The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
The brainstem reticular formation is a small-world, not scale-free, network
Open accessAbstract
Recently, it has been demonstrated that several complex systems may have simple graph-theoretic characterizations as so-called ‘small-world’ and ‘scale-free’ networks. These networks have also been applied to the gross neural connectivity between primate cortical areas and the nervous system of Caenorhabditis elegans. Here, we extend this work to a specific neural circuit of the vertebrate brain—the medial reticular formation (RF) of the brainstem—and, in doing so, we have made three key contributions. First, this work constitutes the first model (and quantitative review) of this important brain structure for over three decades. Second, we have developed the first graph-theoretic analysis of vertebrate brain connectivity at the neural network level. Third, we propose simple metrics to quantitatively assess the extent to which the networks studied are small-world or scale-free. We conclude that the medial RF is configured to create small-world (implying coherent rapid-processing capabilities), but not scale-free, type networks under assumptions which are amenable to quantitative measurement.
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Cites
Emergence of Scaling in Random Networks
Barabási, A.-L., & Albert, R. (1999) · Science · doi:10.1126/science.286.5439.509 · Cited by 36,135
Classes of small-world networks
Amaral, L. A. N., Scala, A., Barthélémy, M., & Stanley, H. E. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.200327197 · Cited by 3,051
Communication in neuronal networks
Laughlin, S. B., & Sejnowski, T. J. (2003) · Science · doi:10.1126/science.1089662 · Cited by 950
Invited Review Anatomical loops and their electrical dynamics in relation to whisking by rat
KLEINFELD, D., BERG, R. W., & O'CONNOR, S. M. (1999) · Somatosensory & Motor Research · doi:10.1080/08990229970528 · Cited by 191
Cited by
Complex brain networks: graph theoretical analysis of structural and functional systems
Bullmore, E., & Sporns, O. (2009) · Nature Reviews Neuroscience · doi:10.1038/nrn2575 · Cited by 11,820
Bassett, D. S., & Bullmore, E. (2006) · The Neuroscientist · doi:10.1177/1073858406293182 · Cited by 2,600
Achard, S., Salvador, R., Whitcher, B., Suckling, J., & Bullmore, E. (2006) · The Journal of Neuroscience · doi:10.1523/jneurosci.3874-05.2006 · Cited by 2,393
Network ‘Small-World-Ness’: A Quantitative Method for Determining Canonical Network Equivalence
Humphries, M. D., & Gurney, K. (2008) · PLoS ONE · doi:10.1371/journal.pone.0002051 · Cited by 1,442
Self-citationIdentification and classification of hubs in brain networks
Sporns, O., Honey, C. J., & Kötter, R. (2007) · PLoS ONE · doi:10.1371/journal.pone.0001049 · Cited by 1,165
Metadata
- Authors
- Humphries, M. D., Gurney, K., & Prescott, T. J.
- Venue
- Proceedings of the Royal Society B: Biological Sciences
- Publisher
- The Royal Society
- Published
- 2005-11-17
- Volume
- 273
- Issue
- 1585
- Pages
- 503-511
- ISSN
- 0080-4649 (ISSN-L)
- 0962-8452
- 1471-2954
- OpenAlex
- W2165096765
- Cited by
- 607
- References
- 4
- FWCI
- 7.63
- Type
- journal article
- Language
- en
- Open access
- green
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