Hi Matt,
Here's the probtrackx calls: For network mode: probtrackx2 --network -x white-masks.txt -l --onewaycondition -c 0.2 -S 2000 --steplength=0.5 -P 5000 --fibthresh=0.01 --distthresh=0.0 --sampvox=0.0 --forcedir --opd -s Diffusion.bedpostX/merged -m Diffusion.bedpostX/nodif_brain_mask.nii.gz --dir=WHITE_NETWORKMODE For seed-to-ROI mode (in this example, the seed ROI is L_1.gii, but I did this for all 360 ROIs): probtrackx2 --seed=../whiteROIs/L_1.gii -l -c 0.3 -S 2000 --steplength=0.3 -P 5000 --fibthresh=0.01 --distthresh=20.0 --forcedir --opd -s ../Diffusion.bedpostX/merged -m ../Diffusion.bedpostX/nodif_brain_mask --dir=L1 --targetmasks=targets.txt --os2t --s2tastext Thanks! Karthik ________________________________ From: Glasser, Matthew <glass...@wustl.edu> Sent: Friday, September 1, 2017 8:16:51 AM To: Gopalakrishnan, Karthik; HCP-Users@humanconnectome.org Subject: Re: [HCP-Users] probtrackx network with HCP data and MMP parcellation Can you post your probtrackx call? Peace, Matt. From: <hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>> on behalf of "Gopalakrishnan, Karthik" <gkart...@gatech.edu<mailto:gkart...@gatech.edu>> Date: Thursday, August 31, 2017 at 9:27 PM To: "HCP-Users@humanconnectome.org<mailto:HCP-Users@humanconnectome.org>" <HCP-Users@humanconnectome.org<mailto:HCP-Users@humanconnectome.org>> Subject: [HCP-Users] probtrackx network with HCP data and MMP parcellation Hi all, I ran probtrackx for HCP subject 100206 using the MMP1.0 Glasser surface ROIs. My seeds in each ROI are at the white matter-gray matter boundary. I ran probtrackx in network mode as well as seed-to-ROI mode for the subject, and I applied the method described in http://journal.frontiersin.org/article/10.3389/fninf.2016.00046/full to infer structural networks from the resultant data from probtrackx. What I observe is that the networks aren't particularly dense. Since MMP1.0 has 360 ROIs, there are 360*359 = 129240 possible directed edges, but the networks I infer have about 2300 edges, which is a density of ~2%. Could someone share their insights on why I'm observing such low-density networks/where I might be doing something wrong? Thanks! 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 http://lists.humanconnectome.org/mailman/listinfo/hcp-users