Data from: Dissecting whole-brain conduction delays through MRI microstructural measures

This dataset was used in the paper by Mancini et al. "Dissecting whole-brain conduction delays through MRI microstructural measures" (Brain Structure and Function, 2021). The data describe brain structural connectivity patterns in healthy subjects using multiple microstructural measures. The code to reproduce the results presented in the paper is available at the following GitHub repository: https://github.com/matteomancini/dissecting-conduction-delays<br>The dataset is provided in the form of connectivity matrices saved as MAT files, reconstructed using two different brain atlases (cmat_dk.mat - Desikan-Killiany atlas, with related labels provided in labels.txt; cmat_lau.mat - Lausanne atlas) as well as with an additional filtering step (cmat_c2.mat - filtered with COMMIT2). The connectivity matrices are arranged in 4D arrays, where the first dimension represents the subjects, the second dimension the specific measure (listed in order in cmat_measures.mat), and the third and fourth dimensions the connections between two given regions. For the Desikan-Killiany atlas, a group connectivity matrix is also provided (group_cmat.mat). Finally, results obtained using the Kuramoto model with delays are provided (kuramoto.mat), describing the global synchronization (in the array rmean) and metastability (in the array rstd) as a function of the coupling factor (in the array lambda).