Thank you for this. We had explored this option in the past and two issues were 
1) there was not a parcellation readily available with subcortical structures 
and 2) I do not feel a need to constrain activation to parcels rather than 
swaths of signal as they appear to cluster themselves.


I'm sure parcellation is a valid approach, but I would really like to be able 
to simply report activation as it appears to cluster such as with TFCE, fdr or 
cluster thresholding (although that is less favored now) as has been typical in 
fMRI reporting. Are there examples available for these kinds of analysis to 
eventually relate activation to behavior or other measures?


I am grateful for all the help you have all provided. Things are quite close, 
and I hope to be able to be able to get through these last steps as quickly as 
possible.




________________________________
From: Glasser, Matthew <glass...@wustl.edu<mailto:glass...@wustl.edu>>
Sent: Tuesday, September 20, 2016 11:06:10 AM
To: Michael F.W. Dreyfuss; NEUROSCIENCE tim
Cc: hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>
Subject: Re: [HCP-Users] ROIs and Betas from Cifti Data

As Tim mentions, it sounds like you might want to use a parcellated analysis, 
as this will be more sensitive/powerful and you’ll know exactly what areas you 
are finding.  The HCP’s multi-modal parcellation is available here:

https://balsa.wustl.edu/study/show/RVVG<https://urldefense.proofpoint.com/v2/url?u=https-3A__balsa.wustl.edu_study_show_RVVG&d=DQMF-g&c=lb62iw4YL4RFalcE2hQUQealT9-RXrryqt9KZX2qu2s&r=rPclmYysc_z1plf99IoNsmxWf1JolkKMmL6bXnYFSwg&m=41tIMVdkyw4FbaKBCuAemq30kaX7FtpSn1fT4mnNgb4&s=LSobQp1e_k82tOjzxrgaFuayanqOIOB0FPCI128My64&e=>

Also, the HCP’s task analysis pipeline will allow you to parcellate before 
fitting the GLM, rather than afterwards to get the addition SNR benefits from 
averaging across a parcel.

Peace,

Matt.

From: 
<hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>>
 on behalf of "Michael F.W. Dreyfuss" 
<mid2...@med.cornell.edu<mailto:mid2...@med.cornell.edu>>
Date: Monday, September 19, 2016 at 9:40 PM
To: Timothy Coalson <tsc...@mst.edu<mailto:tsc...@mst.edu>>
Cc: "Michael F.W. Dreyfuss" 
<mid2...@med.cornell.edu<mailto:mid2...@med.cornell.edu>>, 
"hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>" 
<hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>
Subject: Re: [HCP-Users] ROIs and Betas from Cifti Data

Thank you,

Are there any examples available for how to use this, possibly? I have been 
trying to figure these out, but there are a lot of options and  I am just not 
able to decipher how to use these from the help page alone. The errors I am 
getting also do not clarify what I need to do to get the output I am looking 
for.

Before using this kind of multi-band data I had been using afni. To give an 
example of what I would want to do in terms of afni commands (if that’s any 
help), I would have saved all ROIs and then used 3dmaskave to extract mean beta 
weights for a given GLM beta for each subject and then I would relate those 
beta weights so subject’s behavior in R or another stats package.

Definitely agree that there’s not much meaning to a peak coordinate per se. I’m 
just trying to figure out how to report the clusters I am finding. In previous 
reports we would typically focus on broadmann areas or more general regional 
nomenclature (i.e. vmPFC, mid temporal lobe, etc.). Some of the clusters I’m 
finding also cover large areas from motor to visual cortex, so I am trying to 
consider good ways to report that.

At this point I would prefer to use TFCE or some other thresholding method to 
identify contiguous swaths of volumetric and surface activation.

Thank you very much again,
Michael

On Sep 19, 2016, at 6:41 PM, Timothy Coalson 
<tsc...@mst.edu<mailto:tsc...@mst.edu>> wrote:


On Mon, Sep 19, 2016 at 4:51 PM, Michael F.W. Dreyfuss 
<mid2...@med.cornell.edu<mailto:mid2...@med.cornell.edu>> wrote:

Thank you,


How can I turn the ROIs into a label file?

You can use -cifti-find-clusters if you just want spatial contiguity to define 
where ROIs should be considered separate, then use -cifti-label-import to make 
them into a dlabel file.

Also, how can I simply get a list of the ROIs with some information like 
cluster extent and peak voxel to be able to identify what part(s) of the brain 
each ROI is covering?

A single coordinate isn't a faithful representation of the cluster.  You can 
make a figure showing the clusters displayed on the brain (for instance, choose 
two of: beta maps, significance outlines, area outlines), and hopefully also 
provide the unthresholded beta and z maps for others to use.

You can get cluster extent info with -cifti-weighted-stats.

If the question you want to ask is "which areas are involved", you could do a 
parcellated analysis instead of a cluster analysis.

Thank you,

Michael

________________________________
From: Timothy Coalson <tsc...@mst.edu<mailto:tsc...@mst.edu>>
Sent: Monday, September 19, 2016 4:48:28 PM
To: Michael F.W. Dreyfuss
Cc: hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>
Subject: Re: [HCP-Users] ROIs and Betas from Cifti Data

The wb_command -cifti-weighted-stats command with -mean is probably what you 
want (outputs a number to the command line), though you'll need to have each 
ROI as a separate file and run it separately for each of them.  Alternatively, 
if you turned the ROIs into a label file, you could get -cifti-parcellate to 
make a file where each parcel contains the answer for an ROI.

Tim


On Mon, Sep 19, 2016 at 3:26 PM, Michael F.W. Dreyfuss 
<mid2...@med.cornell.edu<mailto:mid2...@med.cornell.edu>> wrote:

Hello, I have run palm with TFCE on my group level data successfully for a task 
based fMRI study (yay!), and I would like to be able to identify ROIs from my 
cifti data (both surface and volume). I then want to extract subject level beta 
weights for a given condition from those ROIs to relate those betas to behavior 
(offline). Are there simple ways to: 1) identify regions implicated on the 
group level and 2) extract subject-level beta weights from them, such as with 
wb_command?


Thank you,

Michael

_______________________________________________
HCP-Users mailing list
HCP-Users@humanconnectome.org<mailto:HCP-Users@humanconnectome.org>
http://lists.humanconnectome.org/mailman/listinfo/hcp-users<https://urldefense.proofpoint.com/v2/url?u=http-3A__lists.humanconnectome.org_mailman_listinfo_hcp-2Dusers&d=DQMFaQ&c=lb62iw4YL4RFalcE2hQUQealT9-RXrryqt9KZX2qu2s&r=rPclmYysc_z1plf99IoNsmxWf1JolkKMmL6bXnYFSwg&m=owdejnaklI6Db2XSiTgha_Wfo4am5eKBMJpc1pFzI1A&s=Ia4QB3ti2OENrr5FEZXT5gcngkIh2Yh34e_N0EOpfFI&e=>




_______________________________________________
HCP-Users mailing list
HCP-Users@humanconnectome.org<mailto:HCP-Users@humanconnectome.org>
http://lists.humanconnectome.org/mailman/listinfo/hcp-users<https://urldefense.proofpoint.com/v2/url?u=http-3A__lists.humanconnectome.org_mailman_listinfo_hcp-2Dusers&d=DQMF-g&c=lb62iw4YL4RFalcE2hQUQealT9-RXrryqt9KZX2qu2s&r=rPclmYysc_z1plf99IoNsmxWf1JolkKMmL6bXnYFSwg&m=41tIMVdkyw4FbaKBCuAemq30kaX7FtpSn1fT4mnNgb4&s=-9ww002FIzbXB56mRLX-twqyvFBmaOjLoF5wqiCRwJE&e=>

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

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

Reply via email to