| Summary: | Typical brain networks consist of many peripheral regions and a few highly centralones, i.e. hubs, playing key functional roles in cerebral inter-regional interactions. Studieshave shown that networks, obtained from the analysis of specific frequency components ofbrain activity, present peculiar architectures with unique profiles of region centrality. However,the identification of hubs in networks built from different frequency bands simultaneouslyis still a challenging problem, remaining largely unexplored. Here we identify eachfrequency component with one layer of a multiplex network and face this challenge by exploitingthe recent advances in the analysis of multiplex topologies. First, we show that eachfrequency band carries unique topological information, fundamental to accurately modelbrain functional networks. We then demonstrate that hubs in the multiplex network, in generaldifferent from those ones obtained after discarding or aggregating the measured signalsas usual, provide a more accurate map of brain’s most important functional regions, allowingto distinguish between healthy and schizophrenic populations better than conventionalnetwork approaches.
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