Fig. 3
Pipeline scheme: A. Parcellation into cortical regions of intrinsic networks, based on the Schaefer atlas (100 regions, representing 7 networks) and subcortical and cerebellar regions from the AAL116 atlas: fronto-parietal (FPN), default mode (DMN), dorsal attention (DAN), limbic (LN), ventral attention (VAN), somatomotor (SMN), visual (VN), subcortical (SUB) and cerebellar (CRB). The parcellated data is used for FC computation, by calculating the Pearson correlation between the average time-courses of each pair of regions; B. The lower triangular matrix (excluding the diagonal) of each FC matrix was vectorized and they were all concatenated for PCA decomposition and reconstruction varying the number of PCs N, for each sample k, using the corresponding weights w and mean μ; C. Multilevel clinical connectome fingerprinting framework with PCs selection using a multilevel identifiability matrix corresponding to the Pearson correlation between vectorized FC matrices for all possible combinations of subjects/sessions (samples). In this matrix, for each level, Iwithin corresponds to the average of the elements in dark gray, Iothers corresponds to the average of the elements in light gray and Idiff (%) corresponds to 100×(Iwithin-Iothers). The FC fingerprints are obtained by reconstructing the data using only the selected number of PCs; D. FC fingerprint correlation was computed within-subject, within-session and between-group by averaging the correlation values per subject for each of these cases; E. Computation of Network-Based Statistic (NBS) for within- and between-group FC analysis. F. Association of identifiability metrics and average FC significant edges (found with NBS) with clinical features, using Spearman correlation.