  The network architecture of the human brain has become a feature of
increasing interest to the neuroscientific community, largely because of its
potential to illuminate human cognition, its variation over development and
aging, and its alteration in disease or injury. Traditional tools and
approaches to study this architecture have largely focused on single scales --
of topology, time, and space. Expanding beyond this narrow view, we focus this
review on pertinent questions and novel methodological advances for the
multi-scale brain. We separate our exposition into content related to
multi-scale topological structure, multi-scale temporal structure, and
multi-scale spatial structure. In each case, we recount empirical evidence for
such structures, survey network-based methodological approaches to reveal these
structures, and outline current frontiers and open questions. Although
predominantly peppered with examples from human neuroimaging, we hope that this
account will offer an accessible guide to any neuroscientist aiming to measure,
characterize, and understand the full richness of the brain's multiscale
network structure -- irrespective of species, imaging modality, or spatial
resolution.
