Dynamical and topological conditions triggering the spontaneous activation of Izhikevich neuronal networks

Understanding the dynamic behavior of neuronal networks in silico is crucial for tackling analysis their biological counterparts and making accurate predictions. Of particular importance determining structural dynamical conditions necessary a network to activate spontaneously, transitioning from quiescent ensemble neurons network-wide coherent burst. Drawing versatility Master Stability Function, we have applied this formalism system coupled described by Izhikevich model derive required activation. These are expressed as critical effective coupling gC, grounded both topology dynamics, above which will activate. For regular spiking neurons, average connectivity noise play significant role ability We tested these against numerical simulations networks, including synthetic topologies biologically-realistic spatial network, showing that theoretical well satisfied. Our findings indicate readily meet criteria spontaneous activation, capacity weakly dependent on microscopic details long sufficiently strong.