Dear Matthew, thanks again for your answer. Just to clarify, after I run -cifti-average-roi–correlation on each participant, do I then merge all the .dscalar.nii files for the members of the respective group before comparing the groups with PALM? Do I do it with -cifti -concatenate?
thanks for all your help. best, Lisa On 7 April 2017 at 22:07, Glasser, Matthew <[email protected]> wrote: > > 1. The order of the pipelines is PreFreeSurfer —> FreeSurfer —> > PostFreeSurfer —> fMRIVolume —> fMRISurface —> ICA+FIX —> MSMAll —> > Analysis. MSMAll is not yet officially released, but we have had a few > people beta testing it. > 2. The output of -cifti-average-roi–correlation would be a > .dscalar.nii file. I would run the command for each participant, as you > said you wanted to do group level stats (which will be based essentially on > the means and variances of your group). > > Matt. > > From: <[email protected]> on behalf of Lisa > Kramarenko <[email protected]> > Date: Friday, April 7, 2017 at 9:06 AM > To: "[email protected]" <[email protected]> > Subject: [HCP-Users] Fwd: Help with the group comparison of seed-based FC > > Dear Matthew, > > thanks for your reply and tips! Naturally, I have a couple more questions. > > 1. What exactly the order of the pipelines would be? (I am still stuck at > the functional preprocessing right now, so I'm not that far yet). Would it > be both functional ones (volume and surface), then ICA+FIX and then MSMAll? > > 2. I'm sorry but I also didn't quite get the procedure for th > e -cifti-average-roi-correlation. I only have one run per subject so I > don't need to average the runs. > So when I have the individual outputs after all the above mentioned > pipelines (.dtseries.nii, right?) do I just use all of them (for one group) > with a -cifti flag for each as input files in one command or do I run the > command for every single participant of a group and afterwards merge the > outputs? I want to do group-level comparison so at some step I need to > create group maps. Or am I misunderstanding something? > > Sorry for such basic confused questions and thanks a lot! > > Lisa > > On 5 April 2017 at 21:05, Glasser, Matthew <[email protected]> wrote: > >> I recommend you use the MSMAll aligned, ICA+FIX denoised data and use >> wb_command -cifti-average-roi-correlation. You may or may not chose to >> do something like global signal regression to clean up residual global >> artifact in the data (which ICA+FIX is not designed to remove) depending on >> if you think leaving in global signals will create a bigger positive bias >> than removing the mean of the RSNs will create a negative bias (or just >> analyze things both ways). We are working on a better solution for this >> issue that does not require removing the mean of the RSNs when cleaning up >> global artifact (i.e. remove the positive bias in connectivity without >> adding in a negative bias). >> >> You can make a -vol-roi of the hippocampus by extracting it from this >> file ${StudyFolder}/${Subject}/MNINonLinear/Results/Atlas_ROIs.2.nii.gz. >> I would use a -cifti flag for each run of a given subject, but run separate >> commands per subject to generate one dense scalar correlation map per >> subject. You can then do statistics on these maps (e.g. with the FSL PALM >> software tool). You may wish to do the Fisher transform on the correlation >> maps first with wb_command -cifti-math “atanh(x)” <output> -var x <input> >> >> Peace, >> >> Matt. >> >> From: <[email protected]> on behalf of Lisa >> Kramarenko <[email protected]> >> Date: Wednesday, April 5, 2017 at 4:40 AM >> To: "[email protected]" <[email protected]> >> Subject: [HCP-Users] Help with the group comparison of seed-based FC >> >> Hello dear experts, >> >> I am very new to HCP so I am struggling with a lot of confusion and hope >> you can help. I would like to calculate seed-based FC of hippocampus of two >> groups (patients/controls) and to perform a group comparison between them. >> Now I am not sure about how to proceed. I see two possible ways: >> >> 1. I could merge .dtseries.nii files for all the subjects in a group with >> cifti-merge to create a group-average dense connectome. However, how do I >> extract the connectivity of the seed of interest and how do I I perform >> statistical analysis on it? >> 2. Or, if I understand correctly, I can use -cifti-average-roi-correlation. >> However, I am not sure about the inputs. Should I first merge .dtseries.nii >> files for all subjects in a group, take this as <cifti-in> and then extract >> hippocampus from Atlas_ROIs.2.nii.gz with cifti-separate and use it >> as <roi-vol>? Second question is when I managed to run it, what would the >> output be and how do I perform statistical analysis on it? >> >> I would be super grateful if you could clarify what the right way is and >> give me a short step-by-step of how to do a seed-based group-level analysis. >> >> Thanks a lot! >> Lisa >> >> _______________________________________________ >> HCP-Users mailing list >> [email protected] >> http://lists.humanconnectome.org/mailman/listinfo/hcp-users >> >> >> ------------------------------ >> >> The materials in this message are private and may contain Protected >> Healthcare Information or other information of a sensitive nature. If you >> are not the intended recipient, be advised that any unauthorized use, >> disclosure, copying or the taking of any action in reliance on the contents >> of this information is strictly prohibited. If you have received this email >> in error, please immediately notify the sender via telephone or return mail. >> > > > _______________________________________________ > HCP-Users mailing list > [email protected] > http://lists.humanconnectome.org/mailman/listinfo/hcp-users > > > ------------------------------ > > The materials in this message are private and may contain Protected > Healthcare Information or other information of a sensitive nature. If you > are not the intended recipient, be advised that any unauthorized use, > disclosure, copying or the taking of any action in reliance on the contents > of this information is strictly prohibited. If you have received this email > in error, please immediately notify the sender via telephone or return mail. > _______________________________________________ HCP-Users mailing list [email protected] http://lists.humanconnectome.org/mailman/listinfo/hcp-users
