However that is actually how it is often done. Actually in so far as the connections follow the right path, tractography should give the best estimates and we used it that way in this paper:
http://www.jneurosci.org/content/36/25/6758.short Peace, Matt. From: "Gopalakrishnan, Karthik" <gkart...@gatech.edu<mailto:gkart...@gatech.edu>> Date: Friday, October 6, 2017 at 5:15 PM To: Matt Glasser <glass...@wustl.edu<mailto:glass...@wustl.edu>> Cc: Timothy Coalson <tsc...@mst.edu<mailto:tsc...@mst.edu>>, "hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>" <hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>> Subject: Re: [HCP-Users] Distance between surface ROIs in MMP Hi Matt/Tim, My goal is to improve network inference from tractography data by better accounting for the distance bias in tractography, so I want to use some proxy for actual connection distance between ROI pairs. Using tractography itself to account for its own bias against long-distance connections doesn’t make sense to me. Do you have any suggestions on how I could best compute this proxy? Regards, Karthik On Oct 5, 2017, at 8:50 AM, Glasser, Matthew <glass...@wustl.edu<mailto:glass...@wustl.edu>> wrote: Indeed I think we would need to know what you needed the distance for to know how best to compute it. For things like MR artifacts, a 3D distance might be most appropriate. For something like smoothing, a geodesic distance would be appropriate. For something neurobiological, the tractography distance might be most appropriate. Peace, Matt. From: <hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>> on behalf of Timothy Coalson <tsc...@mst.edu<mailto:tsc...@mst.edu>> Date: Tuesday, October 3, 2017 at 6:30 PM To: "Gopalakrishnan, Karthik" <gkart...@gatech.edu<mailto:gkart...@gatech.edu>> Cc: "hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>" <hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>> Subject: Re: [HCP-Users] Distance between surface ROIs in MMP Since ROIs are not points, distance between them becomes a trickier question. Since areas are connected through white matter rather than gray matter, that also implies that the easy ways to calculate distance may not be all that biologically relevant. This would point to using tractography to find distances. So, I don't think there is an easy answer, sorry. If you want to compute distance along the gray matter anyway, a possibility is to find the center of gravity of each ROI, translate them back to surface vertices (the centers will not actually be on the surface anymore, so you may want to double check them), and then find geodesic distances between those points (you can use -surface-geodesic-distance, running it once per area - you can then get the values from the other vertices near the centers to build the all-to-all matrix a row at a time). Note, however, that this will not give you a distance to areas in the other hemisphere. Tim On Tue, Oct 3, 2017 at 5:06 PM, Gopalakrishnan, Karthik <gkart...@gatech.edu<mailto:gkart...@gatech.edu>> wrote: Hi, I’m working with the Glasser multi-modal parcellation and I’d like to know if there is some prevalent notion of distance between any two surface ROIs in the parcellation? If there is, could you please tell me how I could obtain it or point me to a source? Thanks a lot! Regards, Karthik _______________________________________________ HCP-Users mailing list HCP-Users@humanconnectome.org<mailto:HCP-Users@humanconnectome.org> http://lists.humanconnectome.org/mailman/listinfo/hcp-users _______________________________________________ HCP-Users mailing list HCP-Users@humanconnectome.org<mailto:HCP-Users@humanconnectome.org> http://lists.humanconnectome.org/mailman/listinfo/hcp-users _______________________________________________ HCP-Users mailing list HCP-Users@humanconnectome.org http://lists.humanconnectome.org/mailman/listinfo/hcp-users
