Chunk #15 — Resting State Functional Connectivity MRI Signal, Brain Networks, and Common Analysis Techniques — Graph Theoretic Analyses of Region Matrices: Communities and Small-World Properties
Many networks can be viewed as being composed of sub-networks. For example, a person's social network might consist of a group of friends, a group of coworkers, and a group of teammates, each with rather dense internal relationships, but few relationships between groups. These groupings of nodes, or sub-network structures, are called communities or modules. Communities have been found in a wide variety of complex networks, and tend to group nodes with shared characteristics (Newman 2010). Viewing networks in terms of communities can simplify and clarify the form and significance of the overall network structure. In functional brain networks, communities should identify brain regions with similar features or functions, which are potentially functional systems. Community detection tools such as modularity optimization algorithms (Newman and Girvan 2004; Newman 2006) or Infomap (Rosvall and Bergstrom 2008) can be applied to the region matrices described above to detect communities of brain regions. These algorithm-based community assignments are attractive because they are 1) quantitative, 2) objective, and 3) work in situations where the eye cannot (for example, when the relationships between large numbers of regions are in question).
