Thanks Jennifer and Matt!

On Tue, Dec 15, 2015 at 9:05 PM, Glasser, Matthew <[email protected]>
wrote:

> We’ll have a multi-modally based parcellation for the MSMAll CIFTI data
> soon.
>
> Peace,
>
> Matt.
>
> From: <[email protected]> on behalf of Jennifer Elam <
> [email protected]>
> Date: Tuesday, December 15, 2015 at 3:51 PM
> To: 'Joelle Zimmermann' <[email protected]>, "Harms, Michael"
> <[email protected]>
> Cc: 'Greg Burgess' <[email protected]>, "[email protected]"
> <[email protected]>
>
> 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
> [email protected]
> www.humanconnectome.org
>
>
>
> *From:* [email protected] [
> mailto:[email protected]
> <[email protected]>] *On Behalf Of *Joelle Zimmermann
> *Sent:* Tuesday, December 15, 2015 2:42 PM
> *To:* Harms, Michael
> *Cc:* Greg Burgess; [email protected]
> *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 <[email protected]> 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
>
> St. Louis, MO  63110 Email: [email protected]
>
>
>
>
>
>
>
> On 12/15/15 11:51 AM, "Greg Burgess" <[email protected]> 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
>
> Email: [email protected]
>
>
>
> On Dec 15, 2015, at 11:24 AM, Joelle Zimmermann <
> [email protected]> 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 <[email protected]> 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
>
> St. Louis, MO  63110  Email: [email protected]
>
> From: Joelle Zimmermann <[email protected]>
>
> Date: Tuesday, December 15, 2015 9:35 AM
>
> To: "[email protected]" <[email protected]>
>
> 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
>
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