Spiral Wave Emergence in Spiking Cortical Fields under Simulated Anesthesia

Spiral waves are spatiotemporal patterns observed in various excitable media, including corticaltissue under specific brain states such as slow-wave sleep and anesthesia. In this work, weinvestigate the emergence and controllability of spiral wavefronts in a two-dimensional lattice ofspiking neurons modeled using the Adaptive Exponential Integrate-and-Fire (AdEx) framework.The network emulates cortical dynamics under different levels of simulated anesthesia by modulatingadaptation strength and external drive, thereby shifting its operating regime within aphysiologically inspired phase diagram.We introduce several population-level observables, including a Hilbert-based phase representationof multi-unit activity (MUA), and define a novel metric, HiPhStd, to detect and classifytraveling waves. Spiral waves are identified based on their effective dimensionality, and their occurrenceis shown to depend critically on both the network’s excitability state and local phasesynchronization heterogeneity.While spiral waves do not emerge spontaneously, we demonstrate that they can be reliablyevoked through focal stimulation and, importantly, through global sinusoidal modulation of theexternal current. These structured inputs—especially in propagating and coherent configurations—induce spontaneous spiral activity in the absence of localized triggers, reinforcing the roleof network synchrony in spiral generation.Our findings provide insight into the mechanisms underlying the emergence of spiral waves incortical circuits and suggest new strategies for probing state-dependent dynamics in both computationaland biological systems.