Hi Andrew,

Use the -m (mask) option for the ROI, where it labels good vertices 1, excluded 
0, e.g.:

palm -i ${MetricIn} -m ${AtlasROI} -s ${SurfaceGii} ${VertexAreas} …

This repository has atlas roi shape.gii for multiple resolutions:

https://github.com/Washington-University/Pipelines/tree/master/global/templates/standard_mesh_atlases

… unless the course practicals list something later/greater.


Donna


> On Sep 29, 2016, at 2:25 PM, Andrew Poppe <poppe...@gmail.com> wrote:
>
> Hello gurus,
>
> I have successfully run first- and second-level stats on a data set that was 
> collected with HCP-compliant parameters, and I am ready to run group stats.
>
> I have looked at the HCP workshop materials (practicals) regarding using PALM 
> for group stats on dense data, and it does not mention masking anything that 
> I can see (I'm looking at practical 8 from the 2016 Course). However, I was 
> told that it would be better to mask out vertices on the medial wall of both 
> hemispheres as they will increase the number of tests being conducted but do 
> not actually contain useful data.
>
> Is this true? Should I be masking out zero voxels from cope images prior to 
> entering them into PALM?
>
>
> Thanks for your help,
>
> Andrew Poppe, Ph.D.
> Postdoctoral Researcher
> Olin Neuropsychiatry Research Center
> Institute of Living
> Hartford Hospital
> _______________________________________________
> HCP-Users mailing list
> HCP-Users@humanconnectome.org
> http://lists.humanconnectome.org/mailman/listinfo/hcp-users
>


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