Functional connectivity dynamically evolves on multiple time-scales over a static structural connectome: Models and mechanisms

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Over the last decade, we have observed a revolution in brain structural and functional Connectomics. On one hand, we have an ever-more detailed characterization of the brain's white matter structural connectome. On the other, we have a repertoire of consistent functional networks that form and dissipate over time during rest. Despite the evident spatial similarities between structural and functional connectivity, understanding how different time-evolving functional networks spontaneously emerge from a single structural network requires analyzing the problem from the perspective of complex network dynamics and dynamical system's theory. In that direction, bottom-up computational models are useful tools to test theoretical scenarios and depict the mechanisms at the genesis of resting-state activity.Here, we provide an overview of the different mechanistic scenarios proposed over the last decade via computational models. Importantly, we highlight the need of incorporating additional model constraints considering the properties observed at finer temporal scales with MEG and the dynamical properties of FC in order to refresh the list of candidate scenarios.HighlightsResting-state functional connectivity reveals a complex network dynamics.Several mechanistic scenarios have been proposed using whole-brain network models.Functional connectivity arises from interactions in the structural connectome.Dynamics on multiple time-scales have not always been addressed in models.Models and mechanisms considering neurophysiological rhythms are the most valuable.

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