Once you have a parcellated timeseries I would expect things to be pretty 
similar and just a matter of getting the data in the expected format for the 
software program.  I don’t have any experience with brain connectivity toolkit, 
but you can use wb_command -cifti-parcellate to generate parcellated timeseries 
and then load these into matlab with the matlab CIFTI reader/writer 
(https://wiki.humanconnectome.org/display/PublicData/HCP+Users+FAQ#HCPUsersFAQ-2.HowdoyougetCIFTIfilesintoMATLAB?)
 or wb_command -cifti-convert to convert CIFTI to text or a NIFTI file.

Peace,

Matt.

From: 
<[email protected]<mailto:[email protected]>>
 on behalf of Yu Sun Chung <[email protected]<mailto:[email protected]>>
Date: Thursday, May 24, 2018 at 10:36 AM
To: "[email protected]<mailto:[email protected]>" 
<[email protected]<mailto:[email protected]>>
Subject: [HCP-Users] Guidelines for preparing HCP-processed data for graph 
theory based analysis

Hi,

I am looking into any publications describing a step-by-step guidelines for 
preparing HCP-processed data to conduct graph theory analysis like brain 
connectivity toolkit. especially, I wonder how any data prep steps might differ 
from conventional volumetric-based processing pipelines. Anyone who can help me 
to clarify these? If any papers or guidelines are already out, would you please 
forward them to me?

Many thanks in advance!

Best,
Yu Sun

--
-------------------------------
Yu Sun Chung, PhD

Postdoctoral Fellow
Clinical Neuroscience and Development Laboratory
Olin Neuropsychiatry Research Center
200 Retreat Avenue
Whitehall Building- Institute of Living
Hartford CT 06106
Phone:860-545-7144
Fax: 860-545-7797
Email: [email protected]<mailto:[email protected]>

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