Enhancement of early warning properties in the Kuramoto model and in an atrial fibrillation model due to an external perturbation of the system

García-Gudiño, David; Landa, Emmanuel; Mendoza-Temis, Joel; Albarado-Ibáñez, Alondra; Toledo-Roy, J. C.; Morales, Irving O.; Frank, A.

doi:10.1371/journal.pone.0181953

Cited by 5 publications

(8 citation statements)

References 15 publications

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“…Hwang et al (2016) and Hwang et al (2017) examined the effect of the ANS on arrhythmogenesis where the role of ganglia on the initiation of AF is highlighted. The concept of early warning that can forecast a change of system’s stability is applied in AF electrophysiology (Garcia-Gudino et al, 2017). In this study, a cellular automaton is used to describe atrial conduction on the tissue.…”

Section: Resultsmentioning

confidence: 99%

Understanding the Beat-to-Beat Variations of P-Waves Morphologies in AF Patients During Sinus Rhythm: A Scoping Review of the Atrial Simulation Studies

et al. 2019

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The remarkable advances in high-performance computing and the resulting increase of the computational power have the potential to leverage computational cardiology toward improving our understanding of the pathophysiological mechanisms of arrhythmias, such as Atrial Fibrillation (AF). In AF, a complex interaction between various triggers and the atrial substrate is considered to be the leading cause of AF initiation and perpetuation. In electrocardiography (ECG), P-wave is supposed to reflect atrial depolarization. It has been found that even during sinus rhythm (SR), multiple P-wave morphologies are present in AF patients with a history of AF, suggesting a higher dispersion of the conduction route in this population. In this scoping review, we focused on the mechanisms which modify the electrical substrate of the atria in AF patients, while investigating the existence of computational models that simulate the propagation of the electrical signal through different routes. The adopted review methodology is based on a structured analytical framework which includes the extraction of the keywords based on an initial limited bibliographic search, the extensive literature search and finally the identification of relevant articles based on the reference list of the studies. The leading mechanisms identified were classified according to their scale, spanning from mechanisms in the cell, tissue or organ level, and the produced outputs. The computational modeling approaches for each of the factors that influence the initiation and the perpetuation of AF are presented here to provide a clear overview of the existing literature. Several levels of categorization were adopted while the studies which aim to translate their findings to ECG phenotyping are highlighted. The results denote the availability of multiple models, which are appropriate under specific conditions. However, the consideration of complex scenarios taking into account multiple spatiotemporal scales, personalization of electrophysiological and anatomical models and the reproducibility in terms of ECG phenotyping has only partially been tackled so far.

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Section: Resultsmentioning

confidence: 99%

Understanding the Beat-to-Beat Variations of P-Waves Morphologies in AF Patients During Sinus Rhythm: A Scoping Review of the Atrial Simulation Studies

et al. 2019

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“…Using TS analysis [7, 15], it was found that the Ising model has a critical temperature value T C ≈ 2.27, while the critical coupling constant in the Kuramoto model is close to K C ≈ 1.65, however, the effects of finiteness and periodicity of the mesh, as well as the effect of finite oscillators, can cause the critical value to be slightly displaced. It was also shown that both models have a change in its behavior as the control parameter approaches to the critical value (from above and below).…”

Section: Resultsmentioning

confidence: 99%

“…As future work there are some other systems, as the atrial model presented in [15], in which it will be desirable to check this visualization algorithms. Also, it will be interesting to probe if other algorithms for building networks, as the one proposed in [30], would preserve this characteristics.…”

Section: Discussionmentioning

confidence: 99%

“…Taking this into account, and the fact that the models presented before, present a distinctive behavior near a critical point [7, 15]; the main objective of our work is to study if this behavior is reflected in some of the properties of the network, built through two of the most popular visibility algorithms: the Natural Visibility Algorithm (NVA) and the Horizontal Visibility Algorithm (HVA). Besides to establish if there is any advantage of choosing one algorithm over the other.…”

Section: From Ts To Networkmentioning

confidence: 99%

“…In order to study which topological quantities of the network could help us to characterize the system we have focused our attention in two classical physics models, which are well known to present a phase transition: the two-dimensional Ising Model and the Kuramoto Model. Both models have been extensively studied through TS analysis [5, 7, 15] because of their relevance and the wide range of systems to which they can be applied. Also, we have used two visibility algorithms, to built networks from TS, to establish if there is an advantage of one of them over the other.…”

Section: Introductionmentioning

confidence: 99%

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Analysis of properties of Ising and Kuramoto models that are preserved in networks constructed by visualization algorithms

et al. 2019

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Recently it has been shown that building networks from time series allows to study complex systems to characterize them when they go through a phase transition. This give us the opportunity to study this systems from a entire new point of view. In the present work we have used the natural and horizontal visualization algorithms to built networks of two popular models, which present phase transitions: the Ising model and the Kuramoto model. By measuring some topological quantities as the average degree, or the clustering coefficient, it was found that the networks retain the capability of detecting the phase transition of the system. From our results it is possible to establish that both visibility algorithms are capable of detecting the critical control parameter, as in every quantity analyzed (the average degree, the average path and the clustering coefficient) there is a minimum or a maximum value. In the case of the natural visualization algorithm, the average path results are much more noisy than in the other quantities in the study. Specially for the Kuramoto Model, which in this case does not allow a detection of the critical point at plain sight as for the other quantities. The horizontal visualization algorithm has proven to be more explicit in every quantity, as every one of them show a clear change of behavior before and after the critical point of the transition.

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Early warning signals of regime shifts for aquatic systems: Can experiments help to bridge the gap between theory and real-world application?

Stelzer

Mesman

Adrian

et al. 2021

Ecological Complexity

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Enhancement of early warning properties in the Kuramoto model and in an atrial fibrillation model due to an external perturbation of the system

Cited by 5 publications

References 15 publications

Understanding the Beat-to-Beat Variations of P-Waves Morphologies in AF Patients During Sinus Rhythm: A Scoping Review of the Atrial Simulation Studies

Understanding the Beat-to-Beat Variations of P-Waves Morphologies in AF Patients During Sinus Rhythm: A Scoping Review of the Atrial Simulation Studies

Analysis of properties of Ising and Kuramoto models that are preserved in networks constructed by visualization algorithms

Early warning signals of regime shifts for aquatic systems: Can experiments help to bridge the gap between theory and real-world application?

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