SIMPLE MATHEMATICAL MODELS FOR COMPLEX DYNAMICS IN PHYSIOLOGICAL SYSTEMS

Author(s):  
Leon Glass
2020 ◽  
Vol 17 (2-3) ◽  
Author(s):  
Michael Clerx ◽  
Michael T. Cooling ◽  
Jonathan Cooper ◽  
Alan Garny ◽  
Keri Moyle ◽  
...  

AbstractWe present here CellML 2.0, an XML-based language for describing and exchanging mathematical models of physiological systems. MathML embedded in CellML documents is used to define the underlying mathematics of models. Models consist of a network of reusable components, each with variables and equations giving relationships between those variables. Models may import other models to create systems of increasing complexity. CellML 2.0 is defined by the normative specification presented here, prescribing the CellML syntax and the rules by which it should be used. The normative specification is intended primarily for the developers of software tools which directly consume CellML syntax. Users of CellML models may prefer to browse the informative rendering of the specification (https://cellml.org/specifications/cellml_2.0/) which extends the normative specification with explanations of the rules combined with examples of their usage.


2018 ◽  
Vol 115 (7) ◽  
pp. E1336-E1345 ◽  
Author(s):  
Jonathan David Touboul ◽  
Ann Carla Staver ◽  
Simon Asher Levin

Simple mathematical models can exhibit rich and complex behaviors. Prototypical examples of these drawn from biology and other disciplines have provided insights that extend well beyond the situations that inspired them. Here, we explore a set of simple, yet realistic, models for savanna–forest vegetation dynamics based on minimal ecological assumptions. These models are aimed at understanding how vegetation interacts with both climate (a primary global determinant of vegetation structure) and feedbacks with chronic disturbances from fire. The model includes three plant functional types—grasses, savanna trees, and forest trees. Grass and (when they allow grass to persist in their subcanopy) savanna trees promote the spread of fires, which in turn, demographically limit trees. The model exhibits a spectacular range of behaviors. In addition to bistability, analysis reveals (i) that diverse cyclic behaviors (including limit and homo- and heteroclinic cycles) occur for broad ranges of parameter space, (ii) that large shifts in landscape structure can result from endogenous dynamics and not just from external drivers or from noise, and (iii) that introducing noise into this system induces resonant and inverse resonant phenomena, some of which have never been previously observed in ecological models. Ecologically, these results raise questions about how to evaluate complicated dynamics with data. Mathematically, they lead to classes of behaviors that are likely to occur in other models with similar structure.


1989 ◽  
Vol 257 (2) ◽  
pp. H693-H706 ◽  
Author(s):  
M. Courtemanche ◽  
L. Glass ◽  
M. D. Rosengarten ◽  
A. L. Goldberger

The dynamics of pure parasystole, a cardiac arrhythmia in which two competing pacemakers fire independently, have recently been fully characterized. This model is now extended in an attempt to account for the more complex dynamics occurring with modulated parasystole, in which there exists nonlinear interaction between the sinus node and the ectopic ventricular focus. Theoretical analysis of modulated parasystole reveals three types of dynamics: entrainment, quasiperiodicity, and chaos. Rhythms associated with quasiperiodicity obey a set of rules derived from pure parasystole. This model is applied to the interpretation of continuous electrocardiographic data sets from three patients with complicated patterns of ventricular ectopic activity. We describe several new statistical properties of these records, related to the number of intervening sinus beats between ectopic events, that are essential in characterizing the dynamics and testing mathematical models. Detailed comparison between data and theory in these cases show substantial areas of agreement as well as potentially important discrepancies. These findings have implications for understanding the dynamics of the heartbeat in normal and pathological conditions.


2017 ◽  
Author(s):  
Jonathan Desponds ◽  
Andreas Mayer ◽  
Thierry Mora ◽  
Aleksandra M. Walczak

The evolution of the adaptive immune system is characterized by changes in the relative abundances of the B and T-cell clones that make up its repertoires. To fully capture this evolution, we need to describe the complex dynamics of the response to pathogenic and self-antigenic stimulations, as well as the statistics of novel lymphocyte receptors introduced throughout life. Recent experiments, ranging from high-throughput immune repertoire sequencing to quantification of the response to specific antigens, can help us characterize the effective dynamics of the immune response. Here we describe mathematical models informed by experiments that lead to a picture of clonal competition in a highly stochastic context. We discuss how different types of competition, noise and selection shape the observed clone-size distributions, and contrast them with predictions of a neutral theory of clonal evolution. These mathematical models show that memory and effector immune repertoire evolution is far from neutral, and is driven by the history of the pathogenic environment, while naive repertoire dynamics are consistent with neutral theory and competition in a fixed antigenic environment. Lastly, we investigate the effect of long-term clonal selection on repertoire aging.


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