It is also known that many of the networks of activity found in the resting brain are also observed in tasks ( 4).
Resting brain activity is far from random and has been shown to organize into a number of large-scale networks with characteristic spatial architectures ( 1– 3). Moreover, we find that the proportion of time that a subject spends in each brain network and metastate is a consistent subject-specific measure, is heritable, and shows a significant relationship with cognitive traits. One metastate is associated with sensory and motor regions, and the other involves areas related to higher order cognition. Further, this nonrandom sequencing is itself hierarchically organized, revealing two distinct sets of networks, or metastates, that the brain has a tendency to cycle within. We find that the transitions between networks are nonrandom, with certain networks more likely to occur after others.
We use an approach designed to find repeating network patterns in whole-brain resting fMRI data, where networks are defined as graphs of interacting brain areas. However, the extent to which large-scale networks exhibit their own organized temporal dynamics is unclear. The brain recruits neuronal populations in a temporally coordinated manner in task and at rest.