Long-range corticocortical connectivity in mammalian brains possesses an intricate, nonrandom organization. Specifically, projections are arranged in ‘small-world’ networks, forming clusters of cortical areas, which are closely linked among each other, but less frequently with areas in other clusters. In order to delineate the structure of cortical clusters and identify their members, we developed a computational approach based on evolutionary optimization. In different compilations of connectivity data for the cat and macaque monkey brain, the algorithm identified a small number of clusters that broadly agreed with functional cortical subdivisions. We propose a simple spatial growth model for evolving clustered connectivity, and discuss structural and functional implications of the clustered, small-world organization of cortical networks.
Index EntriesRhesus macaque monkey cat cluster analysis neural networks cortical development robustness vulnerability network function small-world networks scale-free networks spatial growth
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- Hilgetag, C. and Barbas, H. (2003) Predictors of primate corticocortical connectivity. Soc Neurosci Abstr 29, 596.522.Google Scholar
- Hilgetag, C., Kötter, R., Stephan, K., and Sporns, O. (2002). Computational methods for the analysis of brain connectivity. in Computational Neuroanatomy: Principles and Methods, Ascoli, G., ed., Humana Press, pp. 295–335.Google Scholar
- Kaiser, M. and Hilgetag, C. (2004b) Modelling the development of cortical networks. Neuro-Computing 58–60, 297–302.Google Scholar
- Kaiser, M. and Hilgetag, C. C. (2004c) Spatial growth of real-world networks. Phys Rev E Stat Nonlin Soft Matter Phys 69, 036103.Google Scholar
- Kruskal, J. B. and Wish, M. (1978). Multidimensional scaling. Sage Publications, Beverly Hills, CA.Google Scholar
- Martin, R., Kaiser, M., Andras, P., and Young, M. (2001) Is the brain a scale-free network? Soc Neurosci Abstr 27, 816.814.Google Scholar
- McIntosh, A. R., Grady, C. L., Ungerleider, L. G., et al. (1994) Network analysis of cortical visual pathways mapped with PET. J Neurosci 14, 655–666.Google Scholar
- Ungerleider, L. G. and Mishkin, M. (1982). Two cortical visual systems. in Analysis of visual behaviour, Ingle, D. G., Goodale, M. A. and Mansfield, R. J. Q., ed., MIT Press, Cambridge, MA, pp. 549–586.Google Scholar