Title
Sequential Noise-Induced Escapes for Oscillatory Network Dynamics.
Abstract
It is well known that the addition of noise in a multistable system can induce random transitions between stable states. The rate of transition can be characterized in terms of the noise-free system's dynamics and the added noise: for potential systems in the presence of asymptotically low noise the well-known Kramers' escape time gives an expression for the mean escape time. This paper examines some general properties and examples of transitions between local steady and oscillatory attractors within networks: the transition rates at each node may be affected by the dynamics at other nodes. We use first passage time theory to explain some properties of scalings noted in the literature for an idealized model of initiation of epileptic seizures in small systems of coupled bistable systems with both steady and oscillatory attractors. We focus on the case of sequential escapes where a steady attractor is only marginally stable but all nodes start in this state. As the nodes escape to the oscillatory regime, we assume that the transitions back are very infrequent in comparison. We quantify and characterize the resulting sequences of noise-induced escapes. For weak enough coupling we show that a master equation approach gives a good quantitative understanding of sequential escapes, but for strong coupling this description breaks down.
Year
DOI
Venue
2018
10.1137/17M1126412
SIAM JOURNAL ON APPLIED DYNAMICAL SYSTEMS
Keywords
Field
DocType
noise-induced escape,mean first passage time,network dynamics,cascading failure,epilepsy
Attractor,Bistability,Network dynamics,Stable states,Control theory,Low noise,Cascading failure,First-hitting-time model,Mathematics
Journal
Volume
Issue
ISSN
17
1
1536-0040
Citations 
PageRank 
References 
0
0.34
2
Authors
3
Name
Order
Citations
PageRank
Jennifer L. Creaser101.69
Krasimira Tsaneva-Atanasova203.04
P. Ashwin3178.26