Litcius/Paper detail

Determinants of collective failure in excitable networks

Uroš Barać, Matjaž Perc, Marko Gosak

2023Chaos An Interdisciplinary Journal of Nonlinear Science18 citationsDOIOpen Access PDF

Abstract

We study collective failures in biologically realistic networks that consist of coupled excitable units. The networks have broad-scale degree distribution, high modularity, and small-world properties, while the excitable dynamics is determined by the paradigmatic FitzHugh-Nagumo model. We consider different coupling strengths, bifurcation distances, and various aging scenarios as potential culprits of collective failure. We find that for intermediate coupling strengths, the network remains globally active the longest if the high-degree nodes are first targets for inactivation. This agrees well with previously published results, which showed that oscillatory networks can be highly fragile to the targeted inactivation of low-degree nodes, especially under weak coupling. However, we also show that the most efficient strategy to enact collective failure does not only non-monotonically depend on the coupling strength, but it also depends on the distance from the bifurcation point to the oscillatory behavior of individual excitable units. Altogether, we provide a comprehensive account of determinants of collective failure in excitable networks, and we hope this will prove useful for better understanding breakdowns in systems that are subject to such dynamics.

Topics & Concepts

Modularity (biology)Coupling strengthCoupling (piping)BifurcationDegree distributionMonotonic functionStatistical physicsDegree (music)Computer scienceStability (learning theory)Point (geometry)Complex networkDynamics (music)Bifurcation theoryTopology (electrical circuits)PhysicsMathematicsNonlinear systemEngineeringBiologyMathematical analysisMechanical engineeringCondensed matter physicsWorld Wide WebGeometryQuantum mechanicsAcousticsGeneticsCombinatoricsMachine learningNeural dynamics and brain functionNonlinear Dynamics and Pattern Formationstochastic dynamics and bifurcation