Noise-shaped synchrony in neuronal oscillator networks

Stochastic fluctuations often act as promoters of activity in excitable and oscillatory systems, giving rise to phenomena such as coherence resonance. Here, we show that in the low-intensity regime, noise plays a dual role in weakly coupled neuronal units: It can both inhibit collective spiking and, with increasing intensity, restore coordinated activity. For a ring of diffusively coupled, oscillatory FitzHugh-Nagumo neurons, we demonstrate how the interplay of noise and coupling strength organizes a rich set of collective dynamical states. We systematically classify emergent dynamical scenarios by an in-depth time-series analysis that integrates multiple complementary measures. We are able to automatically identify five distinct dynamical clusters in parameter space: pure noise, quiescent state, noisy synchronization, complete synchronization, and intermittent switching. Our workflow provides a general, automated framework for characterizing collective dynamics in coupled oscillator networks.