  Human brain structural networks contain sets of centrally embedded hub
regions that enable efficient information communication. However, it remains
largely unknown about categories of structural brain hubs and their
microstructural, functional and cognitive characteristics as well as
contributions to individual identification. Here, we employed three multi-modal
imaging data sets with structural MRI, diffusion MRI and resting-state
functional MRI to construct individual structural brain networks, identify
brain hubs based on eight commonly used graph-nodal metrics, and perform
comprehensive validation analysis. We found three categories of structural hubs
in the brain networks, namely, aggregated, distributed and connector hubs.
Spatially, these distinct categories of hubs were primarily located in the
default-mode system and additionally in the visual and limbic systems for
aggregated hubs, in the frontoparietal system for distributed hubs, and in the
sensorimotor and ventral attention systems for connector hubs. Importantly,
these three categories of hubs exhibited various distinct characteristics, with
the highest level of microstructural organization in the aggregated hubs, the
largest wiring cost and topological vulnerability in the distributed hubs, and
the highest functional associations and cognitive flexibility in the connector
hubs, although they behaved better regarding these characteristics compared to
non-hubs. Finally, all three categories of hub indices displayed high
across-session spatial similarities and acted as a structural fingerprint with
high predictive rates (100%, 100% and 84.2%) for individual identification.
Collectively, our findings highlighted three categories of brain hubs with
differential microstructural, functional and cognitive associations, which may
shed light on the topological mechanisms of the human connectome.
