Brain networks appear to have few and well localized regions with high functional connectivity density (hubs) for fast integration of neural processing, and their dysfunction could contribute to neuropsychiatric diseases. However the variability in the distribution of these brain hubs is unknown due in part to the overwhelming computational demands associated to their localization. Recently we developed a fast algorithm to map the local functional connectivity density (lFCD). Here we extend our method to map the global density (gFDC) taking advantage of parallel computing. We mapped the gFCD in the brain of 1031 subjects from the 1000 Functional Connectomes project and show that the strongest hubs are located in regions of the default mode network (DMN) and in sensory cortices, whereas subcortical regions exhibited the weakest hubs. The strongest hubs were consistently located in ventral precuneus/cingulate gyrus (previously identified by other analytical methods including lFCD) and in primary visual cortex (BA 17/18), which highlights their centrality to resting connectivity networks. In contrast and after rescaling, hubs in prefrontal regions had lower gFCD than lFCD, which suggests that their local functional connectivity (as opposed to long-range connectivity) prevails in the resting state. The power scaling of the probability distribution of gFCD hubs (as for lFCD) was consistent across research centers further corroborating the “scale-free” topology of brain networks. Within and between-subject variability for gFCD were twice than that for lFCD (20% vs. 12% and 84% vs. 34%, respectively) suggesting that gFCD is more sensitive to individual differences in functional connectivity. ► The study maps brain functional connectivity hubs in 1031 subjects. ► Cortical regions included prominent long-range connectivity hubs. ► The variability of the global hubs was higher than that of the local hubs. ► Gender effects accounted for 45% of the variability of the global hubs.