Mapping multiplex hubs in human functional brain network

TL;DR

This study introduces a multiplex network approach to identify brain hubs across multiple frequency bands, revealing unique topological information and improving differentiation between healthy and schizophrenic brains.

Contribution

It pioneers the use of multiplex topologies for brain network analysis, uncovering frequency-specific hubs that enhance understanding of brain function and pathology.

Findings

Multiplex hubs differ from traditional single-layer hubs.

Frequency-specific topologies carry unique information.

Multiplex approach improves classification of healthy vs. schizophrenic brains.

Abstract

Typical brain networks consist of many peripheral regions and a few highly central ones, i.e. hubs, playing key functional roles in cerebral inter-regional interactions. Studies have shown that networks, obtained from the analysis of specific frequency components of brain activity, present peculiar architectures with unique profiles of region centrality. However, the identification of hubs in networks built from different frequency bands simultaneously is still a challenging problem, remaining largely unexplored. Here we identify each frequency component with one layer of a multiplex network and face this challenge by exploiting the recent advances in the analysis of multiplex topologies. First, we show that each frequency band carries unique topological information, fundamental to accurately model brain functional networks. We then demonstrate that hubs in the multiplex network, in general different from those ones obtained after discarding or aggregating the measured signals as usual, provide a more accurate map of brain's most important functional regions, allowing to distinguish between healthy and schizophrenic populations better than conventional network approaches.