• DocumentCode
    2050223
  • Title

    Modeling cortical function starting with minimal connectivity

  • Author

    Towsey, Michael ; Diederich, Joachim

  • Author_Institution
    Machine Learning Res. Centre, Queensland Univ. of Technol., Brisbane, Qld., Australia
  • Volume
    2
  • fYear
    1999
  • fDate
    1999
  • Firstpage
    783
  • Abstract
    Neural models of cortical function frequently assume initial profuse connectivity and ignore issues of cortical development. There is increasing interest in cortical models that minimise pre-specification of architecture and instead allow input and learning rules to sculpt connectivity. We describe a model of cortical development that begins with minimal connectivity but arrives at useful functionality through a variety of mechanisms, including Hebbian learning, volume learning, synaptic sprouting and structured input. We discuss some of the issues pertinent to the building of neural structure
  • Keywords
    Hebbian learning; brain models; content-addressable storage; neural nets; Hebbian learning; cortical development; cortical function modeling; learning rules; minimal connectivity; neural models; neural structure; pre-specification; structured input; synaptic sprouting; volume learning; Australia; Brain modeling; Neurons; Retina;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Information Processing, 1999. Proceedings. ICONIP '99. 6th International Conference on
  • Conference_Location
    Perth, WA
  • Print_ISBN
    0-7803-5871-6
  • Type

    conf

  • DOI
    10.1109/ICONIP.1999.845695
  • Filename
    845695