Before revision:  We find that brain states are composed of interdigitated functional networks and exhibit context-dependent dynamics . Using diffusion-weighted imaging acquired from the same subjects, we show that structural connectivity constrains the temporal progression of brainstates. We also combine tools from network control theory with geometrically conservative null models to demonstrate that brains are wired to sup- port states of high activity in default mode areas, while requiring relatively low energy .
After revision:  We find that brain states are composed of interdigitated functional networks and exhibit context-dependent dynamics . Using diffusion-weighted imaging acquired from the same subjects, we use tools from network control theory to show that linear spread of activity along white matter connections constrains the brain's state space trajectories at rest. Additionally, accounting for stimulus-driven visual inputs explains the different trajectories taken during the n-back task. We also used models of network rewiring to show that these findings are the result of non-trivial geometric and topological properties of white matter architecture .