Self-tuned critical anti-Hebbian networks

Phys Rev Lett. 2009 Jun 26;102(25):258102. doi: 10.1103/PhysRevLett.102.258102. Epub 2009 Jun 22.

Abstract

It is widely recognized that balancing excitation and inhibition is important in the nervous system. When such a balance is sought by global strategies, few modes remain poised close to instability, and all other modes are strongly stable. Here we present a simple abstract model in which this balance is sought locally by units following "anti-Hebbian" evolution: all degrees of freedom achieve a close balance of excitation and inhibition and become "critical" in the dynamical sense. At long time scales, a complex "breakout" dynamics ensues in which different modes of the system oscillate between prominence and extinction; the model develops various long-tailed statistical behaviors and may become self-organized critical.

MeSH terms

  • Models, Neurological*
  • Neural Networks, Computer*
  • Neurons / physiology*