Hi team HCP, I have two semi-related questions about generating resting-state gradients:
1) What is the theoretical motivation behind using cifti-correlation-gradient rather than cifti-gradient to generate a resting-state gradient .dscalar.nii from a .dconn.nii file, per this thread ( http://www.mail-archive.com/hcp-users%40humanconnectome.org/msg01431.html )? Based on the documentation, cifti-gradient takes the first spatial derivative of the input .dconn.nii (i.e. the correlation matrix of every voxel/vertex) and (optionally) averages them. Cifti-correlation-gradient, by contrast, first correlates the .dconn.nii correlation matrix, and then takes the spatial derivative of the resulting maps and averages them. What is the purpose of this second-order correlation? 2) Is it possible to generate volume-based dense connectomes and downstream resting-state gradients using the HCP tools? My goal is to examine resting-state gradients just beyond the edges of the subcortical volume as defined in grayordinate space. Thank you for any feedback! -Ely _______________________________________________ HCP-Users mailing list [email protected] http://lists.humanconnectome.org/mailman/listinfo/hcp-users
