Self-organized critical neural networks

Self-organized critical neural networks.

A mechanism for self-organization of the degree of connectivity in model neural networks is studied. Network connectivity is regulated locally on the basis of an order parameter of the global dynamics, which is estimated from an observable at the single synapse level. This principle is studied in a two-dimensional neural network with randomly wired asymmetric weights. In this class of networks,...

Self-organized critical random Boolean networks.

Standard random Boolean networks display an order-disorder phase transition. We add to the standard random Boolean networks a disconnection rule that couples the control and order parameters. In this way, the system is driven to the critical line transition. Under the influence of perturbations the system points out self-organized critical behavior. Several numerical simulations have been done ...

Self-organized criticality in adaptive neural networks

Avalanches in Self-Organized Critical Neural Networks: A Minimal Model for the Neural SOC Universality Class

The brain keeps its overall dynamics in a corridor of intermediate activity and it has been a long standing question what possible mechanism could achieve this task. Mechanisms from the field of statistical physics have long been suggesting that this homeostasis of brain activity could occur even without a central regulator, via self-organization on the level of neurons and their interactions, ...

A Self-Organized Critical Universe

A model of the universe as a self-organized critical system is considered. The universe evolves to a state independently of the initial conditions at the edge of chaos. The critical state is an attractor of the dynamics. Random metric fluctuations exhibit noise without any characteristic length scales, and the power spectrum for the fluctuations has a self-similar fractal behavior. In the early...