Hi Francesco,

This has been discussed quite a bit on the list. Please see 
https://www.mail-archive.com/hcp-users@humanconnectome.org/msg03000.html and 
other messages on the thread, especially the discussion of the price you pay in 
terms of spatial fidelity when you convert from surface to volume.


Also see this article “The Human Connectome Project’s neuroimaging 
approach”<http://www.nature.com/neuro/journal/v19/n9/full/nn.4361.html> 
published in Nature Neuroscience in late August 2016 that discusses this issue.


Note that FSL is currently working on getting CIFTI compatibility in their next 
release, which should be coming out soon.


Best,

Jenn

Jennifer Elam, Ph.D.
Scientific Outreach, Human Connectome Project
Washington University School of Medicine
Department of Neuroscience, Box 8108
660 South Euclid Avenue
St. Louis, MO 63110
314-362-9387<tel:314-362-9387>
e...@wustl.edu<mailto:e...@wustl.edu>
www.humanconnectome.org<http://www.humanconnectome.org/>


________________________________
From: hcp-users-boun...@humanconnectome.org 
<hcp-users-boun...@humanconnectome.org> on behalf of Francesco Sammartino 
<francesco.sammartino....@gmail.com>
Sent: Wednesday, October 12, 2016 8:59:54 AM
To: hcp-users@humanconnectome.org
Subject: [HCP-Users] Extract 137 RSN networks - Glasser et al. - Nature 2016

Hi

We are aiming to integrate the new high resolution cortical parcellation and 
the 137 resting state networks into our probabilistic tractography (FSL based) 
pipeline.

Could you please tell me how should I convert to nifti labelmaps the content of 
the file 
Q1-Q6_RelatedParcellation210.individual_RSNs_d137_WR_norm_MSMAll_2_d41_WRN_DeDrift.32k_fs_LR.dscalar.nii
 or direct me to a tutorial/howto on how to project those parcellation 
information to a nifti volume?

We are heavily based on FSL and it would be great to convert all the files in 
its format.

Thanks and sorry for the newbie question.


Francesco Sammartino


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