1. The HCP-YA data were not variance normalized. 2. wb_command -cifti-parcellate 3. There isn’t a good sub-cortical parcellation like the cortical parcellation yet unfortunately.
If you are comparing functional connectivity across runs within a subject, you don’t need to concatenate or variance normalize the runs. Matt. From: Tali Weiss <tali.we...@weizmann.ac.il<mailto:tali.we...@weizmann.ac.il>> Date: Sunday, March 3, 2019 at 4:28 AM To: Matt Glasser <glass...@wustl.edu<mailto:glass...@wustl.edu>>, "hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>" <hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>> Subject: RE: [HCP-Users] rs-fMRI with-in subject comparison Thank you Mattew! 1. Download Packages: State fMRI FIX-Denoised (Compact) {Subject}_REST/MNINonLinear/Results/{fMRIName}/{fMRIName}_Atlas_MSMAll_hp2000_clean.dtseries.nii - The raw data were zscore (overall standard deviation) and then cleaned by sICA+FIX? - In wb there is a layer: .dynconn.nii. Is it for each of the 4 rs-scan of each subject? 2. I’m not sure which command I need to use to extract the timecourse of each parcel and then to apply correlation between all parcel of each network. input_label= Q1-Q6_RelatedValidation210.CorticalAreas_dil_Final_Final_Areas_Group_Colors.32k_fs_LR.dlabel.nii wb_command -cifti-all-labels-to-rois $input_label 1 ROIvalidation210.dscalar.nii what I need to do next? 3. I like to create correlation also between subcortical (volume). I read your article https://www.ncbi.nlm.nih.gov/pubmed/29925602 What is your recommendation to define subcortical volume? My analysis is “within subject” paradigm (comparing the scans in different days). ________________________________ From: Glasser, Matthew [glass...@wustl.edu<mailto:glass...@wustl.edu>] Sent: Thursday, February 28, 2019 3:39 AM To: Tali Weiss; hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org> Subject: Re: [HCP-Users] rs-fMRI with-in subject comparison 1. You would need to post the full path and filename. 2. This will be handled by multi-run sICA+FIX in the future. We will recommend all data be cleaned with sICA+FIX. Really you want to be dividing by the unstructured noise standard deviation, rather than the overall standard deviation. 3. Parcels have more statistical power than grayordinates. The HCP’s multi-modal parcellation is here: https://balsa.wustl.edu/file/show/3VLx Matt. From: <hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>> on behalf of Tali Weiss <tali.we...@weizmann.ac.il<mailto:tali.we...@weizmann.ac.il>> Date: Wednesday, February 27, 2019 at 7:26 AM To: "hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>" <hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>> Subject: [HCP-Users] rs-fMRI with-in subject comparison Dear Prof.Smith, I really appreciate your help. I like to compare the second rs-fmri scan (from two different days) of the same subject. 1.when i open MSMAII_hp2000_clean.dtseries in WB, I get also a layer "dynconn", for example: rfMRI_REST1_LR_Atlas_MSMAII_hp2000_clean.dynconn.nii Are those group average? 2. It is recommended in the HCP Users FAQ: "demean and normalize the individual timeseries." wb_command -cifti-math '(x - mean) / stdev' <output> I am confused because it is writing demean andnormalize. (zscore include demean, am I missing something?). My design is "within", so should I only apply demean? or because it is in a different day I should apply zscore? 3. I believe that statistically there are not enough time points in one scan to use all grayordinates. Thus, I will need to chose parcels/ROI. What is the best parcels/ROI I can use? (I like to focus on the attentional network, working memory and DMN) Is there an easy way to get those ROIs from the tasks? Thank you Tali _______________________________________________ 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. If you have received this email in error, please immediately notify the sender via telephone or return mail. ________________________________ 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 HCP-Users@humanconnectome.org http://lists.humanconnectome.org/mailman/listinfo/hcp-users
