网络化可激介质中的不稳定动力学、非平衡相与临界性

Here we numerically study a model of excitable media, namely, a network with occasionally quiet nodes and connection weights that vary with activity on a short-time scale. Even in the absence of stimuli, this exhibits unstable dynamics, nonequilibrium phases -including one in which the global activity wanders irregularly among attractors- and 1/f noise while the system falls into the most irregular behavior. A net result is resilience which results in an efficient search in the model attractors space that can explain the origin of certain phenomenology in neural, genetic and ill-condensed matter systems. By extensive computer simulation we also address a relation previously conjectured between observed power-law distributions and the occurrence of a "critical state" during functionality of (e.g.) cortical networks, and describe the precise nature of such criticality in the model.