When a complex dynamical system is externally disturbed, the statistical moments of signals associated to it can be affected in ways that depend on the nature and amplitude of the perturbation. In systems that exhibit phase transitions, the statistical moments can be used as Early Warnings (EW) of the transition. A natural question is thus to wonder what effect external disturbances have on the EWs of system. In this work we study the impact of external noise added to the system on the EWs, with particular focus on understanding the importance of the amplitude and complexity of the noise. We do this by analyzing the EWs of two computational models related to biology: the Kuramoto model, which is a paradigm of synchronization for biological systems, and a cellular automaton model of cardiac dynamics which has been used as a model for atrial fibrillation. For each model we first characterize the EWs. Then, we introduce external noise of varying intensity and nature to observe what effect this has on the EWs. In both cases we find that the introduction of noise amplified the EWs, with more complex noise having a greater effect. This both offers a way to improve the chance of detection of EWs in real systems and suggests that natural variability in the real world does not have a detrimental effect on EWs, but the opposite.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5533321 | PMC |
| http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0181953 | PLOS |
Publication Analysis
Top Keywords
Similar Publications
Mean-field approximation for networks with synchrony-driven adaptive coupling.
Chaos
January 2025
School of Mathematics and Statistics, University College Dublin, Dublin 4 D04 V1W8, Ireland.
Synaptic plasticity plays a fundamental role in neuronal dynamics, governing how connections between neurons evolve in response to experience. In this study, we extend a network model of θ-neuron oscillators to include a realistic form of adaptive plasticity. In place of the less tractable spike-timing-dependent plasticity, we employ recently validated phase-difference-dependent plasticity rules, which adjust coupling strengths based on the relative phases of θ-neuron oscillators.
View Article and Find Full Text PDFModeling of Jet Lag and Searching for an Optimal Light Treatment.
J Biol Rhythms
January 2025
Department of Physics and i3n, University of Aveiro, Aveiro, Portugal.
The role of the hierarchical organization of the suprachiasmatic nucleus (SCN) in its functioning, jet lag, and the light treatment of jet lag remains poorly understood. Using the core-shell model, we mimic collective behavior of the core and shell populations of the SCN oscillators in transient states after rapid traveling east and west. The existence of a special region of slow dynamical states of the SCN oscillators can explain phenomena such as the east-west asymmetry of jet lag, instances when entrainment to an advance is via delay shifts, and the dynamics of jet lag recovery time.
View Article and Find Full Text PDFStudying power-grid synchronization with incremental refinement of model heterogeneity.
Chaos
January 2025
Institute of Technical Physics and Materials Science, HUN-REN Centre for Energy Research, P.O. Box 49, H-1525 Budapest, Hungary.
The dynamics of electric power systems are widely studied through the phase synchronization of oscillators, typically with the use of the Kuramoto equation. While there are numerous well-known order parameters to characterize these dynamics, shortcoming of these metrics are also recognized. To capture all transitions from phase disordered states over phase locking to fully synchronized systems, new metrics were proposed and demonstrated on homogeneous models.
View Article and Find Full Text PDFSynchronization stability of epileptic brain network with higher-order interactions.
Chaos
January 2025
Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing 100053, China.
Generally, epilepsy is considered as abnormally enhanced neuronal excitability and synchronization. So far, previous studies on the synchronization of epileptic brain networks mainly focused on the synchronization strength, but the synchronization stability has not yet been explored as deserved. In this paper, we propose a novel idea to construct a hypergraph brain network (HGBN) based on phase synchronization.
View Article and Find Full Text PDFTaming chimeras in coupled oscillators using soft actor-critic based reinforcement learning.
Chaos
January 2025
Complex Systems Group, Department of Mathematics and Statistics, The University of Western Australia, Crawley, Western Australia 6009, Australia.
We propose a universal method based on deep reinforcement learning (specifically, soft actor-critic) to control the chimera state in the coupled oscillators. The policy for control is learned by maximizing the expectation of the cumulative reward in the reinforcement learning framework. With the aid of the local order parameter, we design a class of reward functions for controlling the chimera state, specifically confining the spatial position of coherent and incoherent domains to any desired lateral position of oscillators.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!