… , sparse, non-negative function networks with high functional coherence. The individual
large-scale functional network … associations between individual functional topography variations …

… sparse coefficients. Here, dictionaries represent the co-activation patterns of functional networks
… estimate the organization of large-scale distributed cortical networks. They employed a …

… (A) 39 ICs were identified and grouped into seven resting state networks; (B) the structural
connectivity matrix … State 2 is mainly characterized by sparse connectivity within and between …

… networks”—sets of segregated brain regions that exhibit similar responses following slow
changes in systemic physiology—resemble patterns associated with large-scale networks …

… networks of each large-scale network show higher functional homogeneity that together support
the network… However, resting state fMRI (rsfMRI) parameters are the same across all sites…

… nostic classification on the large-scale aggregated data sets. In … network (DBN) and the
Autism Brain Imaging Data Exchange (ABIDE) database, which is a worldwide multisite functional …

… select the optimal threshold to sparse the network, as well as … large-scale ECSN analysis,
to explore the relationship between the inter-regional community similarity of resting-state fMRI …

… (23) used large-scale network (LSN) analysis with an AUC of … series to construct brain
function network, and linear SVM … (46) was used to solve sparse linear regression. To solve the …

… in the spatial distribution of large-scale functional networks between MDD patients before
ECT and HC as well as MDD patients after ECT, we measured the network variability in three …

… cognitive impairment through the functional interaction of plasma NFL with large-scale brain
… between all functional networks was very sparse. Compared with state 2, state 4 showed the …