Hello all, I have a set of ROIs, in MNI-space and nifti format - basically binary boxes where '1' indicates the ROI. I'd like to use these masks to process some of the group-averaged rfMRI data, extracting activation time series and computing cross-correlations and so on. But I'm having trouble projecting either data-type onto the other.
HCP Data: When I read the file: <HCP_Q1-Q6_R468_rfMRI_groupPCA_d4500_Eigenmaps.dtseries.nii> into Matlab (using cifitopen), I get a 2D matrix which is ~92,000x4500 cells. As I understand (but please correct me I'm wrong), this matrix has 'grayordinates' as rows and time as columns. ROIs: My regions are in boxes, in MNI space of size [91,109,91]. These regions have been used as seeds for other analyses that don't involve HCP data, so even though they may be 'worse' than the HCP data, in the sense that they don't represent surface features explicitly, I'm not keen to dump them in favour of a more natively surface-including parcellation. What I need to do, is work out what grayordinates go with what ROI (or vice versa). I either need to convert the HCP data into 4D (brain-box + time), or convert my brain-box ROIs into grayordinate vectors. I've searched the forum for answers here, and tried to convert the HCP files to nifti, but even allowing for the rather odd 'wrapping' of the voxels into 3 dimensions, I'm finding I can't quite work the conversion out. Can anyone help? Many thanks, Tom Thomas Hope Wellcome Trust Centre for Neuroimaging Institute of Neurology University College London 12 Queen Square LONDON, WC1N 3BG E-mail: [email protected]<mailto:[email protected]> Website: www.ucl.ac.uk/ploras<http://www.ucl.ac.uk/ploras> [cid:[email protected]] [cid:[email protected]] _______________________________________________ HCP-Users mailing list [email protected] http://lists.humanconnectome.org/mailman/listinfo/hcp-users
