Self-organized critical neural networks

Abstract

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, network connectivity is closely related to a phase transition between ordered and disordered dynamics. A slow topology change is imposed on the network through a local rewiring rule motivated by activity-dependent synaptic development: Neighbor neurons whose activity is correlated, on average develop a new connection while uncorrelated neighbors tend to disconnect. As a result, robust self-organization of the network towards the order disorder transition occurs. Convergence is independent of initial conditions, robust against thermal noise, and does not require fine tuning of parameters.

5 pages RevTeX, 7 figures PostScript

Cited by in corpus (32)

• Adaptive Coevolutionary Networks: A Review
• Failure of adaptive self-organized criticality during epileptic seizure attacks
• Adaptive self-organization in a realistic neural network model
• Cumulative effects of triadic closure and homophily in social networks
• Self-organization toward criticality by synaptic plasticity
• Growing Critical: Self-Organized Criticality in a Developing Neural System
• Development of structural correlations and synchronization from adaptive rewiring in networks of Kuramoto oscillators
• Homeostatic plasticity and emergence of functional networks in a whole-brain model at criticality
• Damage Spreading and Criticality in Finite Random Dynamical Networks
• Avalanches in self-organized critical neural networks: A minimal model for the neural SOC universality class
• A simple spontaneously active Hebbian learning model: homeostasis of activity and connectivity, and consequences for learning and epileptogenesis
• Time-Scale and Noise Optimality in Self-Organized Critical Adaptive Networks
• Self-organized criticality in neural networks from activity-based rewiring
• Binary threshold networks as a natural null model for biological networks
• Broad edge of chaos in strongly heterogeneous Boolean networks
• Self-organization of heterogeneous topology and symmetry breaking in networks with adaptive thresholds and rewiring
• Microdynamics and Criticality of Adaptive Regulatory Networks
• Critical Line in Random Threshold Networks with Inhomogeneous Thresholds
• Complex Networks: Time-Dependent Connections and Silent Nodes
• Reverberating activity in a neural network with distributed signal transmission delays
• Recurrent chaotic clustering and slow chaos in adaptive networks
• Moment-Closure Approximations for Discrete Adaptive Networks
• Slow synaptic dynamics in a network: from exponential to power-law forgetting
• Mechanisms of self-organized quasicriticality in neuronal networks models
• Spontaneous organizations of diverse network structures in coupled logistic maps with a delayed connection change
• A synthesis and a practical approach to complex systems
• Storing and retrieving long-term memories: cooperation and competition in synaptic dynamics
• Distinct criticality of phase and amplitude dynamics in the resting brain
• Self-Organization of Diverse Directional Hierarchical Networks in Simple Coupled Maps with Connection Changes
• A neuronal dynamics study on a neuromorphic chip
• The rise and fall of hubs in Self-Organized Critical learning networks
• Maximal Information Transfer and Behavior Diversity in Random Threshold Networks