The rise and fall of hubs in self-organized critical learning networks

Information processing networks are the result of local rewiring rules. In many instances, such rules promote links where the activity at the two end nodes is positively correlated. The conceptual problem we address is what network architecture prevails under such rules and how does the resulting network, in turn, constrain the dynamics. We focus on a simple toy model that captures the interplay between link self-reinforcement and self-organised critical dynamics in a simple way. Our main finding is that, under these conditions, a core of densely connected nodes forms spontaneously. Moreover, we show that the appearance of such a clustered state can be dynamically regulated by a fatigue mechanism, eventually giving rise to non-trivial avalanche exponents.

• Publication year

  2021

• Venue

  Journal of Statistical Mechanics: Theory and Experiment

• Publication date

  2021-04-27

• Fields of study

  Physics, Computer Science

• Identifiers
  DOI 10.1088/1742-5468/ac150darXiv 2104.13034
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• The role of network architecture in the onset of spontaneous activity

  2020cited by this paper
• Mechanisms of Homeostatic Synaptic Plasticity in vivo

  2019cited by this paper
• Neuronal avalanche dynamics indicates different universality classes in neuronal cultures

  2018cited by this paper
• The insect central complex.

  2016cited by this paper
• Extreme variability in convergence to structural balance in frustrated dynamical systems

  2013cited by this paper
• What do leaders know?

  2013cited by this paper
• STDP-driven networks and the C. elegans neuronal network

  2010cited by this paper
• Structural Properties of the Caenorhabditis elegans Neuronal Network

  2009cited by this paper
• Evolution of network structure by temporal learning

  2008cited by this paper
• Statistical properties of community structure in large social and information networks

  2008cited by this paper
• Dynamics and plasticity in developing neuronal networks in vitro.

  2005cited by this paper
• The role of stationarity in magnetic crackling noise

  2005cited by this paper
• Clogging and self-organized criticality in complex networks.

  2004cited by this paper
• Homeostatic plasticity in the developing nervous system

  2004cited by this paper
• Self-organized criticality and scale-free properties in emergent functional neural networks.

  2004cited by this paper
• Universal finite-size scaling behavior and universal dynamical scaling behavior of absorbing phase transitions with a conserved field.

  2003cited by this paper
• Neuronal Avalanches in Neocortical Circuits

  2003cited by this paper
• A simple model of global cascades on random networks

  2002cited by this paper
• Self-organized critical neural networks.

  2001cited by this paper
• Avalanche and spreading exponents in systems with absorbing states.

  1998cited by this paper
• Self organization of interacting polya urns

  1998cited by this paper
• Synaptic Depression and Cortical Gain Control

  1997cited by this paper
• The neural code between neocortical pyramidal neurons depends on neurotransmitter release probability.

  1997cited by this paper
• Learning from mistakes.

  1997cited by this paper
• Earthquake cycles and neural reverberations: Collective oscillations in systems with pulse-coupled threshold elements.

  1995cited by this paper
• Democratic reinforcement: A principle for brain function.

  1995cited by this paper
• Punctuated equilibrium and criticality in a simple model of evolution.

  1993cited by this paper
• The organization of behavior: A neuropsychological theory

  1951cited by this paper

• No citing papers are available for this paper.