1) I would recommend starting with the MIGP dense PCASeries instead of the
connectome (the .dtseries.nii file), as you can get the benefits of
averaging the ³timeseries² within the ROI prior to computing the
correlation.  You can use this command for this purpose: wb_command
-cifti-average-roi-correlation.

2) The dense connectome is in CIFTI grayordinates space.  You can learn
more about CIFTI and grayordinates from these references:

http://www.nature.com/neuro/journal/v19/n9/abs/nn.4361.html
http://www.sciencedirect.com/science/article/pii/S1053811913005053

The subcortical data are in MNI space, but the surface data are on a
registered 32k mesh that has been aligned across subjects using areal
features (such as myelin, and resting state connectivity) to give better
cross-subject alignment than traditional volume-based alignment approaches
to MNI space.

Peace,

Matt.

On 11/18/16, 5:06 AM, "hcp-users-boun...@humanconnectome.org on behalf of
Nicola Toschi" <hcp-users-boun...@humanconnectome.org on behalf of
tos...@med.uniroma2.it> wrote:

>Hi List,
>
>we are working with the R820 dense connectome (in connectome workbench)
>and have a few (basic?) questions which we are struggling with:
>
>1) What is the recommended sequence of commands to extract a seed-based
>connectome from the 33GB dense connectome file (e.g. all nodes which are
>connected to a ROI in greyordinate space, say the right amygdala for
>example), ad successively visualize it in the workbench? We tried to do
>this with the matlab tools but without success.
>
>2) What exactly is the native coordinate space in which the dense
>connectome 'lives' (the workbench visualizes coordinates in mm, but they
>do not look like MNI coordinates)?
>
>Thank you very much in advance!
>
>Nicola
>_______________________________________________
>HCP-Users mailing list
>HCP-Users@humanconnectome.org
>http://lists.humanconnectome.org/mailman/listinfo/hcp-users


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