-effect based multi-subject analysis,
can I just combine the multi-subject data directly? if the fMRI cross
subjects are registered to the same reference structure? I found each
individual has a T1W data, are they same across all the subjects?


2. which file stores the preprocessed 4D tfMRI data? I found the file names are listed in the document, but no clearly explaination.

Best Shulin


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