And, to answer the Q in your 1st paragraph: yes.
BTW: Since you want the “betas", you should use the pe1.dtseries.nii files.
But, as an aside, note that these pe’s/cope’s are the results of the Level2
analysis, essentially averaging the Level 1 (individual runs). Because all the
contrasts were defined in Level 1, and then essentially averaged for Level 2,
I’m pretty sure that within each GrayordinateStats/cope{i}.feat directory, the
actual grayordinate-values of the pe1.dtseries.nii and cope1.dtseries.nii files
are identical. (i.e., we didn’t define any “new” contrasts specifically at
Level 2, which means that the pe1 and cope1 will be the same within each
contrast).
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: [email protected]
From: "Glasser, Matthew" <[email protected]<mailto:[email protected]>>
Date: Monday, October 17, 2016 at 2:05 PM
To: Vadim Axelrod <[email protected]<mailto:[email protected]>>, Michael
Harms <[email protected]<mailto:[email protected]>>
Cc: "[email protected]<mailto:[email protected]>"
<[email protected]<mailto:[email protected]>>
Subject: Re: [HCP-Users] Extracting beta values from analyzed task-data
Grand mean 10000. Find out what SPM uses and adjust your internal scale
accordingly...
Peace,
Matt.
________________________________
From: Vadim Axelrod <[email protected]<mailto:[email protected]>>
Sent: Monday, October 17, 2016 1:41:35 PM
To: Harms, Michael
Cc: Glasser, Matthew;
[email protected]<mailto:[email protected]>
Subject: Re: [HCP-Users] Extracting beta values from analyzed task-data
Thank you for the help! So, if I want to get a beta estimate for the
condition, I should take pe image in the cope#.feat folder, where this
condition is compared vs. fixation. For example, in the Language task, for the
Math beta I should take pe image in cope1.feat (MATH-fixation) and the Story
betas are stored in cope2.feat (STORY-fixation contrast). Correct?
One more question: I noticed that betas might have high values (e.g., 50). I am
used to work with SPM, and their the beta estimates are order of magnitude
smaller. Is there some scaling here?
Harms, Michael <[email protected]<mailto:[email protected]>> wrote:
No, in the updated pipeline, we simply have some code to merge the copes/betas
from the different contrasts into a single file for each task (as we did for
the zstat maps, which perhaps somewhat confusingly, are the files named as
<subject>_tfMRI_<task>_level2_hp200_s?.dscalar.nii or
<subject>_tfMRI_<task>_level2_hp200_s?_MSMAll.dscalar.nii — i.e., “zstat” is
not part of the file name).
There is no need to re-run the pipelines. You can just use the appropriate
“merge” command in wb_shortcuts to merge the copes/betas into a similar single
file. As Matt pointed out, those copes/betas are in the
GrayordinateStats/cope{i}.feat/{pe1,cope1}.dtseries.nii files — “pe1” for the
betas; “cope1” for the contrasts).
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:314-747-6173>
St. Louis, MO 63110Email: [email protected]<mailto:[email protected]>
From:
<[email protected]<mailto:[email protected]>>
on behalf of Vadim Axelrod <[email protected]<mailto:[email protected]>>
Date: Monday, October 17, 2016 at 8:28 AM
To: "Glasser, Matthew" <[email protected]<mailto:[email protected]>>
Cc: "[email protected]<mailto:[email protected]>"
<[email protected]<mailto:[email protected]>>
Subject: Re: [HCP-Users] Extracting beta values from analyzed task-data
Thank you, Matt.
So, you mean that in the updated pipeline cope1.dtseries.nii contains multiple
beta maps (two or more, depending on a contrast)? Practically, do you think in
the foreseeable future there will be an update of task data for the download,
that will include the betas? If not, then I should probably run the pipeline
myself. Can you please advice the efficient way of doing this (see my original
post).
Many thanks!
On Mon, Oct 17, 2016 at 4:02 PM, Glasser, Matthew
<[email protected]<mailto:[email protected]>> wrote:
It looks like the released HCP task fMRI data were produced using an older
version of the Task analysis pipeline that does not automatically collate the
beta maps into a labeled and easy to use dscalar file. The beta maps will be
in these files:
${StudyFolder}/${Subject}/MNINonLinear/Results/${fMRIName}/${fMRIName}_hp200_s2_level2_MSMAll.feat/GrayordinatesStats/cope${i}.feat/cope1.dtseries.nii
where ${i} = 1 to N contrasts
Peace,
Matt.
From:
<[email protected]<mailto:[email protected]>>
on behalf of Vadim Axelrod <[email protected]<mailto:[email protected]>>
Date: Sunday, October 16, 2016 at 7:31 AM
To: Stephen Smith <[email protected]<mailto:[email protected]>>
Cc: "[email protected]<mailto:[email protected]>"
<[email protected]<mailto:[email protected]>>
Subject: Re: [HCP-Users] Extracting beta values from analyzed task-data
Thank you Stephen for the prompt reply.
But why there is only one pe1 file with only one volume in it? For the contrast
like, story > math I would expect to find two beta images, one for the
"story" and one for the "math". In addition, the pe1.dtseries.nii maps are
very correlated with tstat1.dtseries.nii (R>0.85) and there is similar
correlation for all contrasts of the same task/subject.
On Sun, Oct 16, 2016 at 2:09 PM, Stephen Smith
<[email protected]<mailto:[email protected]>> wrote:
HI - "pe" are the beta files and "cope" are contrasts of these.
Cheers.
On 16 Oct 2016, at 12:03, Vadim Axelrod
<[email protected]<mailto:[email protected]>> wrote:
Dear list,
I downloaded the analyzed 3T HCP fMRI task-data. In the cope* subfolders I can
find the outputs of the contrast calculation, e.g., Zstat1.dtseries.nii.
However, I do not see beta estimates for each regressor. Do I miss something or
they are just not included in the analyzed archive. If the latter is correct,
should I download non-analyzed data and run the analysis myself? What is the
simplest way to to that? The only instructions that I found are from the last
year course, and I am not sure how valid they are:
https://www.humanconnectome.org/courses/2015/exploring-the-human-connectome.php
https://wustl.box.com/shared/static/0vcsqc0yg3ncqmirryyxpgsiqhxww659.pdf
Probably someone can post more recent instructions from the last month course.
Many thanks for the help,
Vadim
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Information or other information of a sensitive nature. If you are not the
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