The authors review evidence that spontaneous, that is, not stimulus or task driven, activity in the brain at the level of large-scale neural systems is not noise, but orderly and organized in a series of functional networks that maintain, at all times, a high level of coherence. These networks of spontaneous activity correlation or resting state networks (RSN) are closely related to the underlying anatomical connectivity, but their topography is also gated by the history of prior task activation. Network coherence does not depend on covert cognitive activity, but its strength and integrity relates to behavioral performance. Some RSN are functionally organized as dynamically competing systems both at rest and during tasks. Computational studies show that one of such dynamics, the anticorrelation between networks, depends on noise-driven transitions between different multistable cluster synchronization states. These multistable states emerge because of transmission delays between regions that are modeled as coupled oscillators systems. Large-scale systems dynamics are useful for keeping different functional subnetworks in a state of heightened competition, which can be stabilized and fired by even small modulations of either sensory or internal signals.