Affiliation:
1. School of Mathematical Sciences, Zhejiang University , Hangzhou 310058, China
Abstract
The theory of self-organized bistability (SOB) is the counterpart of self-organized criticality for systems tuning themselves to the edge of bistability of a discontinuous phase transition, rather than to the critical point of a continuous one. As far as we are concerned, there are currently few neural network models that display SOB or rather its non-conservative version, self-organized collective oscillations (SOCO). We show that by slightly modifying the firing function, a stochastic excitatory/inhibitory network model can display SOCO behaviors, thus providing some insights into how SOCO behaviors can be generated in neural network models.
Subject
Applied Mathematics,General Physics and Astronomy,Mathematical Physics,Statistical and Nonlinear Physics
Cited by
1 articles.
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