Mapping voxel-wise morphological connectivity in the single subject level using wavelet transform
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https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/PRC6CM
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资源简介：
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)
提供机构：
Harvard Dataverse
创建时间：
2018-04-25
