Mapping voxel-wise morphological connectivity in the single subject level using wavelet transform

The goal of this research is to build novel morphological connectivity in the single subject level. To this end, a cohort of healthy subjects with anatomical scans was obtained from a public database(https://www.nitrc.org/projects/multimodal/). The anatomical datasets were preprocessed and normalized to standard brain space. For each individual, wavelet-transform was applied on the VBM measures to obtain voxel-wise hierarchical features. The voxel-wise morphological connectivity was computed based on the wavelet features. Each preprocessed file is named in the following form: s3wKKI2009-{scan}_sym4_{w}_zscore_dc_{r}_DegreeCentrality_Positive{type}SumBrain.nii.gz san: scan sessions(i.e., 1, 2, 3,..., 42) w: wavelet scales(i.e., 3, 4, 5) r: thresholds(i.e., 0.5, 0.6, 0.7, 0.8, 0.9) type:type of network(i.e., Binarized or Weighted)