Hi Michael and all, My goal is to use the aparc+aseg (in MNI from the standard Structural package 100307/MNINonLinear/aparc+aseg.nii.gz)as a parcellation for the volumetric 4D FIX extended clean data that's in MNI (100307/MNINonLinear/Results/rfMRI_REST1_RL/rfMRI_REST1_RL_hp2000_clean.nii.gz). However, the aparc+aseg and the fMRI volumetric 4D data are of different dimensions and resolution.
I'm assuming that the warp was really done in the same (MNI) template, but that the aparc+aseg parcellation was not resliced to match the 4D functional data? Is there another aparc+aseg that's of dimensions matching the volumetric 4D data (in MNINonLinear) that can be directly overlaid? Thanks, Joelle On Tue, Dec 15, 2015 at 1:02 PM, Harms, Michael <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 > St. Louis, MO 63110 Email: mha...@wustl.edu > > > > On 12/15/15 11:51 AM, "Greg Burgess" <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 > Email: gburg...@wustl.edu > > On Dec 15, 2015, at 11:24 AM, Joelle Zimmermann < > 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> 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: mha...@wustl.edu > From: Joelle Zimmermann <joelle.t.zimmerm...@gmail.com> > Date: Tuesday, December 15, 2015 9:35 AM > To: "hcp-users@humanconnectome.org" <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 > 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. 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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 http://lists.humanconnectome.org/mailman/listinfo/hcp-users
