The study of brain dynamics enables us to characterize the time-varying functional connectivity among distinct neural groups. However, current methods suffer from the absence of structural connectivity information. We propose to integrate infra-slow neural oscillations and anatomical-connectivity maps, as derived from functional and diffusion MRI, in a multilayer-graph framework that captures transient networks of spatio-temporal connectivity. These networks group anatomically wired and temporary synchronized brain regions and encode the propagation of functional activity on the structural connectome. In a group of 71 healthy subjects, we find that these transient networks demonstrate power-law spatial and temporal size, globally organize into wellknown functional systems and describe wave-like trajectories of activation across anatomically connected regions. Within the transient networks, activity propagates through polysynaptic paths that include selective ensembles of structural connections and differ from the structural shortest paths. In the light of the communication-through-coherence principle, the identified spatio-temporal networks could encode communication channels' selection and neural assemblies, which deserves further attention. This work contributes to the understanding of brain structure-function relationships by considering the time-varying nature of restingstate interactions on the axonal scaffold, and it offers a convenient framework to study large-scale communication mechanisms and functional dynamics.
The work of Griffa et al. REF proposes a method to captures the network of spatio-temporal connectivity integrating neural oscillations and anatomical connectivity from diffusion fMRI.
Transient networks of spatio‐temporal connectivity map communication pathways in brain functional systems
Neuroimage
Computer Science Medicine