• DocumentCode
    3012856
  • Title

    The Chaos And The Complexity of the Abnormal Oscillations Propagation in A 2-D Strong Coupling Neuronal Network

  • Author

    Ge, Manling ; Guo, Hongyong ; Dong, Guoya ; Hui, Meng ; Jia, Wenyan ; Sun, Minghui ; Yan, Weili

  • Author_Institution
    Key Lab. of Electromagn. Field & Electr. Apparatus Reliability, Hefei Univ. of Technol., Tianjin
  • fYear
    2005
  • fDate
    16-19 March 2005
  • Firstpage
    612
  • Lastpage
    615
  • Abstract
    The abnormal oscillations propagation in an actual neural tissue is often irregular and complex so that it can´t be understood thoroughly until now, however some special work can prove helpful. In our work, a 2-D network is built where the nonlinear oscillators are coupled via resistors. Based on the network, a 2-D spatial-temporal partial differential equation (PDE) is presented to investigate the turbulence caused by the abnormal oscillations propagation. In the PDE, the Chay model is regarded as an oscillator that gives some abnormal oscillations. Resistors represent the effect of gap junctions. The Lyapunov exponent and the approximate entropy (ApEn) are applied to the analysis for the chaos and the complexity in the propagation. Numerical results show that the nonlinear and the complexity of the activity are large when the activity is affected by the abnormal propagation. It is also indicated that neurons in distinct state behave differently when affected by the propagation. Although, the theoretical work is so limited far to explain all problems in disorder, the theoretical work can be helpful to understand the new oscillations giving birth to during the abnormal oscillations propagation
  • Keywords
    Lyapunov methods; bioelectric phenomena; biological tissues; chaos; entropy; medical signal processing; neural nets; neurophysiology; oscillations; partial differential equations; spatiotemporal phenomena; turbulence; 2-D spatial-temporal partial differential equation; 2-D strong coupling neuronal network; Chay model; Lyapunov exponent; abnormal oscillations propagation; approximate entropy; chaos; complexity; gap junctions; neural tissue; turbulence; Bifurcation; Biological neural networks; Chaos; Couplings; Electromagnetic propagation; Epilepsy; Intelligent networks; Neurons; Oscillators; Resistors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Engineering, 2005. Conference Proceedings. 2nd International IEEE EMBS Conference on
  • Conference_Location
    Arlington, VA
  • Print_ISBN
    0-7803-8710-4
  • Type

    conf

  • DOI
    10.1109/CNE.2005.1419699
  • Filename
    1419699