Hi everyone,
i am trying for the MEG practicals to downsample a 32K dconn fMRI group
functional connectivity cifti:
HCP_S900_820_rfMRI_MSMAll_groupPCA_d4500ROW_zcorr.dconn.nii
into a dconn cifti in the 4K space that we use in the MEG analysis in OT4.
I am trying to use cifti-resample to do so.
Hi Georgios,
I would not recommend downsampling a dense connectome. Instead it would
be better to downsample the dense timeseries and then recompute the dense
connectome.
Peace,
Matt.
On 7/16/16, 9:47 AM, "hcp-users-boun...@humanconnectome.org on behalf of
Georgios Michalareas" wrote:
>Hi ev
Thanks for the tip Matt.
I ll stick to parcellations for comparing fMRI and MEG connectivity in
the practicals.
But in any case , if one would want to do such a deconn resampling , do
you know what is the mistake(s) I am doing in the command below?
Thanks again
Giorgos
On 7/16/2016 4:49 PM
Hi Georgios,
Looks like you asked for adaptive barycentric resampling without providing
areas to use (the algorithm does not accept spherical surfaces to be the
source of anatomical vertex areas). Resampling a dense connectome would
only be appropriate for tractography data. For fMRI data, you w
Thanks
On 7/16/2016 5:03 PM, Glasser, Matthew wrote:
> Hi Georgios,
>
> Looks like you asked for adaptive barycentric resampling without providing
> areas to use (the algorithm does not accept spherical surfaces to be the
> source of anatomical vertex areas). Resampling a dense connectome would
To clarify, the ADAP_BARY_AREA method requires either the -*-area-surfs or
-*-area-metrics options of each spheres option. While they would proceed
if you gave the spheres for the area surfs options, it is not recommended
(you should use midthickness surfaces for individuals, and midthickness
vert