Neuroinformatics

, Volume 2, Issue 3, pp 353–360 | Cite as

Clustered organization of cortical connectivity

Review Article

Abstract

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 Entries

Rhesus macaque monkey cat cluster analysis neural networks cortical development robustness vulnerability network function small-world networks scale-free networks spatial growth 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Barabasi, A. L. and Albert, R. (1999) Emergence of scaling in random networks. Science 286, 509–512.CrossRefGoogle Scholar
  2. Barbas, H. (2000) Connections underlying the synthesis of cognition, memory, and emotion in primate prefrontal cortices. Brain Res Bull 52, 319–330.CrossRefGoogle Scholar
  3. Büchel, C. and Friston, K. J. (1997) Modulation of connectivity in visual pathways by attention: cortical interactions evaluated with structural equation modelling and fMRI. Cereb Cortex 7, 768–778.CrossRefGoogle Scholar
  4. Felleman, D. J. and Van Essen, D. C. (1991) Distributed hierarchical processing in the primate cerebral cortex. Cereb Cortex 1, 1–47.CrossRefGoogle Scholar
  5. Friston, K. J. (1994) Functional and effective connectivity in neuroimaging: a synthesis. Hum Brain Mapp 2, 56–78.CrossRefGoogle Scholar
  6. Gupta, A., Wang, Y., and Markram, H. (2000) Organizing principles for a diversity of GABAergic interneurons and synapses in the neocortex. Science 287, 273–278.CrossRefGoogle Scholar
  7. Hilgetag, C. and Barbas, H. (2003) Predictors of primate corticocortical connectivity. Soc Neurosci Abstr 29, 596.522.Google Scholar
  8. 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
  9. Hilgetag, C. C., Burns, G. A., O’Neill, M. A., et al. (2000a) Anatomical connectivity defines the organization of clusters of cortical areas in the macaque monkey and the cat. Philos Trans R Soc Lond B Biol Sci 355, 91–110.CrossRefGoogle Scholar
  10. Hilgetag, C. C. and Grant, S. (2000) Uniformity, specificity and variability of corticocortical connectivity. Philos. Trans R Soc Lond B Biol Sci 355, 7–20.CrossRefGoogle Scholar
  11. Hilgetag, C. C., O’Neill, M. A., and Young, M. P. (1996) Indeterminate organization of the visual system. Science 271, 776–777.CrossRefGoogle Scholar
  12. Hilgetag, C. C., O’Neill, M. A., and Young, M. P. (2000b) Hierarchical organization of macaque and cat cortical sensory systems explored with a novel network processor. Philos Trans R Soc Lond B Biol Sci 355, 71–89.CrossRefGoogle Scholar
  13. Jeong, H., Mason, S. P., Barabasi, A. L., and Oltvai, Z. N. (2001) Lethality and centrality in protein networks. Nature 411, 41–42.CrossRefGoogle Scholar
  14. Kaiser, M. and Hilgetag, C. (2004a) Edge vulnerability in neural and metabolic networks. Biol. Cybern. 90, 311–317.CrossRefGoogle Scholar
  15. Kaiser, M. and Hilgetag, C. (2004b) Modelling the development of cortical networks. Neuro-Computing 58–60, 297–302.Google Scholar
  16. 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
  17. Kalisman, N., Silberberg, G., and Markram, H. (2003) Deriving physical connectivity from neuronal morphology. Biol Cybern 88, 210–218.CrossRefGoogle Scholar
  18. Kötter, R., and Stephan, K. E. (2003) Network participation indices: characterizing component roles for information processing in neural networks. Neural Netw 16, 1261–1275.CrossRefGoogle Scholar
  19. Kruskal, J. B. and Wish, M. (1978). Multidimensional scaling. Sage Publications, Beverly Hills, CA.Google Scholar
  20. 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
  21. 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
  22. Milo, R., Shen-Orr, S., Itzkovitz, S., et al. (2002) Network motifs: Simple building blocks of complex networks. Science 298, 824–827.CrossRefGoogle Scholar
  23. Petroni, F., Panzeri, S., Hilgetag, C. C., et al. (2001) Simultaneity of responses in a hierarchical visual network. Neuroreport 12, 2753–2759.CrossRefGoogle Scholar
  24. Sporns, O., Tononi, G., and Edelman, G. M. (2000a) Connectivity and complexity: the relationship between neuroanatomy and brain dynamics. Neural Netw 13, 909–922.CrossRefGoogle Scholar
  25. Sporns, O., Tononi, G., and Edelman, G. M. (2000b) Theoretical neuroanatomy: relating anatomical and functional connectivity in graphs and cortical connection matrices. Cereb Cortex 10, 127–141.CrossRefGoogle Scholar
  26. Stephan, K. E., Hilgetag, C. C., Burns, G. A., et al. (2000) Computational analysis of functional connectivity between areas of primate cerebral cortex. Philos Trans R Soc Lond B Biol Sci 355, 111–126.CrossRefGoogle Scholar
  27. Sur, M., and Leamey, C. A. (2001) Development and plasticity of cortical areas and networks. Nat Rev Neurosci 2, 251–262.CrossRefGoogle Scholar
  28. 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
  29. Verhage, M., Maia, A. S., Plomp, J. J., et al. (2000) Synaptic assembly of the brain in the absence of neurotransmitter secretion. Science 287, 864–869.CrossRefGoogle Scholar
  30. Watts, D. J., and Strogatz, S. H. (1998) Collective dynamics of ‘small-world’ networks. Nature 393, 440–442.CrossRefGoogle Scholar
  31. Young, M. P. (1992) Objective analysis of the topological organization of the primate cortical visual system. Nature 358, 152–155.CrossRefGoogle Scholar
  32. Young, M. P., Scannell, J. W., O’Neill, M. A., et al. (1995) Non-metric multidimensional scaling in the analysis of neuroanatomical connection data and the organization of the primate cortical visual system. Philos Trans R Soc Lond B Biol Sci 348, 281–308.CrossRefGoogle Scholar

Copyright information

© Humana Press Inc 2004

Authors and Affiliations

  1. 1.School of Engineering and ScienceInternational University BremenBremenGermany
  2. 2.Department of Health SciencesBoston UniversityBostonUSA

Personalised recommendations