Matt, thank you very much for your explanations. Taking a pragmatic view, I just loaded the time series data from the grayordinates file rfMRI_REST1_LR_Atlas_hp2000_clean.dtseries.nii
picked up one of the time series and subtracted it from all of the time series in the file rfMRI_REST1_LR_hp2000_clean.nii.gz There was no match. This answers my question about the location of the grayordinates in the full MNI space time series data. Basically, the time series in grayordinates from the file rfMRI_REST1_LR_Atlas_hp2000_clean.dtseries.nii are not a subset of MNI space 91x109x91 1200 time point time series data from the file rfMRI_REST1_LR_hp2000_clean.nii.gz Therefore, grayordinate time series data are obtained after registration transformations targeting the surface points, I am guessing, as you explained in your e-mails. Please allow me to follow up by asking if there is a segmentation or a binary mask on the 91x109x91 data set (rfMRI_REST1_LR_hp2000_clean.nii.gz) for example using the 1st time point brain volume that gives the segmentation for the cortex? Thanks in advance and thank you for your patience, alpay On 28-Mar-15 11:19, Glasser, Matthew wrote: > The surface grayordinates simply don’t exist in a 3D cartesian space, they > exist on a 2D surface mesh made up of triangular tiles and their neighbors > are determined by the topology of that mesh. Most vertices have six > neighbors, but a very few have 5 (also those along the medial wall may > have fewer valid neighbors for a different reason). You find the > neighbors of surface grayordinates by looking at the topology section of a > GIFTI surface file. The first data array of a GIFTI surface file are the > 3D coordinates of each vertex, the second data array are the topological > relationships between the vertices that form each triangular tile. > Individual subject standard mesh surfaces may have different 3D > coordinates across subjects, but always have the same topology and hence > are said to be on the same mesh. It is this standard mesh that is the > equivalent of a standard voxel grid in volume space. We provide the > command wb_command -surface-geodesic-rois that you can use to find the > nearest surface vertices within some number of mm of a given vertex. > There is the command wb_command -surface-geodesic-distance which you can > use to compute the distances between a vertex and the rest of the surface > (you can limit this to a max distance to speed it up). Finally, there is > the command wb_command -cifti-export-dense-mapping that will tell you > which grayordinate indices correspond to which surface vertex indices or > subcortical voxels. Perhaps one or more of these will address your > request. > > If for some reason you need to know about an individual subject’s voxels, > you can work with the data before it has been resampled to grayordinates > space and then resample any results to grayordinates space after you’re > done (however you’ll want to be sure you are only working with voxels > inside the greymatter ribbon). You’ll also need to be careful you don’t > accidentally average across subjects in volume space or smooth the data in > volume space. At some point we’ll make it possible to completely reverse > the grayordinates projection (e.g. go from group average results in > grayordiantes space to individual subject native or MNI volume space), but > this has not yet been a high enough priority for our developers, as most > people don’t need to run their analysis in that direction. > > I’ll be honest that despite your lengthy e-mail, I’m not really clear what > you are doing and hence why you need what you are requesting. If you > don’t want to post sensitive details in public, you can e-mail me off the > list. If you don’t want to tell me specifically what you’re up to, I’m > more limited in my ability to help. > > Peace, > > Matt. > > On 3/28/15, 8:44 AM, "Alpay Özcan" <[email protected]> wrote: _______________________________________________ HCP-Users mailing list [email protected] http://lists.humanconnectome.org/mailman/listinfo/hcp-users
