Looks like it does what you wanted. Side note, if you have multiple
non-overlapping ROIs to do this with, you could also make them into a
dlabel file, then use -cifti-parcellate on the timeseries, and do a
-cifti-cross-correlation using it and the smoothed dtseries. However,
you'll need to figure out the correct order of files in the cross
correlation to avoid needing -cifti-transpose to display it the way you
want.
Tim
On Thu, May 4, 2017 at 4:28 PM, Ely, Benjamin <benjamin....@mssm.edu> wrote:
> Good to know, thanks - that's consistent with what I'm seeing. Will keep
> the transformation for now. For future ref to anyone trying this, the
> corrected sequence is:
>
> 1) Extract mean unsmoothed ROI data to text:
> wb_command -cifti-roi-average ${sub}_${run}.dtseries.nii
> roi_data_${sub}_${run}_unsmoothed.txt -vol-roi ${sub}_roi_mask.nii
> 2) Convert extracted ROI data to cifti:
> wb_command -cifti-create-scalar-series roi_data_${sub}_${run}_unsmoothed.txt
> roi_data_${sub}_${run}_unsmoothed.dscalar.nii -transpose -series SECOND 0 1
> 3) Cross-correlate this new ROI timeseries cifti with the smoothed
> whole-brain cifti data and (optionally) z transform:
> wb_command -cifti-cross-correlation ${subject}_${run}_smoothed.dtseries.nii
> roi_data_${sub}_${run}_unsmoothed.dscalar.nii
> z_correlation_${sub}_${run}.dscalar.nii -fisher-z
> 4) Repeat for all runs and average:
> wb_command -cifti-average z_correlation_${sub}_average.dscalar.nii \
>
> -cifti z_correlation_${sub}_run1.dscalar.nii \
>
> -cifti z_correlation_${sub}_run2.dscalar.nii \
>
> -cifti z_correlation_${sub}_run3.dscalar.nii \
>
> -cifti z_correlation_${sub}_run4.dscalar.nii
>
> ------------------------------
> *From:* Benjamin Risk [bb...@cornell.edu]
> *Sent:* Thursday, May 04, 2017 2:34 PM
> *To:* Harms, Michael
> *Cc:* Ely, Benjamin
> *Subject:* Re: [HCP-Users] unsmoothed ROI to smoothed cifti correlation
>
> That's true, but the sample correlation coefficient is asymptotically
> normal. I agree with Benjamin based on some correlations I looked at from
> HCP data. They do tend to be pretty Gaussian because the number of time
> points is large and the correlations I looked at were not close to 1 or
> -1.
>
> Even when the correlations are close to Gaussian, the Fisher-transform is
> variance stabilizing and results in a standard Gaussian, which is nice for
> hypothesis testing. But there are cases where you might not want to
> transform, e.g., interpretability.
>
> On Thu, May 4, 2017 at 1:49 PM, Harms, Michael <mha...@wustl.edu> wrote:
>
>>
>> To be clear, depending on the r-value, the Fisher’s z-transform may not
>> change the value much, but that doesn’t mean that the correlation
>> (Pearson’s r) has a *distribution* that is close to Gaussian.
>>
>> cheers,
>> -MH
>>
>> --
>> Michael Harms, Ph.D.
>> -----------------------------------------------------------
>> Conte Center for the Neuroscience of Mental Disorders
>> Washington University School of Medicine
>> Department of Psychiatry, Box 8134
>> 660 South Euclid Ave. Tel: 314-747-6173 <(314)%20747-6173>
>> St. Louis, MO 63110 Email: mha...@wustl.edu
>>
>> From: "Ely, Benjamin" <benjamin....@mssm.edu>
>> Date: Thursday, May 4, 2017 at 12:43 PM
>> To: Michael Harms <mha...@wustl.edu>, "Glasser, Matthew" <
>> glass...@wustl.edu>, "HCP-Users@humanconnectome.org" <
>> HCP-Users@humanconnectome.org>
>> Subject: RE: [HCP-Users] unsmoothed ROI to smoothed cifti correlation
>>
>> Ah that makes sense, thanks! The effect of the z transformation is quite
>> subtle (as expected since the correlation distributions are close to
>> gaussian before transformation).
>> ------------------------------
>> *From:* Harms, Michael [mha...@wustl.edu]
>> *Sent:* Thursday, May 04, 2017 10:21 AM
>> *To:* Ely, Benjamin; Glasser, Matthew; HCP-Users@humanconnectome.org
>> *Subject:* Re: [HCP-Users] unsmoothed ROI to smoothed cifti correlation
>>
>>
>> I would probably z transform before averaging across runs, so that you
>> are averaging something with at least an approximately gaussian
>> distribution.
>>
>> cheers,
>> -MH
>>
>> --
>> Michael Harms, Ph.D.
>> -----------------------------------------------------------
>> Conte Center for the Neuroscience of Mental Disorders
>> Washington University School of Medicine
>> Department of Psychiatry, Box 8134
>> 660 South Euclid Ave. Tel: 314-747-6173 <(314)%20747-6173>
>> St. Louis, MO 63110 Email: mha...@wustl.edu
>>
>> From: <hcp-users-boun...@humanconnectome.org> on behalf of "Ely,
>> Benjamin" <benjamin....@mssm.edu>
>> Date: Wednesday, May 3, 2017 at 11:46 PM
>> To: "Glasser, Matthew" <glass...@wustl.edu>, "
>> HCP-Users@humanconnectome.org" <HCP-Users@humanconnectome.org>
>> Subject: Re: [HCP-Users] unsmoothed ROI to smoothed cifti correlation
>>
>> Hi Matt,
>>
>> Thanks for getting back to me - after some further tinkering, I think
>> this command sequence yields the desired output:
>>
>> 1) Extract mean unsmoothed ROI data to text:
>> wb_command -cifti-roi-average ${subject}_${run}.dtseries.nii
>> roi_data_${sub}_${run}_unsmoothed.txt -vol-roi ${sub}_roi_mask.nii #
>> probably works for surface-based ROIs as well but I haven't tested
>> 2) Convert extracted ROI data to cifti:
>> wb_command -cifti-create-scalar-series roi_data_${sub}_${run}_unsmoothe
>> d.txt roi_data_${sub}_${run}_unsmoothed.dscalar.nii -transpose -series
>> SECOND 0 1
>> 3) Cross-correlate this new ROI timeseries cifti with the smoothed
>> whole-brain cifti data:
>> wb_command -cifti-cross-correlation ${subject}_${run}_smoothed.dtseries
>> .nii roi_data_${sub}_${run}_unsmoothed.dscalar.nii
>> correlation_${sub}_${run}.dscalar.nii
>> 4) Repeat for all runs and average:
>> wb_command -cifti-average correlation_${sub}_average.dscalar.nii
>> -cifti correlation_${sub}_run1.dscalar.nii -cifti correlatio
>> n_${sub}_run2.dscalar.nii -cifti correlation_${sub}_run3.
>> dscalar.nii -cifti correlation_${sub}_run4.dscalar.nii
>> 5) Fisher z transform results:
>> wb_command -cifti-math "atanh(x)" z_correlation_${sub}_average.dscalar.nii
>> -var x correlation_${sub}_average.dscalar.nii
>>
>> The resulting files appear as expected (similar to the
>> smoothed-ROI-to-smoothed-cifti results but with more variation/less smooth
>> appearance). Please let me know if you see any errors.
>>
>> Thanks again!
>> -Ely
>>
>> ------------------------------
>> *From:* Glasser, Matthew [glass...@wustl.edu]
>> *Sent:* Wednesday, May 03, 2017 11:32 PM
>> *To:* Ely, Benjamin; HCP-Users@humanconnectome.org
>> *Subject:* Re: [HCP-Users] unsmoothed ROI to smoothed cifti correlation
>>
>> Hi Ely,
>>
>> We don’t have a function like this yet, but have been discussing making
>> one. I think matlab is your best bet at this time.
>>
>> Peace,
>>
>> Matt.
>>
>> From: <hcp-users-boun...@humanconnectome.org> on behalf of "Ely,
>> Benjamin" <benjamin....@mssm.edu>
>> Date: Wednesday, May 3, 2017 at 10:06 PM
>> To: "HCP-Users@humanconnectome.org" <HCP-Users@humanconnectome.org>
>> Subject: [HCP-Users] unsmoothed ROI to smoothed cifti correlation
>>
>> Hi everyone,
>>
>> I'm running some connectivity analyses following the procedure outlined
>> in this thread https://www.mail-archive.com/hcp-users@humanconnectom
>> e.org/msg04403.html
>> <https://urldefense.proofpoint.com/v2/url?u=https-3A__www.mail-2Darchive.com_hcp-2Dusers-40humanconnectome.org_msg04403.html&d=DwMF-g&c=shNJtf5dKgNcPZ6Yh64b-A&r=wkbWuLo29rcKlS_jqY-IWyhtdbOPOJ4YiqipZSzm0r4&m=yPHnchyPW8zwQAjrQNcCAh2TbX5ft58rzU3tH0B6K54&s=XOJJuzw82VOhaCYWwXk5uBoLsl8E7AyfiW_3Uz35EJo&e=>.
>> Since my ROIs are fairly small, I'd like to calculate the correlation
>> between the mean unsmoothed timeseries of each ROI (i.e. "smoothed" only by
>> averaging within the ROI) and the subject's smoothed cifti data. However,
>> the wb_command -cifti-average-roi-correlation function only generates
>> correlations from an ROI within the same cifti file, and none of the other
>> functions seem appropriate (possibly -cifti-cross-correlation where one
>> input is a cifti containing a single row with the mean unsmoothed
>> timeseries, but I couldn't get this to work). Is there a straightforward
>> way to generate these correlations using workbench, or will I need to e.g.
>> write a matlab script? My ROIs are subcortical (voxel-based), if that
>> matters.
>>
>> Thank you!
>> -Ely
>>
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>> The materials in this message are private and may contain Protected
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>> 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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>> 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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