Dear Tim,
Thank you so much for this detailed explanation. I will combine both of your
suggestions and have a try then. :)
Best regards,
Xinyang
At 2018-09-22 04:43:55, "Timothy Coalson" <tsc...@mst.edu> wrote:
-cifti-cross-correlation is for when you want to correlate between two
different files. If you want roi-to-roi correlations, it is not the best way
to get them.
The easy way to get roi-to-roi correlations is to use -cifti-parcellate and
then -cifti-correlation. However, you first need to convert your ROIs into a
cifti dlabel file. To do that, first use -cifti-create-dense-from-template to
convert your ROI files to cifti dscalar, using some standard 91282 grayordinate
file as the template, then concatenate them. You then need to use
-cifti-reduce, computing both the INDEXMAX and the MAX reductions, and then use
-cifti-math to multiply the INDEXMAX file by whether the MAX file is nonzero at
that location (something like 'index * (max > 0)'). The point of this is to
make a single map where each ROI has a different nonzero integer value, and
where there is no ROI, it is zero. This file can then be used in
-cifti-label-import to make the dlabel file.
Tim
On Fri, Sep 21, 2018 at 7:22 AM, Xinyang Liu <xinyang_ie...@163.com> wrote:
Dear Matt,
Thank you very much for your prompt reply.
I will have a try according to your suggestions.
Best regards,
Xinyang
At 2018-09-21 19:37:13, "Glasser, Matthew" <glass...@wustl.edu> wrote:
1.
${StudyFolder}/${Subject}/MNINonLinear/Results/${fMRIName}/${fMRIName}_Atlas_MSMAll_hp2000_clean.dtseries.nii
2.1 wb_command -cifti-parcellate after wb_command -metric-merge wb_command
-metric-label-import and wb_command -cifti-create-dense-label
2.2 See above
2.3 wb_command -cifti-correlation on the individual subject dense timeseries
above (ideally after demeaning, potentially variance normalizing, and
concatenating across the runs in each subject—see wb_shortcuts).
Matt.
From: <hcp-users-boun...@humanconnectome.org> on behalf of Xinyang Liu
<xinyang_ie...@163.com>
Date: Friday, September 21, 2018 at 4:00 AM
To: HCP 讨论组 <hcp-users@humanconnectome.org>
Subject: [HCP-Users] rfMRI connecitivity
Dear HCP experts,
Hi. We are trying to compute resting state fMRI connectivity between several
ROIs for single individuals. The surface ROIs (.func.gii) were acquired from
task fMRI data. The plan is to compute the averaged rfMRI timeseries within
each ROI, and then compute their correlations.
We have several questions to ask:
1. The HCP user manual suggests to use dtseries.nii data in the FIX folder.
However, there are two rfMRI dtseries.nii files there, one with MSMALL, and one
without it. Which one is more recommended to use?
2. We are quite lost in using the wb_commands. By checking previous emails, it
seems that we could use "-cifti-parcellate" to compute the ROI-wise averaged
time series. But before that, it seems that we also need to create some .dlabel
files. So,
(1) which command should we use to extract dtseries covered by those
.func.gii ROIs?
(2) To compute the averaged time series, should we merge all ROIs together
in one cortical surface or compute one by one? Because the .func.gii surface
ROIs are saved as separate files.
(3) We would like to compute rfMRI connectivity for single individuals, not
group average. Is -cifti-cross-correlation the correct choice?
Look forward to your kind guidance. Thank you very much.
Best regards,
Xinyang
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