We’ll have a multi-modally based parcellation for the MSMAll CIFTI data soon.
Peace, Matt. From: <hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>> on behalf of Jennifer Elam <el...@pcg.wustl.edu<mailto:el...@pcg.wustl.edu>> Date: Tuesday, December 15, 2015 at 3:51 PM To: 'Joelle Zimmermann' <joelle.t.zimmerm...@gmail.com<mailto:joelle.t.zimmerm...@gmail.com>>, "Harms, Michael" <mha...@wustl.edu<mailto:mha...@wustl.edu>> Cc: 'Greg Burgess' <gcburg...@gmail.com<mailto:gcburg...@gmail.com>>, "hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>" <hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>> Subject: Re: [HCP-Users] ROI parcellation We have not distributed the Gordon et al. parcellation in any of the released HCP data yet. There are CIFTI surface-based parcellations available in both the Group Average and Connectome Workbench datasets available on the HCP project page in ConnectomeDB: https://db.humanconnectome.org/data/projects/HCP_900 as maps in the RSN-networks.32k_fs_LR.dlabel.nii file – the 7 and 17 RSN network parcellation from Yeo et al., JNP 2011 and the RSN network communities from Power et al., Neuron 2011. Best, Jenn Jennifer Elam, Ph.D. Outreach Coordinator, Human Connectome Project Washington University School of Medicine Department of Anatomy and Neurobiology, Box 8108 660 South Euclid Avenue St. Louis, MO 63110 314-362-9387<tel:314-362-9387> el...@pcg.wustl.edu<mailto:el...@pcg.wustl.edu> www.humanconnectome.org<http://www.humanconnectome.org> From: hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org> [mailto:hcp-users-boun...@humanconnectome.org] On Behalf Of Joelle Zimmermann Sent: Tuesday, December 15, 2015 2:42 PM To: Harms, Michael Cc: Greg Burgess; hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org> Subject: Re: [HCP-Users] ROI parcellation Thank you Michael, I found those aparc+asegs there. Is the Gordon et al. parcellation available in the package? Greg, I'm aware of the advantages of the functional parcellation, it's sort of a test run I'm starting off with the anatomical parcellations. Thanks for the refs. Joelle On Tue, Dec 15, 2015 at 1:02 PM, Harms, Michael <mha...@wustl.edu<mailto:mha...@wustl.edu>> wrote: Also, we encourage you to work in CIFTI-land so as to have a surface-based analysis of the cortical data. But to answer your question, volumetric versions of both those FS parcellations are available in each subject's MNINonLinear folder; e.g., 100307/MNINonLinear/aparc+aseg.nii.gz 100307/MNINonLinear/aparc.a2009s+aseg.nii.gz Those particular files should be part of the standard Structural package. cheers, -MH -- Michael Harms, Ph.D. ----------------------------------------------------------- Conte Center for the Neuroscience of Mental Disorders Washington University School of Medicine Department of Psychiatry, Box 8134 660 South Euclid Ave. Tel: 314-747-6173<tel:314-747-6173> St. Louis, MO 63110 Email: mha...@wustl.edu<mailto:mha...@wustl.edu> On 12/15/15 11:51 AM, "Greg Burgess" <gcburg...@gmail.com<mailto:gcburg...@gmail.com>> wrote: Hi Joelle, You should be aware of potential issues with using anatomically-defined ROIs for rfMRI network analysis. Smith, S. M., Miller, K. L., Salimi-Khorshidi, G., Webster, M., Beckmann, C. F., Nichols, T. E., et al. (2011). Network modelling methods for FMRI. NeuroImage, 54(2), 875–891. http://doi.org/10.1016/j.neuroimage.2010.08.063 Gordon, E. M., Laumann, T. O., Adeyemo, B., Huckins, J. F., Kelley, W. M., & Petersen, S. E. (2014). Generation and Evaluation of a Cortical Area Parcellation from Resting-State Correlations. Cerebral Cortex. http://doi.org/10.1093/cercor/bhu239 --Greg ____________________________________________________________________ Greg Burgess, Ph.D. Staff Scientist, Human Connectome Project Washington University School of Medicine Department of Neuroscience Phone: 314-362-7864<tel:314-362-7864> Email: gburg...@wustl.edu<mailto:gburg...@wustl.edu> On Dec 15, 2015, at 11:24 AM, Joelle Zimmermann <joelle.t.zimmerm...@gmail.com<mailto:joelle.t.zimmerm...@gmail.com>> wrote: Hi Michael, Thanks! So currently, the 2 available parcellation schemes are the Freesurfer Desikan-Killiany (aparc+aseg.mgz) and Destrieux (aparc.a2009s+aseg.mgz) in the structural extended preprocessed/T1w/mri folder? Im presuming these are in the subject's T1 individual subject space. Are you aware whether these parcellation schemes are already available in the MNI standard space? The goal is to parcellate the functional BOLD data (which are currently in MNI standard space; Ie in the FIX extended package, the MNINonLinear/Results/rfMRI_REST1_LR/rfMRI_REST1_LR_hp2000_clean.nii). Or alternatively, if you could point me to where the volumetric functional BOLD data in T1 space is (I cannot locate it in the FIX extended package - this only seems to have func already normalized to MNI), I could directly apply the aparc+aseg parcellation (that's in T1 space) to this. Thanks, Joelle On Tue, Dec 15, 2015 at 10:46 AM, Harms, Michael <mha...@wustl.edu<mailto:mha...@wustl.edu>> wrote: Hi, The only purely anatomical parcellation that is available currently are those provided by FreeSurfer, which you seem to be familiar with. If you are interested in a functional parcellation, there is the Gordon et al. parcellation derived from non-HCP rfMRI data. A parcellation that incorporates the myelin maps and rfMRI data and which is specifically derived from a subset of HCP participants is in the works (from Matt G.) cheers, -MH -- Michael Harms, Ph.D. ----------------------------------------------------------- Conte Center for the Neuroscience of Mental Disorders Washington University School of Medicine Department of Psychiatry, Box 8134 660 South Euclid Ave. Tel: 314-747-6173<tel:314-747-6173> St. Louis, MO 63110 Email: mha...@wustl.edu<mailto:mha...@wustl.edu> From: Joelle Zimmermann <joelle.t.zimmerm...@gmail.com<mailto:joelle.t.zimmerm...@gmail.com>> Date: Tuesday, December 15, 2015 9:35 AM To: "hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>" <hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>> Subject: [HCP-Users] ROI parcellation Hi everyone, Does HCP have a specific ROI parcellation that is commonly used/recommended? I would prefer to begin with anatomically (rather than functionally defined) ROIs. My goal is to parcellate the voxel-wise time series into larger ROIs. I've previously used the Desikan-Killiany atlas, but ideally would be interested in using something with a finer parcellation. The only HCP parcellation I was able to find was the parcellation from the ICA decomposition (resulting in one timeseries per ICA component), with 25, 50, 100, 200, 300 components. However, I don't think this is something I am interested in, as a single node (ie component) may comprise voxels that are scattered across the brain. Is there anything like an anatomical ROI parcellation that's typically used by HCP people? Thanks, Joelle _______________________________________________ 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 have received this email in error, please immediately notify the sender via telephone or return mail. _______________________________________________ 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 ________________________________ 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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