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Brain networks can be defined and explored through their connectivity. Here,we analyzed the relationship between structural connectivity (SC) across 2,514regions that cover the entire brain and brainstem, and their dynamic functionalconnectivity (DFC). To do so, we focused on a combination of two metrics: thefirst assesses the degree of SC-DFC similarity and the second is the intrinsicvariability of the DFC networks over time. Overall, we found that cerebellarnetworks have a smaller DFC variability than other networks in the brain.Moreover, the internal structure of the cerebellum could be clearly divided intwo distinct posterior and anterior parts, the latter also connected to thebrainstem. The mechanism to maintain small variability of the DFC in theposterior part of the cerebellum is consistent with another of our findings,namely, that this structure exhibits the highest SC-DFC similarity relative tothe other networks studied. By contrast, the anterior part of the cerebellumalso exhibits small DFC variability but it has the lowest SC-DFC similarity,suggesting a different mechanism is at play. Because this structure connects tothe brainstem, which regulates sleep cycles, cardiac and respiratoryfunctioning, we suggest that such critical functionality drives the lowvariability in the DFC. Overall, the low variability detected in DFC expandsour current knowledge of cerebellar networks, which are extremely rich andcomplex, participating in a wide range of cognitive functions, from movementcontrol and coordination to executive function or emotional regulation.Moreover, the association between such low variability and structure suggeststhat differentiated computational principles can be applied in the cerebellumas opposed to other structures, such as the cerebral cortex.

Small variation in dynamic functional connectivity in cerebellar networks