Title: Finding influential nodes for integration in brain networks using optimal percolation theory,
Abstract: Global integration of information in the brain results from complex
interactions of segregated brain networks. Identifying the most influential
neuronal populations that efficiently bind these networks is a fundamental
problem of systems neuroscience. Here we apply optimal percolation theory and
pharmacogenetic interventions in-vivo to predict and subsequently target nodes
that are essential for global integration of a memory network in rodents. The
theory predicts that integration in the memory network is mediated by a set of
low-degree nodes located in the nucleus accumbens. This result is confirmed
with pharmacogenetic inactivation of the nucleus accumbens, which eliminates
the formation of the memory network, while inactivations of other brain areas
leave the network intact. Thus, optimal percolation theory predicts essential
nodes in brain networks. This could be used to identify targets of
interventions to modulate brain function.