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Cited by 1,165Functional Brain Connectivity StudiesComplex Network Analysis TechniquesAdvanced Neuroimaging Techniques and Applications

Identification and classification of hubs in brain networks

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Sporns, Olaf, Honey, Christopher J., Kötter, Rolf·2007·PLoS ONE
DOI 10.1371/journal.pone.0001049PMC PMC2013941
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Abstract

Brain regions in the mammalian cerebral cortex are linked by a complex network of fiber bundles. These inter-regional networks have previously been analyzed in terms of their node degree, structural motif, path length and clustering coefficient distributions. In this paper we focus on the identification and classification of hub regions, which are thought to play pivotal roles in the coordination of information flow. We identify hubs and characterize their network contributions by examining motif fingerprints and centrality indices for all regions within the cerebral cortices of both the cat and the macaque. Motif fingerprints capture the statistics of local connection patterns, while measures of centrality identify regions that lie on many of the shortest paths between parts of the network. Within both cat and macaque networks, we find that a combination of degree, motif participation, betweenness centrality and closeness centrality allows for reliable identification of hub regions, many of which have previously been functionally classified as polysensory or multimodal. We then classify hubs as either provincial (intra-cluster) hubs or connector (inter-cluster) hubs, and proceed to show that lesioning hubs of each type from the network produces opposite effects on the small-world index. Our study presents an approach to the identification and classification of putative hub regions in brain networks on the basis of multiple network attributes and charts potential links between the structural embedding of such regions and their functional roles.

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Authors
Sporns, O., Honey, C. J., & Kötter, R.
Affiliations
  • Indiana University Bloomington (US)
  • Radboud University Medical Center (NL)
Corresponding author
Sporns, Olaf
ORCID
Venue
PLoS ONE
Publisher
Public Library of Science (PLoS)
Published
2007-10-17
Volume
2
Issue
10
Pages
e1049
ISSN
1932-6203 (ISSN-L)
DOI
10.1371/journal.pone.0001049
PMC
PMC2013941
OpenAlex
W2033078279
Cited by
1,165
References
8
Citations by year
2026: 40 · 2025: 48 · 2024: 42 · 2023: 58 · 2022: 78 · 2021: 65 · 2020: 78 · 2019: 64 · 2018: 77 · 2017: 79 · 2016: 89 · 2015: 78 · 2014: 91 · 2013: 71 · 2012: 74
FWCI
15.03
Type
journal article
Language
en
Open access
Licence
Locations
  • PLoS ONE (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Radboud Repository (Radboud University) (submittedVersion)
  • Radboud Repository (Radboud University) (submittedVersion, other-oa)
Funders
  • James S. McDonnell Foundation
  • Deutsche Forschungsgemeinschaft
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
  • Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
Keywords
brain network hubs, cerebral cortex, structural connectivity, network centrality, betweenness centrality, closeness centrality, degree distribution, cats, macaque, lesion effects
MeSH terms
Algorithms, Animals, Brain, Brain Mapping, Cats, Cerebral Cortex, Computer Simulation, Macaca, Models, Anatomic, Models, Biological, Nerve Net, Neural Pathways, Species Specificity, Models, Statistical, Protein Interaction Mapping

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