• DocumentCode
    288455
  • Title

    Synchronization and desynchronization in locally coupled Wilson-Cowan oscillators

  • Author

    Campbell, Shannon ; Wang, DeLiang

  • Author_Institution
    Dept. of Phys., Ohio State Univ., Columbus, OH, USA
  • Volume
    2
  • fYear
    1994
  • fDate
    27 Jun-2 Jul 1994
  • Firstpage
    964
  • Abstract
    A network of Wilson-Cowan oscillators is constructed, and its emergent properties of synchronization and desynchronization are investigated by both computer simulation and formal analysis. The network is a two-dimensional matrix, where each oscillator is coupled only to its nearest neighbors. The coupling strengths are rapidly adjusted based on a Hebbian rule. A global inhibitor is introduced which receives input from the matrix and inhibits each oscillator in the matrix. We found that a group of oscillators which is stimulated by a single object quickly produces phase synchrony within the group. Furthermore, global inhibition drives the network to desynchronize different oscillator groups. Different from many other studies, the abilities of this model emerge from local connections, which preserve spatial relationships among object components, critical for encoding Gestalt principles of feature grouping. These properties of the oscillator network offer a very promising approach for pattern segmentation based on synchrony and desynchrony
  • Keywords
    correlation methods; image segmentation; neurophysiology; oscillators; pattern recognition; physiological models; synchronisation; visual perception; Gestalt principles; Hebbian rule; desynchronization; encoding; feature grouping; formal analysis; global inhibitor; locally coupled Wilson-Cowan oscillators; pattern segmentation; synchronization; two-dimensional matrix; Brain modeling; Cognitive science; Computer networks; Equations; Information science; Inhibitors; Intelligent networks; Local oscillators; Nearest neighbor searches; Physics computing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
  • Conference_Location
    Orlando, FL
  • Print_ISBN
    0-7803-1901-X
  • Type

    conf

  • DOI
    10.1109/ICNN.1994.374312
  • Filename
    374312