Resolving inter-regional communication capacity in the human connectome

Applications of graph theory to the human brain network have led to the development of several models of how neural signaling unfolds atop its structure. Analytic measures derived from these communication models have mainly been used to extract global characteristics of brain networks, obscuring potentially informative inter-regional relationships. Here we develop a simple standardization method to investigate polysynaptic communication pathways between pairs of cortical regions. This procedure allows us to determine which pairs of nodes are topologically closer and which are topologically further than expected on the basis of their degree. We find that communication pathways delineate canonical intrinsic functional systems. By relating nodal communication capacity to meta-analytic probabilistic patterns of functional specialization, we also show that areas that are most closely integrated within the network are associated with higher-order cognitive functions. We find that these regions’ proclivity towards functional integration could naturally arise from the brain’s anatomical configuration through evenly distributed connections among multiple specialized communities. Throughout, we consider the effect of the network’s spatial embedding on inter-regional communication capacity. Altogether, the present findings uncover a relationship between polysynaptic communication pathways and the brain’s intrinsic functional organization and demonstrate that network integration facilitates cognitive integration.