  Activity in the human brain moves between diverse functional states to meet
the demands of our dynamic environment, but fundamental principles guiding
these transitions remain poorly understood. Here, we capitalize on recent
advances in network science to analyze patterns of functional interactions
between brain regions. We use dynamic network representations to probe the
landscape of brain reconfigurations that accompany task performance both within
and between four cognitive states: a task-free resting state, an
attention-demanding state, and two memory-demanding states. Using the formalism
of hypergraphs, we identify the presence of groups of functional interactions
that fluctuate coherently in strength over time both within (task-specific) and
across (task-general) brain states. In contrast to prior emphases on the
complexity of many dyadic (region-to-region) relationships, these results
demonstrate that brain adapt- ability can be described by common processes that
drive the dynamic integration of cognitive systems. Moreover, our results
establish the hypergraph as an effective measure for understanding functional
brain dynamics, which may also prove useful in examining cross-task, cross-age,
and cross-cohort functional change.
