I would have a look at PALM’s documentation. I am not sure. Peace,
Matt. From: Lisa Kramarenko <lisa.kramare...@gmail.com<mailto:lisa.kramare...@gmail.com>> Date: Monday, April 10, 2017 at 6:24 AM To: Matt Glasser <glass...@wustl.edu<mailto:glass...@wustl.edu>> Cc: "hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>" <hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>> Subject: Re: [HCP-Users] Fwd: Help with the group comparison of seed-based FC 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 <glass...@wustl.edu<mailto:glass...@wustl.edu>> 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: <hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>> on behalf of Lisa Kramarenko <lisa.kramare...@gmail.com<mailto:lisa.kramare...@gmail.com>> Date: Friday, April 7, 2017 at 9:06 AM To: "hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>" <hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>> 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 the -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 <glass...@wustl.edu<mailto:glass...@wustl.edu>> 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: <hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>> on behalf of Lisa Kramarenko <lisa.kramare...@gmail.com<mailto:lisa.kramare...@gmail.com>> Date: Wednesday, April 5, 2017 at 4:40 AM To: "hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>" <hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>> 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 HCP-Users@humanconnectome.org<mailto:HCP-Users@humanconnectome.org> 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. 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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 HCP-Users@humanconnectome.org http://lists.humanconnectome.org/mailman/listinfo/hcp-users
