• DocumentCode
    1664735
  • Title

    Hypergraphs: Organizing complex natural neural networks

  • Author

    Jain, Eakta ; Healy, Michael J. ; Saland, Linda ; Hamilton, Derek ; Allan, Andrea ; Caldwell, Kevin ; Caudell, Thomas P.

  • Author_Institution
    Dept. of Electr. Eng., Indian Inst. of Technol., Kanpur
  • fYear
    2005
  • Firstpage
    20
  • Lastpage
    26
  • Abstract
    Data from neuroscience research has shown that the brain can be studied as a neural network. In view of the brain´s seemingly infinite complexity, we organize the entire network into a series of sub-networks, each of whose functionalities combine to become the knowledge representation capability of the entire network. Thus, we look at the brain in terms of modules and sub-modules, at varying levels of `granularity´. Since a network can be mathematically represented as a graph, this hierarchical structure is captured through the notion of `hypergraphs´ and `hyper-matrices´. The proposed structure has been implemented on a graph specification software tool. Finally, a metaphoric visualization for the structure was proposed
  • Keywords
    brain; graph theory; knowledge representation; matrix algebra; neural nets; neurophysiology; complex natural neural networks; graph specification software tool; hyper-matrices; hypergraphs; knowledge representation; mathematical graph representation; metaphoric visualization; neuroscience research; Artificial neural networks; Biological neural networks; Circuit simulation; Computer networks; Data engineering; Knowledge representation; Neural networks; Neurons; Organizing; Yarn;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Sensing and Information Processing, 2005. ICISIP 2005. Third International Conference on
  • Conference_Location
    Bangalore
  • Print_ISBN
    0-7803-9588-3
  • Type

    conf

  • DOI
    10.1109/ICISIP.2005.1619407
  • Filename
    1619407