• DocumentCode
    240563
  • Title

    Self organizing neuro-glial network, SONG-Net

  • Author

    Landolsi, H. ; Marzouki, K.

  • Author_Institution
    Inf. for Ind. Syst. Lab., LISI-INSAT, Tunis, Tunisia
  • fYear
    2014
  • fDate
    9-12 Dec. 2014
  • Firstpage
    85
  • Lastpage
    91
  • Abstract
    More convincing evidence has proven the existence of a bidirectional relationship between neurons and astrocytes. Assume now that astrocytes, a new type of glial cells previously considered as passive cells of support, constitute a system of nonsynaptic transmission plays a major role in modulating the activity of neurons. In this context, we proposed to model the effect of these cells to develop a new type of artificial neural network operating on new mechanisms to improve the information processing and reduce learning time, very expensive in traditional networks. The obtained results indicate that the implementation of bio-inspired functions such as of astrocytes, improve very considerably learning speed. The developed model achieves learning up to twelve times faster than traditional artificial neural networks.
  • Keywords
    biocomputing; cellular biophysics; self-organising feature maps; SONG-NET; artificial neural network; astrocytes; bio-inspired functions; information processing improvement; learning speed; learning time reduction; neuron activity modulation; self organizing neuro-glial network; Artificial neural networks; Biological system modeling; Classification algorithms; Mathematical model; Neurons; Training; Artificial Neural Network; Astrocytes; Brain; Calcium Waves…; Glial Cells; Glue; Kohonen; Neurons;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB), 2014 IEEE Symposium on
  • Conference_Location
    Orlando, FL
  • Type

    conf

  • DOI
    10.1109/CCMB.2014.7020698
  • Filename
    7020698