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Published, Version of Record (VoR)CC BY V4.0, Open
Journal article
The modular organization of human anatomical brain networks: Accounting for the cost of wiring
Network neuroscience (Cambridge, Mass.), v 1(1)
01 Feb 2017
PMID: 30793069
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Brain networks are expected to be modular. However, existing techniques for estimating a network’s modules make it difficult to assess the influence of organizational principles such as wiring cost reduction on the detected modules. Here we present a modification of an existing module detection algorithm that allowed us to focus on connections that are unexpected under a cost-reduction wiring rule and to identify modules from among these connections. We applied this technique to anatomical brain networks and showed that the modules we detected differ from those detected using the standard technique. We demonstrated that these novel modules are spatially distributed, exhibit unique functional fingerprints, and overlap considerably with rich clubs, giving rise to an alternative and complementary interpretation of the functional roles of specific brain regions. Finally, we demonstrated that, using the modified module detection approach, we can detect modules in a
developmental dataset that track normative patterns of maturation. Collectively, these findings support the hypothesis that brain networks are composed of modules and provide additional insight into the function of those modules.
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Details
- Title
- The modular organization of human anatomical brain networks: Accounting for the cost of wiring
- Creators
- Richard F Betzel - University of PennsylvaniaJohn D Medaglia - University of PennsylvaniaLia Papadopoulos - University of PennsylvaniaGraham L Baum - University of PennsylvaniaRuben Gur - University of PennsylvaniaRaquel Gur - University of PennsylvaniaDavid Roalf - University of PennsylvaniaTheodore D Satterthwaite - University of PennsylvaniaDanielle S Bassett - University of Pennsylvania
- Publication Details
- Network neuroscience (Cambridge, Mass.), v 1(1)
- Publisher
- MIT Press
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Psychological and Brain Sciences (Psychology)
- Web of Science ID
- WOS:000449587400005
- Scopus ID
- 2-s2.0-85016718348
- Other Identifier
- 991019296519804721
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- Web of Science research areas
- Neurosciences