The command you are looking for is -metric-to-volume-mapping for an ROI, or -label-to-volume-mapping for the entire label file. Note that these take gifti inputs, so you will need -cifti-separate and possibly -gifti-label-to-roi first (alternatively, -volume-label-to-roi afterwards). We don't have a command to give the center of gravity of an ROI, though - if you make a volume file containing the coordinates of every voxel (in matlab or octave), then you can use -volume-weighted-stats on it with -roi and -mean and that will give you center of gravity.
The problem we keep mentioning with MNI volume space is when it is used for averaging voxel data across subjects, because current volume registrations don't achieve the cross-subject functional correspondence that even folding-based surface registration does. It is valid to use surfaces and volumes of a single individual in MNI space (we actually do this with functional data, mostly for computational and storage reasons), and these are provided in the MNINonLinear folder. However, be aware that our MNI space is nonlinear registered, and as such it has local deformations of features compared to what the subject anatomy really is. Our "T1w" space is actually rigidly (rotation and translation only) registered to an MNI template, so you can treat it mostly like a linear MNI registration (however, note that the MNI templates and the related 12-DOF registrations have different expansion ratios on different axes compared to average human brain size). So, our "T1w" space is an anatomically accurate space for the subject, but has been mostly aligned to the MNI coordinate system. You will have to work out whether the slightly-larger MNI coordinates are compensated for in your software, and thus you would need to either "add in" the typical MNI scaling to our "T1w" coordinates, or do your own affine registration to MNI. Alternatively, if you can back out the computed solution into a subject-specific space before actually positioning the coils, then it may not matter that what you put into the software isn't "really" MNI space. Volume space issues are always a bunch of fun... Tim On Wed, Feb 13, 2019 at 12:36 PM Stevens, Michael < michael.stev...@hhchealth.org> wrote: > It also occurs to me that if someone has already worked out even roughly > approximate locations for parcels (e.g., centers?) that correspond to > volume space coordinates in MNI-land, this would be “good enough” for me to > finalize the grant proposal in the next day or so. Admittedly, I’d rather > learn which files/commands I can use to do the transformations directly so > I can explore a bit with real data. But I’d be really happy just to be > able to have something that allows us to generate the typical tDCS field > intensity mappings and electrode configuration for this grant proposal’s > methods section. > > > > Thanks! > > Mike > > > > > > *From:* Glasser, Matthew [mailto:glass...@wustl.edu] > *Sent:* Tuesday, February 12, 2019 10:58 PM > *To:* Stevens, Michael; hcp-users@humanconnectome.org > *Subject:* Re: [HCP-Users] Individualized HCP parcel to MNI coord > > > > EXTERNAL email from Outside HHC! Do NOT open attachments or click links > from unknown senders. > > If we leave out the “MNI coordinates” part of this question and think in > terms of the volume space coordinates of the individual being studied, it > is perfectly valid to bring results from the group surface back to an > individual’s physical volume space. Is a single coordinate what you need or > would an ROI be better? > > > > Matt. > > > > *From: *<hcp-users-boun...@humanconnectome.org> on behalf of "Stevens, > Michael" <michael.stev...@hhchealth.org> > *Date: *Tuesday, February 12, 2019 at 9:47 PM > *To: *"hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org> > *Subject: *[HCP-Users] Individualized HCP parcel to MNI coord > > > > Hi everyone, > > > > I know by now this is a tired subject that’s come up in several ways on > the HCP listserv over the past few years. But can y’all remind me the most > straightforward way to go backwards from a given HCP parcel (e.g., IFSa) > and find a reasonably close approximation in MNI space? > > > > The problems in working from “group level” surface data and the > differences from subject to subject have been discussed here before. But > I’m pretty sure I’m not risking those pitfalls with what I’m planning > here. I’m finalizing a study design and I need a “starting point” to > select precise brain stimulation coordinates for individuals. This study > formulation is based on several years’ worth of my fMRI data in HCP space > that I’ve done some things with ICA and DCM to put together some > interesting systems-level circuit maps. Now, based on findings within HCP > localized space, I want to use specific parcels to plan how best to > modulate those circuits experimentally with tDCS. The catch… of course… is > that the neurotargeting software works in voxelwise space. In practice, I > suspect this won’t be too significant a hurdle. I envision taking each > subject’s individual surface, backtracking a given HCP parcel to their own > volume space, then use neurotargeting software to figure out how to > optimize focality/field intensity to that region in volume space… purely on > a subject-by-subject basis. Even the individual parcel-to-volume mapping > would be nothing more than a starting point for individualized > optimization. You can only do so much to maximize tDCS focality… even with > impressive recent advances in multifocal current flow modeling. So there’s > always going to be some slop. The trick simply is to minimize that slop as > much as possible, including making sure I don’t inadvertently divert > current through OTHER key regions of the neural circuit. > > > > So what I lack is a set of wb_command’s that can do that individualized > back-tracking. If possible, I want to actually do this on my own data > prior to finalizing the grant proposal I’m working up right now, just to be > sure I’ve got all this right. I’ve already got some code (thank to y’all a > few months back) that uses the –volume-to-surface-mapping command to go the > OTHER way. Sure, I could make a string of guesses of which MNI coordinates > might map best to my target parcels, and test iteratively over a 100 or so > subject datasets until I find a convincing match. But it just seems > “cleaner” if I could simply do the reverse of this… That is, truly go from > a given parcel (e.g., IFSa) to MNI coordinate in each subject. I might’ve > missed it, but I just don’t see an obvious command candidate for going in > the other direction. If there’s not, is there a way to string together a > bunch of other wb_command’s to achieve this result? > > > > Any guidance would be welcome. Thanks in advance! > > > > Mike > > > > > > Michael C. Stevens, Ph.D. > > Director, CNDLAB, Olin Neuropsychiatry Research Center > > Director, Child & Adolescent Research, The Institute of Living > > Adjunct Professor of Psychiatry, Yale University School of Medicine > > > > > > > *This e-mail message, including any attachments, is for the sole use of > the intended recipient(s) and may contain confidential and privileged > information. Any unauthorized review, use, disclosure, or distribution is > prohibited. 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