  Recent advances in computational models of signal propagation and routing in
the human brain have underscored the critical role of white matter structure. A
complementary approach has utilized the framework of network control theory to
better understand how white matter constrains the manner in which a region or
set of regions can direct or control the activity of other regions. Despite the
potential for both of these approaches to enhance our understanding of the role
of network structure in brain function, little work has sought to understand
the relations between them. Here, we seek to explicitly bridge computational
models of communication and principles of network control in a conceptual
review of the current literature. By drawing comparisons between communication
and control models in terms of the level of abstraction, the dynamical
complexity, the dependence on network attributes, and the interplay of multiple
spatiotemporal scales, we highlight the convergence of and distinctions between
the two frameworks. Based on the understanding of the intertwined nature of
communication and control in human brain networks, this work provides an
integrative perspective for the field and outlines exciting directions for
future work.
