Modular organization as a basis for the functional integration/segregation in large-scale brain networks

TL;DR

This study reveals that large-scale brain networks have a modular organization that supports both specialized functions and integration across different brain regions during rest, using fMRI data and a novel analysis method.

Contribution

It introduces a random walk-based method to identify modular structures in voxel-level brain networks and links these modules to anatomical and functional significance.

Findings

Modules match anatomical brain structures

Modular architecture supports functional integration and segregation

Brain network modules are spatially distributed and functionally relevant

Abstract

Modular structure is ubiquitous among real-world networks from related proteins to social groups. Here we analyze the modular organization of brain networks at a large-scale (voxel level) extracted from functional magnetic resonance imaging (fMRI) signals. By using a random walk-based method, we unveil the modularity of brain-webs, and show that modules with a spatial distribution that matches anatomical structures with functional significance. The functional role of each node in the network is studied by analyzing its patterns of inter- and intra-modular connections. Results suggest that the modular architecture constitutes the structural basis for the coexistence of functional integration of distant and specialized brain areas during normal brain activities at rest.