Type of self-organized criticality model based on neural networks

2002 ◽  
Vol 65 (2) ◽  
Author(s):  
XiaoWei Zhao ◽  
TianLun Chen
Keyword(s):  
Neural Networks ◽  
Model Based ◽  
Self Organized ◽  
Self Organized Criticality

scholarly journals Analytical investigation of self-organized criticality in neural networks

2013 ◽  
Vol 10 (78) ◽  
pp. 20120558 ◽  
Author(s):  
Felix Droste ◽  
Anne-Ly Do ◽  
Thilo Gross
Keyword(s):  
Neural Networks ◽  
Stochastic Dynamics ◽  
Analytical Investigation ◽  
Homeostatic Plasticity ◽  
Dynamical Phase Transition ◽  
Discrete State ◽  
Dynamical Phase ◽  
Self Organized ◽  
Self Organized Criticality ◽  
Activity Dependent

Dynamical criticality has been shown to enhance information processing in dynamical systems, and there is evidence for self-organized criticality in neural networks. A plausible mechanism for such self-organization is activity-dependent synaptic plasticity. Here, we model neurons as discrete-state nodes on an adaptive network following stochastic dynamics. At a threshold connectivity, this system undergoes a dynamical phase transition at which persistent activity sets in. In a low-dimensional representation of the macroscopic dynamics, this corresponds to a transcritical bifurcation. We show analytically that adding activity-dependent rewiring rules, inspired by homeostatic plasticity, leads to the emergence of an attractive steady state at criticality and present numerical evidence for the system's evolution to such a state.

Scaling behaviors and self-organized criticality of two-dimensional small-world neural networks

2020 ◽  
Vol 540 ◽  
pp. 123191 ◽  
Author(s):  
Hong-Li Zeng ◽  
Chen-Ping Zhu ◽  
Shu-Xuan Wang ◽  
Yan-Dong Guo ◽  
Zhi-Ming Gu ◽  
...  
Keyword(s):  
Neural Networks ◽  
Small World ◽  
Two Dimensional ◽  
Self Organized ◽  
Self Organized Criticality
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