Emergence of Self-Sustaining Activation in Dynamically Growing Networks

Here we present a network model in which self-sustaining recurrent activation emerges from simple cascades of activation. It is demonstrated that the ability to support such self-sustaining activation in our model depends on network connectivity as well as the ability to grow new links over time. Additionally, we explore how the probability of emergence of self-sustaining activity can be modulated by changing various network parameters and suggest potential applications of our findings.