Entropy | |
Self-Organized Supercriticality and Oscillations in Networks of Stochastic Spiking Neurons | |
Ludmila Brochini1  Osame Kinouchi2  Ariadne A. Costa3  | |
[1] Departamento de Estatística, Instituto de Matemática e Estatística (IME), Universidade de São Paulo, São Paulo-SP 05508-090, Brazil;Departamento de Física, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto (FFCLRP), Universidade de São Paulo, Ribeirão Preto-SP 14040-901, Brazil;Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405, USA; | |
关键词: self-organized criticality; neuronal avalanche; stochastic neuron; spiking neuron; neuron models; neuronal networks; power law; supercriticality; | |
DOI : 10.3390/e19080399 | |
来源: DOAJ |
【 摘 要 】
Networks of stochastic spiking neurons are interesting models in the area of theoretical neuroscience, presenting both continuous and discontinuous phase transitions. Here, we study fully-connected networks analytically, numerically and by computational simulations. The neurons have dynamic gains that enable the network to converge to a stationary slightly supercritical state (self-organized supercriticality (SOSC)) in the presence of the continuous transition. We show that SOSC, which presents power laws for neuronal avalanches plus some large events, is robust as a function of the main parameter of the neuronal gain dynamics. We discuss the possible applications of the idea of SOSC to biological phenomena like epilepsy and Dragon-king avalanches. We also find that neuronal gains can produce collective oscillations that coexist with neuronal avalanches.
【 授权许可】
Unknown