Re: [HCP-Users] FIRST & FAST Data

[Harms, Michael]

Sorry, no.

--
Michael Harms, Ph.D.

---

Associate Professor of Psychiatry

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
On 7/10/18, 3:16 PM, "hcp-users-boun...@humanconnectome.org on behalf of 
Bajada, Claude Julien"  wrote:

Dear all,

Is there any pre computed FIRST & FAST data for the HCP releases?

Regards,
Claude




Forschungszentrum Juelich GmbH
52425 Juelich
Sitz der Gesellschaft: Juelich
Eingetragen im Handelsregister des Amtsgerichts Dueren Nr. HR B 3498
Vorsitzender des Aufsichtsrats: MinDir Dr. Karl Eugen Huthmacher
Geschaeftsfuehrung: Prof. Dr.-Ing. Wolfgang Marquardt (Vorsitzender),
Karsten Beneke (stellv. Vorsitzender), Prof. Dr.-Ing. Harald Bolt,
Prof. Dr. Sebastian M. Schmidt




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Re: [HCP-Users] Blank p-value maps after running PALM on CIFTI files

[Harms, Michael]

Hi,
If you are just testing the mean activation, then you need to use the -ise 
option to allow sign flipping.  Otherwise, by default, PALM does permutations, 
but permutations of your model will always generate the exact same mean, which 
explains your results.

Cheers,
-MH

--
Michael Harms, Ph.D.
---
Associate Professor of Psychiatry
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:  on behalf of Gail Rosenbaum 

Date: Monday, July 2, 2018 at 4:42 PM
To: NEUROSCIENCE tim 
Cc: hcp-users 
Subject: Re: [HCP-Users] Blank p-value maps after running PALM on CIFTI files

Hi Tim,

Thanks for the clarification.

Here  are the calls to palm for the separated subcortical and cortical files:


palm -i data_sub.nii -d ${StudyFolder}Level3/L3Setup.mat -t 
${StudyFolder}Level3/L3Setup.con -o mbmfResults${contrast}_vol -T -logp

palm -i data_L.func.gii -d ${StudyFolder}Level3/L3Setup.mat -t 
${StudyFolder}Level3/L3Setup.con -o mbmfResults${contrast}_SurfL -T -tfce2D -s 
${StudyFolder}Level3/mbmfGroup_L.midthick.surf.gii 
${StudyFolder}Level3/L_area.func.gii -logp

palm -i data_R.func.gii -d ${StudyFolder}Level3/L3Setup.mat -t 
${StudyFolder}Level3/L3Setup.con -o mbmfResults${contrast}_SurfR -T -tfce2D -s 
${StudyFolder}Level3/mbmfGroup_R.midthick.surf.gii 
${StudyFolder}Level3/R_area.func.gii -logp


For this analysis, I am simply trying to take the mean of the activation to see 
if any clusters are significantly greater than baseline. The design matrix 
(L3Setup.mat) is a 36x1 matrix (there are 36 subjects in my current analysis) 
and the t- L3Setup.con is just a 1. Maybe I set this up incorrectly?

Thanks,
Gail


On Mon, Jul 2, 2018 at 5:27 PM, Timothy Coalson 
mailto:tsc...@mst.edu>> wrote:
As you have found, the outputs from PALM contain only 0s, therefore using a 
different wb_command operation to convert them will not help with your current 
issue.

If you can post the PALM call you used, it might help others who know PALM 
figure out what your problem might be.

Tim


On Mon, Jul 2, 2018 at 4:12 PM, Gail Rosenbaum 
mailto:gailrosenb...@nyu.edu>> wrote:
Hi Tim,

Thank you for your quick reply.

I renamed the maps and confirmed that there are no values in the maps (I pasted 
the output of wb_command -file-information for the left hemisphere output below 
in case that is useful).

Regarding -cifti-create-dense-from-template: I used this command in the first 
iteration of my analyses and had the same issue. I switched to 
-cifti-create-dense-scalar to see if it would work (and because this is the 
suggested command and usage in the "HCP Practical 11: Task fMRI Analyses" pdf) 
and again did not have any luck. That being said, I'm new to CIFTI files so I 
appreciate the usage suggestions, and I will try -cifti-create-dense-scalar and 
specify ROIs, but I am not sure this will help this issue because using a full 
template produced the same issue.

Thanks,
Gail

Output of wb_command -file-information:

Name: mbmfResultsAllRPE3_SurfL_dpv_tstat_uncp.func.gii
Type: Metric
Structure:CortexLeft
Data Size:129.97 Kilobytes
Maps to Surface:  true
Maps to Volume:   false
Maps with LabelTable: false
Maps with Palette:true
All Map Palettes Equal:   true
Map Interval Units:   NIFTI_UNITS_UNKNOWN
Number of Maps:   1

Number of Vertices:   32492
Map   Minimum   MaximumMean   Sample Dev   % Positive   % Negative   
Inf/NaN   Map Name
  1 0.000 0.000   0.0000.0000.0000.000 
0   #1

On Mon, Jul 2, 2018 at 4:45 PM, Timothy Coalson 
mailto:tsc...@mst.edu>> wrote:
Please name your tstat and p-value outputs ending in .func.gii, not simply .gii 
.  This will allow you to open them in wb_view directly, allowing you to do 
sanity checks with fewer intervening steps.  However, from what you have said, 
I am fairly certain they are entirely 0s (you can use wb_command 
-file-information to check the range of the maps, and any non-numeric values, 
once you have named your outputs ending in .func.gii).  I am not sure how to 
check whether PALM was called with meaningful inputs that would be expected to 
give significant results.

On a side note, by using -cifti-create-dense-scalar without specifying ROIs for 
right and left cortex, you have generated CIFTI files that include the medial 
wall, and do not match the 91k grayordinates of HCP data.  I am guessing that 
your subcortical labels are in fact the same as the HCP 91k grayordinate 
subcortical labels, so I suggest you use -cifti-create-dense-from-template, 
which makes it easier to match an existing specification of grayordinates.

Tim



On Mon, Jul 2, 2018 at 3:17 PM, Gail Rosenbaum 
mailto:gailrosenb...@nyu.edu>> 

Re: [HCP-Users] Communities for MMP atlas?

[Harms, Michael]

Hi,
There is something in the works:
https://www.biorxiv.org/content/early/2018/01/12/206292

cheers,
-MH

--
Michael Harms, Ph.D.
---
Associate Professor of Psychiatry
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:  on behalf of Benjamin Risk 

Date: Monday, July 2, 2018 at 12:17 PM
To: "hcp-users@humanconnectome.org" 
Subject: [HCP-Users] Communities for MMP atlas?

Hi all,

Are there any community definitions based on the MMP atlas, preferably based on 
functional connectivity? I saw there are 22 regions in Fig 1 in 
https://media.nature.com/full/nature-assets/nature/journal/v536/n7615/extref/nature18933-s3.pdf.
 I am looking for something aligning more with 7 or so resting-state networks, 
and wondering if someone had already done this.

Thank you!
Ben Risk

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Re: [HCP-Users] A few specific questions about the HCP data | MNI space dedrifting & file structure

[Harms, Michael]

Hi,
Re (1):
If you want to work with streamlines in MNI space then you have to accept the 
"drift" (volume expansion) that is part of MNI space itself.

Re (2):
Maps may be resampled to surfaces in MNI space.  But all the FreeSurfer 
structural quantities that we provide in the database/spreadsheet in 
ConnectomeDB are measured in the subject's real (native) space.

Cheers,
-MH

--
Michael Harms, Ph.D.

---

Associate Professor of Psychiatry

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
On 7/2/18, 7:14 AM, "hcp-users-boun...@humanconnectome.org on behalf of Claude 
Bajada"  wrote:

Dear experts,

I have a few questions:

1) I am currently working on a project using tractography and the HCP
data. I have used the HCP provided FNIRT based MNI registration in order
to register individual streamlines from "native" or diffusion space (as
per post HCP minimal processing pipeline) to MNI space. However, in
Glasser 2016 supplementary text, it states that the MNI space is drifted
relative to the mean brain size of individual brains (greatest along the
x and z axes). I've been told that it is possible to "dedrift" these
data and I wonder if anyone has experience in doing this and is able to
point me in the right direction.

2) from what I understand, structural qualities such as cortical
thickness etc are measured in the individual's real space. However then,
what I do not understand is the file structure of the HCP data. The
structural measures such as cortical thickness, curvature and myelin
maps etc live in the MNINonLinear/fsaverage_LR32k rather than in the
'native space' directory. Can anyone shed light on this?

Regards,

Claude





Forschungszentrum Juelich GmbH
52425 Juelich
Sitz der Gesellschaft: Juelich
Eingetragen im Handelsregister des Amtsgerichts Dueren Nr. HR B 3498
Vorsitzender des Aufsichtsrats: MinDir Dr. Karl Eugen Huthmacher
Geschaeftsfuehrung: Prof. Dr.-Ing. Wolfgang Marquardt (Vorsitzender),
Karsten Beneke (stellv. Vorsitzender), Prof. Dr.-Ing. Harald Bolt,
Prof. Dr. Sebastian M. Schmidt




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Re: [HCP-Users] HCPID in TAB.txt

[Harms, Michael]

“functional session A” and “functional session B”.  That is related to the 
internals of how the data was collected at the scanner.

Cheers,
-MH


--
Michael Harms, Ph.D.
---
Associate Professor of Psychiatry
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:  on behalf of Xinyang Liu 

Date: Thursday, June 21, 2018 at 2:28 AM
To: HCP 讨论组 
Subject: [HCP-Users] HCPID in TAB.txt

Dear HCP experts,

In the behavioral TAB.txt of each participant's tfMRI folder, there is a column 
named HCPID. In this column, each participant's ID number is followed by a 
"_fnca" or "_fncb". Could you please tell what these fnca and fncb mean? Thank 
you very much.

Best regards,
Xinyang







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Re: [HCP-Users] HCP processing with ciftify requirements

[Harms, Michael]

The issue with using FreeSurfer 6.0 in the HCP Pipelines is that some aspects 
of the surface generation on HCP-Young Adult data were better using the 
FreeSurfer 5.3.0-HCP release.  We are in the process of checking the 
performance of a beta version of FreeSurfer 6.X on HCP-YA data.

If you use FreeSurfer 6.0, our advice is that you check your surfaces (which 
you should be doing anyway!), and decide if you are satisfied with them.

Cheers,
-MH

--
Michael Harms, Ph.D.
---
Associate Professor of Psychiatry
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:  on behalf of Timothy Coalson 

Date: Tuesday, June 19, 2018 at 3:22 PM
To: "Parvathaneni, Prasanna" 
Cc: "hcp-users@humanconnectome.org" 
Subject: Re: [HCP-Users] HCP processing with ciftify requirements

On Sat, Jun 16, 2018 at 8:36 PM, Parvathaneni, Prasanna 
mailto:prasanna.parvathan...@vanderbilt.edu>>
 wrote:
Hi All,

  Thank you for suggesting “ciftify” on non-HCP datasets. We are trying to run 
HCP pipeline using “ciftify" tool on our custom dataset and have few questions

  *   For running recon-all can we use Freesurfer v6.  Suggested version for 
HCP (Freesurfer 5.0.3_HCP) seem to have compatibility issues on Ubuntu 16.08 as 
mentioned in below thread
https://www.mail-archive.com/hcp-users@humanconnectome.org/msg04158.html

The ciftify pipeline is not the HCP pipelines.  It is a workaround for studies 
that don't follow HCP acquisition guidelines, to be able to get some (but not 
all) of the advantages of the HCP preprocessing methods.

I would expect that it can accept freesurfer v6 output, but I don't know for 
sure.

  *   Do you have any scripts for transforming diffusion data that is aligned 
to subject T1 into “cifti” space similar to ciftify_subject_fmri for FMRI data
We haven't released tractography results for HCP data due to unsolved issues 
with tractography in general ("gyral bias").  You can run tractography using 
surface-based counting, and surface-based cortical results make sense to 
convert to standard grayordinate space.  However, the diffusion/fiber direction 
information is most definitive in the white matter, while our standard 
grayordinate space only covers gray matter, so it would not make sense to 
convert that into grayordinate space.

Appreciate your feedback.

Thanks
Prasanna







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Re: [HCP-Users] Minimally preprocessed 7T files - don't see the rest

[Harms, Michael]

Hi,
Have you checked the Release Notes documentation?  We don't have a description 
of every single file at this point in time.  (The Pipeline code is the 
description).  If you have a question about a particular file, feel free to 
contact this list.

Cheers,
-MH

--
Michael Harms, Ph.D.

---

Associate Professor of Psychiatry

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
On 6/19/18, 11:16 AM, "Nina de Lacy"  wrote:

Hi Mike:

Ah - very helpful.

We may use the FIX-cleaned data for other things but right now we are doing 
work on methods development and would prefer not to use data cleaned with ICA. 
We can also of course process the unprocessed data and use that :)

We are in general having trouble with deciphering the meaning of each of the 
filenames so if you can help with that or there is a source somewhere on the 
interwebs you can point us to that would be great. Basically, something that 
tells us what is in each filename-type in the 7T release. Ideally would include 
the .txt files.

Thanks v much,
Nina

On Tue, 19 Jun 2018, Harms, Michael wrote:

>
> Hi,
> rfMRI_REST1_7T_PA_Atlas_1.6mm_MSMAll.dtseries.nii is the CIFTI version, using 
> MSMAll registration, on a surface mesh with ~ 1.6 mm (average) vertex spacing.
>
> Note that we've provided CIFTI data on both 1.6 mm and 2.0 mm meshes.  
> Depending on your research question, the latter may be easier to work with.
>
> Also, we'd suggest that you consider using the FIX-cleaned data instead, 
> available in the "FIX-Denoised (Compact)" packages.
>
> Cheers,
> -MH
>
> --
> Michael Harms, Ph.D.
>
> ---
>
> Associate Professor of Psychiatry
>
> 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
> On 6/19/18, 10:01 AM, "hcp-users-boun...@humanconnectome.org on behalf of 
> Nina de Lacy"  dela...@u.washington.edu> wrote:
>
> Hi there:
>
> I have downloaded the 1.6mm 7T minimally preprocessed files and after looking 
> at a few subjects, I can't find the actual resting state timeseries 
> (presumably of 900 volumes). Here are the .nii files I have for an example 
> subject:
>
> rfMRI_REST1_7T_PA_Atlas_1.6mm_MSMAll.dtseries.nii
> rfMRI_REST1_7T_PA_Atlas_1.6mm.dtseries.nii
> rfMRI_REST1_7T_PA_dropouts.nii
> rfMRI_REST1_7T_PA_Jacobian.nii
> rfMRI_REST1_7T_PA_PhaseOne_gdc_dc.nii
> rfMRI_REST1_7T_PA_PhaseTwo_gdc_dc.ii
> rfMRI_REST1_7T_PA_SBRef.nii
> rfMRI_REST1_7T_PA_sebased_bias.nii
> rfMRI_REST1_7T_PA_sebased_reference.nii
>
> I also downloaded the unprocessed and extended release, which have the same 
> file structure and do contain the 900 volume timeseries.
>
> Could someone advise if I am missing something here?
>
> Thanks v much
> Nina
>
>
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Re: [HCP-Users] Minimally preprocessed 7T files - don't see the rest

[Harms, Michael]

Hi,
rfMRI_REST1_7T_PA_Atlas_1.6mm_MSMAll.dtseries.nii is the CIFTI version, using 
MSMAll registration, on a surface mesh with ~ 1.6 mm (average) vertex spacing.

Note that we've provided CIFTI data on both 1.6 mm and 2.0 mm meshes.  
Depending on your research question, the latter may be easier to work with.

Also, we'd suggest that you consider using the FIX-cleaned data instead, 
available in the "FIX-Denoised (Compact)" packages.

Cheers,
-MH

--
Michael Harms, Ph.D.

---

Associate Professor of Psychiatry

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
On 6/19/18, 10:01 AM, "hcp-users-boun...@humanconnectome.org on behalf of Nina 
de Lacy"  wrote:

Hi there:

I have downloaded the 1.6mm 7T minimally preprocessed files and after looking 
at a few subjects, I can't find the actual resting state timeseries (presumably 
of 900 volumes). Here are the .nii files I have for an example subject:

rfMRI_REST1_7T_PA_Atlas_1.6mm_MSMAll.dtseries.nii
rfMRI_REST1_7T_PA_Atlas_1.6mm.dtseries.nii
rfMRI_REST1_7T_PA_dropouts.nii
rfMRI_REST1_7T_PA_Jacobian.nii
rfMRI_REST1_7T_PA_PhaseOne_gdc_dc.nii
rfMRI_REST1_7T_PA_PhaseTwo_gdc_dc.ii
rfMRI_REST1_7T_PA_SBRef.nii
rfMRI_REST1_7T_PA_sebased_bias.nii
rfMRI_REST1_7T_PA_sebased_reference.nii

I also downloaded the unprocessed and extended release, which have the same 
file structure and do contain the 900 volume timeseries.

Could someone advise if I am missing something here?

Thanks v much
Nina


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Re: [HCP-Users] wb_command help

[Harms, Michael]

Hi,
See the “HCP1200 Parcellation+Timeseries+Netmats (PTN)” packages hosted at
https://db.humanconnectome.org/data/projects/HCP_1200

There are “soft parcellations” (ICA-based, and cortical only) computed at 
dimensionalities of 15, 25, 50, 100, 200, and 300.

Cheers,
-MH

--
Michael Harms, Ph.D.
---
Associate Professor of Psychiatry
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:  on behalf of "Rakib Al-Fahad 
(ralfahad)" 
Date: Tuesday, June 12, 2018 at 11:58 AM
To: "hcp-users@humanconnectome.org" 
Subject: [HCP-Users] wb_command help

Hello,

I am a student of machine learning. I want to study structural and functional 
brain connectivity from HCP data. Is there any way to get ROI based time series 
and structural connectivity using wb_command ? I am not sure about which ROI 
atlas should I use. I need suggestion for specific atlas having 50~100 ROIs.


Thanks

Rakib Al-Fahad
Ph.D. Student
CVPIA Lab
Department of Electrical and Computer Engineering
The University of Memphis
Email: ralfa...@memphis.edu



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[HCP-Users] perceptually uniform sequential colormaps?

[Harms, Michael]

Hi guys,
Which of the colormaps currently in Workbench are perceptually uniform and 
monotonically increasing in lightness?

In the interest of supporting some of the recent colormaps with considerable 
thought behind them, what about including the viridis, plasma, inferno, and 
magma colormaps from Matplotlib into Workbench?

http://medvis.org/2016/02/23/better-than-the-rainbow-the-matplotlib-alternative-colormaps/
https://matplotlib.org/users/colormaps.html

Cheers,
-MH

--
Michael Harms, Ph.D.
---
Associate Professor of Psychiatry
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


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[HCP-Users] -cifti-reduce -exclude-outliers

[Harms, Michael]

Hi Tim,
I was wondering about the details of the -cifti-reduce -exclude-outliers 
operation.  In particular, is it “iterative”? i.e., does it recompute the std 
without the outliers from the previous pass(es) and iterate until no further 
new outliers are identified?

Thanks,
-MH

--
Michael Harms, Ph.D.
---
Associate Professor of Psychiatry
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


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Re: [HCP-Users] FSL version in the HCP pipelines

[Harms, Michael]

Yes, you should be able to use the latest FSL release.
In fact, due to code consolidation in the newest release, FSL 5.0.6 is no 
longer allowed for the task-fMRI processing.

Cheers,
-MH

--
Michael Harms, Ph.D.

---

Associate Professor of Psychiatry

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
On 6/4/18, 11:23 AM, "hcp-users-boun...@humanconnectome.org on behalf of Cook, 
Philip"  wrote:

Hi,

The README.md on Github points to release notes for 3.0.4, which specifically 
requires FSL 5.0.6.

With pipelines v 3.27.0, is it still necessary to use 5.0.6 at all? Is it 
possible to use the latest release (5.0.11)?


Thanks
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Re: [HCP-Users] Exact time of measurements for task fMRI

[Harms, Michael]

Hi,
The tasks are triggered by the scanner (so you can assume the start of the 
acquisition is at t=0) and you can assume that the spacing between frames is 
exactly the TR (0.720 sec for the 3T HCP-Young Adult acquisitions).

Cheers,
-MH

--
Michael Harms, Ph.D.
---
Associate Professor of Psychiatry
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:  on behalf of Katharina Ring 

Date: Saturday, June 2, 2018 at 7:21 AM
To: "hcp-users@humanconnectome.org" 
Subject: [HCP-Users] Exact time of measurements for task fMRI

Hi everyone,

I'm currently working with the preprocessed fMRI data for the Motor task. I 
would like to match the experimental stimulus (for which I have exact time 
stamps) to the fMRI images. However, so far I could only find out that there 
are 284 frames per run and that the run lasts 214 seconds, which gives me an 
approximate timestamp if I assume they are perfectly evenly spaced and the 
first measurement is at exactly t=0.

Is there any way to get the exact time for each fMRI image?

Thanks in advance and greetings from Munich,
Katy

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Re: [HCP-Users] MSMSulc data

[Harms, Michael]

Hi,
Due to the manner in which the pipeline code developed, the CIFTI files that do 
NOT contain “MSMAll” are by default based on “MSMSulc” registration.
Perhaps at some point we will revise the pipeline code to explicitly include 
“MSMSulc” as part of the file names, to avoid this confusion.

Cheers,
-MH

--
Michael Harms, Ph.D.
---
Associate Professor of Psychiatry
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:  on behalf of Aaron C 

Date: Monday, May 14, 2018 at 10:34 AM
To: "hcp-users@humanconnectome.org" 
Subject: [HCP-Users] MSMSulc data


Dear HCP experts,



I tried to find the MSMSulc version of cortical thickness, myelin, and 
resting-state fMRI data in the HCP datasets but cannot find them. Are they 
available somewhere? Thank you.

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Re: [HCP-Users] Volumes from dscalar.nii files?

[Harms, Michael]

Hi,
Cortical thickness is purely a surface-based measure, so that particular 
dscalar indeed doesn’t contain any volume-based grayordinates.

The task fMRI data would be one example in which volume-based grayordinates are 
present in the CIFTI (i.e., cerebellum and subcortical voxels)

Cheers,
-MH

--
Michael Harms, Ph.D.

---

Associate Professor of Psychiatry

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

On 5/2/18, 4:30 PM, "hcp-users-boun...@humanconnectome.org on behalf of Ho, 
Wilson Christopher"  wrote:

Hello experts,

I’m looking at the examples for FSL’s PALM on CIFTI files 
(https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/PALM/Examples#Example_10:_Using_CIFTI_files)
 and one of the processing steps is separating the volume and surface data from 
the CIFTI. When I run wb_command’s CIFTI-Separate, I can’t seem to separate any 
volume data from the dscalar file specified. For example, I run:
> wb_command -cifti-separate 
> ../352132.corrThickness_MSMAll.32k_fs_LR.dscalar.nii COLUMN -volume-all 
> data_sub.nii -metric CORTEX_LEFT data_L.func.gii -metric CORTEX_RIGHT 
> data_R.func.gii
...and I get the error, "ERROR: specified file and direction does not contain 
any volume data"

If the volumes are not present in the CIFTI dscalar.nii's, is there another 
CIFTI file with the volume present? They don't seem to be present for the 
native or 164k fsaverage files, or non-MSMAll files either. Is there anywhere I 
could locate this volume data? Or would anyone know whether they are necessary 
for the PALM analysis (ie. could a sufficient analysis be done by omitting the 
volume aspect and using solely the extracted GIFTI surfaces?).

Would appreciate some insight on what seems to be a simple misunderstanding on 
my end. Thank you!

Wilson




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Re: [HCP-Users] Native space surface curvature available?

[Harms, Michael]

Hi,
The entirety of the original FS output is available at 
${subject}/T1w/${subject}, which you can obtain via the “Structural Extended” 
packages, or as part of “Connectome-in-a-Box” (no longer taking new orders, but 
perhaps you already have one) or available on S3.

Cheers,
-MH

--
Michael Harms, Ph.D.
---
Associate Professor of Psychiatry
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:  on behalf of Jacob Miller 

Date: Wednesday, April 18, 2018 at 9:04 PM
To: "hcp-users@humanconnectome.org" 
Subject: [HCP-Users] Native space surface curvature available?

Hi all,

I am seeking to perform an anatomical analysis on the HCP dataset which 
requires the surfaces and cortical folding (gyri/sulci curvature) for each 
individual subject, in native space. This information is available in a typical 
FreeSurfer recon-all analysis. However, in the HCP data (namely, in 
$subject/T1w/Native/) the surfaces do not appear to have curvature information. 
Was this information released in the data from the modified HCP FreeSurfer 
pipelines, and I'm missing where this may be stored? Or, are the gyru/sulci 
curvature for each subject not available? If so, is there a way to obtain these 
curvatures without running an entire recon-all pipeline on each native T1 scan?

Please let me know if I may be mistaken! I've only just begun trying to use 
this great dataset.

Best,
Jacob

--

Jacob Miller

Graduate Student, D'Esposito Lab

Helen Wills Neuroscience Institute (HWNI)

University of California, Berkeley

https://despolab.berkeley.edu/

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Re: [HCP-Users] Grand Mean Intensity Normalization

[Harms, Michael]

We consider those “intermediate” files and thus they aren’t part of our 
released packages or “CinaBox” disks.  So, this could be rather challenging.  
You would need to use “REST” calls into the ConnectomDB database directly to 
pull down the files for each run.

Perhaps you could describe why you need this scaling factor, and we can see if 
we have any further insight.

Cheers,
-MH


--
Michael Harms, Ph.D.
---
Associate Professor of Psychiatry
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: "Glasser, Matthew" <glass...@wustl.edu>
Date: Wednesday, April 11, 2018 at 5:35 PM
To: erik lee <erik.lee...@gmail.com>, "Harms, Michael" <mha...@wustl.edu>
Cc: "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org>
Subject: Re: [HCP-Users] Grand Mean Intensity Normalization

Jacobian wasn’t used for the 3T fMRI data.  Also the bias field correction was 
non-optimal.  These are the files that you would want:

1) ${StudyFolder}/${Subject}/${fMRIName}/BiasField.2.nii.gz
2) ${StudyFolder}/${Subject}/${fMRIName}/rfMRI_REST1_LR_nonlin.nii.gz
3) ${StudyFolder}/${Subject}/${fMRIName}/rfMRI_REST1_LR_nonlin_norm.nii.gz

I expect you will find the normalization factor will be correlated with head 
size and be related to the amount of coil loading each subject has.

Keep in mind the same normalization factor was applied to all voxels.

Matt.

From: erik lee <erik.lee...@gmail.com<mailto:erik.lee...@gmail.com>>
Date: Wednesday, April 11, 2018 at 5:05 PM
To: "Harms, Michael" <mha...@wustl.edu<mailto:mha...@wustl.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] Grand Mean Intensity Normalization

Hi Matt and Michael,

Thank you both for your helpful replies.

If I wanted to back-calculate the original mean of the rfMRI image after bias 
field and Jacobian correction, do you know what the appropriate files would be 
to do this?

Looking at the HCP data/intensity normalization script, I wasn’t exactly sure 
what the file names would be for the following:

1. Input rfMRI (pre-Jacobian/Bias Field correction)
2. Bias Image
3. Jacobian Image
4. Output rfMRI (post-Jacobian/Bias Field correction and global intensity 
normalization, but before any temporal processing)

Presumably once I have these, I could do some simple algebra at any given voxel 
to find the global mean used in the intensity normalization.

Thanks,
Erik




On Apr 11, 2018, at 3:43 PM, Harms, Michael 
<mha...@wustl.edu<mailto:mha...@wustl.edu>> wrote:


Just to expand on this, since I think I might know why you are asking.

The grand mean is computed on the brain masked volume timeseries, after bias 
field correction and jacobian modulation is first applied – see the end of 
IntensityNormalization.sh, which is called as the final step in 
GenericfMRIVolumeProcessingPipeline.sh

There is NOT another grand mean normalization applied specifically to the CIFTI 
data, so don’t expect the CIFTI data to have a grand mean of 1.  IIRC, the 
grand mean of the CIFTI timeseries tends to end up in the 8000-9000 range.

Cheers,
-MH

--
Michael Harms, Ph.D.

---

Associate Professor of Psychiatry

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<mailto:mha...@wustl.edu>

On 4/11/18, 2:31 PM, 
"hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>
 on behalf of Glasser, Matthew" 
<hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>
 on behalf of glass...@wustl.edu<mailto:glass...@wustl.edu>> wrote:

1) The overall mean of each scan is 1, this is not done voxelwise
(e.g. like a bias correction would be).

2) Unfortunately this information is not saved.  I don¹t think fslmaths
outputs it, perhaps it could be back computed from some intermediate
files.

Peace,

Matt.

On 4/11/18, 2:21 PM, 
"hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>
 on behalf of
erik lee" 
<hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>
 on behalf of
erik.lee...@gmail.com<mailto:erik.lee...@gmail.com>> wrote:

>Dear HCP Experts,
>
>I am currently using the temporally preprocessed rfMRI data in the S900
>release (aka rfMRI_

Re: [HCP-Users] Grand Mean Intensity Normalization

[Harms, Michael]

Just to expand on this, since I think I might know why you are asking.



The grand mean is computed on the brain masked volume timeseries, after bias 
field correction and jacobian modulation is first applied – see the end of 
IntensityNormalization.sh, which is called as the final step in 
GenericfMRIVolumeProcessingPipeline.sh



There is NOT another grand mean normalization applied specifically to the CIFTI 
data, so don’t expect the CIFTI data to have a grand mean of 1.  IIRC, the 
grand mean of the CIFTI timeseries tends to end up in the 8000-9000 range.



Cheers,

-MH



--

Michael Harms, Ph.D.



---



Associate Professor of Psychiatry



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



On 4/11/18, 2:31 PM, "hcp-users-boun...@humanconnectome.org on behalf of 
Glasser, Matthew"  wrote:



1) The overall mean of each scan is 1, this is not done voxelwise

(e.g. like a bias correction would be).



2) Unfortunately this information is not saved.  I don¹t think fslmaths

outputs it, perhaps it could be back computed from some intermediate

files.



Peace,



Matt.



On 4/11/18, 2:21 PM, "hcp-users-boun...@humanconnectome.org on behalf of

erik lee"  wrote:



>Dear HCP Experts,

>

>I am currently using the temporally preprocessed rfMRI data in the S900

>release (aka rfMRI_REST?_??_Atlas_hp2000_clean.dtseries.nii).

>

>According to the Smith 2013 NeuroImage paper, it sounds like the images I

>am using have all received global intensity normalization prior to the

>temporal preprocessing.

>

>I have two sets of questions relating to this:

>

>(1) Does this mean that the global mean of all voxels (averaged across

>time points) is used to normalize each voxel? If this is the case, is

>this the mean of every voxel in the image, or exclusively those in the

>brain?

>

>(2) Looking through ConnectomeDB, I couldn¹t find a file with the scaling

>factor used for normalizing. Is this something that is saved anywhere?

>

>Thanks for the help!

>

>Best,

>Erik Lee

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Re: [HCP-Users] gradient nonlinearity correction question

[Harms, Michael]

One thought: Are you sure you are using the “3D” (and not the “2D”) correction 
on the scanner?

--
Michael Harms, Ph.D.

---

Associate Professor of Psychiatry

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

On 4/11/18, 8:31 AM, "hcp-users-boun...@humanconnectome.org on behalf of 
Kristian Loewe"  wrote:

Hi Joo-won and Keith,

I don't think that the table has been moved. Is there any information
somewhere in the dicom header to double-check this?

I am using the coeff_AS82.grad file for the Prisma data (the second
command). The first command was what I used for the Verio data. Also,
I double-checked that I am using the uncorrected volume as input.

I am not sure if I am supposed/allowed to send screenshots of the
actual data in the subject's native space to the list. I'm going to
check that. Meanwhile, I asked our local MR team to acquire an
additional data set using a phantom. The difference between the
scanner-corrected image and the offline-corrected image is not as
striking in this case but it's visible. Based on the phantom data, I
am inclined to say that both corrections work reasonably well, even
though they are not exactly the same. I also tried the
offline-correction on some phantom EPI data and it seems to work well
as it (together with EPI distortion correction) restores the original
shape of the phantom pretty nicely.

The differences between the correction variants applied to the
subject's data are actually rather small inside the brain but become
larger towards the neck, which is to be expected as the distance to
the magnetic isocenter becomes greater in that direction.
Nevertheless, I orginally thought that the differences between
scanner- and offline-corrected images would be smaller than that.

Find attached some plots of the T1 phantom data:

T1_ND*.png - uncorrected images
T1*.png- scanner-corrected images
T1_ND_gdc*.png - offline-corrected images

Cheers,

Kristian


PS:
I am sending this email for the second time (apparently the attachment
was too large). I am not sure if the first email was successfully
cancelled. I apologize if you are receiving this twice now.


Quoting "Kim, Joo-won" :

> Hi Kristian,
>
> Have you moved table? If you moved the table, you should manually
> subtract it from qform, sform, and/or affine matrix in the nifty
> header.
>
> Best,
> Joo-won
>
> ---
> Joo-won Kim, Ph.D.
> Postdoctoral Fellow
> Translational and Molecular Imaging Institute
> Icahn School of Medicine at Mount Sinai
>
>
> From:  on behalf of Keith
> Jamison 
> Date: Monday, April 9, 2018 at 10:36 AM
> To: Kristian Loewe 
> Cc: HCP Users 
> Subject: Re: [HCP-Users] gradient nonlinearity correction question
>
> First make sure you're using the right coefficient file, copied
> directly from the scanner.  The Prisma should have a file called
> coeff_AS82.grad, so the one you used in your *second* command above
> should be correct.
> Second is to be absolutely sure your input is the uncorrected volume (*_ND).
> If you include some matched screenshots of the uncorrected,
> offline-corrected, and scanner-corrected volumes, we can maybe help
> evaluate the difference.
>
>
> On Mon, Apr 9, 2018 at 4:09 AM, Kristian Loewe
> > wrote:
> Thanks Keith,
>
> Cropping is turned off by default in the version of dcm2niix that
> I'm using but I re-ran the conversion with "-x n" anyway. I also
> used fslreorient2std as per your suggestion. Unfortunately, the
> result is still the same. Do you have any other ideas?
>
>
> Cheers,
>
> Kristian
>
>
> Quoting Keith Jamison >:
> Some problems can arrise if the NIFTI files are unexpectedly manipulated
> prior gradient_unwarp. Two things to check:
>
> 1. dcm2nii and dcm2niix has options to perform additional processing like
> reorienting or cropping, some of which may be enabled by default. Make sure
> those are all DISABLED. (for dcm2niix add "-x n" and for dcm2nii you can
> add "-x N -r N"
> 2. We also usually use "fslreorient2std  _new and then
> gradient_unwarp.py
>  on
> _new
>
> -Keith
>
>
> On Fri, Apr 6, 2018 at 12:05 PM, Kristian Loewe
> >
> wrote:
> Hi,
>
> I would like to use gradunwarp for offline gradient nonlinearity
> correction of some 

Re: [HCP-Users] HCP Pipeline BIDS app - fMRI processing with reversed phase-encode file in "fmap" directory?

[Harms, Michael]

Hi,
We didn’t create the HCP Pipeline BIDS app, and have no experience using it.  
Users should be aware that the current BIDS App “hides” various choices that 
one would normally have to make when running the HCP Pipelines, and I’m not 
sure what particular choices it has implemented.  In that regard, starting with 
the BID App, rather than the HCP Pipeline scripts themselves, may abstract the 
pipelines in a manner that is not conducive to you understanding what they are 
doing with your data.

Additionally, last time I checked (which was many months ago) there was no 
simple process for getting HCP-style acquired data into the BID directory 
structure.

More fundamentally, the “PEpolar” method for correcting the distortions expects 
that spin-echo acquisitions with both polarities were collected, so that you 
avoid susceptibility dropout and can estimate the field properly throughout the 
entire brain.  The HCP Pipelines are not constructed to correct for distortions 
using gradient-echo acquisitions to estimate the field maps, and thus I rather 
doubt that the BIDS app is equipped to handle that situation either, since the 
BIDS app is simply a “wrapper” into the HCP Pipeline scripts.

Cheers,
-MH

--
Michael Harms, Ph.D.
---
Associate Professor of Psychiatry
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:  on behalf of Scott Burwell 

Date: Friday, April 6, 2018 at 10:35 AM
To: "hcp-users@humanconnectome.org" 
Subject: [HCP-Users] HCP Pipeline BIDS app - fMRI processing with reversed 
phase-encode file in "fmap" directory?

I want to use the HCP Pipeline BIDS app to preprocess T1w, T2w, and BOLD data 
collected at the CMRR. The BOLD data were acquired to apply the "PEpolar" 
method, whereby one short (TR=1.5s, 10 reps) set of EPI data were collected 
with AP phase-encoding, and one long (TR=1.5s, 400 reps) set of EPI data were 
collected with PA phase-encoding. Per BIDS specifications and others' 
suggestions (e.g., 
https://neurostars.org/t/fmriprep-docker-fieldmap-correction/623 ), I have 
stored the short acquisition AP data in the "fmap" directory and the long 
acquisition PA data in the "func" directory; the JSON sidecar for the "fmap" 
file points to the appropriate BOLD series via the "IntendedFor" key (see 
directory contents below).

I know that the HCP Pipeline BIDS app expects a fieldmap in order for the 
functional data to be preprocessed. However, based on documentation, I suspect 
the BIDS app in its current version does not support when the "fmap" is a 
paired reverse-phase encode image? I.e., the BIDS app does not sense that FSL's 
TOPUP should be used (rather than FUGUE or whatever program is currently used 
for this distortion correction). Has anyone else encountered this dilemma? Are 
there plans to add this functionality to the BIDS app?

Any information would be greatly appreciated. Thank you in advance.

Best,
Scott

##bids subject session directory contents:
./func/sub-7536262_ses-00_task-rest_run-01_bold.nii.gz
./func/sub-7536262_ses-00_task-rest_run-01_bold.json
./func/sub-7536262_ses-00_task-rest_run-01_events.tsv
-
./fmap/sub-7536262_ses-00_acq-rest_dir-AP_run-01_epi.nii.gz
./fmap/sub-7536262_ses-00_acq-rest_dir-AP_run-01_epi.json
-
cat ./fmap/sub-7536262_ses-00_acq-rest_dir-AP_run-01_epi.json
"PhaseEncodingDirection": "j-",
"IntendedFor": "func/sub-7536262_ses-00_task-rest_run-01_bold.nii.gz",
"TotalReadoutTime": 0.0527996,


--
Scott J. Burwell, PhD
Postdoctoral Research Fellow
Department of Psychiatry
University of Minnesota, Minneapolis, MN
burw...@umn.edu

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Re: [HCP-Users] -surface-distortion -local-affine-method

[Harms, Michael]

That feature isn’t yet in the released wb_command.
Try using the latest “released” version of the Pipelines from GitHub, rather 
than the master branch.

--
Michael Harms, Ph.D.
---
Associate Professor of Psychiatry
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:  on behalf of Moataz Assem 

Date: Wednesday, April 4, 2018 at 1:30 PM
To: "hcp-users@humanconnectome.org" 
Subject: [HCP-Users] -surface-distortion -local-affine-method

Hi,

I am trying to run the PostFreeSurfer step using the latest Pipelines-master 
(downloaded today 04 April 2018 from github) but I get an error while running 
the script FreeSurfer2CaretConvertAndRegisterNonlinear.sh:  ERROR: Unexpected 
parameter: -local-affine-method

It seems the wb_command –surface-distortion does not have the option for 
“–local-affine-method” although I have the latest version of workbench 
(v1.2.3). The source code seems to have this option though here: 
https://github.com/Washington-University/workbench/commit/576dbfba0f66b7cf5c0b1b58e660c3ffe8e6b356

Do I have to update my local workbench version to incorporate the source code 
updates?

Thanks

Moataz

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Re: [HCP-Users] Please inform me the actual value of echo timing used in HCP lifespan pilot 1a

[Harms, Michael]

That page appears to be down for the moment.  We’ll get it fixed.

The Echo Spacing for the dMRI from the Lifespan1a pilot was 0.69 ms.  
(Although, FWIW, if you already processed your data using 0.78 ms, it doesn’t 
matter in this particular case.  You’ll still get a completely correct 
distortion correction of the dMRI data).

Cheers,
-MH

--
Michael Harms, Ph.D.
---
Associate Professor of Psychiatry
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:  on behalf of "Glasser, Matthew" 

Date: Tuesday, April 3, 2018 at 11:42 AM
To: 张辉 , "hcp-users@humanconnectome.org" 

Cc: "Cler, Eileen" 
Subject: Re: [HCP-Users] Please inform me the actual value of echo timing used 
in HCP lifespan pilot 1a

The page where this info might be appears to be down:

https://www.humanconnectome.org/study-hcp-lifespan-pilot/phase1a-pilot-parameters

Peace,

Matt.

From: 张辉 >
Date: Tuesday, April 3, 2018 at 3:31 AM
To: Matt Glasser >
Subject: Please inform me the actual value of echo timing used in HCP lifespan 
pilot 1a

Dear Matt
Under your guidence discribed in your letter, I have started 
preprocessing the raw diffusion data of HCP lifespan pilot 1a. I have done my 
best, however could not find the value of echo timing for topup on the internet 
which is explicitly declared for it. I used 0.78 ms as the value of echo timing 
to implement topup and obtained priliminary results (showed in Attachment 1).
Please inform me the actual value of echo timing.
Could I ask for Full scanning protocols of HCP-lifespan-pilot-1a 
diffusion and fMRI data?


Best wish,

Zhang Hui


At 2018-03-22 22:26:16, "Glasser, Matthew" 
> wrote:

Did you try running the HCP Pipelines on the data?  This will handle the 
combination for dMRI.  For fMRI the data can be combined after sICA+FIX cleanup 
after demeaning (and perhaps variance normalizing) it.  Given that you may not 
wish to deal with preprocessing the lifespan pilot data, you might be better 
off exploring your hypothesis in the already preprocessed young adult HCP data 
and waiting for the lifespan data release of preprocessed data.

Peace,

Matt.

From: 
>
 on behalf of 张辉 >
Date: Thursday, March 22, 2018 at 9:13 AM
To: "hcp-users@humanconnectome.org" 
>
Subject: [HCP-Users] asking for one method to combine LR.nii and RL.nii of dMRI 
or fMRI data of HCP lifespan pilot 1a

Dear Sir

I’m a pediatric neurosurgeon from Guangzhou China. For testing my hypothesis 
inspireed by pediatric neurosurgery practice, I attempt to use the data of HCP 
lifespan pilot 1a to expore the function of some brain region. Although I spent 
about several monthes searching the solution for combining LR.nii and RL.nii of 
dMRI or fMRI data, I find I can’t do it. Could you please send me the solution 
you recommend? Thank you very much!


Best regards, and to my


Zhang hui

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Re: [HCP-Users] Convert activation cifti data to volume nifti

[Harms, Michael]

That depends on which of the contrasts for the EMOTION you want to use.  You 
can find a listing of them in the Contrasts.txt file.


--
Michael Harms, Ph.D.
---
Associate Professor of Psychiatry
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> on behalf of Yassine Benhajali 
<yanama...@gmail.com>
Date: Tuesday, March 27, 2018 at 12:08 PM
To: "Harms, Michael" <mha...@wustl.edu>
Cc: hcp-users <hcp-users@humanconnectome.org>
Subject: Re: [HCP-Users] Convert activation cifti data to volume nifti

Thank you for the clarification.
Here is a tree structure of one subject folder  
"tfMRI_EMOTION_hp200_s2_level2.feat" , could you tell me which cope folder you 
are talking about? there is six of them, and which file to be read on matlab?

.
├── 139435_tfMRI_EMOTION_level2_hp200_s2.dscalar.nii
├── Contrasts.txt
├── design.con
├── design_cov.png
├── design_cov.ppm
├── design.fsf
├── design.grp
├── design.mat
├── design.png
├── design.ppm
└── GrayordinatesStats
├── cope1.feat
│   ├── cope1.dtseries.nii
│   ├── logfile
│   ├── mask.dtseries.nii
│   ├── mean_random_effects_var1.dtseries.nii
│   ├── pe1.dtseries.nii
│   ├── res4d.dtseries.nii
│   ├── tdof_t1.dtseries.nii
│   ├── tstat1.dtseries.nii
│   ├── varcope1.dtseries.nii
│   ├── weights1.dtseries.nii
│   ├── zflame1lowertstat1.dtseries.nii
│   ├── zflame1uppertstat1.dtseries.nii
│   └── zstat1.dtseries.nii
├── cope2.feat
│   ├── cope1.dtseries.nii
│   ├── logfile
│   ├── mask.dtseries.nii
│   ├── mean_random_effects_var1.dtseries.nii
│   ├── pe1.dtseries.nii
│   ├── res4d.dtseries.nii
│   ├── tdof_t1.dtseries.nii
│   ├── tstat1.dtseries.nii
│   ├── varcope1.dtseries.nii
│   ├── weights1.dtseries.nii
│   ├── zflame1lowertstat1.dtseries.nii
│   ├── zflame1uppertstat1.dtseries.nii
│   └── zstat1.dtseries.nii
├── cope3.feat
│   ├── cope1.dtseries.nii
│   ├── logfile
│   ├── mask.dtseries.nii
│   ├── mean_random_effects_var1.dtseries.nii
│   ├── pe1.dtseries.nii
│   ├── res4d.dtseries.nii
│   ├── tdof_t1.dtseries.nii
│   ├── tstat1.dtseries.nii
│   ├── varcope1.dtseries.nii
│   ├── weights1.dtseries.nii
│   ├── zflame1lowertstat1.dtseries.nii
│   ├── zflame1uppertstat1.dtseries.nii
│   └── zstat1.dtseries.nii
├── cope4.feat
│   ├── cope1.dtseries.nii
│   ├── logfile
│   ├── mask.dtseries.nii
│   ├── mean_random_effects_var1.dtseries.nii
│   ├── pe1.dtseries.nii
│   ├── res4d.dtseries.nii
│   ├── tdof_t1.dtseries.nii
│   ├── tstat1.dtseries.nii
│   ├── varcope1.dtseries.nii
│   ├── weights1.dtseries.nii
│   ├── zflame1lowertstat1.dtseries.nii
│   ├── zflame1uppertstat1.dtseries.nii
│   └── zstat1.dtseries.nii
├── cope5.feat
│   ├── cope1.dtseries.nii
│   ├── logfile
│   ├── mask.dtseries.nii
│   ├── mean_random_effects_var1.dtseries.nii
│   ├── pe1.dtseries.nii
│   ├── res4d.dtseries.nii
│   ├── tdof_t1.dtseries.nii
│   ├── tstat1.dtseries.nii
│   ├── varcope1.dtseries.nii
│   ├── weights1.dtseries.nii
│   ├── zflame1lowertstat1.dtseries.nii
│   ├── zflame1uppertstat1.dtseries.nii
│   └── zstat1.dtseries.nii
└── cope6.feat
├── cope1.dtseries.nii
├── logfile
├── mask.dtseries.nii
├── mean_random_effects_var1.dtseries.nii
├── pe1.dtseries.nii
├── res4d.dtseries.nii
├── tdof_t1.dtseries.nii
├── tstat1.dtseries.nii
├── varcope1.dtseries.nii
├── weights1.dtseries.nii
├── zflame1lowertstat1.dtseries.nii
├── zflame1uppertstat1.dtseries.nii
└── zstat1.dtseries.nii

 Cheers,
Yassine


Le mar. 27 mars 2018 à 12:18, Harms, Michael 
<mha...@wustl.edu<mailto:mha...@wustl.edu>> a écrit :

Certainly that can be done.  Take the beta (cope) maps from the CIFTI data, 
load them into (e.g., matlab), and correlate those vectors across subjects.  If 
you specifically want only the cortex, you’d need to exclude the subcortical 
voxels from the grayordinates.

There is no need to go back to voxels for what you are trying to do.

Cheers,
-MH

--
Michael Harms, Ph.D.
---
Associate Professor of Psychiatry
Washington University School of Medicine
Department of Psychiatry, Box 8134
660 South Euclid 
Ave<https://maps.google.com/?q=660+South+Euclid+Ave=gmail=g>.  
  Tel: 314-747-6173<tel:(314)%20747-6173>
St. Louis, MO  63110  Email: 
mha...@wustl.edu<mailto:mha...@wustl.edu>

From

Re: [HCP-Users] Convert activation cifti data to volume nifti

[Harms, Michael]

Certainly that can be done.  Take the beta (cope) maps from the CIFTI data, 
load them into (e.g., matlab), and correlate those vectors across subjects.  If 
you specifically want only the cortex, you’d need to exclude the subcortical 
voxels from the grayordinates.

There is no need to go back to voxels for what you are trying to do.

Cheers,
-MH

--
Michael Harms, Ph.D.
---
Associate Professor of Psychiatry
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: Yassine Benhajali <yanama...@gmail.com>
Date: Tuesday, March 27, 2018 at 11:05 AM
To: "Harms, Michael" <mha...@wustl.edu>
Cc: NEUROSCIENCE tim <tsc...@mst.edu>, hcp-users <hcp-users@humanconnectome.org>
Subject: Re: [HCP-Users] Convert activation cifti data to volume nifti

Ok, here te hole story behind what I try to achieve:

- What I did?
The surface maps you see on the figure is originally a volume based activation 
maps that I mapped on surface. This map is generated from unprocessed HCP data 
with our lab software NIAK<http://niak.simexp-lab.org/>. My analysis consist of 
stacking volume activation maps as vector of voxels, then correlate each 
subject vector with the rest of the dataset to have a subject by subject 
correlation matrix.

- What I'm trying to do?
My aim is to repeat the same process above but now with already computed 
activation map from HCP pipeline. So i need a way to transform activation 
surface map to a vector of voxels in order to correlate thse vector between 
subjects.

If you think that there is a way to correlate activation maps between subject 
directly from surface, I would be happy to know how.

Thanks
Yassine

Le mar. 27 mars 2018 à 10:04, Harms, Michael 
<mha...@wustl.edu<mailto:mha...@wustl.edu>> a écrit :

For the surfaces, why not quantify the activation via the surface area, rather 
than volume?

Cheers,
-MH

--
Michael Harms, Ph.D.
---
Associate Professor of Psychiatry
Washington University School of Medicine
Department of Psychiatry, Box 8134
660 South Euclid 
Ave<https://maps.google.com/?q=660+South+Euclid+Ave=gmail=g>.  
  Tel: 314-747-6173<tel:(314)%20747-6173>
St. Louis, MO  63110  Email: 
mha...@wustl.edu<mailto:mha...@wustl.edu>

From: 
<hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>>
 on behalf of Yassine Benhajali 
<yanama...@gmail.com<mailto:yanama...@gmail.com>>
Date: Tuesday, March 27, 2018 at 8:58 AM
To: NEUROSCIENCE tim <tsc...@mst.edu<mailto:tsc...@mst.edu>>
Cc: hcp-users 
<hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] Convert activation cifti data to volume nifti

Thank you for your reply.
I would like to extract the volume based activation maps from each subject and 
put it as vector and do the same for each subject then stack them all in one 
matrix like this figure. Then, I'll do some clustering on that  stack.
[age.png]

If you have any hint on how to accomplish that without loosing the benefit of 
surface based registration.

Best,
Yassine

Le lun. 26 mars 2018 à 17:20, Timothy Coalson 
<tsc...@mst.edu<mailto:tsc...@mst.edu>> a écrit :
For subcortical structures, it is as simple as wb_command -cifti-separate using 
-volume-all.

For surface data, you would need to map it back into volume, using that 
subject's surfaces, thereby losing the advantages of surface registration (for 
both analysis and display).  You would need to use -cifti-separate with 
-metric, and then use -metric-to-volume-mapping.

Why are you trying to do this?  We might have suggestions of other ways to 
accomplish your task.

Tim


On Mon, Mar 26, 2018 at 12:37 PM, Yassine Benhajali 
<yanama...@gmail.com<mailto:yanama...@gmail.com>> wrote:
Hi all,
Any one knows how to extract activation volume in nifti from cifti file like 
this one : 
'139435/FMRI/fMRI_EMOTION/tfMRI_EMOTION_hp200_s4_level2.feat/139435_tfMRI_EMOTION_level2_hp200_s4.dscalar.nii'

Best,
Yassine
--
Yassine Benhajali
Doctorant en Neuroanthropologie
au Laboratoire SIMEXP - http://www.simexp-lab.org/members/
Université de Montréal, Québec, Canada
514 839 0501<tel:(514)%20839-0501>

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--
Yassine Benhajali
Doctorant en Neuroanthropologie
au Laboratoire SIMEXP - http://www.simexp-lab.org/members/
Université de Montréal, Québec, Canada
514 839 0501<tel:(514)%20839-0501>

__

Re: [HCP-Users] Fwd: analysing the 7T rsfMRI

[Harms, Michael]

Hi,
“AP” (short for anterior-to-posterior) and “PA” (short for 
posterior-to-anterior) refer to the phase encoding direction.
In general, as Jenn said, we recommend using both the AP and PA data, so that 
your results aren’t “biased” toward a particular phase-encoding direction.

Is there a particular reason that you only want to use a single “AP” run?

Cheers,
-MH

--
Michael Harms, Ph.D.
---
Associate Professor of Psychiatry
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:  on behalf of Laserboy 1122233 

Date: Monday, March 26, 2018 at 10:57 AM
To: "Elam, Jennifer" 
Cc: "hcp-users@humanconnectome.org" 
Subject: Re: [HCP-Users] Fwd: analysing the 7T rsfMRI

Dear Jenn and all,

Many thanks for your email and replay. Is the AP the fold direction? or what is 
it exactly? May I ask if I analyze the data with AP flold direction is this 
acceptable? I have used and downloaded other free data (e.g. the fcon 1000) but 
all what I analysed before where one nifit file and never seen such rsfMRI. So 
how much will this be going to affect the data analysis? and whether it is a 
big problem?

Many thanks

Aser

On Mon, Mar 26, 2018 at 4:25 PM, Elam, Jennifer 
> wrote:

Hi Aser,

First off, if you have 7T preprocessed rfMRI data that we previously released, 
do not use it. There was a processing error that we have now fixed and are 
preparing to rerelease the corrected preprocessed data in the next couple of 
weeks.

If you are processing the unprocessed 7T data yourself, we recommend analyzing 
the runs in AP/PA pairs, or using all 4 runs. Advice on demeaning and 
normalizing the timeseries and then concatenating the runs is on the HCP-Users 
FAQ 
wikipage.



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 Laserboy 1122233 >
Sent: Monday, March 26, 2018 10:15:39 AM
To: hcp-users@humanconnectome.org
Subject: [HCP-Users] Fwd: analysing the 7T rsfMRI

Hello

I am new to the data and apologies if this is a naive question.

All of the data contain or acquired with AP and or PA. If I would like to use 
for example conn to analyse the data can I just analyse rest 1 (PA) or it has 
to be both? If both how can I combine them or proceed ?

Many thanks

Aser


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Re: [HCP-Users] Simple GLM for cordial thickness and myelin maps in workbench?

[Harms, Michael]

Hi,
Not in wb_command at the current time.  You could of course load the data into 
Matlab and run a regression there, if all you care about is the effect size of 
the relationship.  What PALM nicely gives you is the ability to control for 
multiple comparisons in a statistically rigorous manner using permutation 
testing.

Cheers,
-MH

--
Michael Harms, Ph.D.
---
Associate Professor of Psychiatry
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:  on behalf of "Linnman, 
Clas,Ph.D." 
Date: Saturday, March 17, 2018 at 8:30 PM
To: "hcp-users@humanconnectome.org" 
Subject: [HCP-Users] Simple GLM for cordial thickness and myelin maps in 
workbench?

Hi,

I would like to do a linear regression between a variable and cortical 
thickness in a subset of participants from the HCP1200, controlling for a 
couple of factors.
Is PALM the (only) way to do that, or are there any basic statistical commands 
that can be used in wb_command?

Best
Clas


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Re: [HCP-Users] Melodic ICA idle

[Harms, Michael]

I think the issue, as I read it, is that Will’s data is only NIFTI currently, 
so he doesn’t have any subject CIFTI that he could use for the stage 1 of dual 
reg.

Our suggestion of course to remedy that would be that you process your data 
into CIFTI, using the HCP Pipelines. ☺

Cheers,
-MH

--
Michael Harms, Ph.D.
---
Associate Professor of Psychiatry
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:  on behalf of Stephen Smith 

Date: Tuesday, March 13, 2018 at 2:31 AM
To: Will Khan 
Cc: "hcp-users@humanconnectome.org" 
Subject: Re: [HCP-Users] Melodic ICA idle

Hi Will

I'm not aware of any outstanding bugs in melodic that would cause it to 
silently hang.  Are you sure it's not just that you've run out of RAM and are 
swapping?

Yes it's better to do group-ICA on grayordinates. You can still dual-regress 
that (step one into subject CIFTI, step two back into either CIFIT and/or 
volume) to get volume maps back, like we did for the most recent group-ICA HCP 
release.

Cheers.





On 13 Mar 2018, at 04:52, Will Khan 
> wrote:

Dear HCP Users,

I am currently using the ICA-FIX denoised volumetric data for 100 unrelated 
subjects. I come across an issue where melodic appears to 'choke' or remain 
idle for a considerable amount of time at the variance normalisation step. I am 
running a group-ICA within a mask of the PCC.

I understand this issue has been reported by others and appears to be a bug 
with the melodic command.

I know Steve Smith and others have cautioned against the use of the volumetric 
data - but I am using the HCP dataset to generate group-ICA maps that I later 
wish to dualreg onto a patient dataset. Since all my patient data is in NIFTI 
format I am initially hesitant to use CIFTI (please correct me if I am wrong 
here).

Am I right to be using the volumetric data in this case?

Many Thanks!

Regards,

Will





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---
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Head of Analysis,  Oxford University FMRIB Centre

FMRIB, JR Hospital, Headington, Oxford  OX3 9DU, UK
+44 (0) 1865 222726  (fax 222717)
st...@fmrib.ox.ac.uk
http://www.fmrib.ox.ac.uk/~steve
---

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Re: [HCP-Users] Concatenating resting state runs

[Harms, Michael]

Hi Tim,
That isn’t quite an analogous situation.  At least for full correlation, 
computed from the 15 min runs of the HCP-YA, computing a separate network 
matrix for each individual 15 min run, Fisher transforming those, and then 
averaging those r-to-z’s appears to be a little bit more robust way to estimate 
a subject’s network matrix than computing the network matrix from a single 
“concatenated” run of 60 min.

Cheers,
-MH

--
Michael Harms, Ph.D.
---
Associate Professor of Psychiatry
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: Timothy Coalson <tsc...@mst.edu>
Date: Wednesday, March 7, 2018 at 5:19 PM
To: "Harms, Michael" <mha...@wustl.edu>
Cc: "Glasser, Matthew" <glass...@wustl.edu>, David Hofmann 
<davidhofma...@gmail.com>, hcp-users <hcp-users@humanconnectome.org>
Subject: Re: [HCP-Users] Concatenating resting state runs

When we compute parcellated connectivity, we first compute the average 
timeseries within the parcels, and then correlate those, as it vastly reduces 
the impact of noise.  If we first computed the correlations, and then averaged 
them within parcels, we would be losing a huge amount of power.

The per-run correlating first and then averaging that you propose sounds like a 
similar situation, though because there are only 4 runs, and each run has lots 
of timepoints, and the averaging isn't spatial, it won't be nearly as dramatic 
a difference.  Keep in mind that the phase encoding direction dictates where 
signal dropouts will be, which will show up in any analysis of non-concatenated 
data.

Tim


On Wed, Mar 7, 2018 at 4:02 PM, Harms, Michael 
<mha...@wustl.edu<mailto:mha...@wustl.edu>> wrote:

In the case of correlations or partial correlations, I would tend to compute 
those separately for each run anyway, Fisher transform them, and then average 
the r-to-z values across runs.  In which case no across-run concatentation is 
necessary in the first place.

I don’t know if a per-run DCM approach, followed by averaging of the DCM 
outputs is a possibility.  If it is, you might just want to consider that 
approach instead.

Cheers,
-MH

--
Michael Harms, Ph.D.
---
Associate Professor of Psychiatry
Washington University School of Medicine
Department of Psychiatry, Box 8134
660 South Euclid 
Ave<https://maps.google.com/?q=660+South+Euclid+Ave=gmail=g>.  
  Tel: 314-747-6173<tel:(314)%20747-6173>
St. Louis, MO  63110  Email: 
mha...@wustl.edu<mailto:mha...@wustl.edu>

From: "Glasser, Matthew" <glass...@wustl.edu<mailto:glass...@wustl.edu>>
Date: Wednesday, March 7, 2018 at 3:39 PM
To: David Hofmann <davidhofma...@gmail.com<mailto:davidhofma...@gmail.com>>

Cc: "Harms, Michael" <mha...@wustl.edu<mailto:mha...@wustl.edu>>, hcp-users 
<hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] Concatenating resting state runs

The basic idea for variance normalization is to equalize the variance of the 
noise.  It is very helpful for ICA and regression-based techniques.  I’m not 
sure we have explicitly tested the effect on correlation.  Correlation is a 
ratio and so it would not matter at all for a single run, though there may be 
benefits to doing variance normalization prior to concatenation for 
correlation.  Not sure of how this will interact with DCM either.

Peace,

Matt.

From: David Hofmann <davidhofma...@gmail.com<mailto:davidhofma...@gmail.com>>
Date: Wednesday, March 7, 2018 at 3:29 PM
To: Matt Glasser <glass...@wustl.edu<mailto:glass...@wustl.edu>>
Cc: "Harms, Michael" <mha...@wustl.edu<mailto:mha...@wustl.edu>>, hcp-users 
<hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] Concatenating resting state runs

Hi all,

that being said, why is this regression approach for variance normalization 
superior to a z-standardization? That is, will it practically matter e.g. for 
correlations or partial correlations?

2018-03-07 19:31 GMT+01:00 Glasser, Matthew 
<glass...@wustl.edu<mailto:glass...@wustl.edu>>:
Hi Mike,

I doubt that matters for this application of making an unstructured noise 
timeseries for the purpose of variance normalization.

Matt.

From: "Harms, Michael" <mha...@wustl.edu<mailto:mha...@wustl.edu>>
Date: Wednesday, March 7, 2018 at 12:09 PM

To: Matt Glasser <glass...@wustl.edu<mailto:glass...@wustl.edu>>, David Hofmann 
<davidhofma...@gmail.com<mailto:davidhofma...@gmail.com>>
Cc: hcp-users 
&l

Re: [HCP-Users] Concatenating resting state runs

[Harms, Michael]

In the case of correlations or partial correlations, I would tend to compute 
those separately for each run anyway, Fisher transform them, and then average 
the r-to-z values across runs.  In which case no across-run concatentation is 
necessary in the first place.

I don’t know if a per-run DCM approach, followed by averaging of the DCM 
outputs is a possibility.  If it is, you might just want to consider that 
approach instead.

Cheers,
-MH

--
Michael Harms, Ph.D.
---
Associate Professor of Psychiatry
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: "Glasser, Matthew" <glass...@wustl.edu>
Date: Wednesday, March 7, 2018 at 3:39 PM
To: David Hofmann <davidhofma...@gmail.com>
Cc: "Harms, Michael" <mha...@wustl.edu>, hcp-users 
<hcp-users@humanconnectome.org>
Subject: Re: [HCP-Users] Concatenating resting state runs

The basic idea for variance normalization is to equalize the variance of the 
noise.  It is very helpful for ICA and regression-based techniques.  I’m not 
sure we have explicitly tested the effect on correlation.  Correlation is a 
ratio and so it would not matter at all for a single run, though there may be 
benefits to doing variance normalization prior to concatenation for 
correlation.  Not sure of how this will interact with DCM either.

Peace,

Matt.

From: David Hofmann <davidhofma...@gmail.com<mailto:davidhofma...@gmail.com>>
Date: Wednesday, March 7, 2018 at 3:29 PM
To: Matt Glasser <glass...@wustl.edu<mailto:glass...@wustl.edu>>
Cc: "Harms, Michael" <mha...@wustl.edu<mailto:mha...@wustl.edu>>, hcp-users 
<hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] Concatenating resting state runs

Hi all,

that being said, why is this regression approach for variance normalization 
superior to a z-standardization? That is, will it practically matter e.g. for 
correlations or partial correlations?

2018-03-07 19:31 GMT+01:00 Glasser, Matthew 
<glass...@wustl.edu<mailto:glass...@wustl.edu>>:
Hi Mike,

I doubt that matters for this application of making an unstructured noise 
timeseries for the purpose of variance normalization.

Matt.

From: "Harms, Michael" <mha...@wustl.edu<mailto:mha...@wustl.edu>>
Date: Wednesday, March 7, 2018 at 12:09 PM

To: Matt Glasser <glass...@wustl.edu<mailto:glass...@wustl.edu>>, David Hofmann 
<davidhofma...@gmail.com<mailto:davidhofma...@gmail.com>>
Cc: hcp-users 
<hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] Concatenating resting state runs


Hi Matt,
Right, that recipe is straightforward, but for completeness there should be two 
additional steps if one wants to match the FIX cleaning precisely:
1) the 24 motion parameters should be filtered with the same HP filter applied 
to the data
2) those HP filtered 24 motion parameters should then be removed from the 
(‘signal’) ICA time-series prior to regressing that (modified) ICA time-series 
onto the cleaned data (i.e., that modified ICA time-series becomes the basis 
for deriving ‘betaICA’).

Cheers,
-MH

--
Michael Harms, Ph.D.
---
Associate Professor of Psychiatry
Washington University School of Medicine
Department of Psychiatry, Box 8134
660 South Euclid 
Ave<https://maps.google.com/?q=660+South+Euclid+Ave=gmail=g>.  
  Tel: 314-747-6173<tel:(314)%20747-6173>
St. Louis, MO  63110      Email: 
mha...@wustl.edu<mailto:mha...@wustl.edu>

From: "Glasser, Matthew" <glass...@wustl.edu<mailto:glass...@wustl.edu>>
Date: Wednesday, March 7, 2018 at 11:24 AM
To: "Harms, Michael" <mha...@wustl.edu<mailto:mha...@wustl.edu>>, David Hofmann 
<davidhofma...@gmail.com<mailto:davidhofma...@gmail.com>>
Cc: hcp-users 
<hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] Concatenating resting state runs

Hi Mike,

Not for the volume data that he is asking about and not for the MSMAll data 
either unfortunately.  I thought it was better to explain this method on the 
list so that it can be applied to arbitrary data whether or not we precomputed 
it.

Matt.

From: "Harms, Michael" <mha...@wustl.edu<mailto:mha...@wustl.edu>>
Date: Wednesday, March 7, 2018 at 11:21 AM
To: Matt Glasser <glass...@wustl.edu<mailto:glass...@wustl.edu>>, David Hofmann 
<davidhofma...@gmail.com<mailto:davidhofma...@gmail.com>>
Cc: hcp-users 
<hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectom

Re: [HCP-Users] Concatenating resting state runs

[Harms, Michael]

Hi Matt,
Right, that recipe is straightforward, but for completeness there should be two 
additional steps if one wants to match the FIX cleaning precisely:
1) the 24 motion parameters should be filtered with the same HP filter applied 
to the data
2) those HP filtered 24 motion parameters should then be removed from the 
(‘signal’) ICA time-series prior to regressing that (modified) ICA time-series 
onto the cleaned data (i.e., that modified ICA time-series becomes the basis 
for deriving ‘betaICA’).

Cheers,
-MH

--
Michael Harms, Ph.D.
---
Associate Professor of Psychiatry
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: "Glasser, Matthew" <glass...@wustl.edu>
Date: Wednesday, March 7, 2018 at 11:24 AM
To: "Harms, Michael" <mha...@wustl.edu>, David Hofmann <davidhofma...@gmail.com>
Cc: hcp-users <hcp-users@humanconnectome.org>
Subject: Re: [HCP-Users] Concatenating resting state runs

Hi Mike,

Not for the volume data that he is asking about and not for the MSMAll data 
either unfortunately.  I thought it was better to explain this method on the 
list so that it can be applied to arbitrary data whether or not we precomputed 
it.

Matt.

From: "Harms, Michael" <mha...@wustl.edu<mailto:mha...@wustl.edu>>
Date: Wednesday, March 7, 2018 at 11:21 AM
To: Matt Glasser <glass...@wustl.edu<mailto:glass...@wustl.edu>>, David Hofmann 
<davidhofma...@gmail.com<mailto:davidhofma...@gmail.com>>
Cc: hcp-users 
<hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] Concatenating resting state runs


Matt,
Don’t we compute an estimate of the unstructured noise variance as part of 
RestingStateState, and then place that into one of the packages?


--
Michael Harms, Ph.D.
---
Associate Professor of Psychiatry
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<mailto:mha...@wustl.edu>

From: 
<hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>>
 on behalf of "Glasser, Matthew" <glass...@wustl.edu<mailto:glass...@wustl.edu>>
Date: Wednesday, March 7, 2018 at 11:01 AM
To: David Hofmann <davidhofma...@gmail.com<mailto:davidhofma...@gmail.com>>
Cc: hcp-users 
<hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] Concatenating resting state runs

Yes they should be in that same package:

${StudyFolder}/${Subject}/MNINonLinear/Results/${fMRIName}/${fMRIName}_hp2000.ica/.fix
 — Tells you which are the noise components (so you can use setdiff to find the 
signal components from a list of all components) so that you can exclude the 
noise component from the regression below.
${StudyFolder}/${Subject}/MNINonLinear/Results/${fMRIName}/${fMRIName}_hp2000.ica/filtered_func_data.ica/melodic_mix
 — ICA component timeseries (you should remove the mean of each ICA component 
timeseries before doing the regression).

Probably the time to read in and write the file will be longer than the time to 
do the regression if you do it in matlab.  Here is some example code:

betaICA = pinv(ICA) * TCS; #TCS is timepoints x space, ICA is timepoints x 
components and should include only the signal components (since the noise 
components were already removed).
UnstructNoiseTCS = TCS - (ICA * betaICA);

You then compute the temporal standard deviation of the unstructured noise 
timeseries and divide the data by it to get the variance normalized data.

Peace,

Matt.

From: David Hofmann <davidhofma...@gmail.com<mailto:davidhofma...@gmail.com>>
Date: Wednesday, March 7, 2018 at 10:47 AM
To: Matt Glasser <glass...@wustl.edu<mailto:glass...@wustl.edu>>
Cc: hcp-users 
<hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] Concatenating resting state runs

Ah I understand. However, I'm not sure how to do this practically for the FIX 
extended data. I'd need all the signal component timeseries and run a 
regression for each voxel which might take a while. I'm not sure if the signals 
are supplied in the dataset, or are they?

Thanks for the support!

2018-03-07 17:07 GMT+01:00 Glasser, Matthew 
<glass...@wustl.edu<mailto:glass...@wustl.edu>>:
The unstructured noise variance is the standard deviation of the timeseries 
after you regress out all of the signal component timeseries.  By doing this 
you make the unstructured noise equal in magnitude across the brain.

I 

Re: [HCP-Users] Concatenating resting state runs

[Harms, Michael]

Also, if David were to do this with HCP-YA data, does he additionally need to 
worry about “backing out” the bias field normalization?

--
Michael Harms, Ph.D.
---
Associate Professor of Psychiatry
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> on behalf of "Harms, Michael" 
<mha...@wustl.edu>
Date: Wednesday, March 7, 2018 at 11:21 AM
To: "Glasser, Matthew" <glass...@wustl.edu>, David Hofmann 
<davidhofma...@gmail.com>
Cc: hcp-users <hcp-users@humanconnectome.org>
Subject: Re: [HCP-Users] Concatenating resting state runs


Matt,
Don’t we compute an estimate of the unstructured noise variance as part of 
RestingStateState, and then place that into one of the packages?


--
Michael Harms, Ph.D.
---
Associate Professor of Psychiatry
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> on behalf of "Glasser, Matthew" 
<glass...@wustl.edu>
Date: Wednesday, March 7, 2018 at 11:01 AM
To: David Hofmann <davidhofma...@gmail.com>
Cc: hcp-users <hcp-users@humanconnectome.org>
Subject: Re: [HCP-Users] Concatenating resting state runs

Yes they should be in that same package:

${StudyFolder}/${Subject}/MNINonLinear/Results/${fMRIName}/${fMRIName}_hp2000.ica/.fix
 — Tells you which are the noise components (so you can use setdiff to find the 
signal components from a list of all components) so that you can exclude the 
noise component from the regression below.
${StudyFolder}/${Subject}/MNINonLinear/Results/${fMRIName}/${fMRIName}_hp2000.ica/filtered_func_data.ica/melodic_mix
 — ICA component timeseries (you should remove the mean of each ICA component 
timeseries before doing the regression).

Probably the time to read in and write the file will be longer than the time to 
do the regression if you do it in matlab.  Here is some example code:

betaICA = pinv(ICA) * TCS; #TCS is timepoints x space, ICA is timepoints x 
components and should include only the signal components (since the noise 
components were already removed).
UnstructNoiseTCS = TCS - (ICA * betaICA);

You then compute the temporal standard deviation of the unstructured noise 
timeseries and divide the data by it to get the variance normalized data.

Peace,

Matt.

From: David Hofmann <davidhofma...@gmail.com<mailto:davidhofma...@gmail.com>>
Date: Wednesday, March 7, 2018 at 10:47 AM
To: Matt Glasser <glass...@wustl.edu<mailto:glass...@wustl.edu>>
Cc: hcp-users 
<hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] Concatenating resting state runs

Ah I understand. However, I'm not sure how to do this practically for the FIX 
extended data. I'd need all the signal component timeseries and run a 
regression for each voxel which might take a while. I'm not sure if the signals 
are supplied in the dataset, or are they?

Thanks for the support!

2018-03-07 17:07 GMT+01:00 Glasser, Matthew 
<glass...@wustl.edu<mailto:glass...@wustl.edu>>:
The unstructured noise variance is the standard deviation of the timeseries 
after you regress out all of the signal component timeseries.  By doing this 
you make the unstructured noise equal in magnitude across the brain.

I wouldn’t do smoothing unless it is constrained to the greymatter.  Really you 
won’t get an obvious benefit if you will be averaging voxels in an ROI anyway 
and that is a more accurate way to do things.

I guess I don’t know enough about your study to know if the order matters.  If 
you are interested in effects that might be related to order (e.g. drowsiness 
being higher in later scans, then order might matter).

Peace,

Matt.

From: David Hofmann <davidhofma...@gmail.com<mailto:davidhofma...@gmail.com>>
Date: Wednesday, March 7, 2018 at 10:02 AM

To: Matt Glasser <glass...@wustl.edu<mailto:glass...@wustl.edu>>
Cc: hcp-users 
<hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] Concatenating resting state runs

Hey Matthew,

not sure I understood where to get the unstructured noise variance from, i.e. 
is it even possible to apply this to the FIX extended datasets?

I thought about using 4mm smoothing (maybe 2mm) before extracting the VOIs / 
ROI timecourses for each subject. This is then fed into the DCMs for each 
subject. I experimented with some HCP data before and it seems smoothing 
increases the effect sizes a little bit. What

Re: [HCP-Users] Concatenating resting state runs

[Harms, Michael]

Matt,
Don’t we compute an estimate of the unstructured noise variance as part of 
RestingStateState, and then place that into one of the packages?


--
Michael Harms, Ph.D.
---
Associate Professor of Psychiatry
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:  on behalf of "Glasser, Matthew" 

Date: Wednesday, March 7, 2018 at 11:01 AM
To: David Hofmann 
Cc: hcp-users 
Subject: Re: [HCP-Users] Concatenating resting state runs

Yes they should be in that same package:

${StudyFolder}/${Subject}/MNINonLinear/Results/${fMRIName}/${fMRIName}_hp2000.ica/.fix
 — Tells you which are the noise components (so you can use setdiff to find the 
signal components from a list of all components) so that you can exclude the 
noise component from the regression below.
${StudyFolder}/${Subject}/MNINonLinear/Results/${fMRIName}/${fMRIName}_hp2000.ica/filtered_func_data.ica/melodic_mix
 — ICA component timeseries (you should remove the mean of each ICA component 
timeseries before doing the regression).

Probably the time to read in and write the file will be longer than the time to 
do the regression if you do it in matlab.  Here is some example code:

betaICA = pinv(ICA) * TCS; #TCS is timepoints x space, ICA is timepoints x 
components and should include only the signal components (since the noise 
components were already removed).
UnstructNoiseTCS = TCS - (ICA * betaICA);

You then compute the temporal standard deviation of the unstructured noise 
timeseries and divide the data by it to get the variance normalized data.

Peace,

Matt.

From: David Hofmann >
Date: Wednesday, March 7, 2018 at 10:47 AM
To: Matt Glasser >
Cc: hcp-users 
>
Subject: Re: [HCP-Users] Concatenating resting state runs

Ah I understand. However, I'm not sure how to do this practically for the FIX 
extended data. I'd need all the signal component timeseries and run a 
regression for each voxel which might take a while. I'm not sure if the signals 
are supplied in the dataset, or are they?

Thanks for the support!

2018-03-07 17:07 GMT+01:00 Glasser, Matthew 
>:
The unstructured noise variance is the standard deviation of the timeseries 
after you regress out all of the signal component timeseries.  By doing this 
you make the unstructured noise equal in magnitude across the brain.

I wouldn’t do smoothing unless it is constrained to the greymatter.  Really you 
won’t get an obvious benefit if you will be averaging voxels in an ROI anyway 
and that is a more accurate way to do things.

I guess I don’t know enough about your study to know if the order matters.  If 
you are interested in effects that might be related to order (e.g. drowsiness 
being higher in later scans, then order might matter).

Peace,

Matt.

From: David Hofmann >
Date: Wednesday, March 7, 2018 at 10:02 AM

To: Matt Glasser >
Cc: hcp-users 
>
Subject: Re: [HCP-Users] Concatenating resting state runs

Hey Matthew,

not sure I understood where to get the unstructured noise variance from, i.e. 
is it even possible to apply this to the FIX extended datasets?

I thought about using 4mm smoothing (maybe 2mm) before extracting the VOIs / 
ROI timecourses for each subject. This is then fed into the DCMs for each 
subject. I experimented with some HCP data before and it seems smoothing 
increases the effect sizes a little bit. What is smoothing between 
parcellations btw.?

Also, any comments on the order of concatenation? I concatenate all of the data 
RL and then LR.

2018-03-07 16:17 GMT+01:00 Glasser, Matthew 
>:
I typically variance normalize before concatenation, but do this based on the 
unstructured noise variance.

I would take the mean time course over an ROI that I thought to be 
representative of a meaningful neuroanatomical subunit.

My understanding of how SPM’s DCM is typically implemented is that there are 
large amounts of spatial smoothing, cross-subject alignment is done in the 
volume, and ROIs are spheres of some radius.  All this would lead to a lot of 
mixing of timecourses.  My suggestion was to use parcel timecourses from some 
kind of parcellation.  If you have a good amygdala parcellation that might be 
fine, though I would avoid smoothing the data between the parcels.

Peace,

Matt.

From: David Hofmann 

Re: [HCP-Users] Concatenate sessions from Emotion task

[Harms, Michael]

Just compute the length of the run implied by the number of frames (# frames * 
TR), and check if any events in the .txt files from the first run have an onset 
later than that!

--
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: David Hofmann <davidhofma...@gmail.com>
Date: Wednesday, February 28, 2018 at 11:03 AM
To: "Harms, Michael" <mha...@wustl.edu>
Cc: "Glasser, Matthew" <glass...@wustl.edu>, hcp-users 
<hcp-users@humanconnectome.org>
Subject: Re: [HCP-Users] Concatenate sessions from Emotion task

Hey again,

how can I check for this?

2018-02-28 15:52 GMT+01:00 Harms, Michael 
<mha...@wustl.edu<mailto:mha...@wustl.edu>>:

Also, there may (very rarely) be cases where the first emotion run was aborted 
(or recon stopped/crashed), while the EPRIME script itself continued to 
completion.  I’m not sure if we edited those condition .txt files to ensure 
that there were no events listed beyond the actual available number of frames, 
because it wouldn’t have mattered in our model framework (when modeling each 
run separately).  But it would matter in your situation, so you probably need 
to add some additional checks for that situation.

--
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<https://maps.google.com/?q=660+South+Euclid+Ave=gmail=g>.  
  Tel: 314-747-6173<tel:(314)%20747-6173>
St. Louis, MO  63110  Email: 
mha...@wustl.edu<mailto:mha...@wustl.edu>

From: David Hofmann <davidhofma...@gmail.com<mailto:davidhofma...@gmail.com>>
Date: Wednesday, February 28, 2018 at 8:45 AM

To: "Harms, Michael" <mha...@wustl.edu<mailto:mha...@wustl.edu>>
Cc: "Glasser, Matthew" <glass...@wustl.edu<mailto:glass...@wustl.edu>>, 
hcp-users <hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] Concatenate sessions from Emotion task

Ok, there were some rounding inaccuracies, get the same onsets as you now!

Thanks for the hint, I will make sure to check the number of frames for each 
file.

Thanks again,

David

2018-02-28 15:05 GMT+01:00 Harms, Michael 
<mha...@wustl.edu<mailto:mha...@wustl.edu>>:

Sure, that’s close.  (I get 158.787, 200.93, and 243.073).

Make sure you use the actual number of frames in the first run (to properly 
determine the correct offset in the case that the first emotion run was aborted 
a little early).  i.e., don’t assume that the first emotion run will *always* 
have 176 frames.

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<https://maps.google.com/?q=660+South+Euclid+Ave=gmail=g>.  
  Tel: 314-747-6173<tel:(314)%20747-6173>
St. Louis, MO  63110  Email: 
mha...@wustl.edu<mailto:mha...@wustl.edu>

From: David Hofmann <davidhofma...@gmail.com<mailto:davidhofma...@gmail.com>>
Date: Wednesday, February 28, 2018 at 7:50 AM
To: "Harms, Michael" <mha...@wustl.edu<mailto:mha...@wustl.edu>>
Cc: "Glasser, Matthew" <glass...@wustl.edu<mailto:glass...@wustl.edu>>, 
hcp-users <hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>

Subject: Re: [HCP-Users] Concatenate sessions from Emotion task

Hi Michael,

there is an SPM function that handles the concatenation by adding session 
regressors and adjusting the high-pass filter. I'm still pondering if I want to 
include a regressor that accounts for the transition between sessions, but not 
sure how it would look like. Any ideas on that?

Ok, that sounds easy :).

TR=0.72
and number of volumes in the emotion task is: 176

My onsets of session 2 are:

32.067
74.21
116.353

So I will just add: 0.72*176=126,72 to all onsets and get:

158,800
200,943
243,085

Can you confirm I got this right?


greetings

David


2018-02-27 16:01 GMT+01:00 Harms, Michael 
<mha...@wustl.edu<mailto:mha...@wustl.edu>>:

Well, you know the TR, and the number of frames in the first run, so just add 
the product of those two to the times in the 2nd run (unless you are manually 
deleting additional frames at the start of either run).

Cheers,
-MH

--
Michael Har

Re: [HCP-Users] Concatenate sessions from Emotion task

[Harms, Michael]

Also, there may (very rarely) be cases where the first emotion run was aborted 
(or recon stopped/crashed), while the EPRIME script itself continued to 
completion.  I’m not sure if we edited those condition .txt files to ensure 
that there were no events listed beyond the actual available number of frames, 
because it wouldn’t have mattered in our model framework (when modeling each 
run separately).  But it would matter in your situation, so you probably need 
to add some additional checks for that situation.

--
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: David Hofmann <davidhofma...@gmail.com>
Date: Wednesday, February 28, 2018 at 8:45 AM
To: "Harms, Michael" <mha...@wustl.edu>
Cc: "Glasser, Matthew" <glass...@wustl.edu>, hcp-users 
<hcp-users@humanconnectome.org>
Subject: Re: [HCP-Users] Concatenate sessions from Emotion task

Ok, there were some rounding inaccuracies, get the same onsets as you now!

Thanks for the hint, I will make sure to check the number of frames for each 
file.

Thanks again,

David

2018-02-28 15:05 GMT+01:00 Harms, Michael 
<mha...@wustl.edu<mailto:mha...@wustl.edu>>:

Sure, that’s close.  (I get 158.787, 200.93, and 243.073).

Make sure you use the actual number of frames in the first run (to properly 
determine the correct offset in the case that the first emotion run was aborted 
a little early).  i.e., don’t assume that the first emotion run will *always* 
have 176 frames.

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<https://maps.google.com/?q=660+South+Euclid+Ave=gmail=g>.  
  Tel: 314-747-6173<tel:(314)%20747-6173>
St. Louis, MO  63110  Email: 
mha...@wustl.edu<mailto:mha...@wustl.edu>

From: David Hofmann <davidhofma...@gmail.com<mailto:davidhofma...@gmail.com>>
Date: Wednesday, February 28, 2018 at 7:50 AM
To: "Harms, Michael" <mha...@wustl.edu<mailto:mha...@wustl.edu>>
Cc: "Glasser, Matthew" <glass...@wustl.edu<mailto:glass...@wustl.edu>>, 
hcp-users <hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>

Subject: Re: [HCP-Users] Concatenate sessions from Emotion task

Hi Michael,

there is an SPM function that handles the concatenation by adding session 
regressors and adjusting the high-pass filter. I'm still pondering if I want to 
include a regressor that accounts for the transition between sessions, but not 
sure how it would look like. Any ideas on that?

Ok, that sounds easy :).

TR=0.72
and number of volumes in the emotion task is: 176

My onsets of session 2 are:

32.067
74.21
116.353

So I will just add: 0.72*176=126,72 to all onsets and get:

158,800
200,943
243,085

Can you confirm I got this right?


greetings

David


2018-02-27 16:01 GMT+01:00 Harms, Michael 
<mha...@wustl.edu<mailto:mha...@wustl.edu>>:

Well, you know the TR, and the number of frames in the first run, so just add 
the product of those two to the times in the 2nd run (unless you are manually 
deleting additional frames at the start of either run).

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<https://maps.google.com/?q=660+South+Euclid+Ave=gmail=g>.  
  Tel: 314-747-6173<tel:(314)%20747-6173>
St. Louis, MO  63110  Email: 
mha...@wustl.edu<mailto:mha...@wustl.edu>

From: 
<hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>>
 on behalf of David Hofmann 
<davidhofma...@gmail.com<mailto:davidhofma...@gmail.com>>
Date: Tuesday, February 27, 2018 at 7:48 AM
To: "Glasser, Matthew" <glass...@wustl.edu<mailto:glass...@wustl.edu>>
Cc: hcp-users 
<hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] Concatenate sessions from Emotion task

Hi Matthew,

I basically want to have one file, that is the concatenation of the RL and LR 
files and one file with the onsets for the fear and neut conditions for both 
sessions. For example, subject 100206 has one fear.txt file for each session 
with the following block onsets:

32.08 18  1
74.223 18
1
116.3

Re: [HCP-Users] Concatenate sessions from Emotion task

[Harms, Michael]

Sure, that’s close.  (I get 158.787, 200.93, and 243.073).

Make sure you use the actual number of frames in the first run (to properly 
determine the correct offset in the case that the first emotion run was aborted 
a little early).  i.e., don’t assume that the first emotion run will *always* 
have 176 frames.

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: David Hofmann <davidhofma...@gmail.com>
Date: Wednesday, February 28, 2018 at 7:50 AM
To: "Harms, Michael" <mha...@wustl.edu>
Cc: "Glasser, Matthew" <glass...@wustl.edu>, hcp-users 
<hcp-users@humanconnectome.org>
Subject: Re: [HCP-Users] Concatenate sessions from Emotion task

Hi Michael,

there is an SPM function that handles the concatenation by adding session 
regressors and adjusting the high-pass filter. I'm still pondering if I want to 
include a regressor that accounts for the transition between sessions, but not 
sure how it would look like. Any ideas on that?

Ok, that sounds easy :).

TR=0.72
and number of volumes in the emotion task is: 176

My onsets of session 2 are:

32.067
74.21
116.353

So I will just add: 0.72*176=126,72 to all onsets and get:

158,800
200,943
243,085

Can you confirm I got this right?




greetings


David



2018-02-27 16:01 GMT+01:00 Harms, Michael 
<mha...@wustl.edu<mailto:mha...@wustl.edu>>:

Well, you know the TR, and the number of frames in the first run, so just add 
the product of those two to the times in the 2nd run (unless you are manually 
deleting additional frames at the start of either run).

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<https://maps.google.com/?q=660+South+Euclid+Ave=gmail=g>.  
  Tel: 314-747-6173<tel:(314)%20747-6173>
St. Louis, MO  63110  Email: 
mha...@wustl.edu<mailto:mha...@wustl.edu>

From: 
<hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>>
 on behalf of David Hofmann 
<davidhofma...@gmail.com<mailto:davidhofma...@gmail.com>>
Date: Tuesday, February 27, 2018 at 7:48 AM
To: "Glasser, Matthew" <glass...@wustl.edu<mailto:glass...@wustl.edu>>
Cc: hcp-users 
<hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] Concatenate sessions from Emotion task

Hi Matthew,

I basically want to have one file, that is the concatenation of the RL and LR 
files and one file with the onsets for the fear and neut conditions for both 
sessions. For example, subject 100206 has one fear.txt file for each session 
with the following block onsets:

32.08 18  1
74.223 18
1
116.365 18
1

for the first session and

32.067 18
1
74.21 18  1
116.353 18
1

for the second session

Now, after concatenation of the data files, I have to adjust the onsets of the 
second session, such that all onsets are now greater than the last onset of the 
first session (116.365). Basically, just add some value to the onsets of the 
second session.  This will depend on the number of "dummy volumes" at the end 
of the first session and begin of the second session asf.

I'm using SPM so I don't think concatenating the design files will work here.

Hope it became clear what I mean.

Thanks!

2018-02-27 14:01 GMT+01:00 Glasser, Matthew 
<glass...@wustl.edu<mailto:glass...@wustl.edu>>:
Is this a question of what to do with the images? Presumably for the design you 
could just concatenate the design files after generation and the image files 
after demean and hp200 or detrend.

Peace,

Matt.

From: 
<hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>>
 on behalf of David Hofmann 
<davidhofma...@gmail.com<mailto:davidhofma...@gmail.com>>
Date: Tuesday, February 27, 2018 at 4:52 AM
To: hcp-users 
<hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>
Subject: [HCP-Users] Concatenate sessions from Emotion task

Hi all,

I would like to concatenate the RL and LR files from the Emotion task 
(modelling the sessions separately is not an option for the analysis I want to 
do later on) and thus have to change the onsets in fear.txt and neu.txt for the 
second session accordingly. I'm not quite sure how to do this properly and hope 
for some guidance.

Many thanks in advance

David

Re: [HCP-Users] Concatenate sessions from Emotion task

[Harms, Michael]

Well, you know the TR, and the number of frames in the first run, so just add 
the product of those two to the times in the 2nd run (unless you are manually 
deleting additional frames at the start of either run).

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:  on behalf of David Hofmann 

Date: Tuesday, February 27, 2018 at 7:48 AM
To: "Glasser, Matthew" 
Cc: hcp-users 
Subject: Re: [HCP-Users] Concatenate sessions from Emotion task

Hi Matthew,

I basically want to have one file, that is the concatenation of the RL and LR 
files and one file with the onsets for the fear and neut conditions for both 
sessions. For example, subject 100206 has one fear.txt file for each session 
with the following block onsets:

32.08 18  1
74.223 18
1
116.365 18
1

for the first session and

32.067 18
1
74.21 18  1
116.353 18
1

for the second session

Now, after concatenation of the data files, I have to adjust the onsets of the 
second session, such that all onsets are now greater than the last onset of the 
first session (116.365). Basically, just add some value to the onsets of the 
second session.  This will depend on the number of "dummy volumes" at the end 
of the first session and begin of the second session asf.

I'm using SPM so I don't think concatenating the design files will work here.

Hope it became clear what I mean.

Thanks!

2018-02-27 14:01 GMT+01:00 Glasser, Matthew 
>:
Is this a question of what to do with the images? Presumably for the design you 
could just concatenate the design files after generation and the image files 
after demean and hp200 or detrend.

Peace,

Matt.

From: 
>
 on behalf of David Hofmann 
>
Date: Tuesday, February 27, 2018 at 4:52 AM
To: hcp-users 
>
Subject: [HCP-Users] Concatenate sessions from Emotion task

Hi all,

I would like to concatenate the RL and LR files from the Emotion task 
(modelling the sessions separately is not an option for the analysis I want to 
do later on) and thus have to change the onsets in fear.txt and neu.txt for the 
second session accordingly. I'm not quite sure how to do this properly and hope 
for some guidance.

Many thanks in advance

David



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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] Concatenate sessions from Emotion task

[Harms, Michael]

What tools are you planning on using for the GLM fitting?  Concatenating the 
runs will lead to some inaccuracies in the auto-correlation modeling at the 
point of concatenation, although I don’t know if anyone has ever investigated 
whether it matters much empirically.

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:  on behalf of "Glasser, Matthew" 

Date: Tuesday, February 27, 2018 at 7:01 AM
To: David Hofmann , hcp-users 

Subject: Re: [HCP-Users] Concatenate sessions from Emotion task

Is this a question of what to do with the images? Presumably for the design you 
could just concatenate the design files after generation and the image files 
after demean and hp200 or detrend.

Peace,

Matt.

From: 
>
 on behalf of David Hofmann 
>
Date: Tuesday, February 27, 2018 at 4:52 AM
To: hcp-users 
>
Subject: [HCP-Users] Concatenate sessions from Emotion task

Hi all,

I would like to concatenate the RL and LR files from the Emotion task 
(modelling the sessions separately is not an option for the analysis I want to 
do later on) and thus have to change the onsets in fear.txt and neu.txt for the 
second session accordingly. I'm not quite sure how to do this properly and hope 
for some guidance.

Many thanks in advance

David



___
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


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] what is rfMRI_REST1_LR_Atlas.dtseries.nii

[Harms, Michael]

The FIX cleaned files have “clean” in their file name.

--
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: redhatw <redh...@gmail.com>
Date: Friday, February 23, 2018 at 9:37 AM
To: "Harms, Michael" <mha...@wustl.edu>
Cc: "Glasser, Matthew" <glass...@wustl.edu>, "hcp-users@humanconnectome.org" 
<hcp-users@humanconnectome.org>
Subject: Re: [HCP-Users] what is rfMRI_REST1_LR_Atlas.dtseries.nii

Was the MSMAll one cleaned?
Thanks
Ze

On Fri, Feb 23, 2018 at 9:43 AM, Harms, Michael 
<mha...@wustl.edu<mailto:mha...@wustl.edu>> wrote:
I guess, if you never plan on using the MSMSulc registered output from the 
preprocessing output.  But the CIFTI files are small compared to the volume 
files, so I wouldn’t.  Also, if you haven’t already cleaned the data (using 
FIX), you’ll need that file.

--
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<https://maps.google.com/?q=660+South+Euclid+Ave=gmail=g>.  
  Tel: 314-747-6173<tel:(314)%20747-6173>
St. Louis, MO  63110  Email: 
mha...@wustl.edu<mailto:mha...@wustl.edu>

From: redhatw <redh...@gmail.com<mailto:redh...@gmail.com>>
Date: Friday, February 23, 2018 at 8:03 AM
To: "Glasser, Matthew" <glass...@wustl.edu<mailto:glass...@wustl.edu>>
Cc: "Harms, Michael" <mha...@wustl.edu<mailto:mha...@wustl.edu>>, 
"hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>" 
<hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>

Subject: Re: [HCP-Users] what is rfMRI_REST1_LR_Atlas.dtseries.nii

Thanks Michael and Matt.  Does that mean I can delete 
rfMRI_REST1_LR_Atlas.dtseries.nii to save some space?
Ze

On Thu, Feb 22, 2018 at 7:18 PM, Glasser, Matthew 
<glass...@wustl.edu<mailto:glass...@wustl.edu>> wrote:
These are both aligned to the FS_LR spherical surface geographic convention.

Peace,

Matt.

From: 
<hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>>
 on behalf of "Harms, Michael" <mha...@wustl.edu<mailto:mha...@wustl.edu>>
Date: Thursday, February 22, 2018 at 3:54 PM
To: redhatw <redh...@gmail.com<mailto:redh...@gmail.com>>, 
"hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>" 
<hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] what is rfMRI_REST1_LR_Atlas.dtseries.nii


The files without any “registration suffix” came first temporally and were 
generated using “MSMSulc” registration.  When the “MSMAll” registration was 
added later, we then added “MSMAll” as part of the file name.

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<https://maps.google.com/?q=660+South+Euclid+Ave=gmail=g>.  
  Tel: 314-747-6173<tel:(314)%20747-6173>
St. Louis, MO  63110  Email: 
mha...@wustl.edu<mailto:mha...@wustl.edu>

From: 
<hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>>
 on behalf of redhatw <redh...@gmail.com<mailto:redh...@gmail.com>>
Date: Thursday, February 22, 2018 at 2:06 PM
To: "hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>" 
<hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>
Subject: [HCP-Users] what is rfMRI_REST1_LR_Atlas.dtseries.nii

Dear HCPers,
 In the preprocessed data, I found two dtseries data. What is 
rfMRI_REST1_LR_Atlas.dtseries.nii? does it differ from 
rfMRI_REST1_LR_Atlas_MSMall.dtseries.nii only by the MSM align method? Which 
atlas it is based?
Sorry I couldn't find details in the documents.
thanks
Ze

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Re: [HCP-Users] what is rfMRI_REST1_LR_Atlas.dtseries.nii

[Harms, Michael]

I guess, if you never plan on using the MSMSulc registered output from the 
preprocessing output.  But the CIFTI files are small compared to the volume 
files, so I wouldn’t.  Also, if you haven’t already cleaned the data (using 
FIX), you’ll need that file.

--
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: redhatw <redh...@gmail.com>
Date: Friday, February 23, 2018 at 8:03 AM
To: "Glasser, Matthew" <glass...@wustl.edu>
Cc: "Harms, Michael" <mha...@wustl.edu>, "hcp-users@humanconnectome.org" 
<hcp-users@humanconnectome.org>
Subject: Re: [HCP-Users] what is rfMRI_REST1_LR_Atlas.dtseries.nii

Thanks Michael and Matt.  Does that mean I can delete 
rfMRI_REST1_LR_Atlas.dtseries.nii to save some space?
Ze

On Thu, Feb 22, 2018 at 7:18 PM, Glasser, Matthew 
<glass...@wustl.edu<mailto:glass...@wustl.edu>> wrote:
These are both aligned to the FS_LR spherical surface geographic convention.

Peace,

Matt.

From: 
<hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>>
 on behalf of "Harms, Michael" <mha...@wustl.edu<mailto:mha...@wustl.edu>>
Date: Thursday, February 22, 2018 at 3:54 PM
To: redhatw <redh...@gmail.com<mailto:redh...@gmail.com>>, 
"hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>" 
<hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] what is rfMRI_REST1_LR_Atlas.dtseries.nii


The files without any “registration suffix” came first temporally and were 
generated using “MSMSulc” registration.  When the “MSMAll” registration was 
added later, we then added “MSMAll” as part of the file name.

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<https://maps.google.com/?q=660+South+Euclid+Ave=gmail=g>.  
  Tel: 314-747-6173<tel:(314)%20747-6173>
St. Louis, MO  63110  Email: 
mha...@wustl.edu<mailto:mha...@wustl.edu>

From: 
<hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>>
 on behalf of redhatw <redh...@gmail.com<mailto:redh...@gmail.com>>
Date: Thursday, February 22, 2018 at 2:06 PM
To: "hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>" 
<hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>
Subject: [HCP-Users] what is rfMRI_REST1_LR_Atlas.dtseries.nii

Dear HCPers,
 In the preprocessed data, I found two dtseries data. What is 
rfMRI_REST1_LR_Atlas.dtseries.nii? does it differ from 
rfMRI_REST1_LR_Atlas_MSMall.dtseries.nii only by the MSM align method? Which 
atlas it is based?
Sorry I couldn't find details in the documents.
thanks
Ze

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Re: [HCP-Users] what is rfMRI_REST1_LR_Atlas.dtseries.nii

[Harms, Michael]

The files without any “registration suffix” came first temporally and were 
generated using “MSMSulc” registration.  When the “MSMAll” registration was 
added later, we then added “MSMAll” as part of the file name.

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:  on behalf of redhatw 

Date: Thursday, February 22, 2018 at 2:06 PM
To: "hcp-users@humanconnectome.org" 
Subject: [HCP-Users] what is rfMRI_REST1_LR_Atlas.dtseries.nii

Dear HCPers,
 In the preprocessed data, I found two dtseries data. What is 
rfMRI_REST1_LR_Atlas.dtseries.nii? does it differ from 
rfMRI_REST1_LR_Atlas_MSMall.dtseries.nii only by the MSM align method? Which 
atlas it is based?
Sorry I couldn't find details in the documents.
thanks
Ze

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Re: [HCP-Users] Cleaning up intermediate files from the minimal pre-processing pipelines

[Harms, Michael]

Hi,
While the documentation is overall very good, I don’t know if I’d rely on that 
pdf for a detailed list of all the files that we recommend “keeping”.  For 
that, you could download and unpack the packages for a subject with complete 
data (e.g., 100307), and see what you all get.

As a relatively simpler clean-up, I *think* that if you keep the entire 
contents of anything in $subj/T1w and $subj/MNINonLinear that you’ll have most 
of what you need for any further downstream processing, while achieving 
substantial space savings.  i.e., Most of the intermediates in the fMRI 
processing end up in the $subj/$task directories, and I think that any that 
have been deemed important (e.g., .native.func.gii) have been copied to 
$subj/MNINonLinear/Results/$task.  @Matt: Can you confirm that?

e.g,. For a subject from the HCP-Young Adult study, the output from the MPP of 
a single REST run (e.g., $subj/MNINonLinear/Results/rfMRI_REST1_LR) is about 
3.7 GB, whereas the contents of $subj/rfMRI_REST1_LR are 28 GB).

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:  on behalf of "Cook, Philip" 

Date: Wednesday, February 21, 2018 at 11:49 AM
To: "hcp-users@humanconnectome.org" 
Subject: [HCP-Users] Cleaning up intermediate files from the minimal 
pre-processing pipelines

Hi,

I am trying to reduce disk usage after running the HCP minimal pre-processing 
pipelines. I would like to clean up intermediate files but retain things needed 
for ongoing analysis. As a reference I have found a list of file names in

WU-Minn HCP 900 Subjects Data Release: Reference Manual
Appendix III - File Names and Directory Structure for 900 Subjects Data

https://www.humanconnectome.org/storage/app/media/documentation/s900/HCP_S900_Release_Appendix_III.pdf

I would like to retain these and clean up the remainder of the output. Are 
there any scripts available to help with this?


Thanks

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Re: [HCP-Users] setting up hcp protocols in Prisma

[Harms, Michael]

An importable protocol for Siemens is available here:
http://protocols.humanconnectome.org/CCF/


--
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:  on behalf of redhatw 

Date: Thursday, January 18, 2018 at 2:04 PM
To: "hcp-users@humanconnectome.org" 
Subject: [HCP-Users] setting up hcp protocols in Prisma

Dear HCPers,
Are there any recommended documents listing the exact parameters for each 
sequence or the required changes?
Thanks
Ze Wang

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Re: [HCP-Users] about the unrestricted data

[Harms, Michael]

All of the subjects scanned at 3T for the HCP-YA (“Young Adult”) project were 
scanned on the same customized ‘Connectom’ scanner.  Details are in Van Essen 
et al. 2013 and Ugurbil et al. (2013), as well as the Reference Manual 
available online.  There *was* a change in the recon algorithm that affects the 
continuity of the fMRI data to some degree – details about that change are 
available in the Reference Manual as well.

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: 罗 <963619...@qq.com>
Date: Thursday, January 18, 2018 at 3:18 AM
To: "Harms, Michael" <mha...@wustl.edu>, hcp-users 
<hcp-users@humanconnectome.org>
Subject: Re: [HCP-Users] about the unrestricted data

Thanks.

We want to ask you whether there is any information about the scanners. We want 
to know how many scanners in total and how many subjects scanned in each 
scanner. Thank you so much for your help.

Best

Luo


-- Original ----------
From: Harms, Michael <mha...@wustl.edu>
Date: 周四,1月 18,2018 0:14 下午
To: 罗 <963619...@qq.com>, hcp-users <hcp-users@humanconnectome.org>
Subject: Re: [HCP-Users] about the unrestricted data


Hi,
It’s an indication of the “quarter” (Q) of the project that the data was 
acquired.

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> on behalf of 罗 <963619...@qq.com>
Date: Wednesday, January 17, 2018 at 7:41 PM
To: hcp-users <hcp-users@humanconnectome.org>
Subject: [HCP-Users] about the unrestricted data

Dear professors
Can I know what does the third column of the unrestricted behavior data 
'Acquisition' 'Q01～Q13' mean?
Thanks very much!

发自我的iPhone

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Re: [HCP-Users] about the unrestricted data

[Harms, Michael]

Hi,
It’s an indication of the “quarter” (Q) of the project that the data was 
acquired.

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:  on behalf of 罗 <963619...@qq.com>
Date: Wednesday, January 17, 2018 at 7:41 PM
To: hcp-users 
Subject: [HCP-Users] about the unrestricted data

Dear professors
Can I know what does the third column of the unrestricted behavior data 
'Acquisition' 'Q01～Q13' mean?
Thanks very much!

发自我的iPhone

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Re: [HCP-Users] ubuntu

[Harms, Michael]

We suggest using the latest version of the HCP Pipelines with the latest 
version of Workbench.

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:  on behalf of Xiangrui Li 

Organization: OSU
Reply-To: "li.2327" 
Date: Wednesday, December 20, 2017 at 11:33 AM
To: hcp-users 
Subject: [HCP-Users] ubuntu

Dear hcp-users,

We are setting up the HCP pipeline under Linux server, but experience library 
issue with wb_command.

Under Ubuntu 14.10, the latest workbench works fine, but the pipeline needs 
workbench v1.0. When I ran wb_command v1.0, I got following error:

wb_command: error while loading shared libraries: libOSMesa.so.8: cannot open 
shared object file: No such file or directory

It seems we can't find this library for ubuntu 14.10. Did anyone experience the 
similar problem, and is there any workaround? Thanks.
_
Xiangrui Li, Ph.D.
Center for Cognitive and Behavioral Brain Imaging
The Ohio State University
Phone: 614-292-1847

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Re: [HCP-Users] A question about the unprocessed structural data

[Harms, Michael]

What subject are you looking at that has a “T1w_MPR1_reorient_sformMod.nii.gz” 
file?  I’m not seeing that file in our “unprocessed” packages for any of a 
handful of HCP-Young Adult subjects that I just checked…

The other files are as Matt explained, and are also explained in the release 
documentation.

Cheers,
-MH

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

From:  on behalf of "Glasser, Matthew" 

Date: Thursday, December 7, 2017 at 10:13 AM
To: Aaron C , "hcp-users@humanconnectome.org" 

Subject: Re: [HCP-Users] A question about the unprocessed structural data

AFI is data that can be used to compute a B1+ transmit field
BIAS_32CH and BIAS_BC are data that can be used to compute a B1- receive field
FieldMap_Magnitude and FieldMap_Phase can be used to compute a b0 field
The other I don’t remember why we generated, but probably has something to do 
with removing the obliques from the sform.

Peace,

Matt.

From: 
>
 on behalf of Aaron C >
Date: Thursday, December 7, 2017 at 8:01 AM
To: "hcp-users@humanconnectome.org" 
>
Subject: [HCP-Users] A question about the unprocessed structural data


Dear HCP experts,



I have a question about the files in the unprocessed structural data. Could you 
please explain what are the following files in the subject folders? Thank you.



{Subject_ID}.strc_AFI.nii.gz

{Subject_ID}.BIAS_32CH.nii.gz

{Subject_ID}.BIAS_BC.nii.gz

{Subject_ID}.FieldMap_Magnitude.nii.gz

{Subject_ID}.FieldMap_Phase.nii.gz

{Subject_ID}.T1w_MPR1_reorient_sformMod.nii.gz

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Re: [HCP-Users] HCP protocol for Skyra VE11C

[Harms, Michael]

I should also mention that the UK Biobank protocol, which is indeed running on 
Skyras is available here:
http://www.fmrib.ox.ac.uk/ukbiobank/protocol/

That is a VD13 EDX file, but you should be able to import it on a VE11C system.

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> on behalf of "Harms, Michael" 
<mha...@wustl.edu>
Date: Tuesday, November 28, 2017 at 8:49 AM
To: Live Eikenes <live.eike...@ntnu.no>, "hcp-users@humanconnectome.org" 
<hcp-users@humanconnectome.org>
Subject: Re: [HCP-Users] HCP protocol for Skyra VE11C


Hi,
We have a VE11C protocol, but built on a Prisma, that various sites have used a 
starting point available here:
http://protocols.humanconnectome.org/CCF/

You can try importing it, and see what sort of adaptations it makes, due to the 
lower strength gradients of the Skyra.  (The main challenge will be the dMRI, 
which will need to change considerably).

In the near future, we will get around to posting VE11C versions (again, 
designed for a Prisma) of the protocol being used for the HCP-Aging and 
Development studies.

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> on behalf of Live Eikenes 
<live.eike...@ntnu.no>
Date: Tuesday, November 28, 2017 at 3:16 AM
To: "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org>
Subject: [HCP-Users] HCP protocol for Skyra VE11C


Dear HCP users,



I am new to the HCP protocol, but would like to set up a HCP protocol for a 
study that we will perform on our Siemens 3T Skyra (VE11C). If there are some 
HCP protocols out there that has already been set up for Skyra VE11C, we would 
really appreciate if we could have a look at this so that we could use this as 
a starting point for setting up our protocol.



Kind regards,

Live Eikenes.





​

Associate Professor

Department of Circulation and Medical Imaging

Faculty of Medicine and Health Sciences

Norwegian University of Science and Technology

Trondheim

Norway

(live.eike...@ntnu.no)

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Re: [HCP-Users] HCP protocol for Skyra VE11C

[Harms, Michael]

Hi,
We have a VE11C protocol, but built on a Prisma, that various sites have used a 
starting point available here:
http://protocols.humanconnectome.org/CCF/

You can try importing it, and see what sort of adaptations it makes, due to the 
lower strength gradients of the Skyra.  (The main challenge will be the dMRI, 
which will need to change considerably).

In the near future, we will get around to posting VE11C versions (again, 
designed for a Prisma) of the protocol being used for the HCP-Aging and 
Development studies.

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:  on behalf of Live Eikenes 

Date: Tuesday, November 28, 2017 at 3:16 AM
To: "hcp-users@humanconnectome.org" 
Subject: [HCP-Users] HCP protocol for Skyra VE11C


Dear HCP users,



I am new to the HCP protocol, but would like to set up a HCP protocol for a 
study that we will perform on our Siemens 3T Skyra (VE11C). If there are some 
HCP protocols out there that has already been set up for Skyra VE11C, we would 
really appreciate if we could have a look at this so that we could use this as 
a starting point for setting up our protocol.



Kind regards,

Live Eikenes.





​

Associate Professor

Department of Circulation and Medical Imaging

Faculty of Medicine and Health Sciences

Norwegian University of Science and Technology

Trondheim

Norway

(live.eike...@ntnu.no)

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Re: [HCP-Users] FreeSurfer brain volume question

[Harms, Michael]

Hi,
In FS, “Intracranial volume”, renamed to “EstimatedTotalIntraCranialVol” (aka 
“eTIV”) in more recent FS versions, is solely based on the determinant of a 
talairach transform that is internal to FS.  That particular transform does not 
necessarily need to be accurate for FS to generate accurate 
surfaces/segmentations, so we did not QC it.  For that reason, I do not 
recommend using it.

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:  on behalf of Chao Zhang 

Date: Wednesday, November 22, 2017 at 2:25 PM
To: "hcp-users@humanconnectome.org" 
Subject: [HCP-Users] FreeSurfer brain volume question

Hi

We were checking the FS brain volumes and found that out of the 1113 subjects 
for 14 subjects the FS_BrainSeg_Vol is larger than the FS_IntraCranial_Vol (so 
that the column FS_BrainSegVol_eTIV_Ratio is larger than 1). We wonder if this 
is due to some error in calculating either of the two columns (FS_BrainSeg_Vol, 
FS_IntraCranial_Vol)? Thanks!

Best,
Chao







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Re: [HCP-Users] How does the HCP calculate the Cohen d effect in S1200 GroupAvg results?

[Harms, Michael]

Hi,
It’s a standard Cohen’s d calculation -- mean of the individual subject (lev2) 
copes, divided by the std of the individual subject copes

In terms of FSL code, if $mergedcope is the 4D file containing all the 
individual subject cope estimates, the code is just:
  fslmaths $mergedcope -Tmean ${mergedcope}_mean
  fslmaths $mergedcope -Tstd -div ${mergedcope}_mean -recip cohensd

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:  on behalf of 王潇潇 

Date: Tuesday, November 21, 2017 at 7:50 PM
To: hcp-users 
Subject: [HCP-Users] How does the HCP calculate the Cohen d effect in S1200 
GroupAvg results?

Dear HCP users
I've downloaded the S1200 GroupAvg results from the HCP website, and looked up 
the 7-task Cohen d effect results.
Could anyone tell me how the Cohen d effect was calculated?
Was it calculated by Cohen t-test d effect size of the beta value of GLM to 
each task?
Thanks, ~^_^~

--
Wang, Xiaoxiao
Biomedical Engineering Center
University of Science & Technology of China
Hefei, Anhui 230027, P.R.China
Email: wang...@mail.ustc.edu.cn


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Re: [HCP-Users] access to files with realilgnment parameter in language task

[Harms, Michael]

Sure, you can download individual files using REST calls – see previous posts 
in the list for example syntax.  Or, you could access the files via Amazon S3 
and identify the subjects that way.

The Movement_RelativeRMS_mean.txt file that accompanies each fMRI run is the 
mean of the relative (frame-to-frame) movement during the run.  So, no need to 
compute any movement metrics, if you are willing to use that as your measure 
for identifying subjects.

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  63110Email: mha...@wustl.edu

On 11/14/17, 4:46 AM, "hcp-users-boun...@humanconnectome.org on behalf of Cesar 
Caballero"  wrote:

Dear all,

We would like to download low movers only of the language task-fMRI data from 
the entire database. Is it possible to access or download only the text files 
of the realignment parameters in order to compute movement metrics?

Thanks very much,
Cesar


--
Cesar Caballero
MRI engineer
www.bcbl.eu

Legal disclaimer/Aviso legal/Lege-oharra: www.bcbl.eu/legal-disclaimer
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Re: [HCP-Users] mcflirt_acc in ABCD

[Harms, Michael]

Hi,

No.  I believe the switch to using FSL’s ‘mcflirt’ as the “default” motion 
correction was around release 3.15.  I’d suggest you switch to using the latest 
release in the 3.x line, which is 3.22.

For additional context, since the original post referenced the ABCD study, I 
assume that the effect you observed (poor motion correction) was with 2.4 mm 
BOLD data.

We observed that exact same effect on 2.4 mm resolution data when using 
MotionCorrection_FLIRTbased.sh as the motion correction.  The reasons for this 
are not entirely clear, but it is the reason which is why we switched the 
fMRIVolume pipeline to use standard FSL ‘mcflirt’ as the motion correcton with 
release 3.15.

Interestingly, the motion correction is fine when using the legacy 
MotionCorrection_FLIRTbased.sh correction applied to the 2.0 mm HCP BOLD data.

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:  on behalf of Marta Moreno 

Date: Wednesday, November 8, 2017 at 5:23 PM
To: "Glasser, Matthew" 
Cc: "Sanchez, Juan (NYSPI)" , 
"hcp-users@humanconnectome.org" 
Subject: Re: [HCP-Users] mcflirt_acc in ABCD

Is the version 3.4.0 the latest version of the pipelines which default to FSL 
mcflirt?

Thanks,

-L

Sent from my iPhone

On Nov 8, 2017, at 4:55 PM, Glasser, Matthew 
> wrote:
I would use the latest version of the pipelines which default to FSL mcflirt 
because some folks had been seeing this issue.

Peace,

Matt.

From: 
>
 on behalf of "Sanchez, Juan (NYSPI)" 
>
Date: Wednesday, November 8, 2017 at 3:41 PM
To: "hcp-users@humanconnectome.org" 
>, 
"hcp-users@humanconnectome.org" 
>, 
"hcp-users@humanconnectome.org" 
>, 
"hcp-users@humanconnectome.org" 
>, 
"hcp-users@humanconnectome.org" 
>, 
"hcp-users@humanconnectome.org" 
>, 
"hcp-users@humanconnectome.org" 
>
Subject: [HCP-Users] mcflirt_acc in ABCD


Dear all,

We are using pipelines version 3.4. Using the TOPUP distortion correction we 
are getting very good Epi to T1 co-registration, however it seems that there is 
intermittent motion in the processed data  that is not present in the raw data.



This is occuring during MotionCorrection_FLIRTbased.sh



the fMRI_gdc.nii.gz shows no motion between volumes, however the fMRI_mc shows 
motion in the entire brain (around a 1mm shift)  see attached qc png



This error was present using both mcflirt.sh and mcflirt_acc.sh



I used fsl mcflirt with these inputs and the motion error was gone.



Any suggestions on how to edit the mcflirt_acc.sh or why this may be happening?



thanks

Juan Sanchez-Pena

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Re: [HCP-Users] Inaccurate b0 Image from DTIFIT

[Harms, Michael]

Hi,
I don’t think the following is necessarily your problem, but know that the 
simple tensor model is not appropriate at high b-values.  You should either
1)  use the “—kurt” or “—kurtdir" flags which will add a “mean kurtosis” or 
“parallel/perpendicular kurtosis” parameters that can account for 
non-exponential decay
or
2) limit the fitting to just the b=1000 shell (+ b=0’s).

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:  on behalf of "Glasser, Matthew" 

Date: Tuesday, October 31, 2017 at 3:57 PM
To: "Archer,Derek B" 
Cc: "hcp-users@humanconnectome.org" 
Subject: Re: [HCP-Users] Inaccurate b0 Image from DTIFIT

That cannot be the command line as not all the parameters are present.  I agree 
that picture looks incorrect.  Does this happen consistently across subjects?  
What subject is this?

Peace,

Matt.

From: "Archer,Derek B" >
Date: Tuesday, October 31, 2017 at 3:06 PM
To: Matt Glasser >
Subject: RE: [HCP-Users] Inaccurate b0 Image from DTIFIT

Hi Matt –

I am only using one line of code, which is:

dtifit –mask=nodif_brain_mask.nii.gz –bvecs=bvecs –bvals=bvals 
–gradnonlin=grad_dev.nii.gz –out=prefix.

This is the exact line of code I run with data from our group, but instead of 
giving bright ventricles it’s dark.  I’ve attached an image of the Human 
Connectome data.

Derek B. Archer
Postdoctoral Research Fellow
Laboratory for Rehabilitation Neuroscience
(812) 259-0687

From: Glasser, Matthew [mailto:glass...@wustl.edu]
Sent: Tuesday, October 31, 2017 3:08 PM
To: Archer,Derek B >; 
hcp-users@humanconnectome.org
Subject: Re: [HCP-Users] Inaccurate b0 Image from DTIFIT

Please post the two command lines and some example images.

Peace,

Matt.

From: 
>
 on behalf of "Archer,Derek B" >
Date: Tuesday, October 31, 2017 at 11:56 AM
To: "hcp-users@humanconnectome.org" 
>
Subject: [HCP-Users] Inaccurate b0 Image from DTIFIT

Hello all –

I am working on running DTIFIT on human connectome project diffusion data, but 
when I run the code using the gradnonlin option, the b0 image doesn’t look 
correct.

On a typical b0 image, the ventricles should be bright.  The output on all of 
my subjects gives me dark ventricles.  Is this inaccurate? Does DTIFIT work 
corrected with high b-values?

Thanks!
Derek B. Archer
Postdoctoral Research Fellow
Laboratory for Rehabilitation Neuroscience
(812) 259-0687


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Re: [HCP-Users] Test-retest data on AWS?

[Harms, Michael]

Yes, there was a ‘melodic’ failure for the rfMRI_REST1_RL run that we were 
never able to resolve.

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  63110Email: mha...@wustl.edu

On 10/30/17, 8:45 AM, "hcp-users-boun...@humanconnectome.org on behalf of 
Angstadt, Mike"  wrote:

Wanted to follow up and say thanks for this, worked great for figuring out 
where the resources are. In doing so, I discovered that it appears that subject 
341834 is missing some FIX/PostFix resources through this interface. They are 
missing FIX/PostFix for rfMRI_REST1_RL.

The summary csv file available from the project through db.humanconnectome.org 
indicates that this subject completed 99.8% of the resting state data, so I'm 
guessing maybe that led to an issue (though there's another subject with 
partial completion who's data is all present).

-Mike

-Original Message-
From: Hodge, Michael [mailto:hod...@wustl.edu]
Sent: Monday, October 23, 2017 5:29 PM
To: Angstadt, Mike ; Elam, Jennifer ; 
Glasser, Matthew ; hcp-users@humanconnectome.org
Subject: RE: [HCP-Users] Test-retest data on AWS?


Hi Mike,

It looks like the CREST resources haven't been generated for the retest 
project.  We'll work on getting those generated, however you can access the 
files from the pipeline outputs in the retest sessions:

curl -u $USERNAME:$PASSWORD -O 
https://db.humanconnectome.org/data/archive/projects/HCP_Retest/subjects/105923/experiments/105923_3T/resources/Structural_preproc/files/MNINonLinear/T1w.nii.gz

>From the session page in ConnectomeDB, you can use the "Get Files" action to 
>navigate through the file resources to see what files are available, or you 
>can get a list of resources via REST:

curl -u $USERNAME:$PASSWORD 
https://db.humanconnectome.org/data/archive/projects/HCP_Retest/subjects/105923/experiments/105923_3T/resources?format=csv

and then a list of the files in a particular pipeline resource:

curl-u $USERNAME:$PASSWORD 
https://db.humanconnectome.org/data/archive/projects/HCP_Retest/subjects/105923/experiments/105923_3T/resources/Structural_preproc/files?format=csv

Regards,

Mike

-Original Message-
From: hcp-users-boun...@humanconnectome.org 
[mailto:hcp-users-boun...@humanconnectome.org] On Behalf Of Angstadt, Mike
Sent: Monday, October 23, 2017 1:22 PM
To: Elam, Jennifer ; Glasser, Matthew ; 
hcp-users@humanconnectome.org
Subject: Re: [HCP-Users] Test-retest data on AWS?

Jenn and Matt,

Thanks for the pointer to this. Unfortunately I can't seem to get it working. 
It works fine on HCP_1200 data, but when replacing that with HCP_Retest and 
checking the subject IDs from those in the retest set, it always just gets an 
HTML response with the message "Unable to find file."

This is an example of what I'm trying:
curl -u $USERNAME:$PASSWORD -O 
https://db.humanconnectome.org/data/archive/projects/HCP_Retest/subjects/105923/experiments/105923_CREST/resources/105923_CREST/files/MNINonLinear/T1w.nii.gz

Just in case, I tried it with HCP_retest as well, but then I get an "Unable to 
identify project" HTML response, so I'm assuming there's some other difference 
in the subsequent path between HCP_1200 and HCP_Retest. Any ideas?

-Mike

From: Elam, Jennifer [mailto:e...@wustl.edu]
Sent: Friday, October 20, 2017 5:36 PM
To: Glasser, Matthew ; Angstadt, Mike 
; hcp-users@humanconnectome.org
Subject: Re: [HCP-Users] Test-retest data on AWS?

Hi Mike,
You can follow the instructions here about using the REST API: 
https://wiki.humanconnectome.org/display/PublicData/How+To+Access+Subject+Data+via+REST
Just change the project in the URLs to HCP_Retest (not HCP_1200). Otherwise the 
directory structure for Retest data is the same as for the main dataset.

I'll ask the team about getting the Retest data into our AWS S3 bucket as well 
in the longer term, but I'm not sure what the timeline would be on that.

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
tel:314-362-9387
mailto:e...@wustl.edu
http://www.humanconnectome.org/


From: mailto:hcp-users-boun...@humanconnectome.org 
 on behalf of Glasser, Matthew 

Sent: Friday, October 20, 2017 3:36:19 PM
To: Angstadt, Mike; mailto:hcp-users@humanconnectome.org
Subject: Re: [HCP-Users] Test-retest data on AWS?

I think you can use the REST interface to get a few 

Re: [HCP-Users] about the hcp data

[Harms, Michael]

Yes, all 1113 subjects with MR data in the S1200 release are available to use.

There are a small number of issues that we discovered in the S500 (and S900) 
release data after the initial release, which were fixed as part of those 
subjects’ data for the S1200 release.
See here for the details:
https://wiki.humanconnectome.org/display/PublicData/HCP+Data+Release+Updates%3A+Known+Issues+and+Planned+fixes

If you downloaded *all* subjects from the S1200 release (including the data for 
subjects initially released in the S500 release), then you don’t need to worry 
about that particular issue.  (Although that same page details a small handful 
of minor issues with the S1200 release itself, that I don’t think we’ve had a 
chance to resolve yet).

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> on behalf of 罗 <963619...@qq.com>
Date: Tuesday, October 24, 2017 at 9:23 AM
To: "Harms, Michael" <mha...@wustl.edu>
Cc: hcp-users <hcp-users@humanconnectome.org>
Subject: Re: [HCP-Users] about the hcp data

I'm sorry.
I question is that whether all the 1113 subjects with MRI are available for our 
research, because some s500 subjects are not included in our brought S500 
connectome box.
Thanks.


------ 原始邮件 --
发件人: "Harms, Michael" <mha...@wustl.edu>;
发送时间: 2017年10月24日(星期二) 21:50
收件人: "罗" <963619...@qq.com>;"hcp-users" <hcp-users@humanconnectome.org>;
主题: Re: [HCP-Users] about the  hcp data


Hi,
Can you rephrase your question?  Are you asking if the S1200 data release is 
available for purchase as part of the “Connectome in a Box” program?

If so, the answer is yes:
https://store.humanconnectome.org/data/

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> on behalf of 罗 <963619...@qq.com>
Date: Tuesday, October 24, 2017 at 8:38 AM
To: hcp-users <hcp-users@humanconnectome.org>
Subject: [HCP-Users] about the hcp data

Dear professors：
We bought the S500 data before, and downloaded the s1200 data as a package, and 
the were 1090 subjects available totally, but we found that there were 1113 
subjects with MRI in the HCP website, so we downloaded the other 23 subjects, 
respectively.
I wander if all those 1113 subjects are available, indiscriminately.
Thanks!

发自我的iPhone

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Re: [HCP-Users] about the hcp data

[Harms, Michael]

Hi,
Can you rephrase your question?  Are you asking if the S1200 data release is 
available for purchase as part of the “Connectome in a Box” program?

If so, the answer is yes:
https://store.humanconnectome.org/data/

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:  on behalf of 罗 <963619...@qq.com>
Date: Tuesday, October 24, 2017 at 8:38 AM
To: hcp-users 
Subject: [HCP-Users] about the hcp data

Dear professors：
We bought the S500 data before, and downloaded the s1200 data as a package, and 
the were 1090 subjects available totally, but we found that there were 1113 
subjects with MRI in the HCP website, so we downloaded the other 23 subjects, 
respectively.
I wander if all those 1113 subjects are available, indiscriminately.
Thanks!

发自我的iPhone

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Re: [HCP-Users] netmats prediction of fluid intelligence

[Harms, Michael]

Germane to this discussion is that using the same methodology, but a different 
sample of subjects, the same Yale group has recently reported that the 
correlation of predicted gF (from netmats) and observed gF was r=0.22.

https://www.ncbi.nlm.nih.gov/pubmed/28968754

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  63110Email: mha...@wustl.edu

On 10/7/17, 2:43 PM, "hcp-users-boun...@humanconnectome.org on behalf of Nina 
de Lacy"  wrote:

This is a very interesting thread and discussion and many of the observations 
conform with ongoing work I'm doing in children/adolescents which generally 
suggests that predicting intelligence measures is very challenging using 
connectivity measures, after including confounders within multivariate 
frameworks. I personally wonder not only about confounding effects, but also 
the difficulty of working with neuropsychological 'intelligence' measures 
designed for other purposes than perhaps some of what we are trying to get at. 
As well, I would raise the question of our samples, which most/much of the time 
in neuroimaging rarely include individuals with lower IQs, therefore distorting 
the distribution.

All that said, what I really joined in for was to ask Julien if he could 
comment more on what he meant by highlighting that part of the effect obtained 
in the FInn study was due to the "specific subject sample" used. Was this due 
to certain characteristics of the smaller subject sample? I of course respect 
this may be content germane to an as yet unpublished paper you may not want to 
share in detail :)

Nina


On Sat, 7 Oct 2017, Julien Dubois wrote:

>   Julien, when you say the method still has predictive value in the large 
> sample 'without confounds', do you mean without removing confounds or after 
> deconfounding? It's also not
>   clear to me whether the scores the Ma study reported are deconfounded 
> or not, but I guess they are not. If one is interested in the added value of 
> fMRI predicting cognition (my
>   case), it makes sense to be conservative, so I would be interested in 
> knowing whether there's something left in the deconfounded space.
>
>
> Sorry, my phrasing wasn't clear. I mean that I obtain similar results to the 
> Megatrawl and to the Ma poster, WITHOUT deconfounding as performed in the 
> Megatrawl. I will let you know how it
> looks once I use the same deconfounding as in the Megatrawl, i.e.: 
> "Prediction takes place after removing sex, age, age^2 , sex*age, sex*age^2 , 
> brain & head size (as estimated by
> FreeSurfer), overall head motion (a summation over all timepoints of 
> timepoint-to-timepoint relative head motion) and acquisition date as 
> confounds (the last of these is actually the
> “acquisition quarter”, which is useful to include because there was a slight 
> change in rfMRI reconstruction code during the third acquisition 
> year-quarter; in future we will instead use
> the actual reconstruction code version as the confound)."
> - Julien
>
> ___HCP-Users mailing 
> listHCP-Users@humanconnectome.orghttp://lists.humanconnectome.org/mailman/listinfo/hcp-users
>
>
>

This message and any attached files might contain confidential information 
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Re: [HCP-Users] dtifit, bedpostx, voxel-wise correction of dMRI gradients

[Harms, Michael]

Also, if you fitting a simple tensor model via ‘dtifit’, you may want to 
consider limiting yourself to just the b=1000 shell (+ b=0’s), because the 
simple tensor model breaks down for high b-values.  There should be a post in 
the archive about this.

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:  on behalf of "Glasser, Matthew" 

Date: Monday, October 9, 2017 at 5:22 PM
To: Athanasia Metoki , 
"hcp-users@humanconnectome.org" 
Subject: Re: [HCP-Users] dtifit, bedpostx, voxel-wise correction of dMRI 
gradients

I believe both binaries will use the grad_dev to perform the correct described 
in the bvals and bvecs in a voxelwise manner.

Peace,

Matt.

From: 
>
 on behalf of Athanasia Metoki 
>
Date: Monday, October 9, 2017 at 3:29 PM
To: "hcp-users@humanconnectome.org" 
>
Subject: [HCP-Users] dtifit, bedpostx, voxel-wise correction of dMRI gradients

Dear HCP experts,

I would like to analyze some HCP diffusion data. I am using the preprocessed 
HCP data from the 900 subjects release.

I would like to do dtifit and run bedpostx and then tractography (I know dtifit 
is unrelated to the latter bt I'm mentioning it because I would like to be 
consistent in my analysis).

Two questions:

a) I found this dtifit command in the HCP mail list archives:
dtifit -k data.nii.gz -r bvecs -b bvals -m nodif_brain_mask.nii.gz -o >>> 
$OUTDIR/$SUBJECT/dti --gradnonlin=grad_dev.nii.gz

But also I found this code for voxel-wise correction of dMRI gradients:
https://www.humanconnectome.org/storage/app/media/documentation/data_release/Q1_Release_Appendix_II.pdf

When I run the dtifit command above do I use the new_bvals and new_bvecs?

Hence do I run:
dtifit -k data.nii.gz -r new_bvecs -b new_bvals -m nodif_brain_mask.nii.gz -o 
>>> $OUTDIR/$SUBJECT/dti --gradnonlin=grad_dev.nii.gz

or does the "--gradnonlin=grad_dev.nii.gz" in the command does the same job as 
the code I found in the Q1_Release_Appendix_II.pdf?

b) When I run bedpostx_gpu do I need to use the new_bvals in a script like this:
bedpostx_gpu T1w/Diffusion -n 3 -b 3000 -model 3 -g —rician

Thank you.

Best,
Athanasia Metoki
Psychology Doctoral Student - Brain and Cognitive Sciences Program
Cognitive Neuroscience Laboratory
Temple University
Department of Psychology
1701 N 13th St.
Philadelphia, PA 19122
Email: athanasia.met...@temple.edu

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Re: [HCP-Users] netmats prediction of fluid intelligence

[Harms, Michael]

In the context of the long resting state runs that we have available, I would 
argue that throwing in additional possible confounds is the appropriate thing 
to do.  Are you suggesting that sex, age, age^2, sex*age, sex*age^2, brain 
size, head size, and average motion shouldn’t all be included?

Regardless, r = 0.21 (without confounds in the MegaTrawl) is a long way from 
the r = 0.5 prediction in Finn et al.

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:  on behalf of Thomas Yeo 

Date: Thursday, October 5, 2017 at 10:01 PM
To: "Glasser, Matthew" 
Cc: "hcp-users@humanconnectome.org" 
Subject: Re: [HCP-Users] netmats prediction of fluid intelligence

Certainly one difference is that HCP (i.e., Steve) tends to take the more 
conservative approach of regressing a *lot* of potential confounds, which tends 
to result in a lower prediction values. You can see that without confound 
regression, Steve's prediction is 0.21 versus 0.06.

Regards,
Thomas

On Fri, Oct 6, 2017 at 1:44 AM, Glasser, Matthew 
> wrote:
Perhaps there is an issue related to data clean up or alignment of brain areas 
across subjects.  The Finn study does not appear to have followed the 
recommended approach to either.

Peace,

Matt.

From: 
>
 on behalf of Benjamin Garzon 
>
Date: Thursday, October 5, 2017 at 1:39 PM
To: "hcp-users@humanconnectome.org" 
>
Subject: [HCP-Users] netmats prediction of fluid intelligence

Dear HCP experts,

I'm trying to reconcile the MegaTrawl prediction of fluid intelligence 
(PMAT24_A_CR)

https://db.humanconnectome.org/megatrawl/3T_HCP820_MSMAll_d200_ts2/megatrawl_1/sm203/index.html

(which shows r = 0.06 between predicted and measured scores)

with the Finn 2015 study

https://www.nature.com/neuro/journal/v18/n11/full/nn.4135.html

claiming an r = 0.5 correlation between predicted and measured scores. In the 
article they used a subset of the HCP data (126 subjects), but the measure of 
fluid intelligence is the same one. What can explain the considerable 
difference? As far as I can see the article did not address confounding, but 
even in that case r = 0.21 for MegaTrawl, which is still far from 0.5. And this 
considering that the model used in the article is a much simpler one than the 
MegaTrawl elastic net regressor.

I've been trying to predict fluid intelligence in an independent sample with 
300 subjects and a netmats + confounds model does not perform better than a 
confounds-only model, more in agreement with the MegaTrawl results.

In the Smith 2015 paper

http://www.nature.com/neuro/journal/v18/n11/full/nn.4125.html

the found mode of covariation with the netmats data correlates with fluid 
intelligence with r = 0.38.

Should I conclude from the Megatrawl analysis (as well as from my own) that the 
single measure of fluid intelligence is not reliable enough to be predicted 
based on connectome data, or am I missing something from the Finn paper?

I would be happy to read people 's thoughts about this topic, in view of the 
disparate results in the literature.

Best regards,

Benjamín Garzón, PhD
Department of Neurobiology, Care Sciences and Society
Aging Research Center | 
113
 30 Stockholm | Gävlegatan 
16
benjamin.gar...@ki.se | 
www.ki-su-arc.se
__
Karolinska Institutet – a medical university



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The materials in 

Re: [HCP-Users] Mean and variance normalization

[Harms, Michael]

I’m not sure what you are looking for, beyond what is in the FAQ.
For a given voxel/grayordinate/parcel, if
M = mean_over_time
S = std_over_time

and X(t) is your time-series

then demeaning is just: X(t) - M
and variance normalization is: (X(t) - M)/S

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: hercp <he...@uw.edu>
Date: Thursday, October 5, 2017 at 3:39 PM
To: "Harms, Michael" <mha...@wustl.edu>
Subject: Re: [HCP-Users] Mean and variance normalization

Hi Michael,

Thanks for the input.  Are you aware of any utility that does the demeaning, 
variance normalization and concatenation.  Jenn Elam suggested FAQ #3 on the 
HCP-Users FAQ.  Would this be also your preference.  Is there a reference or 
mathematical definitions for these functions (other than the obvious ones), so 
I can do a mathematical comparison between the two approaches?

Heracles Panagiotides, PhD


From: Harms, Michael
Sent: Thursday, October 05, 2017 12:13 PM
To: Glasser, Matthew ; hercp ; HUMAN CONNECTOME
Subject: Re: [HCP-Users] Mean and variance normalization


Re (2) (expanding on Matt’s response): Demeaning and variance normalizing a 
parcellated timeseries (or equivalently the time series for a single ROI), and 
then concatenating those, is not the same as demeaning and variance normalizing 
the dense time series, concatenating those, and then parcellating.  That’s not 
to say that the former isn’t sensible, but it *is* a different operation.  If 
it was me, before I adopted the former, I’d run some analyses both ways, and 
compare the results to see if there are any appreciable differences.

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> on behalf of "Glasser, Matthew" 
<glass...@wustl.edu>
Date: Thursday, October 5, 2017 at 1:19 PM
To: hercp <he...@uw.edu>, HUMAN CONNECTOME <hcp-users@humanconnectome.org>
Subject: Re: [HCP-Users] Mean and variance normalization


  1.  Yes
  2.  I haven’t tried it on parcellated timeseries, but suspect that would be 
fine too.
Matt.

From: <hcp-users-boun...@humanconnectome.org> on behalf of hercp <he...@uw.edu>
Date: Thursday, October 5, 2017 at 2:12 PM
To: HUMAN CONNECTOME <hcp-users@humanconnectome.org>
Subject: [HCP-Users] Mean and variance normalization

I am extracting time series from regions of interest.  Matt Glasser suggested 
that I mean/variance-correct and concatenate the RL and LR phase encoded time 
series.  I still have a couple of questions.

1.  Is the concatenation over time?  If so, doesn’t this introduce temporal 
discontinuity?  Am I understanding the concatenation correctly?

2.  Would the outcome be equivalent whether I do the preprocessing to the 
original rfMRI file  OR to the ROI extracted time series and why?

Thank you in advance for any suggestions you may offer.

Heracles Panagiotides, PhD

Heracles Panagiotides, PhD



From: Elam, Jennifer
Sent: Wednesday, October 04, 2017 2:50 PM
To: hercp
Subject: Re: [HCP-Users] Fw: rfMRI data files


Hi Heracles,

From what I've heard from others who have more experience, I would do the 
preprocessing and concatenating prior to extracting the ROI vector. The big 
caveat is that I don't actually do any processing, etc. myself as my expertise 
is in a different field. So, if you want to be sure you should ask your 
question on the list and get a real expert answer there.



Cheers,

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<http://www.humanconnectome.org/>


From: hercp <he...@uw.edu>
Sent: Wednesday, October 4, 2017 4:12:39 PM
To: Elam, Jennifer
Subject: Re: [HCP-Users] Fw: rfMRI data files

Hi Jenn,

Thank you so much the reply and pointing at FAQ #3.

I am wondering if we are talking about the same thing when referring to “time 
series”.   Perhaps, if I tell you what I have done so far, my question will be 
more clear:  I have defined a ROI and extracted a time series from the original 
data file; the time series is a single vector corresponding to the mean lever 
of activity of that ROI .  S

Re: [HCP-Users] Mean and variance normalization

[Harms, Michael]

Re (2) (expanding on Matt’s response): Demeaning and variance normalizing a 
parcellated timeseries (or equivalently the time series for a single ROI), and 
then concatenating those, is not the same as demeaning and variance normalizing 
the dense time series, concatenating those, and then parcellating.  That’s not 
to say that the former isn’t sensible, but it *is* a different operation.  If 
it was me, before I adopted the former, I’d run some analyses both ways, and 
compare the results to see if there are any appreciable differences.

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:  on behalf of "Glasser, Matthew" 

Date: Thursday, October 5, 2017 at 1:19 PM
To: hercp , HUMAN CONNECTOME 
Subject: Re: [HCP-Users] Mean and variance normalization


  1.  Yes
  2.  I haven’t tried it on parcellated timeseries, but suspect that would be 
fine too.
Matt.

From: 
>
 on behalf of hercp >
Date: Thursday, October 5, 2017 at 2:12 PM
To: HUMAN CONNECTOME 
>
Subject: [HCP-Users] Mean and variance normalization

I am extracting time series from regions of interest.  Matt Glasser suggested 
that I mean/variance-correct and concatenate the RL and LR phase encoded time 
series.  I still have a couple of questions.

1.  Is the concatenation over time?  If so, doesn’t this introduce temporal 
discontinuity?  Am I understanding the concatenation correctly?

2.  Would the outcome be equivalent whether I do the preprocessing to the 
original rfMRI file  OR to the ROI extracted time series and why?

Thank you in advance for any suggestions you may offer.

Heracles Panagiotides, PhD

Heracles Panagiotides, PhD


From: Elam, Jennifer
Sent: Wednesday, October 04, 2017 2:50 PM
To: hercp
Subject: Re: [HCP-Users] Fw: rfMRI data files


Hi Heracles,

From what I've heard from others who have more experience, I would do the 
preprocessing and concatenating prior to extracting the ROI vector. The big 
caveat is that I don't actually do any processing, etc. myself as my expertise 
is in a different field. So, if you want to be sure you should ask your 
question on the list and get a real expert answer there.



Cheers,

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: hercp >
Sent: Wednesday, October 4, 2017 4:12:39 PM
To: Elam, Jennifer
Subject: Re: [HCP-Users] Fw: rfMRI data files

Hi Jenn,

Thank you so much the reply and pointing at FAQ #3.

I am wondering if we are talking about the same thing when referring to “time 
series”.   Perhaps, if I tell you what I have done so far, my question will be 
more clear:  I have defined a ROI and extracted a time series from the original 
data file; the time series is a single vector corresponding to the mean lever 
of activity of that ROI .  So, do I apply the mean and variance normalization 
to this vector and then concatenate the vectors, or do I do all this 
(preprocessing and concatenating) prior to extracting the ROI vector time 
series.   (As a side note, I can do all this vector preprocessing in Matlab.)  
Would these two approaches be equivalent?

Thank you very much for being so helpful,
Heracles Panagiotides, PhD


From: Elam, Jennifer
Sent: Wednesday, October 04, 2017 1:30 PM
To: hercp ; HUMAN CONNECTOME
Subject: Re: [HCP-Users] Fw: rfMRI data files


Hi Heracles,

FAQ #3 on the HCP-Users 
FAQ might 
help you do what Matt is suggesting.



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 hercp >
Sent: Wednesday, October 4, 2017 1:32:38 PM
To: HUMAN CONNECTOME
Subject: [HCP-Users] Fw: rfMRI data files

Does 

Re: [HCP-Users] DWI in CCF Prisma protocol

[Harms, Michael]

And it is all handled automatically for the dMRI data in the HCP Pipeline.

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:  on behalf of Keith Jamison 

Date: Friday, September 29, 2017 at 3:38 PM
To: Jeffrey Spielberg 
Cc: "hcp-users@humanconnectome.org" 
Subject: Re: [HCP-Users] DWI in CCF Prisma protocol

That's right.

-Keith

On Fri, Sep 29, 2017 at 4:33 PM, Jeffrey Spielberg 
> wrote:
One further question: it looks like there no separate AP/PA fieldmaps for dMRI 
in the CCF protocol, whereas there are SE fieldmaps for resting - is that 
correct?  If so, is this because the b0 images from the dMRI can be used for 
this purpose (e.g., in topup)?

Best,
Jeff

--
Jeffrey M. Spielberg, Ph.D.
Assistant Professor, Clinical Science
Department of Psychological and Brain Sciences
University of Delaware
Newark, DE 19716

Office: 307 McKinly Laboratory
Lab:Suite 405 Wolf Hall
Phone:302.831.7078
Email:  
j...@udel.edu>
Website:  http://sites.udel.edu/jmsp/

On Sep 27, 2017, at 3:37 PM, Keith Jamison 
>>
 wrote:

To clarify, hopefully:

"Vector set 1"
dMRI_dir98_AP = 46 b=1500, 46 b=3000, 6 b=0
dMRI_dir98_PA = exact same as dir98_AP, but phase encode=P>>A

"Vector set 2"
dMRI_dir99_AP = 47 b=1500, 46 b=3000, 6 b=0
dMRI_dir99_PA = exact same as dir99_AP, but phase encode=P>>A

So in total, we have 93 unique directions the b=1500 shell, and 92 unique 
directions for the b=3000 shell, plus 12 interspersed b=0.  Each direction is 
acquired with phase-encode A>>P and then again with P>>A.

For some added info, see attached screenshot, which is page 22 of the dMRI 
screenshot PDF distributed with the CCF protocol.

-Keith


On Wed, Sep 27, 2017 at 3:06 PM, Keith Jamison 
>>
 wrote:
We essentially split the ~197 direction in half, and the two halves can't have 
the exact same number of directions due to how they are stored on the scanner, 
so "part 1" is 98 directions and "part 2 is 99.  each is then collected both AP 
and PA.  FYI, each scan is actually 92 diffusion volumes plus 6 or 7 
non-diffusion "b=0"

This is probably available elsewhere under the CCF documentation, but the DWI 
scans are adapted from here:
https://www.humanconnectome.org/study-hcp-lifespan-pilot/phase1b-pilot-parameters

The way the sequence runs on the scanner, we set a single "maximum" b-value 
(b=3000), by which each of the diffusion vectors in the table is scaled.  The 
entries that norm to 1 are b=3000, and the vectors that norm to 0.707 are 
b=1500.  Note: 0.707 = sqrt(0.5).  For whatever reason, this is how the scanner 
handles vector magnitudes.

-Keith


On Wed, Sep 27, 2017 at 2:29 PM, Glasser, Matthew 
>>
 wrote:
In general one wants to get as many gradient directions as possible.
Perhaps Mike knows the answer to your other question.

Matt.

On 9/28/17, 2:59 AM, 
"hcp-users-boun...@humanconnectome.org>
 on behalf of
Jeffrey Spielberg" 
>
 on behalf of
jspielb...@psych.udel.edu>>
 wrote:

>Hi all,
>
>I¹m interested in setting up a diffusion protocol similar to the CCF
>protocol and have two questions.  First, what¹s the difference between
>the dir98 and dir99 acquisitions (beyond having different vectors)?  It
>looks like both sample on 2 shells, use the same b-values, and have about
>50:50 vectors on each shell, so I¹m not clear on why both are needed.
>
>Second, I was playing around with the Caruyer q-space sampling tool and
>noticed that the output differs from the vectors provided as part of the
>CCF protocol.  Specifically, for dir98, they match for 1 shell, but the
>vector magnitudes in the other shell have been shortened to .7071.  My
>guess is that this is necessary to tell the scanner to use the second
>b-value (e.g., 1500).  Is that correct?
>
>Best,
>Jeff
>

Re: [HCP-Users] HCP Longitudinal Pipeline

[Harms, Michael]

Hi Tim,
We plan on creating at least a structural pipeline that will support the use of 
FreeSurfer’s longitudinal processing.  Unfortunately, there is no beta version, 
and I don’t want to speculate at this time on a timeline.

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:  on behalf of Timothy Hendrickson 

Date: Wednesday, September 20, 2017 at 12:47 PM
To: "hcp-users@humanconnectome.org" 
Subject: [HCP-Users] HCP Longitudinal Pipeline

HCP experts,
I did some research on the HCP users list and if I missed this question I 
apologize.

I am curious what the timeline for a HCP longitudinal processing pipeline 
public release?
Is there possibly a beta version that I may gain access to in order to use?
-Tim


Timothy Hendrickson
Department of Psychiatry
University of Minnesota
Bioinformatics and Computational Biology M.S. Candidate
Office: 612-624-6441
Mobile: 507-259-3434 (texts okay)

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Re: [HCP-Users] clustering of subcortical structures - flipping and smoothing

[Harms, Michael]

@Matt: The minimally preprocessed subcortical data in the CIFTI was smoothed 
with a 2 mm FWHM “parcel-constrained” kernel, right?  (i.e, the smoothing does 
not cross boundaries of subcortical structures).  In that case, if they were to 
then further smooth the subcortical data, but smooth across subcortical 
boundaries (as they proposed), wouldn’t that potentially lead to some odd 
effects at the boundaries?  [I don’t know if you caught that part of their 
proposal…]

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:  on behalf of "Glasser, Matthew" 

Date: Friday, September 1, 2017 at 1:50 PM
To: Daria Jensen , "hcp-users@humanconnectome.org" 

Cc: Miriam Klein-Flugge 
Subject: Re: [HCP-Users] clustering of subcortical structures - flipping and 
smoothing

1.  That command for the surface is not quite what you are looking for.  For 
the surface, the left and right hemisphere vertices are already in register 
(meaning that vertices with the same number will be in the anatomically 
corresponding location).  You would need to translate between the CIFTI indices 
and the GIFTI surface indices to take advantage of that however.  The easiest 
way to do this would be to use wb_command -cifti-separate and the you can do 
operations on the resulting GIFTI files.
2.  I think if you fed wb_command -volume-resample (on the NIFTI files that 
result from wb_command -cifti-separate) a matrix with the form:

-1 0 0 0
 0 1 0 0
 0 0 1 0
 0 0 0 1

This might accomplish the left right flip in the volume, however Tim should 
confirm if he agrees.

Matt.

From: 
>
 on behalf of Daria Jensen >
Date: Friday, September 1, 2017 at 11:47 AM
To: "hcp-users@humanconnectome.org" 
>
Cc: Miriam Klein-Flugge 
>
Subject: [HCP-Users] clustering of subcortical structures - flipping and 
smoothing


Dear HCP list,

We’re interested in clustering of subcortical structures in the HCP 
resting-state fMRI data and have two questions regarding the pre-processing:

1. We’re looking for a way to flip the data of the two hemispheres, including 
subcortical structures, It seems that an option exist to do his for the surface 
(-surface-flip-lr). Which procedure would you recommend for flipping the 
hemispheres of the whole brain, including the volume data?

2. Moreover, we’re thinking of applying  wb_command -cifti-smoothing to the 
individual dtseries files with a fwhm of 3mm for subcortical structures to make 
the clustering more robust. Our approach would be to smooth across subcortical 
boundaries. What would be your advice? Has anyone got advice with regards to 
the kernel size? And finally, why do we need to indicate a left and right 
surface file in the command? How are these files used the smoothing process 
(and do they have to correspond to the surface from each individual)?


Thank's a lot!

Daria Jensen

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Re: [HCP-Users] intracranial volume < brain volume!

[Harms, Michael]

IntraCranial volume is based entirely on the determinant of the talairch 
transform.  We don’t check the accuracy of that transform because it doesn’t 
even need to be accurate for FreeSurfer to generate correct surfaces and 
segmentations.

So, frankly, I wouldn’t use the IntraCranial volume estimate.

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:  on behalf of Clas Linnman 

Date: Thursday, August 31, 2017 at 1:07 PM
To: "hcp-users@humanconnectome.org" 
Subject: [HCP-Users] intracranial volume < brain volume!

Hi,

I noticed that the intracranial volume (FS_IntraCranial_Vol) is lower than 
total brain volume (FS_BrainSeg_Vol) in the following subjects:

104012

109830

118124

121820

139637

140420

163836

190132

202820

204521

208428

561242

701535

867468


checked one subject, structural looks good:
PastedGraphic-1.tiff

Any ideas as to what might be going on?

best
Clas




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Re: [HCP-Users] motion parameters

[Harms, Michael]

Hi,
We don’t have a single average head motion for each subject stored as a 
variable in ConnectomeDB.  You can find the average frame-to-frame motion for 
each fMRI run (rfMRI or tfMR) in the Movement_RelativeRMS_mean.txt file for 
that run.

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:  on behalf of Joelle Zimmermann 

Date: Tuesday, August 29, 2017 at 5:16 PM
To: "hcp-users@humanconnectome.org" 
Subject: [HCP-Users] motion parameters

Hi HCPers,
I was wondering where I can find an average head motion parameter for each 
subject?
Thanks,
Joelle

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Re: [HCP-Users] dMRI: Error while running "eddy_postproc.sh"

[Harms, Michael]

See the --combine-data-flag in DiffPreprocPipeline.sh
The default value of 1 is intended for acquisitions in which you have acquired 
the full vector table with both polarities, which isn’t how you acquired your 
data.
In your case, you’ll need to use a value of ‘2’ for that flag.

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  63110Email: mha...@wustl.edu

On 8/25/17, 11:23 AM, "hcp-users-boun...@humanconnectome.org on behalf of 
Sang-Young Kim"  wrote:

Dear HCP users:

I have another problem for running Diffusion Preprocessing pipeline. After eddy 
current correction, the pipeline proceeded to run eddy_postproc.sh. But I got 
error message as follow:

**
Traceback (most recent call last):
  File "/Users/sang-young/projects/Pipelines/global/scripts/average_bvecs.py", 
line 296, in 
overlap2)
  File "/Users/sang-young/projects/Pipelines/global/scripts/average_bvecs.py", 
line 36, in main
bvals1 = loadFile(bvals1file, 1, [-1])
  File "/Users/sang-young/projects/Pipelines/global/scripts/average_bvecs.py", 
line 127, in loadFile
raise ValueError('Wrong number of dimensions: {0}'.format(filename))
ValueError: Wrong number of dimensions: 
/Volumes/LaCieMac3TB/HIV_HCP_pipeline/Data/30067/Diffusion/eddy/Pos.bval
**

Above message came up while running the command (see below) in 
"eddy_postproc.sh".
*
${globalscriptsdir}/average_bvecs.py ${eddydir}/Pos.bval 
${eddydir}/Pos_rotated.bvec ${eddydir}/Neg.bval ${eddydir}/Neg_rotated.bvec 
${datadir}/avg_data ${eddydir}/Pos_SeriesVolNum.txt 
${eddydir}/Neg_SeriesVolNum.txt
*

Our dMRI data has been acquired with diffusion direction of 113 (AP direction) 
and b0 image were acquired with opposite direction (e.g., PA) for topup. So I 
have 1x113 bval and 3x113 bvec for DWI AP data, and 1x1 bval (e.g., 0 value) 
and 3x1 bvec (also 0 values) for DWI PA data.

Something is wrong in bval and/or bvec file?

It will be greatly appreciated if you can help me.

Thanks in advance.

Sang-Young Kim, Ph.D.

Postdoctoral Research Fellow
Department of Radiology, University of Pittsburgh



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Re: [HCP-Users] residuals fmri

[Harms, Michael]

There is no “modeling” of the rfMRI data, and thus no residuals (unlike the 
task data).

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:  on behalf of Francesco 

Date: Wednesday, August 23, 2017 at 12:48 PM
To: "hcp-users@humanconnectome.org" 
Subject: [HCP-Users] residuals fmri

Hi everyone
I'm using Afni 3dclustsim and I was looking for the appropriate residuals files 
in the resting state fmri directories to run smoothness estimation.
Do someone know where those are?
thanks a lot

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Re: [HCP-Users] Offline vs. online gradient nonlinearity correction

[Harms, Michael]

FYI: We are switching over to using ‘dcm2niix’, which is Chris Rorden’s newer, 
actively maintained conversion tool.

--
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:  on behalf of "Glasser, Matthew" 

Date: Friday, August 4, 2017 at 1:21 PM
To: Sandhitsu Das , "hcp-users@humanconnectome.org" 

Subject: Re: [HCP-Users] Offline vs. online gradient nonlinearity correction


  1.  Yes
  2.  We use dcm2nii.
  3.  Probably
I would use offline so you are sure that all of your images are being corrected 
the same way and have control over how the resampling is being done (i.e. not 
adding blurring from trilinear interpolation).

Peace,

Matt.

From: 
>
 on behalf of Sandhitsu Das >
Date: Friday, August 4, 2017 at 12:06 PM
To: "hcp-users@humanconnectome.org" 
>
Subject: [HCP-Users] Offline vs. online gradient nonlinearity correction

This is following up on a thread here

https://www.mail-archive.com/hcp-users@humanconnectome.org/msg03502.html

We are evaluating online vs. offline correction on our 3T Simens Prisma system 
using a phantom. I have three questions:

1) Looks like the gradunwarp script is agnostic to the sequence type. Does this 
mean that we should use it the same way for any sequence (including structural 
or functional) as a first preprocesing step ?

2) The gradunwarp script takes nifti input. My understanding is that the 
coefficient file defines the known nonlinearity profile using scanner 
coordinates. Does this mean the output may be different when using nifti files 
produced by different dicom converters which can potentially change the 
coordinate system in some way ?

3) Please see the two attached screenshots that compare online vs. offline 
corrections. The two images show a middle coronal slice and and a terminal one 
respectively. Bottom shows original, top left shows online corrected, top right 
shows offline corrected. While in the middle slice it looks like offline and 
online produces pretty much the same output (although we didn't quantitatively 
evaluate yet), there is something funny going on at the terminal slices. 
Artifact of boundary condition assumptions ?

Any help is much appreciated. We can't move on with our studies until we figure 
out the right way to do this as this is (presumably) the very first 
pre-processing step.

Thanks,
Sandy

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Re: [HCP-Users] Follow-up to: Obtaining the MNI coordinates of cluster peaks in the melodic_IC.dscalar.nii ICA maps

[Harms, Michael]

Creating an “average-surface” is fine, and we in fact to that and provide it as 
part of our “group-average” data (available for download from ConnectomDB).

But, those average surfaces are just a “back-drop” for overlaying/visualizing 
the metric/cifti data, and aren’t intended to be used as a substrate for 
extracting coordinates.

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:  on behalf of Claude Bajada 

Date: Thursday, August 3, 2017 at 9:06 AM
To: "hcp-users@humanconnectome.org" 
Subject: [HCP-Users] Follow-up to: Obtaining the MNI coordinates of cluster 
peaks in the melodic_IC.dscalar.nii ICA maps


Hi all,

I am starting a new thread because while my question is related to the one ask, 
it is tangential.

Can I confirm that what you mean by not averaging surfaces is that one should 
not average the vertex points across gifti surfaces to create a so-called 
"average surface"

Can I ask then, is averaging the data associated with vertices from individual 
subjects and plotting the result on a template surface (eg colin or a just 
using an individual as a template) also problematic?
Regards,
Claude
On 03.08.2017 02:05, Timothy Coalson wrote:
On Wed, Aug 2, 2017 at 6:02 PM, James Morrow 
> wrote:
Thanks Tim and Matt for the detailed responses.

I agree that mapping to volumes is sub-optimal. Our goal is to identify coords 
to be used as targets for brain stimulation with TMS. We need MNI coords for 
neuronavigation. Given the extent of the TMS field, we have some tolerance for 
imprecisions in the mapping.

I see.  We generally get asked these questions in the context of fMRI analysis, 
hence our reluctance.

How does the neuronavigation go from MNI coordinates to subject coordinates, do 
you happen to have a reasonable T1w MRI scan of your subjects?  I don't know 
how big the TMS field is, and I hadn't looked at the distance from subject to 
group average surfaces before, but in one of the HCP subjects, I got a maximum 
of 2cm distance from the group average surface (using midthickness surfaces), 
which occurred in a few specific locations, while 90% of the surface was 1cm 
distance or less.

Can I clarify – was the ICA run on the volumes and then later mapped on to 
surfaces, or was it performed on the surface data? If the former, are the 
original volumetric results for the ICA of each subject available anywhere in 
.nii format?

Cheers,
James

James Morrow
Research assistant
Brain & Mental Health Laboratory

Monash Institute of Cognitive and Clinical Neurosciences
School of Psychological Sciences
Monash University
c/o MBI, 770 Blackburn Road
Clayton VIC 3800
Australia

T: 03 9902 9768
E: james.mor...@monash.edu
www.med.monash.edu.au/psych/bmh/

[mage removed by sender.]
[mage removed by sender.]

On 3 August 2017 at 07:00, Timothy Coalson 
> wrote:
As Matt said, "MNI coordinates" of functionally-aligned cortical surface 
features don't have much meaning, similar to how T1w-aligned MNI space volumes 
don't have good cortical functional alignment (except in a few low-variability 
regions).  We have shown that group average surface coordinates do not follow 
the MNI cortical ribbon (see attached image that simply shows the average white 
and pial contours on top of the MNI nonlinear template).  The ICA maps 
themselves are also more informative than just the vertices at their peaks.

Surface group results should not be turned into volumetric files, group average 
surfaces do not have much folding left in them, and as such they do not match 
the MNI template anymore - this is due to folding incompatibilities between 
subjects, but also due to using functional surface registration instead of 
folding patterns.  Using the individual surfaces to map to the volume and then 
averaging across them would spread your data out just as badly as doing 
volume-based analysis of cortex, so this is also highly discouraged.

Despite strongly advising you not to do what you outlined, I will tell you what 
commands you would need.  The -cifti-extrema command will output a map with 1s 
and -1s at each local extrema.  The surface it uses is for neighbor information 
and distance computation - this isn't as critical as coordinates are, as it 
merely sets the maximum possible density of extrema (what you could get from a 
very noisy map).  You will need to 

Re: [HCP-Users] CIFTI and MATLAB

[Harms, Michael]

Yes, unless you want to deal with the NaNs.

--
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  63110Email: mha...@wustl.edu

On 7/31/17, 9:58 AM, "hcp-users-boun...@humanconnectome.org on behalf of Claude 
Bajada"  wrote:

Dear all,

Is this post still valid re: cifti in matlab?

https://wiki.humanconnectome.org/display/PublicData/HCP+Users+FAQ#HCPUsersFAQ-2.HowdoyougetCIFTIfilesintoMATLAB?

Is cifti-matlab still only recommended for MEG data?

https://github.com/Washington-University/cifti-matlab

Claude





Forschungszentrum Juelich GmbH
52425 Juelich
Sitz der Gesellschaft: Juelich
Eingetragen im Handelsregister des Amtsgerichts Dueren Nr. HR B 3498
Vorsitzender des Aufsichtsrats: MinDir Dr. Karl Eugen Huthmacher
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Re: [HCP-Users] signal to noise ratio

[Harms, Michael]

Sure, we have data, but I'm not sure how useful it would be to you without 
getting into various details.  e.g., What type of preprocessing are you 
intending?  Does it include any denoising?  How are you going to define your 
spatial mask?  Etc...


How exactly were you thinking of quantifying the temporal SNR?


cheers,

-MH


From: hcp-users-boun...@humanconnectome.org 
 on behalf of Sebastien Hetu 

Sent: Wednesday, July 19, 2017 2:54:09 PM
To: hcp-users@humanconnectome.org
Subject: [HCP-Users] signal to noise ratio

Hi,

We are trying to use the HCP lifespan rfMRI sequences on our PRISMA. Is there 
any data on the temporal SNR that can be expected (for single subject) using 
these rfMRI sequences that we could use to compare to our own acquisitions.

Best regards

Seb


Sébastien Hétu Ph.D.
Postdoctoral Fellow
Human Neuroimaging Laboratory
Virginia Tech Carilion Research Institute
Virginia, USA

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Re: [HCP-Users] Statistical comparison of whole brain (surface "voxels" + subcortical / cerebellar voxels) connectivity between two explicitly defined voxels

[Harms, Michael]

Hi,
A couple extensions to Tim’s recipe.

PALM has a “transposedata” option, so you can always transpose at the PALM 
stage if you prefer to not explicitly create a transposed CIFTI file.

PALM can indeed accept CIFTI files “as is”, *if* you want to do permutation on 
the max statistic across grayordinates.  If you want to do TFCE, you currently 
do indeed need to separate the CIFTI first.  We have an example of that 
particular approach in the Task fMRI practical of the HCP Course.  (Jenn can 
hopefully provide an update on when we anticipate being able to get the 
materials from the latest course online).

Similar to Tim, I’m not exactly sure what you’re intending to permute.  Are you 
going to compute a dense connectome *for each subject*?  Then you could take 
the difference between the “A” and “B” maps for each subject, and use those as 
input to PALM to test whether that difference is consistently different from 0 
across subjects (using sign-flippings).  As Tim suggests, it would likely be 
much easier to compute a parcellated connectome for each subject instead.

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: 
>
 on behalf of Timothy Coalson >
Date: Monday, July 17, 2017 at 7:52 PM
To: "Regner, Michael" 
>
Cc: "hcp-users@humanconnectome.org" 
>
Subject: Re: [HCP-Users] Statistical comparison of whole brain (surface 
"voxels" + subcortical / cerebellar voxels) connectivity between two explicitly 
defined voxels

On Mon, Jul 17, 2017 at 6:21 PM, Regner, Michael 
> wrote:
Hello Matt and HCP Community,

Thank you for the helpful e-mail and words of encouragement. We are very 
encouraged by the data / results we can view in the Connectome Workbench; 
however, statistical analysis has proved challenging.

Just to reiterate what we are attempting to do:  we are hoping to compare 
whole-brain (all ~91k brainordinates) connectivity between two predefined 
brainordinates to determine the areas of the brain in which there is a 
statistically significant difference in connectivity.  We intend to eventually 
extend this analysis to compare two different ROIs (sets or masks of 
brainordinates); however, for simplicity’s sake (and to prove to our PI that we 
can do this) we would like to perform this comparison first between two voxels 
/ vertices (henceforth brainordinates “A” and “B”).

The general pipeline (using the 33 GB resting state dense connectome CIFTI file 
as our starting point) is as follows step-by-step:

1.Reduce the resting state dense connectivity CIFT file (91k x 91k) into 
two separate CIFTI files, which are NOT dense.

They would in fact still be dense, just on one dimension of the matrix, rather 
than both.  Read this if you haven't yet (and let me know if it doesn't explain 
it well enough):

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


  These CIFTI files (“A” and “B”) would contain the whole-brain connectivity 
data from two a priori specified brainordinates (“A” and “B”).  By size, these 
intuitively should be around 91k in number of brainordinates.  We are not 
exactly sure how to best achieve this in wb_command… would “CIFTI-parcellate” 
do the trick?

Honestly, you might as well skip straight to using ROIs, especially if they are 
from an existing parcellation, as it may actually be easier (and more closely 
relates to the commands you would need to use).  When you want to compare 
connectivity of two ROIs, it is highly advisable to get the ROI's average 
timeseries first, and then do a fresh correlation to the timeseries - this 
removes a large amount of noise-based variance from the denominator (among 
other things).

So, if you are in fact using an existing parcellation in cifti dlabel format, 
you would want to do -cifti-parcellate on a dtseries file, and then you can do 
-cifti-cross-correlation with the dtseries file and this new parcellated file 
(ptseries).  If you want to view the per-parcel dense maps in workbench, you 
should have the ptseries file as the first input, and name the output ending in 
".pdconn.nii".  To arrange them similarly to a dscalar file, which is probably 
what PALM expects, you can use -cifti-transpose to turn it into a .dpconn.nii 
file.

If you want to use arbitrary ROI files (which can overlap), then you instead 
need to use -cifti-average-roi-correlation on the dtseries file.  Note that 
this also 

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: 
>
 on behalf of David Hartman 
>
Date: Monday, July 17, 2017 at 12:21 PM
To: "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 
> 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



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Re: [HCP-Users] diffusion data merge pipeline

[Harms, Michael]

Hi,
Is there a particular reason that you can’t provide all the dMRI scans at once, 
and let the pipeline handle the merging for you?
If you process each dMRI run separately, then the individual runs will not be 
in optimal alignment.  (You would be relying on the registration of each run to 
the T1, rather than registering the dMRI directly to each other as part of 
‘eddy’).

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: 
>
 on behalf of Yeun Kim >
Date: Monday, July 17, 2017 at 1:32 PM
To: "Glasser, Matthew" >
Cc: "hcp-users@humanconnectome.org" 
>
Subject: Re: [HCP-Users] diffusion data merge pipeline

I am using the following function (and is looped through the pairs of unique 
sets of gradient tables (i.e. loops twice for dir99 and dir98):
${HCPPIPEDIR}/DiffusionPreprocessing/DiffPreprocPipeline.sh  \
  --posData="{posData}" \
  --negData="{negData}"  \
  --path="{path}" \
  --subject="{subject}"  \
  --echospacing="{echospacing}"  \
  --PEdir={PEdir}  \
  --gdcoeffs="NONE"  \
  --dwiname="{dwiname}"  \
  --printcom=""'

Where:
$posData = diffusion data in the positive direction
$negData = diffusion data in the negative direction
$path = output directory path
$echospacing = echospacing
$PEdir = 2
$dwiname = i.e. Diffusion_dir-98_run-01


FYI: I'm using HCPPipelines v3.17.

-

Technical details:

I run ${HCPPIPEDIR}/DiffusionPreprocessing/DiffPreprocPipeline.sh in a Docker 
container with the following python code. It is looped through the pairs of 
unique sets of gradient tables (i.e. loops twice for dir99 and dir98) and set 
to process in parallel:

dwi_stage_dict = OrderedDict([("DiffusionPreprocessing", 
partial(run_diffusion_processsing,

 posData=pos,

 negData=neg,

 path=args.output_dir,

 subject="sub-%s" % subject_label,

 echospacing=echospacing,

 PEdir=PEdir,

 gdcoeffs="NONE",

 dwiname=dwiname,

 n_cpus=args.n_cpus))])
for stage, stage_func in dwi_stage_dict.iteritems():
if stage in args.stages:
Process(target=stage_func).start()

On Mon, Jul 17, 2017 at 11:15 AM, Glasser, Matthew 
> wrote:
The pipeline is capable of doing the merge for you if you want.  Can you post 
how you called the diffusion pipeline?

Peace,

Matt.

From: Yeun Kim >
Date: Monday, July 17, 2017 at 1:12 PM
To: Matt Glasser >
Cc: "hcp-users@humanconnectome.org" 
>
Subject: Re: [HCP-Users] diffusion data merge pipeline

When I run DiffusionPreprocessing, I make the --dwiname=DWIName specific to the 
diffusion scan (i.e. DWIName= Diffusion_dir-98_run-01) to prevent files from 
being overwritten.
I end up with:
${StudyFolder}/${Subject}/T1w/Diffusion_dir-98_run-01/data.nii.gz
${StudyFolder}/${Subject}/T1w/Diffusion_dir-99_run-01/data.nii.gz

I would like to combine the two data.nii.gz files.

On Mon, Jul 17, 2017 at 10:58 AM, Glasser, Matthew 
> wrote:
Look for the ${StudyFolder}/${Subject}/T1w/Diffusion/data.nii.gz file.

Peace,

Matt.

From: 
>
 on behalf of Yeun Kim >
Date: Monday, July 17, 2017 at 12:56 PM
To: 

Re: [HCP-Users] Questions about reconstruction speed of Multi-band EPI sequence in LSCMRR

[Harms, Michael]

Hi,
You want the high-end recon computer with the GPU.

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: HMZ <hmz...@163.com<mailto:hmz...@163.com>>
Date: Monday, July 17, 2017 at 8:20 AM
To: Michael Harms <mha...@wustl.edu<mailto:mha...@wustl.edu>>
Cc: "Glasser, Matthew" <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>>, 葛鉴桥 
<g...@pku.edu.cn<mailto:g...@pku.edu.cn>>, Jia-Hong Gao 
<j...@pku.edu.cn<mailto:j...@pku.edu.cn>>, 门卫伟 
<w...@pku.edu.cn<mailto:w...@pku.edu.cn>>
Subject: Re: [HCP-Users] Questions about reconstruction speed of Multi-band EPI 
sequence in LSCMRR

Dear HCP team,

Thanks a lot for your suggestion and help.

I have tested the reconstruction speed with both head coils. Our protocol is 
similar to "LSCMRR_3T_printout_2014.08.15", similar matrix, voxel size, slice, 
and TR, etc. The reconstruction speed is 1.1s per volume for 64CH and 0.9s for 
32CH, which are slower than TR(0.73s).

We just have a chance to upgrade our SIEMENS Prisma from VD13D to VE11C which 
was recommended by SIEMENS, and we will upgrade the reconstruction computer at 
the same time. SIEMENS provide us two kinds of MR workplace as follows (image 
reconstruction computer), standard and high-end, respectively. I would like to 
know which kind of recontruction workplace as follows are you using? If 
neither, did you modify the reconstruction computer yourselves?

 I would be very grateful if I can have more detail information about your 
prisma reconstruction specifications, so that we can compare and decide what 
kind of MR workplace is suitable for us to run HCP style protocol.

A. The standard Computer HW upgrade kit for the syngo MR Workplace includes:
1. a syngo MR Workplace with 1 x Intel Xeon Quad Core CPU / 3.6 GHz, 8 GB 
RAM,
2. one 300 GB system hard disk,
3. one 300 GB hard disk for image data and
4. one CD-R/DVD-R drive for image storage.


B. The high-end image reconstruction computer has the following specifications:

≥ 2x Intel W5690 (hexacore) processors 3.46 GHz

≥ 128 GB Main Memory (RAM)

≥ 750 GB Hard disk for raw data

≥ 100 GB Hard disk for system software

Tesla GPGPU

 By the way, the following is the acquisition workplace offered by SIEMENS. I 
would like to know if it is OK for HCP style acquisition? Thanks a lot!
The Computer HW upgrade kit for the syngo Acquisition Workplace includes:
1. a syngo Acquisition Workplace with 1 x Intel Xeon Quad Core CPU / 3.6 
GHz, 32 GB RAM,
2. one 300 GB system hard disk,
3. one 300 GB hard disk for database,
4. one 300 GB hard disk for image data and
5. one CD-R/DVD-R drive for image storage,

Any relevant information and idea would help a lot. Thank you very much!

Looking forward to your reply.

--
Meizhen Han
PhD Candidate
Center for MRI Research
Peking University
Beijing, China

At 2017-07-01 00:03:22, "Harms, Michael" 
<mha...@wustl.edu<mailto:mha...@wustl.edu>> wrote:

We have a more recent (and importable) protocol available here that I would 
suggest you use as a starting point:
http://protocols.humanconnectome.org/CCF/

Your Prisma should already come with GPUs.  Are you using the 64 channel coil?  
That will be a slower recon than the 32 ch coil, but I believe the recon still 
shouldn’t get too far behind even with the 64 ch coil.

Try importing the VD13D version of the protocol available above, and compare 
the recon times for both the 32 and 64 ch coils, if you have both available.

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<mailto:mha...@wustl.edu>

From: 
<hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>>
 on behalf of "Glasser, Matthew" <glass...@wustl.edu<mailto:glass...@wustl.edu>>
Date: Friday, June 30, 2017 at 5:52 AM
To: HMZ <hmz...@163.com<mailto:hmz...@163.com>>, 
"hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>" 
<hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>
Cc: 葛鉴桥 <g...@pku.edu.cn<mailto:g...@pku.edu.cn>>, 周思中 
<zhou.sizh...@163.com<mailto:zhou.sizh...@163.com>>
Subject: Re: [HCP-Users] Questions ab

Re: [HCP-Users] CMRR vs MGH multiband/SMS sequences

[Harms, Michael]

What banding artifact are you referring to?  Could you post a picture to a 
sharing site?

thx
--
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: 
>
 on behalf of A R >
Date: Friday, July 14, 2017 at 8:25 AM
To: "Juranek, Jenifer" 
>
Cc: "HCP-Users@humanconnectome.org" 
>
Subject: Re: [HCP-Users] CMRR vs MGH multiband/SMS sequences

In my experience they both suffer from the same banding artifact affecting the 
middle 25% of slices.


On Jul 11, 2017, at 5:34 PM, Juranek, Jenifer 
> wrote:

Just curious if anyone is aware of head-to-head comparisons of CMRR and MGH 
MB/SMS sequences?
Someone recently mentioned to me that “the general consensus is that MGH 
outperforms CMRR”.
Is there a “general consensus” in the research community on this issue? Any 
differences between dMRI and fMRI applications?
I’m interested in using an HCP-style acquisition protocol for a 5yr study about 
to start…from what I can tell, CMRR MB sequences have been selected across the 
board for HCP-style studies currently funded by NIH.
Does anyone have any thoughts they can share?
Many Thanks,
Jenifer
~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~
Jenifer Juranek, PhD
Associate Professor
Department of Pediatrics
UTHealth
Houston, TX 77030
713.500.8233


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Re: [HCP-Users] CMRR vs MGH multiband/SMS sequences

[Harms, Michael]

Essa Yacoub from CMRR sent me the following for distribution to the HCP-User 
list on this issue:


"A lot of investigators have done comparisons between the sequences. Most of 
this data is not public, although there are some sites that have published 
things - e.g. 
https://practicalfmri.blogspot.com/2016/06/starting-points-for-sms-epi-at-3-t-part.html#more

It should be noted that there are many different variants of the sequences from 
WIP to Product to MGH-c2p and CMRR-c2p -and- that it is difficult to directly 
compare the sequences as they have different options/features. There are many 
differences from acquisition to image reconstruction for both fMRI and 
diffusion. That said, I have yet to see any feedback to suggest that the MGH 
sequence (or other) outperforms the CMRR sequence, let alone a consensus. We 
get this type of question all of the time and what we tell people is to run the 
comparison for their particular protocol and metrics of interest and decide for 
themselves which sequence better fits their needs.


--
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: 
>
 on behalf of Mahmoud >
Date: Tuesday, July 11, 2017 at 8:18 PM
To: "Glasser, Matthew" >
Cc: "HCP-Users@humanconnectome.org" 
>
Subject: Re: [HCP-Users] CMRR vs MGH multiband/SMS sequences

And please let us know if you figured it out which sequence is better.

Thank you,
Mahmoud

On Tue, Jul 11, 2017 at 4:44 PM, Glasser, Matthew 
> wrote:
I am not part of such a consensus.  I don’t know if there have been rigorous 
comparison of the two sequences or by what metrics it is being asserted that 
MGH outperforms CMRR.  Perhaps you could ask your source for this 
recommendation why they say that?

Peace,

Matt.

From: 
>
 on behalf of "Juranek, Jenifer" 
>
Date: Tuesday, July 11, 2017 at 10:34 AM
To: "HCP-Users@humanconnectome.org" 
>
Subject: [HCP-Users] CMRR vs MGH multiband/SMS sequences

Just curious if anyone is aware of head-to-head comparisons of CMRR and MGH 
MB/SMS sequences?
Someone recently mentioned to me that “the general consensus is that MGH 
outperforms CMRR”.
Is there a “general consensus” in the research community on this issue? Any 
differences between dMRI and fMRI applications?
I’m interested in using an HCP-style acquisition protocol for a 5yr study about 
to start…from what I can tell, CMRR MB sequences have been selected across the 
board for HCP-style studies currently funded by NIH.
Does anyone have any thoughts they can share?
Many Thanks,
Jenifer
~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~
Jenifer Juranek, PhD
Associate Professor
Department of Pediatrics
UTHealth
Houston, TX 77030
713.500.8233


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Re: [HCP-Users] Diffusion Preprocessing Error/Bug

[Harms, Michael]

Which version of FSL are you using?  I believe that the 
eddy_unwarped_images.eddy_rotated_bvecs file will be created by the version of 
‘eddy’ that comes with the newest FSL (5.0.10), but if you are using FSL 5.0.9, 
you needed to install the “eddy patch” to get that functionality.

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: 
>
 on behalf of Timothy Hendrickson >
Date: Thursday, July 6, 2017 at 3:24 PM
To: "hcp-users@humanconnectome.org" 
>
Subject: [HCP-Users] Diffusion Preprocessing Error/Bug

Hello,

I am having trouble running the diffusion preprocessing. Once the processing 
gets to eddy_postproc.sh I get the following error: awk: cmd. line:1: fatal: 
cannot open file 
`/home/lnpi15-raid3/cgilmore-data-lnpi15/272_CENC/49769/Diffusion/eddy/eddy_unwarped_images.eddy_rotated_bvecs.
 The error is pretty straightforward, but I cannot figure out why the diffusion 
preprocessing scripts are not generating the 
eddy_unwarped_images.eddy_rotated_bvecs file. I notice that there is a file 
named eddy_unwarped_images.eddy_parameters. Is this similar to the rotated bvec 
file?

Thanks!

-Tim

Timothy Hendrickson
Department of Psychiatry
University of Minnesota
Bioinformatics and Computational Biology M.S. Candidate
Office: 612-624-6441
Mobile: 507-259-3434 (texts okay)

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Re: [HCP-Users] Convert a .dscalar.nii to multiple nifti files?

[Harms, Michael]

In that case, I believe what you need is -cifti-separate

--
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: Xavier Guell Paradis <xavie...@mit.edu<mailto:xavie...@mit.edu>>
Date: Wednesday, July 5, 2017 at 11:07 AM
To: Michael Harms <mha...@wustl.edu<mailto:mha...@wustl.edu>>, 
"hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>" 
<hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>
Subject: RE: [HCP-Users] Convert a .dscalar.nii to multiple nifti files?

Thank you very much for the reply.
The .dscalar.nii file that I am interesting in converting to multiple nifti 
files contains only cerebellar data, which is not surface information.
Would there be any way of converting that to multiple nifti files?

Thank you very much,
Xavier.
____
From: Harms, Michael [mha...@wustl.edu<mailto:mha...@wustl.edu>]
Sent: Wednesday, July 05, 2017 12:02 PM
To: Xavier Guell Paradis; 
hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>
Subject: Re: [HCP-Users] Convert a .dscalar.nii to multiple nifti files?


Hi,
You can’t represent the surface information in a .dscalar.nii via a nifti file.
The -cifti-convert -to-nifti command exists for converting a CIFTI to a 
“fake”-NIFTI file for use in external tools/analyses that can be conducted on a 
per-grayordinate basis (i.e., without any regard to spatial information).

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<mailto:mha...@wustl.edu>

From: 
<hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>>
 on behalf of Xavier Guell Paradis <xavie...@mit.edu<mailto:xavie...@mit.edu>>
Date: Wednesday, July 5, 2017 at 10:55 AM
To: "hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>" 
<hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>
Subject: [HCP-Users] Convert a .dscalar.nii to multiple nifti files?

Dear HCP experts,
Is it possible to convert a .dscalar.nii which contains 4 different maps to 4 
different nifti files (one for each map)?
I have tried -cifti-convert -to-nifti but the output was a very strange nifti 
file.

Thank you very much,
Xavier.

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immediately notify the sender via telephone or return mail.


The materials in this message are private and may contain Protected Healthcare 
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Re: [HCP-Users] Maximal number of unrelated subjects that have complete 3T resting state and task data

[Harms, Michael]

Hi,
No plans to provide such a subject group in the interface, but it is easy 
enough to compute such a group using the variables that we have provided in the 
database.

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: 
>
 on behalf of David Hofmann 
>
Date: Friday, June 30, 2017 at 6:04 PM
To: hcp-users 
>
Subject: [HCP-Users] Maximal number of unrelated subjects that have complete 3T 
resting state and task data

Hi all,

since the final data release is now out, I was wondering what the maximal 
number of unrelated subjects is, that have complete 3T resting state and task 
data and if there will be an update on the 100 subjects that can be downloaded 
so far soon?

greetings

David

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Re: [HCP-Users] Questions about reconstruction speed of Multi-band EPI sequence in LSCMRR

[Harms, Michael]

We have a more recent (and importable) protocol available here that I would 
suggest you use as a starting point:
http://protocols.humanconnectome.org/CCF/

Your Prisma should already come with GPUs.  Are you using the 64 channel coil?  
That will be a slower recon than the 32 ch coil, but I believe the recon still 
shouldn’t get too far behind even with the 64 ch coil.

Try importing the VD13D version of the protocol available above, and compare 
the recon times for both the 32 and 64 ch coils, if you have both available.

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: 
>
 on behalf of "Glasser, Matthew" >
Date: Friday, June 30, 2017 at 5:52 AM
To: HMZ >, 
"hcp-users@humanconnectome.org" 
>
Cc: 葛鉴桥 >, 周思中 
>
Subject: Re: [HCP-Users] Questions about reconstruction speed of Multi-band EPI 
sequence in LSCMRR

I believe we use GPUs to speed this up.

Peace,

Matt.

From: 
>
 on behalf of HMZ >
Date: Thursday, June 29, 2017 at 11:23 PM
To: "hcp-users@humanconnectome.org" 
>
Cc: 葛鉴桥 >, 周思中 
>
Subject: [HCP-Users] Questions about reconstruction speed of Multi-band EPI 
sequence in LSCMRR

Dear HCP experts,

This is Meizhen Han from Center for MRI research at Peking University in China. 
I'm writing for seeking a solution for the problem we encountered during the 
application of HCP MRI sequence on our recent research.

We tried a similar protocol as "LSCMRR_3T_printout_2014.08.15" on our prisma 
(software format is VD13D), while the reconstruction is quite slow. When 
several continuous Multi-band EPI are used, if the former Multi-band EPI hasn't 
started to reconstruct and the latter sequence is ready to go, the 
reconstruction of the former sequence will be skipped with an error message 
(Something like “Image reconstruction is failed.” )

I noticed the software format of prisma in CMRR is also VD13D, so I'm wondering 
whether you have encountered this kind of reconstruction problem. If yes, how 
did you deal with it? If no, what is the speed of your reconstruction computer 
andcan we have the model type of it, so that we can compare and improve ours.

Any relevant information and idea would help a lot. Thank you very much!

Looking forward to your reply.


--
Meizhen Han
PhD Candidate
Center for MRI Research
Peking University
Beijing, China







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Re: [HCP-Users] mapping of ROIs to networks - "posted question"

[Harms, Michael]

We’ve run InfoMap on them, but I haven’t had a chance to review them.

--
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: 
>
 on behalf of David Hartman 
>
Date: Friday, June 30, 2017 at 8:34 AM
To: "hcp-users@humanconnectome.org" 
>
Subject: [HCP-Users] mapping of ROIs to networks - "posted question"

Hi,

Regarding the parcellation of the cortex (as in the paper: A multi-modal 
parcellation of human cerebral cortex, Glasser et al.) the cortex is broken 
down into 360 ROIs.

Do you know how these ROIs might be labeled in a way that makes it possible to 
assign them to standard networks (like visual, executive, default. etc.)?

Thank you,
David Hartman

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Re: [HCP-Users] Structural Protocol

[Harms, Michael]

Sorry, but we don’t have the funding or resources to support hosting projects 
that aren’t officially under the umbrella of a “Connectomes Related to Disease” 
project.

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: Rachel Woodall 
<rachel.wood...@york.ac.uk<mailto:rachel.wood...@york.ac.uk>>
Date: Friday, June 23, 2017 at 4:02 AM
To: Michael Harms <mha...@wustl.edu<mailto:mha...@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] Structural Protocol

Thanks Michael.
Do you think my study would be eligible for registration with the HCP?  If so, 
how would I go about setting this up?

Best wishes,
Rachel

On 22 June 2017 at 18:46, Harms, Michael 
<mha...@wustl.edu<mailto:mha...@wustl.edu>> wrote:

Hi,
Check out the various “Connectomes Related to Disease” projects on the 
re-designed humanconnectome.org<http://humanconnectome.org> website.  A couple 
of them involve vision loss, and several involve individuals over the age of 
60.  And of course the HCP-Aging project will include individuals over 60 as 
well.

Data from all these projects will be distributed eventually via the Connectome 
Coordination Facility at WU.

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<tel:(314)%20747-6173>
St. Louis, MO  63110Email: mha...@wustl.edu<mailto:mha...@wustl.edu>

From: Rachel Woodall 
<rachel.wood...@york.ac.uk<mailto:rachel.wood...@york.ac.uk>>
Date: Thursday, June 22, 2017 at 4:06 AM
To: Michael Harms <mha...@wustl.edu<mailto:mha...@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] Structural Protocol

Thanks for this Michael.
I'm acquiring structural scans on elderly patients with vision loss and 
age-matched sighted controls (age range 60-80+).  Are you aware of any other 
groups who are acquiring similar data sets of visually impaired and sighted 
controls of this age?  It might be useful to talk about sharing data as 
recruiting age-matched sighted controls is actually more difficult than 
recruiting patients.

Best wishes,
Rachel

On 21 June 2017 at 14:33, Harms, Michael 
<mha...@wustl.edu<mailto:mha...@wustl.edu>> wrote:

Hi,
You can find an importable protocol here:
http://protocols.humanconnectome.org/CCF/

The protocols that we are using for the HCP-Aging/Development projects are 
highly similar, but include a few additions (e.g., switch to 
navigator-corrected anatomicals; addition of PCASL scan).  Those will be posted 
once we can organize the documentation (sometime after OHBM).

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<tel:(314)%20747-6173>
St. Louis, MO  63110Email: mha...@wustl.edu<mailto:mha...@wustl.edu>

From: 
<hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>>
 on behalf of Rachel Woodall 
<rachel.wood...@york.ac.uk<mailto:rachel.wood...@york.ac.uk>>
Date: Wednesday, June 21, 2017 at 3:42 AM
To: "hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>" 
<hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>
Subject: [HCP-Users] Structural Protocol

Hello,

Is the Pheonix ZIP file available for the structural protocol on a 3T Siemens 
Prisma?

Many thanks,
Rachel

--
Rachel Woodall

PhD Student
University of York
Department of Psychology
YO10 5DD

Email: rachel.wood...@york.ac.uk<mailto:rachel.wood...@york.ac.uk>
Phone: 01904 567613


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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 conte

Re: [HCP-Users] Structural Protocol

[Harms, Michael]

Hi,
Check out the various “Connectomes Related to Disease” projects on the 
re-designed humanconnectome.org website.  A couple of them involve vision loss, 
and several involve individuals over the age of 60.  And of course the 
HCP-Aging project will include individuals over 60 as well.

Data from all these projects will be distributed eventually via the Connectome 
Coordination Facility at WU.

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: Rachel Woodall 
<rachel.wood...@york.ac.uk<mailto:rachel.wood...@york.ac.uk>>
Date: Thursday, June 22, 2017 at 4:06 AM
To: Michael Harms <mha...@wustl.edu<mailto:mha...@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] Structural Protocol

Thanks for this Michael.
I'm acquiring structural scans on elderly patients with vision loss and 
age-matched sighted controls (age range 60-80+).  Are you aware of any other 
groups who are acquiring similar data sets of visually impaired and sighted 
controls of this age?  It might be useful to talk about sharing data as 
recruiting age-matched sighted controls is actually more difficult than 
recruiting patients.

Best wishes,
Rachel

On 21 June 2017 at 14:33, Harms, Michael 
<mha...@wustl.edu<mailto:mha...@wustl.edu>> wrote:

Hi,
You can find an importable protocol here:
http://protocols.humanconnectome.org/CCF/

The protocols that we are using for the HCP-Aging/Development projects are 
highly similar, but include a few additions (e.g., switch to 
navigator-corrected anatomicals; addition of PCASL scan).  Those will be posted 
once we can organize the documentation (sometime after OHBM).

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<tel:(314)%20747-6173>
St. Louis, MO  63110Email: mha...@wustl.edu<mailto:mha...@wustl.edu>

From: 
<hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>>
 on behalf of Rachel Woodall 
<rachel.wood...@york.ac.uk<mailto:rachel.wood...@york.ac.uk>>
Date: Wednesday, June 21, 2017 at 3:42 AM
To: "hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>" 
<hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>
Subject: [HCP-Users] Structural Protocol

Hello,

Is the Pheonix ZIP file available for the structural protocol on a 3T Siemens 
Prisma?

Many thanks,
Rachel

--
Rachel Woodall

PhD Student
University of York
Department of Psychology
YO10 5DD

Email: rachel.wood...@york.ac.uk<mailto:rachel.wood...@york.ac.uk>
Phone: 01904 567613


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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.



--
Rachel Woodall

PhD Student
University of York
Department of Psychology
YO10 5DD

Email: rachel.wood...@york.ac.uk<mailto:rachel.wood...@york.ac.uk>
Phone: 01904 567613



The materials in this message are private and may contain Protected Healthcare 
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or the taking of any action in reliance on the contents of this information is 
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immediately notify the sender via telephone or return mail.

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Re: [HCP-Users] Structural Protocol

[Harms, Michael]

Hi,
You can find an importable protocol here:
http://protocols.humanconnectome.org/CCF/

The protocols that we are using for the HCP-Aging/Development projects are 
highly similar, but include a few additions (e.g., switch to 
navigator-corrected anatomicals; addition of PCASL scan).  Those will be posted 
once we can organize the documentation (sometime after OHBM).

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: 
>
 on behalf of Rachel Woodall 
>
Date: Wednesday, June 21, 2017 at 3:42 AM
To: "hcp-users@humanconnectome.org" 
>
Subject: [HCP-Users] Structural Protocol

Hello,

Is the Pheonix ZIP file available for the structural protocol on a 3T Siemens 
Prisma?

Many thanks,
Rachel

--
Rachel Woodall

PhD Student
University of York
Department of Psychology
YO10 5DD

Email: rachel.wood...@york.ac.uk
Phone: 01904 567613


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Re: [HCP-Users] rejected datasets

[Harms, Michael]

Hi,
We will not be releasing any additional data that hasn’t already been released. 
 (Such subjects have been reported to our IRB as excluded from the Young Adult 
HCP, and are not eligible for release).  Information on existing released 
subjects with identified quality control issues can be found here:

https://wiki.humanconnectome.org/pages/viewpage.action?pageId=88901591

Take a look at those, and see if those are useful for your purposes.

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: 
>
 on behalf of valabregue 
>
Date: Friday, June 16, 2017 at 3:29 AM
To: "hcp-users@humanconnectome.org" 
>
Subject: [HCP-Users] rejected datasets




Dear HCP consortium


I am working on automatic QC and I will be very interested to have access to 
all rejected data (for bad quality purpose or because of subject abnormalities) 
(with the corresponding reason)

Are those data available ?


Many thanks


Romain

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Re: [HCP-Users] Question about unprocessed fMRI data

[Harms, Michael]

This is via Essa:

It is the same as what is done in the Siemens product - these are Siemens 
code/algorithms. But yes - they do B0 corrections, including in post-processing.

--
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: 
>
 on behalf of Benjamin Risk >
Date: Thursday, June 8, 2017 at 11:05 AM
To: "hcp-users@humanconnectome.org" 
>
Subject: [HCP-Users] Question about unprocessed fMRI data

Dear HCP experts,

I am trying to better understand the unprocessed fMRI data. Does the online 
reconstruction include corrections for spatial shifts due to B0 fluctuations? 
There is a note about this in Ugurbil et al 2013 but I am wondering if this 
applies to the final HCP acquisition protocol.

Thank you!
Ben Risk


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Re: [HCP-Users] Matching field map resolutions to images

[Harms, Michael]

In theory, the resolutions and matrix size don’t need to match.  But I thought 
that, as a practical matter, the Pipelines don’t work if they don’t match.  At 
least that was the case at some point in the past...

--
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: 
>
 on behalf of "Glasser, Matthew" >
Date: Thursday, June 8, 2017 at 8:29 AM
To: Grant Sutcliffe >, 
"hcp-users@humanconnectome.org" 
>
Subject: Re: [HCP-Users] Matching field map resolutions to images

What is most important is that they both cover the whole brain for gradient 
echo field maps.  Matching geometry more exactly is nice but not necessary.

Peace,

Matt.

From: 
>
 on behalf of Grant Sutcliffe >
Date: Thursday, June 8, 2017 at 4:32 AM
To: "hcp-users@humanconnectome.org" 
>
Subject: [HCP-Users] Matching field map resolutions to images

Hi,

just to check, for the preprocessing pipelines, is it necessary or advisable to 
match the resolutions between field map images and the images to be corrected? 
Specifically I am interested in the case of gradient echo field maps and fMRI 
timeseries.

Regards,
Grant

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Re: [HCP-Users] values in myelin maps

[Harms, Michael]

‘mkdir’ is telling you that the directory already exists.  Normally that won’t 
abort a script, but it does in this case because of the “set -e” at the top of 
the script.
The easy solution is to add the -p flag to the mkdir command, so that it is no 
longer considered an error if the directory already exists.

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: "Glasser, Matthew" <glass...@wustl.edu<mailto:glass...@wustl.edu>>
Date: Thursday, June 8, 2017 at 8:30 AM
To: Lisa Kramarenko 
<lisa.kramare...@gmail.com<mailto:lisa.kramare...@gmail.com>>
Cc: Michael Harms <mha...@wustl.edu<mailto:mha...@wustl.edu>>, 
"hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>" 
<hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] values in myelin maps

You could delete that or make the mkdir a conditional if it doesn’t already 
exist.

Peace,

Matt.

From: Lisa Kramarenko 
<lisa.kramare...@gmail.com<mailto:lisa.kramare...@gmail.com>>
Date: Thursday, June 8, 2017 at 4:21 AM
To: Matt Glasser <glass...@wustl.edu<mailto:glass...@wustl.edu>>
Cc: "Harms, Michael" <mha...@wustl.edu<mailto:mha...@wustl.edu>>, 
"hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>" 
<hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] values in myelin maps

I am sorry, I have made a mistake in the mail above. It seems that the Pipeline 
ended in the end of the "FreeSurferHiresPial.sh" script and not the 
Intermediate recon-all steps. It ended after


Reading surface file /Users/user/Desktop/003/T1w/003/surf/rh.pial.postT2.pass2

Applying linear registration transform

 1.000   0.000   0.000   0.000;

 0.000   0.000  -1.000   0.350;

 0.000   1.000   0.000   0.000;

 0.000   0.000   0.000   1.000;

INFO: trgsubject = srcsubject

Saving target data

mkdir: ribbon.postT2.pass1: File exists


So as I understand it, the only part that didn't finish are the Final Recon-all 
Steps. Should I delete the folder "ribbon.postT2.pass1" before running the 
pipeline the way I described above, so that it can be created again (and the 
ribbon files moved there) and the pipeline can end?

Sorry for naive questions and thanks again.

Lisa

On 8 June 2017 at 09:59, Lisa Kramarenko 
<lisa.kramare...@gmail.com<mailto:lisa.kramare...@gmail.com>> wrote:
I wasn't sure about the exact hacking process and just naively commented out 
lines 133-167 in the FreeSurfer script, so that I started with
recon-all -subjid $SubjectID -sd $SubjectDIR -autorecon2 -nosmooth2 -noinflate2 
-nocurvstats -nosegstats -openmp ${num_cores} ${seed_cmd_appendix}   (with 
brainmask and wm being edited)

It ran without problems, but stopped after saying

"mkdir: ribbon.postT2.pass1: File exists" in the Intermediate Recon-all Steps. 
So it was rewriting everything up to this point but for some reason stopped 
there.

Nevertheless, seeing that surfaces seemed to have been regenerated, I tried to 
run PostFreeSurfer and apart from the warnings ("annot file: 
/Users/user/Desktop/003/T1w/003/label/lh.BA.annot MRISreadAnnotationIntoArray: 
vertex index out of range: 146448 i=00190519, in_array_size=146066) it went 
without error and my myelin map looks good now.

What do you think? Can I use it or should I change something else so that the 
complete pipeline finishes?

Thanks!

Lisa

On 7 June 2017 at 19:53, Glasser, Matthew 
<glass...@wustl.edu<mailto:glass...@wustl.edu>> wrote:
Right she would want to comment out stuff that had already been done.

Matt.

From: "Harms, Michael" <mha...@wustl.edu<mailto:mha...@wustl.edu>>
Date: Wednesday, June 7, 2017 at 12:50 PM
To: Matt Glasser <glass...@wustl.edu<mailto:glass...@wustl.edu>>, Lisa 
Kramarenko <lisa.kramare...@gmail.com<mailto:lisa.kramare...@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] values in myelin maps


I haven’t thought this all through, but I think that one of the main things 
you’d need to hack is to be able to make use of an already existing FS output.  
Currently, I believe that re-running the pipeline will simply overwrite any 
existing FS files, as if you were running FS de-novo.

cheers,
-MH

--
Michael Harms, Ph.D.
---
Conte Center for the Neuroscience of Mental Disorders
Washington Universit

Re: [HCP-Users] values in myelin maps

[Harms, Michael]

I haven’t thought this all through, but I think that one of the main things 
you’d need to hack is to be able to make use of an already existing FS output.  
Currently, I believe that re-running the pipeline will simply overwrite any 
existing FS files, as if you were running FS de-novo.

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: "Glasser, Matthew" <glass...@wustl.edu<mailto:glass...@wustl.edu>>
Date: Wednesday, June 7, 2017 at 11:55 AM
To: Lisa Kramarenko 
<lisa.kramare...@gmail.com<mailto:lisa.kramare...@gmail.com>>, Michael Harms 
<mha...@wustl.edu<mailto:mha...@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] values in myelin maps

Hi Lisa,

I was going to suggest that you hack the pipeline yourself if you are 
comfortable with that.  You might try starting at line 167 of the FreeSurfer 
pipeline to incorporate the brainmask edits (the WM edits might not be needed 
then).  As for the control points, I don’t know enough about that to advise you 
so you’ll need to consult the FreeSurfer documentation to see where to add them 
in.

The main things we do to modify the recon-all script is to assist with brain 
masking, to fine tune the white surface to be placed based on high res data, 
and place the pial surface based on highres T1w and T2w data using the script 
modules.

The white surface tuning happens in between –white and –smooth2 whereas the 
pial surface tuning happens between -pial and -surfvolume on this table: 
http://surfer.nmr.mgh.harvard.edu/fswiki/ReconAllTableStableV5.3

Peace,
Matt.

From: Lisa Kramarenko 
<lisa.kramare...@gmail.com<mailto:lisa.kramare...@gmail.com>>
Date: Wednesday, June 7, 2017 at 11:16 AM
To: "Harms, Michael" <mha...@wustl.edu<mailto:mha...@wustl.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] values in myelin maps

so that means if something went wrong with the skull strip and surfaces during 
the FreeSurfer Pipeline there is no other alternative than to exclude these 
subjects?

On 7 June 2017 at 18:04, Harms, Michael 
<mha...@wustl.edu<mailto:mha...@wustl.edu>> wrote:

Unfortunately, the HCP Pipelines do not currently support rerunning FreeSurfer 
after editing.  It is on our list of “things to do” to add that functionality.

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<tel:(314)%20747-6173>
St. Louis, MO  63110Email: mha...@wustl.edu<mailto:mha...@wustl.edu>

From: 
<hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>>
 on behalf of Lisa Kramarenko 
<lisa.kramare...@gmail.com<mailto:lisa.kramare...@gmail.com>>
Date: Wednesday, June 7, 2017 at 11:00 AM
To: "Glasser, Matthew" <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] values in myelin maps

Dear Matthew,

I have now manually edited brainmask.gmz ans wm.gmz to remove dura that was 
still mistaken for a surface. Now I am not sure from which step to re-run these 
participants.
1. Do I understand it correctly that after replacing brainmask.gmz and wm.gmz 
in the /mri I need to start the FreeSurfer Pipeline after the step "# 
Generate brain mask" (meaning starting with the step "# Call recon-all to run 
most of the "-autorecon2" stages, but turning off smooth2, inflate2, curvstats, 
and segstats stages")?
2. Do I need to use any additional flags in the autorecon after my intervention?
3. I also created some control points to fix missing white matter. Should I put 
the control.dat file in the /tmp folder? Will FreeSurfer see the file 
automatically or should I add some flag for it?

thanks a lot for your help!
Lisa

On 30 May 2017 at 16:38, Lisa Kramarenko 
<lisa.kramare...@gmail.com<mailto:lisa.kramare...@gmail.com>> wrote:
thanks

best,
Lisa

On 30 May 2017 at 16:37, Glasser, Matthew 
<glass...@wustl.edu<mai

Re: [HCP-Users] values in myelin maps

[Harms, Michael]

Unfortunately, the HCP Pipelines do not currently support rerunning FreeSurfer 
after editing.  It is on our list of “things to do” to add that functionality.

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: 
>
 on behalf of Lisa Kramarenko 
>
Date: Wednesday, June 7, 2017 at 11:00 AM
To: "Glasser, Matthew" >, 
"hcp-users@humanconnectome.org" 
>
Subject: Re: [HCP-Users] values in myelin maps

Dear Matthew,

I have now manually edited brainmask.gmz ans wm.gmz to remove dura that was 
still mistaken for a surface. Now I am not sure from which step to re-run these 
participants.
1. Do I understand it correctly that after replacing brainmask.gmz and wm.gmz 
in the /mri I need to start the FreeSurfer Pipeline after the step "# 
Generate brain mask" (meaning starting with the step "# Call recon-all to run 
most of the "-autorecon2" stages, but turning off smooth2, inflate2, curvstats, 
and segstats stages")?
2. Do I need to use any additional flags in the autorecon after my intervention?
3. I also created some control points to fix missing white matter. Should I put 
the control.dat file in the /tmp folder? Will FreeSurfer see the file 
automatically or should I add some flag for it?

thanks a lot for your help!
Lisa

On 30 May 2017 at 16:38, Lisa Kramarenko 
> wrote:
thanks

best,
Lisa

On 30 May 2017 at 16:37, Glasser, Matthew 
> wrote:
Yes.

Peace,

Matt.

From: Lisa Kramarenko 
>
Date: Tuesday, May 30, 2017 at 9:31 AM

To: Matt Glasser >
Cc: "hcp-users@humanconnectome.org" 
>
Subject: Re: [HCP-Users] values in myelin maps

do I find the files I should inspect in the {subject_id}/T1w/{subject_id}/mri/ 
folder?

On 30 May 2017 at 16:28, Lisa Kramarenko 
> wrote:
ok. so basically just go through recon-all output and manually correct whatever 
might have gone wrong?

best,
Lisa

On 30 May 2017 at 16:13, Glasser, Matthew 
> wrote:
I would look for locations in which the FreeSurfer aseg is clearly labeling 
things outside of the brain as grey or white matter.

Peace,

Matt.

From: Lisa Kramarenko 
>
Date: Tuesday, May 30, 2017 at 8:59 AM

To: Matt Glasser >
Cc: "hcp-users@humanconnectome.org" 
>
Subject: Re: [HCP-Users] values in myelin maps

Alright, thanks for the quick reply! Should I look for some specific problem 
with the surfaces which is to be fixed? I mean I imagine a lot of things can go 
wrong with a surface, so that I need to know what exactly to fix? Or is it 
something more general like this: 
http://sites.bu.edu/cnrlab/lab-resources/freesurfer-quality-control-guide/freesurfer-quality-control-step-1-fix-pial-surface/
  ?

And does it look like it affect both pial and white matter surfaces, so that 
both need to be fixed?

Sorry for the naive questions and thanks again.

On 30 May 2017 at 15:51, Glasser, Matthew 
> wrote:
Fat saturation reduces the intensity of the fat within the bone marrow, which 
reduces the chance that FreeSurfer will mistake this fat for white matter.  You 
would need to have this on during acquisition.  As for how to fix the surfaces 
after the fact, I would look at FreeSurfer’s documentation.

Peace,

Matt.

From: Lisa Kramarenko 
>
Date: Tuesday, May 30, 2017 at 8:49 AM

To: Matt Glasser >
Cc: "hcp-users@humanconnectome.org" 
>
Subject: Re: [HCP-Users] values in myelin maps

Yes, this is data of the lab I am in. I assume that I don't have fat saturation 
as I have never heard about it before... If I understand correctly it can't be 
done post-hoc after acquisition and should have been done during scanning? 
Other patients from the same batch 

Re: [HCP-Users] slice-to-volume registration in DWI - venetian blind artifact

[Harms, Michael]

Jesper’s plan is to release an updated version of ‘eddy’ that includes the 
slice-to-volume registration after OHBM.

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: 
>
 on behalf of Antonin Skoch >
Date: Monday, June 5, 2017 at 12:45 PM
To: "hcp-users@humanconnectome.org" 
>
Subject: [HCP-Users] slice-to-volume registration in DWI - venetian blind 
artifact

Dear experts,

I am very interested in the slice-to-volume registration method for diffusion 
preprocessing pipeline as it was presented in the ISMRM abstract on Developing 
Human connectome project 
http://cds.ismrm.org/protected/17MPresentations/abstracts/1269.html

We have dataset with specific slice-wise distortions which cannot be corrected 
by volume-wise registration techniques.

Our distortions manifest itself as artifact which is described as "venetian 
blind artifact" in DTIprep paper (shown in fig. 5d of  
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3864968/ ). In the paper the 
artifact is described as originating by motion, but I am in doubt the motion is 
a basis of the artifact in our case since it systematically affects only some 
specific diffusion directions and the slices are not interleavely shifted to 
each other but squeezed/stretched in AP direction. Also, it affects only our 
64-direction DWI, it is not seen in 30-direction DWI.

Do you have any suggestion what the origin of the artifact might be and how to 
correct it? I believe that dHCP pipeline with slice-to-volume registration 
framework could be a way to go. What do you think? Do you have this pipeline 
already publicly available? If not, when is the expected timeline of its 
release?

Regards,

Antonin Skoch




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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: 
>
 on behalf of "Reid, Erin" >
Date: Wednesday, May 24, 2017 at 1:10 PM
To: Ariana Cahn >
Cc: "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 
> 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] cifti file

[Harms, Michael]

They were acquired with opposite phase encoding (PE) directions, and thus will 
have differing areas of susceptibility dropout.  We recommend using them 
together, as a *pair* of scans, so as to avoid potential biases from using just 
one of the two PE directions.

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: 
>
 on behalf of wtj <1257735...@qq.com>
Date: Thursday, May 25, 2017 at 3:20 AM
To: "hcp-users@humanconnectome.org" 
>
Subject: [HCP-Users] cifti file

Hi,
There is a .dtseries.nii file in rfMRI_REST1_LR and the other in 
rfMRI_REST1_RL, which one should I use? What’s the difference?
Thanks.


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Re: [HCP-Users] run-level (level 1） functional MRI data

[Harms, Michael]

No.  Those native.func.gii files are not what you want.

We didn’t release the Level 1 task processing because we considered them 
“intermediate” files that would not be needed, or of much interest to others.

What are you wanting to do with them?

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: Jiang Jian <jiangjian...@163.com<mailto:jiangjian...@163.com>>
Date: Tuesday, May 23, 2017 at 9:11 PM
To: Michael Harms <mha...@wustl.edu<mailto:mha...@wustl.edu>>
Cc: "hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>" 
<hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>
Subject: Re:Re: [HCP-Users] run-level (level 1） functional MRI data

Hi Michael,

I am sorry I didn't put it clearly. I want "level 1 " results processed through 
the task model (GLM)? Are they in file
 
${subj}/MNINonLinear/Results/${fMRIName}_{LR,RL}/${fMRIName}_{LR,RL}__{L,R}.native.func.gii?

Thanks,
Jiang Jian





At 2017-05-23 22:31:34, "Harms, Michael" 
<mha...@wustl.edu<mailto:mha...@wustl.edu>> wrote:

Hi,
Do you want the “Level 1” results processed through the task model (GLM)?

Or, do you just want the “minimally preprocessed” data that entered into the 
task analysis scripts?  These are available in:
${subj}/MNINonLinear/Results/${fMRIName}_{LR,RL}/${fMRIName}_{LR,RL}_Atlas_MSMAll.dtseries.nii
 for the “MSMAll” registered version.

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<mailto:mha...@wustl.edu>

From: 
<hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>>
 on behalf of Jiang Jian <jiangjian...@163.com<mailto:jiangjian...@163.com>>
Date: Monday, May 22, 2017 at 9:26 PM
To: "hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>" 
<hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>
Subject: [HCP-Users] run-level (level 1） functional MRI data

Dear Professors,

I want to use run-level data to do some analysis, and I wonder would  file 
named *.native.fun.gii (e.g., tfMRI_WM_LR.L.natiive.func.gii) contains 
run-level functional data?


Best,

Jiang Jian

-
Graduate Student
Beijing Normal University, 100875





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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 
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or the taking of any action in reliance on the contents of this information is 
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Re: [HCP-Users] run-level (level 1） functional MRI data

[Harms, Michael]

Hi,
Do you want the “Level 1” results processed through the task model (GLM)?

Or, do you just want the “minimally preprocessed” data that entered into the 
task analysis scripts?  These are available in:
${subj}/MNINonLinear/Results/${fMRIName}_{LR,RL}/${fMRIName}_{LR,RL}_Atlas_MSMAll.dtseries.nii
 for the “MSMAll” registered version.

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: 
>
 on behalf of Jiang Jian >
Date: Monday, May 22, 2017 at 9:26 PM
To: "hcp-users@humanconnectome.org" 
>
Subject: [HCP-Users] run-level (level 1） functional MRI data

Dear Professors,

I want to use run-level data to do some analysis, and I wonder would  file 
named *.native.fun.gii (e.g., tfMRI_WM_LR.L.natiive.func.gii) contains 
run-level functional data?


Best,

Jiang Jian

-
Graduate Student
Beijing Normal University, 100875





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Re: [HCP-Users] Question about DWI protocol

[Harms, Michael]

Yes, in DiffPreprocPipeline_PostEddy.sh you’ll need to use 
“--combine-data-flag=2”

Also, I want to caution you about collecting only half of the total dMRI data 
that we collected in the UMN Lifespan piloting.  There is a reason that we 
collected a full 20 min of dMRI when using 1.5 mm resolution.  Before you 
collect less total data (at that same spatial resolution), I would run some 
piloting to check if reducing the amount of data is sufficient to generate good 
quality for your measures of interest.

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: 
>
 on behalf of "Glasser, Matthew" >
Date: Tuesday, May 23, 2017 at 9:01 AM
To: HMZ >, 
"hcp-users@humanconnectome.org" 
>
Cc: "g...@pku.edu.cn" 
>, Jia-Hong Gao 
>
Subject: Re: [HCP-Users] Question about DWI protocol

Yes as long as you have phase reversed b0s you can have the DWIs have unique 
directions. The HCP diffusion pipeline might need modification to accommodate 
that.

Peace,

Matt.

From: 
>
 on behalf of HMZ >
Date: Tuesday, May 23, 2017 at 2:14 AM
To: "hcp-users@humanconnectome.org" 
>
Cc: "g...@pku.edu.cn" 
>, Jia-Hong Gao 
>
Subject: [HCP-Users] Question about DWI protocol

Dear HCP experts,

This is Meizhen Han from Center for MRI research at Peking University in China. 
I'm writing for seeking a solution for the problem we encountered during the 
application of HCP MRI sequence on our recent research.

I noticed that HCP acquired DWI data twice with reversed phase direction in 
order to calculate the fieldmap, which I think is perfect but a little 
time-consuming especially when 2 or 3 gradient tables are used.

I'm wondering whether it is OK to acquire one phase encoding direction of one 
gradient table and reversed direction of another gradient table.
Taking Lifespan DWI protocol of UM for example, can we only get DWI_dir98_AP 
and DWI_dir99_PA, and then take out b0 images in both files to caculate 
fieldmap?

Any relevant information and idea would help a lot. Thank you very much!

Looking forward to your reply.

--
Best Regards!
Meizhen Han

--
Meizhen Han
PhD Candidate
Center for MRI Research
Peking University
Beijing, China





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Re: [HCP-Users] Subject keys

[Harms, Michael]

Yes, you can use the subject IDs in a public document, PROVIDED that NOTHING 
that comes from the RESTRICTED data is associated with that subject ID in your 
public document.

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: 
>
 on behalf of "HINDRIKS, RIKKERT" 
>
Date: Tuesday, May 23, 2017 at 5:16 AM
To: "hcp-users@humanconnectome.org" 
>
Subject: [HCP-Users] Subject keys

Dear HCP-users,

Is it allowed to use the original HCP subject keys in public documents?
(I do not use the restricted data).

Thanks and kind regards,
Rikkert Hindriks

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Re: [HCP-Users] cifti MATLAB

[Harms, Michael]

Hi,

Are you using the latest gifti library available via the link mentioned here?
https://wiki.humanconnectome.org/display/PublicData/HCP+Users+FAQ#HCPUsersFAQ-2.HowdoyougetCIFTIfilesintoMATLAB?

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: 
>
 on behalf of wtj <1257735...@qq.com>
Date: Tuesday, May 23, 2017 at 6:05 AM
To: "hcp-users@humanconnectome.org" 
>
Subject: [HCP-Users] cifti MATLAB

Hi,
There’s something wrong when I load the cifti dense timeseries file into matlab.
>> which ciftiopen
/home/Tianjie/cifti/ciftiopen.m
>>cii=ciftiopen('/home/Tianjie/projects/WU-Minn_HCP_Lifespan_Pilot_Data_structure_preprocess/LS2001/MNINonLinear/Results/rfMRI_REST1_LR/rfMRI_REST1_LR_Atlas.dtseries.nii','/home/Tianjie/workbench/bin_rh_linux64/wb_command')
Error using file_array/permute (line 10)
file_array objects can not be permuted.

Error in read_gifti_file>gifti_Data (line 201)
d = permute(reshape(d,fliplr(s.Dim)),length(s.Dim):-1:1);

Error in read_gifti_file>gifti_DataArray (line 122)
s(1).data = gifti_Data(t,c(i),s(1).attributes);

Error in read_gifti_file (line 45)
this.data{end+1} = gifti_DataArray(t,uid(i),filename);

Error in gifti (line 74)
this = read_gifti_file(varargin{1},giftistruct);

Error in ciftiopen (line 31)
cifti = gifti([tmpfile '.gii']);

Can you see what’s wrong?
Thanks.

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