The brain’s structural connectivity supports the propagation of electrical impulses, manifesting as patterns of coactivation, termed functional connectivity. Functional connectivity emerges from the underlying sparse structural connections, particularly through polysynaptic communication. As a result, functional connections between brain regions without direct structural links are numerous, but their organization is not completely understood. Here we investigate the organization of functional connections without direct structural links. We develop a simple, data-driven method to benchmark functional connections with respect to their underlying structural and geometric embedding. We then use this method to reweigh and reexpress functional connectivity. We find evidence of unexpectedly strong functional connectivity among distal brain regions and within the default mode network. We also find unexpectedly strong functional connectivity at the apex of the unimodal-transmodal hierarchy. Our results suggest that both phenomena—functional modules and functional hierarchies—emerge from functional interactions that transcend the underlying structure and geometry. These findings also potentially explain recent reports that structural and functional connectivity gradually diverge in transmodal cortex. Collectively, we show how structural connectivity and geometry can be used as a natural frame of reference with which to study functional connectivity patterns in the brain.

The structural connectivity of the brain supports interregional signaling, manifesting as highly organized patterns of functional connectivity. Importantly, structural and functional connectivity are fundamentally constrained by the spatial embedding of brain regions, such that proximal regions are more likely to exhibit stronger connectivity. Here we develop a simple method that uses robust relationships between geometry, structure, and function as the baseline to reweigh and reexpress functional connectivity. We use the method to identify functional connections that are greater than expected given their structural and geometric embedding. We then show that the arrangement of these connections systematically follows the functional modules and the putative unimodal-transmodal hierarchy of the brain. Collectively, our findings demonstrate highly organized patterns of polysynaptic functional connections that support the emergence of canonical features of functional connectivity networks, including modules and hierarchies.

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Author notes

Competing Interests: The authors have declared that no competing interests exist.

Handling Editor: Sean Hill

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