Dynamics of large-scale fMRI networks: Deconstruct brain activity to build better models of brain function

Abstract Ongoing fluctuations of brain activity measured by functional magnetic resonance imaging (fMRI) provide a novel window onto the organizational principles of brain function. Advances in data analysis have focussed on extracting the constituting elements of temporal dynamics in terms of activity or connectivity patterns. Subsequently, brain states can be defined and then be analyzed using temporal features and computational models as to capture subtle interactions between functional networks. These new methodological advances allow to deconstruct the rich spatiotemporal structure of functional components that dynamically assemble into resting-state networks long been observed using conventional measures of functional connectivity. Applications of these emerging methods demonstrate that changes in functional connectivity are indeed driven by complex reorganization of network interactions, and thus provide valuable observations to build better models of brain function and dysfunction. Here, we give an overview of the recent developments in this exciting field, together with main findings and perspectives on future research.