Abstract
Both natural and engineered networks are often modular. Whether a network node interacts with only nodes from its own module or nodes from multiple modules provides insight into its functional role. The participation coefficient (PC) is typically used to measure this attribute, although its value also depends on the size and connectedness of the module it belongs to and may lead to nonintuitive identification of highly connected nodes. Here, we develop a normalized PC that reduces the influence of intramodular connectivity compared with the conventional PC. Using brain, C. elegans, airport, and simulated networks, we show that our measure of participation is not influenced by the size or connectedness of modules, while preserving conceptual and mathematical properties, of the classic formulation of PC. Unlike the conventional PC, we identify London and New York as high participators in the air traffic network and demonstrate stronger associations with working memory in human brain networks, yielding new insights into nodal participation across network modules.
Highlights
Many natural and engineered networks are modular
participation coefficient (PC) is influenced by modularity algorithms that tend to favor large modules with strong intramodule connectivity, that in turn generate low PC values, even if a node has strong intermodule connectivity
As first demonstrated and comprehensively addressed elsewhere (Klimm et al, 2014), PC is influenced by the extent of intramodular connectivity, which may lead to inaccurate inference in networks with modules that vary in size
Summary
Many natural and engineered networks are modular. Networks that are highly modular can be partitioned into communities of nodes, or modules, such that the density of connections is greater between the nodes within modules, relative to the density between nodes in different modules. Some nodes have connections that are distributed across many modules, whereas others are only connected with other nodes in their own module. This distinction can provide important insight into a node’s functional role in a modular architecture. Participation coefficient (PC): Estimates how well a node within a given module is connected to other brain-wide modules. It is a measure of intermodular diversity
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