Abstract
In this study, we investigate how lightning-derived electric-field influences nonlinear excitation dynamics in excitable systems. Cloud-to-ground (CG) lightning observations from the National Lightning Detection Network (NLDN), including event time, location, and peak current, were used to reconstruct realistic lightning-derived electric-field inputs. The electric field distribution was estimated from lightning peak current and propagation distance using a physical formulation, and discrete lightning events were converted into continuous time-dependent forcing signals through Gaussian kernel superposition while preserving their spatiotemporal organization. The resulting electric-field signals were then applied to the FitzHugh–Nagumo (FHN) model, where biologically inspired excitation dynamics were simulated and analyzed using normalized external inputs. The simulations demonstrate that temporally accumulated lightning-derived forcing induces nonlinear transitions between excitation regimes. Stronger peak-current inputs more readily exceed excitation thresholds and produce enhanced responses, including repeated excitation events, whereas weaker inputs generate limited or sub-threshold responses. These results show that excitation dynamics depend not only on electric-field amplitude but also on the temporal accumulation and organization of lightning activity. Furthermore, a spatially extended reaction–diffusion FHN model demonstrates that lightning-induced electric-field attenuation coupled with nonlinear dynamics can generate spatially propagating excitation structures. This physics-based framework provides a conceptual approach for linking naturally occurring electric-field environments with nonlinear excitable-system dynamics. Although the present model does not represent direct physiological coupling, it provides a foundation for exploring how structured environmental electric fields may influence threshold-dependent dynamical responses.