Abstract
Many real-world networks, including nervous systems, exhibit meso-scale structure. This means that their elements can be grouped into meaningful subnetworks. In general, these subnetworks are unknown ahead of time and must be “discovered” algorithmically using community detection methods. In this chapter, we review evidence that nervous systems exhibit meso-scale structure in the form of communities, clusters, and modules. We also provide a set of guidelines to assist users in applying community detection methods to their own network data. These guidelines focus on the method of modularity maximization but, in many cases, are general and applicable to other techniques.
Original language | English (US) |
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Title of host publication | Connectome Analysis |
Subtitle of host publication | Characterization, Methods, and Analysis |
Publisher | Elsevier |
Pages | 149-171 |
Number of pages | 23 |
ISBN (Electronic) | 9780323852807 |
ISBN (Print) | 9780323852814 |
DOIs | |
State | Published - Jan 1 2023 |
Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2023 Elsevier Inc. All rights reserved.
Keywords
- brain
- community
- meso-scale
- modularity
- network
- Neuroscience