Dynamical phase transitions and self-organized criticality in a theoretical spring-block model

1995 ◽  
Vol 51 (3) ◽  
pp. 1916-1928 ◽  
Author(s):  
W.-S. Liu ◽  
Y. N. Lu ◽  
E. J. Ding
2013 ◽  
Vol 10 (78) ◽  
pp. 20120558 ◽  
Author(s):  
Felix Droste ◽  
Anne-Ly Do ◽  
Thilo Gross

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.


2018 ◽  
Vol 97 (9) ◽  
Author(s):  
Bruno Mera ◽  
Chrysoula Vlachou ◽  
Nikola Paunković ◽  
Vítor R. Vieira ◽  
Oscar Viyuela

Nature ◽  
2020 ◽  
Vol 580 (7805) ◽  
pp. 602-607 ◽  
Author(s):  
Juan A. Muniz ◽  
Diego Barberena ◽  
Robert J. Lewis-Swan ◽  
Dylan J. Young ◽  
Julia R. K. Cline ◽  
...  

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