Criticality in spreading processes without time-scale separation and the critical brain hypothesis
Daniel J. Korchinski, Javier G. Orlandi, Seung-Woo Son, J\"orn, Davidsen

TL;DR
This paper investigates how the nature of critical spreading processes changes when there is no clear separation of time scales, revealing a transition between universality classes that impacts understanding of phenomena like epidemics and brain activity.
Contribution
It provides analytical results describing the critical line and universality class transitions in spreading processes without time-scale separation, challenging traditional measures of criticality.
Findings
Identifies a transition between directed and undirected percolation universality classes.
Shows that common criticality measures fail without time-scale separation.
Derives a scaling relationship governing the transition point.
Abstract
Spreading processes on networks are ubiquitous in both human-made and natural systems. Understanding their behavior is of broad interest; from the control of epidemics to understanding brain dynamics. While in some cases there exists a clear separation of time scales between the propagation of a single spreading cascade and the initiation of the next -- such that spreading can be modelled as directed percolation or a branching process -- there are also processes for which this is not the case, such as zoonotic diseases or spiking cascades in neural networks. For a large class of relevant network topologies, we show here that in such a scenario the nature of the overall spreading fundamentally changes. This change manifests itself in a transition between different universality classes of critical spreading, which determines the onset and the properties of an avalanche turning epidemic or…
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