Community detection in network neuroscience

Research output: Chapter in Book/Report/Conference proceedingChapter

2 Scopus citations

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 languageEnglish (US)
Title of host publicationConnectome Analysis
Subtitle of host publicationCharacterization, Methods, and Analysis
PublisherElsevier
Pages149-171
Number of pages23
ISBN (Electronic)9780323852807
ISBN (Print)9780323852814
DOIs
StatePublished - Jan 1 2023
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2023 Elsevier Inc. All rights reserved.

Keywords

  • brain
  • community
  • meso-scale
  • modularity
  • network
  • Neuroscience

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