The Brain, Complex Networks, and Beyond

  • L. M. Patnaik
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3741)

Abstract

This presentation covers a synthesizing overview of the structural organisation of the brain, viewed as a complex network. Such an organisation is encountered in social, information, technological, and biological networks. The underlying conclusions may, in future, lead to interesting studies in the areas of cognition, and distribution computing. It is also hoped that the brain network structure studied through scale-free, small world, and clustering concepts may facilitate better understanding and design of brain-computer interface (BCI) systems.

Keywords

Fractal Dimension Degree Distribution Cluster Coefficient Brain Network Small World 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Watts, D.J., Strogatz, S.H.: Collective Dynamics of ‘Small World’ Networks. Nature 393, 440–442 (1998)CrossRefGoogle Scholar
  2. 2.
    Barabasi, A.L., Albert, R.: Emergence of Scaling in Random Networks. Science 286, 509–512 (1999)CrossRefMathSciNetGoogle Scholar
  3. 3.
    Hilgetag, C.C., et al.: Anatomical Connectivity Defines the Macaque Monkey and the Cat. Philosophical Transactions of the Royal Society of London B Biological Sciences 335, 91–110 (2000)CrossRefGoogle Scholar
  4. 4.
    Sporns, O., Tononi, G.: Classes of Network Connectivity and Dynamics. Complexity 7, 28–38 (2002)CrossRefMathSciNetGoogle Scholar
  5. 5.
    Kaiser, M., Hilgetag, C.C.: Edge Vulnerability in Neural and Metabolic Networks. Biological Cybernetics 90, 311–331 (2004)MATHCrossRefGoogle Scholar
  6. 6.
    Smith, T.G., Lange, G.D., Mark, W.B.: Fractal Methods in Cellular Morphology n- Dimensions, Lacunarity, and Multifractals. Journal of Neuroscience Methods 69, 123–136 (1996)CrossRefGoogle Scholar
  7. 7.
    Mc Farland, D.J., Sarnacki, W.A., Wolpaw, J.R.: Brain-Computer Interface (BCI) Operation: Optimizing Information Transfer Rates. Biological Psychology 36, 237–251 (2003)CrossRefGoogle Scholar
  8. 8.
    Patnaik, L. M.: Daubechis-4 Wavelet with SVM as an Efficient Method for Classification of Brain Images. Journal of Electronic Imaging 14, 1–7 (2005)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • L. M. Patnaik
    • 1
  1. 1.Indian Institute of ScienceBangalore

Personalised recommendations