Topological Randomness and Number of Edges Predict Modular Structure in Functional Brain Networks

TL;DR

This paper investigates how topological randomness and the number of edges influence the modular structure of functional brain networks, challenging previous claims of a nested multiscale modular organization.

Contribution

It demonstrates that the observed multiscale modular structure is largely mediated by random variation in correlation coefficients across time scales.

Findings

Random variation significantly affects modular structure

Number of edges correlates with modular organization

Challenges previous claims of nested multiscale modularity

Abstract

In a recent paper, Bassett et al. (2011) have analyzed the static and dynamic organization of functional brain networks in humans. We here focus on the first claim made in this paper, which states that the static modular structure of such networks is nested with respect to time. Bassett et al. (2011) argue that this graded structure underlines a "multiscale modular structure". In this letter, however, we show that such a relationship is substantially mediated by an increase in the random variation of the correlation coefficients computed at different time scales.