• DocumentCode
    2373833
  • Title

    Models of cyclic oscillation using VLSI-based neural elements

  • Author

    Wolpert, Seth

  • Author_Institution
    Dept. of Electr. Eng., Maine Univ., Orono, ME, USA
  • fYear
    1994
  • fDate
    1994
  • Firstpage
    1113
  • Abstract
    As a prelude to the VLSI implementation of a biologically-based locomotory network, the phenomenon of recurrent cyclic inhibition was recreated in VLSI-based artificial neurons for parametric analysis of its oscillatory range and stability. The IC-based artificial neurons used in this study are behaviorally comprehensive and highly configurable, allowing for a variety of transient and steady characteristics to be precisely and continuously adjustable. Circuit tests indicate that recurrent cyclic inhibitory prototypes do not require synaptic dynamics, and show remarkable stability, even when the self-excitatory frequency of each component neuron varies over two orders of magnitude
  • Keywords
    VLSI; IC-based artificial neurons; VLSI implementation; VLSI-based neural elements; behaviorally comprehensive neurons; biologically-based locomotory network; circuit tests; cyclic oscillation models; highly configurable neurons; oscillatory range; parametric analysis; self-excitatory frequency; stability; steady characteristics; synaptic dynamics; transient characteristics; Automatic testing; Biological system modeling; Biomembranes; Circuit stability; Circuit testing; Frequency; Neurons; Oscillators; Prototypes; Stability analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 1994. Engineering Advances: New Opportunities for Biomedical Engineers. Proceedings of the 16th Annual International Conference of the IEEE
  • Conference_Location
    Baltimore, MD
  • Print_ISBN
    0-7803-2050-6
  • Type

    conf

  • DOI
    10.1109/IEMBS.1994.415349
  • Filename
    415349