• DocumentCode
    1948555
  • Title

    Do Neural Models Scale up to a Human Brain?

  • Author

    Belavkin, Roman V.

  • Author_Institution
    Middlesex Univ., London
  • fYear
    2007
  • fDate
    12-17 Aug. 2007
  • Firstpage
    2312
  • Lastpage
    2317
  • Abstract
    Models of cognition generally operate either at a micro or a macro level. It is not clear, however, if the micro models can predict the macroscopic properties of biological neural systems, such as the human brain. Here, I evaluate some hypotheses about the main functions of neural processing by scaling them to higher levels. Using neurobiological literature, I estimate the numbers of inputs and outputs of the entire nervous system. Then, I apply optimal control and information theories to predict the numbers of neurons required to implement these functions. The addition of constraints on connectivity leads to numerical estimates comparable to the numbers of neurons and synapses in human brain.
  • Keywords
    brain models; cognition; information theory; neural nets; neurophysiology; optimal control; biological neural systems; cognition model; human brain synapsis; information theory; nervous system; neural models; neural processing; neurobiology; neurons; optimal control; Biological information theory; Biological system modeling; Brain modeling; Cognition; Humans; Information theory; Nervous system; Neurons; Optimal control; Predictive models;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2007. IJCNN 2007. International Joint Conference on
  • Conference_Location
    Orlando, FL
  • ISSN
    1098-7576
  • Print_ISBN
    978-1-4244-1379-9
  • Electronic_ISBN
    1098-7576
  • Type

    conf

  • DOI
    10.1109/IJCNN.2007.4371319
  • Filename
    4371319