  Today the human brain can be modeled as a graph where nodes represent
different regions and links stand for statistical interactions between their
activities as recorded by different neuroimaging techniques. Empirical studies
have lead to the hypothesis that brain functions rely on the coordination of a
scattered mosaic of functionally specialized brain regions (modules or
sub-networks), forming a web-like structure of coordinated assemblies (a
network of networks). The study of brain dynamics would therefore benefit from
an inspection of how functional sub-networks interact between them. In this
paper, we model the brain as an interconnected system composed of two specific
sub-networks, the left (L) and right (R) hemispheres, which compete with each
other for centrality, a topological measure of importance in a networked
system. Specifically, we consideredfunctional brain networks derived from
high-density electroencephalographic (EEG) recordings and investigated how node
centrality is shaped by interhemispheric connections. Our results show that the
distribution of centrality strongly depends on the number of functional
connections between hemispheres and the way these connections are distributed.
Additionally, we investigated the consequences of node failure on hemispherical
centrality, and showed how the abundance of inter-hemispheric links favors the
functional balance of centrality distribution between the hemispheres.
