Publications
88 results found
Shi X, Sau A, Li X, et al., 2023, Information theory-based direct causality measure to assess cardiac fibrillation dynamics, Journal of the Royal Society Interface, Vol: 20, ISSN: 1742-5662
Understanding the mechanism sustaining cardiac fibrillation can facilitate the personalization of treatment. Granger causality analysis can be used to determine the existence of a hierarchical fibrillation mechanism that is more amenable to ablation treatment in cardiac time-series data. Conventional Granger causality based on linear predictability may fail if the assumption is not met or given sparsely sampled, high-dimensional data. More recently developed information theory-based causality measures could potentially provide a more accurate estimate of the nonlinear coupling. However, despite their successful application to linear and nonlinear physical systems, their use is not known in the clinical field. Partial mutual information from mixed embedding (PMIME) was implemented to identify the direct coupling of cardiac electrophysiology signals. We show that PMIME requires less data and is more robust to extrinsic confounding factors. The algorithms were then extended for efficient characterization of fibrillation organization and hierarchy using clinical high-dimensional data. We show that PMIME network measures correlate well with the spatio-temporal organization of fibrillation and demonstrated that hierarchical type of fibrillation and drivers could be identified in a subset of ventricular fibrillation patients, such that regions of high hierarchy are associated with high dominant frequency.
Bolko AE, Christensen K, Pakkanen MS, et al., 2023, A GMM approach to estimate the roughness of stochastic volatility, Journal of Econometrics, Vol: 235, Pages: 745-778, ISSN: 0304-4076
We develop a GMM approach for estimation of log-normal stochastic volatility modelsdriven by a fractional Brownian motion with unrestricted Hurst exponent. We show thata parameter estimator based on the integrated variance is consistent and, under strongerconditions, asymptotically normally distributed. We inspect the behavior of our procedurewhen integrated variance is replaced with a noisy measure of volatility calculated from discretehigh-frequency data. The realized estimator contains sampling error, which skews the fractalcoefficient toward “illusive roughness.” We construct an analytical approach to control theimpact of measurement error without introducing nuisance parameters. In a simulation study,we demonstrate convincing small sample properties of our approach based both on integratedand realized variance over the entire memory spectrum. We show the bias correction attenuatesany systematic deviance in the parameter estimates. Our procedure is applied to empiricalhigh-frequency data from numerous leading equity indexes. With our robust approach theHurst index is estimated around 0.05, confirming roughness in stochastic volatility.
Yao Q, Ma S, Liang J, et al., 2023, Syndication network associates with specialisation and performance of venture capital firms, JOURNAL OF PHYSICS-COMPLEXITY, Vol: 4
Falkenberg McGillivray M, Coleman JA, Dobson S, et al., 2022, Identifying locations susceptible to micro-anatomical reentry using a spatial network representation of atrial fibre maps, PLoS One, Vol: 17, Pages: 1-24, ISSN: 1932-6203
Micro-anatomical reentry has been identified as a potential driver of atrial fibrillation (AF). In this paper, we introduce a novel computational method which aims to identify which atrial regions are most susceptible to micro-reentry. The approach, which considers the structural basis for micro-reentry only, is based on the premise that the accumulation of electrically insulating interstitial fibrosis can be modelled by simulating percolation-like phenomena on spatial networks. Our results suggest that at high coupling, where micro-reentry is rare, the micro-reentrant substrate is highly clusteredin areas where the atrial walls are thin and have convex wall morphology, likely facilitating localised treatment via ablation. However, as transverse connections between fibres are removed, mimicking the accumulation of interstitial fibrosis, the substrate becomes less spatially clustered, and the bias to forming in thin, convex regions of the atria is reduced, possibly restricting the efficacy of localised ablation. Comparing our algorithm on image-based models with and without atrial fibre structure, we find thatstrong longitudinal fibre coupling can suppress the micro-reentrant substrate, whereas regions with disordered fibre orientations have an enhanced risk of micro-reentry. With further development, these methods may be useful for modelling the temporal development of the fibrotic substrate on an individualised basis.
Yao Q, Evans T, Chen B, et al., 2021, Higher-order temporal network effects through triplet evolution, Scientific Reports, Vol: 11, Pages: 1-17, ISSN: 2045-2322
We study the evolution of networks through ‘triplets’ — three-node graphlets. We develop a method to compute a transitionmatrix to describe the evolution of triplets in temporal networks. To identify the importance of higher-order interactions inthe evolution of networks, we compare both artificial and real-world data to a model based on pairwise interactions only.The significant differences between the computed matrix and the calculated matrix from the fitted parameters demonstratethat non-pairwise interactions exist for various real-world systems in space and time, such as our data sets. Furthermore,this also reveals that different patterns of higher-order interaction are involved in different real-world situations.To test our approach, we then use these transition matrices as the basis of a link prediction algorithm. We investigate ouralgorithm’s performance on four temporal networks, comparing our approach against ten other link prediction methods.Our results show that higher-order interactions in both space and time play a crucial role in the evolution of networks as wefind our method, along with two other methods based on non-local interactions, give the best overall performance. Theresults also confirm the concept that the higher-order interaction patterns, i.e., triplet dynamics, can help us understandand predict the evolution of different real-world systems.
Liu S-W, Willsher J, Bilitewski T, et al., 2021, Butterfly effect and spatial structure of information spreading in a chaotic cellular automaton, Physical Review B, Vol: 103, Pages: 1-6, ISSN: 2469-9950
Inspired by recent developments in the study of chaos in many-body systems, we construct a measure of local information spreading for a stochastic cellular automaton in the form of a spatiotemporally resolved Hamming distance. This decorrelator is a classical version of an out-of-time-order correlator studied in the context of quantum many-body systems. Focusing on the one-dimensional Kauffman cellular automaton, we extract the scaling form of our decorrelator with an associated butterfly velocity vb and a velocity-dependent Lyapunov exponent λ(v). The existence of the latter is not a given in a discrete classical system. Second, we account for the behavior of the decorrelator in a framework based solely on the boundary of the information spreading, including an effective boundary random walk model yielding the full functional form of the decorrelator. In particular, we obtain analytic results for vb and the exponent β in the scaling ansatz λ(v)∼μ(v−vb)β, which is usually only obtained numerically. Finally, a full scaling collapse establishes the decorrelator as a unifying diagnostic of information spreading.
Cocconi L, Kuhn-Regnier A, Neuss M, et al., 2021, Reconstructing the intrinsic statistical properties of intermittent locomotion through corrections for boundary effects, Bulletin of Mathematical Biology, Vol: 83, Pages: 1-17, ISSN: 0092-8240
Locomotion characteristics are often recorded within bounded spaces, a constraint which introduces geometry-specific biases and potentially complicates the inference of behavioural features from empirical observations. We describe how statistical properties of an uncorrelated random walk, namely the steady-state stopping location probability density and the empirical step probability density, are affected by enclosure in a bounded space. The random walk here is considered as a null model for an organism moving intermittently in such a space, that is, the points represent stopping locations and the step is the displacement between them. Closed-form expressions are derived for motion in one dimension and simple two-dimensional geometries, in addition to an implicit expression for arbitrary (convex) geometries. For the particular choice of no-go boundary conditions, we demonstrate that the empirical step distribution is related to the intrinsic step distribution, i.e. the one we would observe in unbounded space, via a multiplicative transformation dependent solely on the boundary geometry. This conclusion allows in practice for the compensation of boundary effects and the reconstruction of the intrinsic step distribution from empirical observations.
Christensen K, Cocconi L, Sendova-Franks AB, 2021, Animal intermittent locomotion: a null model for the probability of moving forward in bounded space., Journal of Theoretical Biology, Vol: 510, Pages: 1-19, ISSN: 0022-5193
We present a null model to be compared with biological data to test for intrinsic persistence in movement between stops during intermittent locomotion in bounded space with different geometries and boundary conditions. We describe spatio-temporal properties of the sequence of stopping points r1,r2,r3,… visited by a Random Walker within a bounded space. The path between stopping points is not considered, only the displacement. Since there are no intrinsic correlations in the displacements between stopping points, there is no intrinsic persistence in the movement between them. Hence, this represents a null-model against which to compare empirical data for directional persistence in the movement between stopping points when there is external bias due to the bounded space. This comparison is a necessary first step in testing hypotheses about the function of the stops that punctuate intermittent locomotion in diverse organisms. We investigate the probability of forward movement, defined as a deviation of less than 90° between two successive displacement vectors, as a function of the ratio between the largest displacement between stops that could be performed by the random walker and the system size, α=Δℓ/Lmax. As expected, the probability of forward movement is 1/2 when α→0. However, when α is finite, this probability is less than 1/2 with a minimum value when α=1. For certain boundary conditions, the minimum value is between 1/3 and 1/4 in 1D while it can be even lower in 2D. The probability of forward movement in 1D is calculated exactly for all values 0<α⩽1 for several boundary conditions. Analytical calculations for the probability of forward movement are performed in 2D for circular and square bounded regions with one boundary condition. Numerical results for all values 0<α⩽1 are presented for several boundary conditions. The cases of rectangle and ellipse are also considered and an approximate model of
Ciacci A, Sueshige T, Takayasu H, et al., 2020, The microscopic relationships between triangular arbitrage and cross-currency correlations in a simple agent based model of foreign exchange markets, PLoS One, Vol: 15, Pages: 1-19, ISSN: 1932-6203
Foreign exchange rates movements exhibit significant cross-correlations even on very short time-scales. The effect of these statistical relationships become evident during extreme market events, such as flash crashes. Although a deep understanding of cross-currency correlations would be clearly beneficial for conceiving more stable and safer foreign exchange markets, the microscopic origins of these interdependencies have not been extensively investigated. This paper introduces an agent-based model which describes the emergence of cross-currency correlations from the interactions between market makers and an arbitrager. The model qualitatively replicates the time-scale vs. cross-correlation diagrams observed in real trading data, suggesting that triangular arbitrage plays a primary role in the entanglement of the dynamics of different foreign exchange rates. Furthermore, the model shows how the features of the cross-correlation function between two foreign exchange rates, such as its sign and value, emerge from the interplay between triangular arbitrage and trend-following strategies. In particular, the interaction of these trading strategies favors certain combinations of price trend signs across markets, thus altering the probability of observing two foreign exchange rates drifting in the same or opposite direction. Ultimately, this entangles the dynamics of foreign exchange rate pairs, leading to cross-correlation functions that resemble those observed in real trading data.
Falkenberg M, Lee J-H, Amano S-I, et al., 2020, Identifying time dependence in network growth, Physical Review & Research International, Vol: 2, Pages: 023352 – 1-023352 – 17, ISSN: 2231-1815
Identifying power-law scaling in real networks—indicative of preferential attachment—has proved controversial. Critics argue that measuring the temporal evolution of a network directly is better than measuring the degree distribution when looking for preferential attachment. However, many of the established methods do not account for any potential time dependence in the attachment kernels of growing networks, or methods assume that node degree is the key observable determining network evolution. In this paper, we argue that these assumptions may lead to misleading conclusions about the evolution of growing networks. We illustrate this by introducing a simple adaptation of the Barabási-Albert model, the “k2 model,” where new nodes attach to nodes in the existing network in proportion to the number of nodes one or two steps from the target node. The k2 model results in time dependent degree distributions and attachment kernels, despite initially appearing to grow as linear preferential attachment, and without the need to include explicit time dependence in key network parameters (such as the average out-degree). We show that similar effects are seen in several real world networks where constant network growth rules do not describe their evolution. This implies that measurements of specific degree distributions in real networks are likely to change over time.
Ciacci A, Falkenberg M, Manani KA, et al., 2020, Understanding the transition from paroxysmal to persistent atrial fibrillation, Physical Review Research, Vol: 2, Pages: 1-23, ISSN: 2643-1564
Atrial fibrillation (AF) is the most common cardiac arrhytmia, characterisedby the chaotic motion of electrical wavefronts in the atria. In clinicalpractice, AF is classified under two primary categories: paroxysmal AF, shortintermittent episodes separated by periods of normal electrical activity, andpersistent AF, longer uninterrupted episodes of chaotic electrical activity.However, the precise reasons why AF in a given patient is paroxysmal orpersistent is poorly understood. Recently, we have introduced the percolationbased Christensen-Manani-Peters (CMP) model of AF which naturally exhibits bothparoxysmal and persistent AF, but precisely how these differences emerge in themodel is unclear. In this paper, we dissect the CMP model to identify the causeof these different AF classifications. Starting from a mean-field model wherewe describe AF as a simple birth-death process, we add layers of complexity tothe model and show that persistent AF arises from the formation of temporallystable structural re-entrant circuits that form from the interaction ofwavefront collisions during paroxysmal AF. These results are compatible withrecent findings suggesting that the formation of re-entrant drivers in fibroticborder zones perpetuates persistent AF.
Falkenberg M, Hickey D, Terrill L, et al., 2020, Identifying potential re-entrant circuit locations from atrial fibre maps., Computing in cardiology, Vol: 46, Pages: 1-4, ISSN: 2325-8861
Re-entrant circuits have been identified as potential drivers of atrial fibrillation (AF). In this paper, we develop a novel computational framework for finding the locations of re-entrant circuits from high resolution fibre orientation data. The technique follows a statistical approach whereby we generate continuous fibre tracts across the tissue and couple adjacent fibres stochastically if they are within a given distance of each other. By varying the connection distance, we identify which regions are most susceptible to forming re-entrant circuits if muscle fibres are uncoupled, through the action of fibrosis or otherwise. Our results highlight the sleeves of the pulmonary veins, the posterior left atrium and the left atrial appendage as the regions most susceptible to re-entrant circuit formation. This is consistent with known risk locations in clinical AF. If the model can be personalised for individual patients undergoing ablation, future versions may be able to suggest suitable ablation targets.
Falkenberg McGillivray M, Ford A, Li A, et al., 2019, Unified mechanism of local drivers in a percolation model of atrial fibrillation, Physical Review E, Vol: 100, ISSN: 2470-0045
The mechanisms of atrial fibrillation (AF) are poorly understood, resulting in disappointing success rates of ablative treatment. Different mechanisms defined largely by different atrial activation patterns have been proposed and, arguably, this dispute has slowed the progress of AF research. Recent clinical evidence suggests a unifying mechanism of local drivers based on sustained re-entrant circuits in the complex atrial architecture. Here, we present a percolation inspired computational model showing spontaneous emergence of AF that strongly supports, and gives a theoretical explanation for, the clinically observed diversity of activation. We show that the difference in surface activation patterns is a direct consequence of the thickness of the discrete network of heart muscle cells through which electrical signals percolate to reach the imaged surface. The model naturally follows the clinical spectrum of AF spanning sinus rhythm, paroxysmal and persistent AF as the decoupling of myocardial cells results in the lattice approaching the percolation threshold. This allows the model to make the novel prediction that for paroxysmal AF, re-entrant circuits emerge near the endocardium, but in persistent AF they emerge deeper in the bulk of the atrial wall. If experimentally verified, this may go towards explaining the lowering ablation success rate as AF becomes more persistent.
Yao Q, Evans TS, Christensen K, 2019, How the network properties of shareholders vary with investor type and country, PLoS One, Vol: 14, Pages: 1-19, ISSN: 1932-6203
We construct two examples of shareholder networks in which shareholders are connected if they have shares in the same company. We do this for the shareholders in Turkish companies and we compare this against the network formed from the shareholdings in Dutch companies. We analyse the properties of these two networks in terms of the different types of shareholder. We create a suitable randomised version of these networks to enable us to find significant features in our networks. For that we find the roles played by different types of shareholder in these networks, and also show how these roles differ in the two countries we study.
Franks N, Worley A, Falkenberg McGillivray M, et al., 2019, Digging the optimum pit: antlions, spirals and spontaneous stratification, Proceedings of the Royal Society B: Biological Sciences, Vol: 286, ISSN: 1471-2954
Most animal traps are constructed from self-secreted silk, so antlions are rare among trap builders because they use only materials found in the environment. We show how antlions exploit the properties of the substrate to produce very effective structures in the minimum amount of time. Our modelling demonstrates how antlions (1) exploit self-stratification in granular media differentially to expose deleterious large grains at the bottom of the construction trench where they can be ejected preferentially and (2) minimize completion time by spiral rather than central digging. Both phenomena are confirmed by our experiments. Spiral digging saves time because it enables the antlion to eject material initially from the periphery of the pit where it is less likely to topple back into the centre. As a result, antlions can produce their pits — lined almost exclusively with small slippery grains to maximize powerful avalanches and hence prey capture — much more quickly than if they simply dig at the pit’s centre. Our demonstration, for the first time, of an animal utilizing self-stratification in granular media exemplifies the sophistication of extended phenotypes even if they are only formed from material found in the animal’s environment.
Fernandez-Anez N, Christensen K, Frette V, et al., 2019, Simulation of fingering behavior in smoldering combustion using a cellular automaton, Physical Review E: Statistical, Nonlinear, and Soft Matter Physics, Vol: 99, ISSN: 1539-3755
Smoldering is the slow, low-temperature, flameless burning of porous fuels and the most persistent type of combustion phenomena. It is a complex physical process that is not yet completely understood, but it is known that it is driven by heat transfer, mass transfer, and fuel chemistry. A specific case of high interest and complexity is fingering behavior. Fingering is an instability that occurs when a thin fuel layer burns against an oxygen current. These instabilities appear when conduction rather than convection is the dominant mode of heat transfer to the fuel ahead and the availability of oxygen is limited during the combustion of a thin fuel, such as paper. The pattern of the fingers can be characterized through the distance between them and their width, and can be classified into three different regimes: isolated fingers, tip-splitting fingers, or no fingers forming and a smooth continuous front. In this paper, a multilayer cellular automaton based on three governing principles (heat, oxygen, and fuel) is shown to reproduce all the regimes and the details of finger structures observed in previous experiments. It is shown how when oxygen is not limited, a smooth smoldering front is formed. If the oxygen speed decreases beyond a critical value, fingers appear first as tip-splitting fingers and later as isolated fingers, increasing the distance between them and decreasing their thickness. The oxygen consumed during oxidation influences these critical values with a positive correlation. This cellular automaton provides an alternative approach to simulate smoldering combustion in large systems over long times. That the model is able to reproduce the complex pattern formation seen in a fingering experiment validates the model. In the future, we could apply the model in various other geometries to make predictions on the outcome of smoldering combustion processes.
Garcia Millan R, Pruessner G, Pickering L, et al., 2018, Correlations and hyperuniformity in the avalanche size of the Oslo Model, Europhysics Letters: a letters journal exploring the frontiers of physics, Vol: 122, ISSN: 1286-4854
Certain random processes display anticorrelations resulting in local Poisson-like disorder and global order, where correlations suppress fluctuations. Such processes are called hyperuniform. Using a map to an interface picture we show via analytic calculations that a sequence of avalanche sizes of the Oslo model is hyperuniform in the temporal domain with the minimal exponent $\lambda=0$ . We identify the conserved quantity in the interface picture that gives rise to the hyperuniformity in the avalanche size. We further discuss the fluctuations of the avalanche size in two variants of the Oslo model. We support our findings with numerical results.
McGillivray MF, Cheng W, Peters NS, et al., 2018, Machine learning methods for locating re-entrant drivers from electrograms in a model of atrial fibrillation, ROYAL SOCIETY OPEN SCIENCE, Vol: 5, ISSN: 2054-5703
Mapping resolution has recently been identified as a key limitation in successfully locating the drivers of atrial fibrillation (AF). Using a simple cellular automata model of AF, we demonstrate a method by which re-entrant drivers can be located quickly and accurately using a collection of indirect electrogram measurements. The method proposed employs simple, out-of-the-box machine learning algorithms to correlate characteristic electrogram gradients with the displacement of an electrogram recording from a re-entrant driver. Such a method is less sensitive to local fluctuations in electrical activity. As a result, the method successfully locates 95.4% of drivers in tissues containing a single driver, and 95.1% (92.6%) for the first (second) driver in tissues containing two drivers of AF. Additionally, we demonstrate how the technique can be applied to tissues with an arbitrary number of drivers. In its current form, the techniques presented are not refined enough for a clinical setting. However, the methods proposed offer a promising path for future investigations aimed at improving targeted ablation for AF.
Fernandez-Anez N, Christensen K, Rein G, 2017, Two-dimensional model of smouldering combustion using multi-layer cellular automaton: The role of ignition location and direction of airflow, Fire Safety Journal, Vol: 91, Pages: 243-251, ISSN: 0379-7112
Smouldering combustion is one of the most common and persistent fire hazards of reactive porous media, such as biomass. In this work, a two-dimensional multi-layer cellular automaton has been developed to study the process of smouldering and the roles of both the ignition location and the direction of airflow for generic biomass. Three different configurations are studied: line front, with forward and opposed airflow respectively, and radial front. The first two configurations simulate ignition of one edge of the sample, while the radial front simulates ignition of a spot at the centre of the sample. The resulting spread patterns of line vs. radial front are significantly different. Furthermore, when smouldering occurs with similar characteristics, where both line front and radial front are self-sustained, the smouldering radial front has a higher growth rate than the line front. However, in the studied cases where enough oxygen is always available for oxidation, the direction of the airflow does not influence the spread of the smouldering front, and the line front with forward and opposed airflow present similar behaviour. Finally, two non-zero minimum values have been detected for self-sustained spread according to the moisture of the fuel (probability of drying) and its tendency for thermal degradation (probability of pyrolysis). This model provides a powerful but simple way of reproducing the complex dynamics of smouldering processes which can be used to investigate different scenarios.
Manani K, Christensen K, Peters NICHOLAS, 2016, Myocardial architecture and patient variability in clinical patterns of atrial fibrillation, Physical Review E - Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics, Vol: 94, ISSN: 1063-651X
Atrial fibrillation (AF) increases the risk of stroke by a factor of 4–5 and is the most common abnormal heart rhythm. The progression of AF with age, from short self-terminating episodes to persistence, varies between individuals and is poorly understood. An inability to understand and predict variation in AF progression has resulted in less patient-specific therapy. Likewise, it has been a challenge to relate the microstructural features of heart muscle tissue (myocardial architecture) with the emergent temporal clinical patterns of AF. We use a simple model of activation wave-front propagation on an anisotropic structure, mimicking heart muscle tissue, to show how variation in AF behavior arises naturally from microstructural differences between individuals. We show that the stochastic nature of progressive transversal uncoupling of muscle strands (e.g., due to fibrosis or gap junctional remodeling), as occurs with age, results in variability in AF episode onset time, frequency, duration, burden, and progression between individuals. This is consistent with clinical observations. The uncoupling of muscle strands can cause critical architectural patterns in the myocardium. These critical patterns anchor microreentrant wave fronts and thereby trigger AF. It is the number of local critical patterns of uncoupling as opposed to global uncoupling that determines AF progression. This insight may eventually lead to patient-specific therapy when it becomes possible to observe the cellular structure of a patient's heart.
Dhar D, Pruessner G, Expert P, et al., 2016, Directed Abelian sandpile with multiple downward neighbors, Physical Review E, Vol: 042107, ISSN: 1539-3755
We study the directed Abelian sandpile model on a square lattice, with K downward neighborsper site, K > 2. The K = 3 case is solved exactly, which extends the earlier known solution forthe K = 2 case. For K > 2, the avalanche clusters can have holes and side-branches and are thusqualitatively different from the K = 2 case where avalanche clusters are compact. However, we findthat the critical exponents for K > 2 are identical with those for the K = 2 case, and the largescale structure of the avalanches for K > 2 tends to the K = 2 case.
Zachariou N, Expert P, Takayasu M, et al., 2015, Generalised Sandpile Dynamics on Artificial and Real-World Directed Networks, PLOS One, Vol: 10, ISSN: 1932-6203
The main finding of this paper is a novel avalanche-size exponent τ 1.87 when the generalisedsandpile dynamics evolves on the real-world Japanese inter-firm network. The topologyof this network is non-layered and directed, displaying the typical bow tie structurefound in real-world directed networks, with cycles and triangles. We show that one canmove from a strictly layered regular lattice to a more fluid structure of the inter-firm networkin a few simple steps. Relaxing the regular lattice structure by introducing an interlayer distributionfor the interactions, forces the scaling exponent of the avalanche-size probabilitydensity function τ out of the two-dimensional directed sandpile universality class τ = 4/3,into the mean field universality class τ = 3/2. Numerical investigation shows that these twoclasses are the only that exist on the directed sandpile, regardless of the underlying topology,as long as it is strictly layered. Randomly adding a small proportion of links connectingnon adjacent layers in an otherwise layered network takes the system out of the mean fieldregime to produce non-trivial avalanche-size probability density function. Although these donot display proper scaling, they closely reproduce the behaviour observed on the Japaneseinter-firm network.
Christensen K, Manani KA, Peters NS, 2015, Simple model for identifying critical regions in atrial fibrillation, Physical Review Letters, Vol: 114, ISSN: 0031-9007
Atrial fibrillation (AF) is the most common abnormal heart rhythm and the single biggest cause of stroke. Ablation, destroying regions of the atria, is applied largely empirically and can be curative but with a disappointing clinical success rate. We design a simple model of activation wave front propagation on an anisotropic structure mimicking the branching network of heart muscle cells. This integration of phenomenological dynamics and pertinent structure shows how AF emerges spontaneously when the transverse cell-to-cell coupling decreases, as occurs with age, beyond a threshold value. We identify critical regions responsible for the initiation and maintenance of AF, the ablation of which terminates AF. The simplicity of the model allows us to calculate analytically the risk of arrhythmia and express the threshold value of transversal cell-to-cell coupling as a function of the model parameters. This threshold value decreases with increasing refractory period by reducing the number of critical regions which can initiate and sustain microreentrant circuits. These biologically testable predictions might inform ablation therapies and arrhythmic risk assessment.
Christensen K, Papavassiliou D, de Figueiredo A, et al., 2015, Universality in ant behaviour, JOURNAL OF THE ROYAL SOCIETY INTERFACE, Vol: 12, ISSN: 1742-5689
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- Citations: 8
Christensen K, Kleppe G, Vold M, et al., 2014, Quantitative projections of a quality measure: Performance of a complex task, PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, Vol: 415, Pages: 503-513, ISSN: 0378-4371
Sarker MOF, Dahl TS, Arcaute E, et al., 2014, Local interactions over global broadcasts for improved task allocation in self-organized multi-robot systems, ROBOTICS AND AUTONOMOUS SYSTEMS, Vol: 62, Pages: 1453-1462, ISSN: 0921-8890
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- Citations: 17
Richardson TO, Christensen K, Franks NR, et al., 2011, Ants in a labyrinth: A statistical mechanics approach to the division of labour, PLOS One, Vol: 6, ISSN: 1932-6203
Division of labour (DoL) is a fundamental organisational principle in human societies, within virtual and robotic swarms and at all levels of biological organisation. DoL reaches a pinnacle in the insect societies where the most widely used model is based on variation in response thresholds among individuals, and the assumption that individuals and stimuli are well-mixed. Here, we present a spatially explicit model of DoL. Our model is inspired by Pierre de Gennes' 'Ant in a Labyrinth' which laid the foundations of an entire new field in statistical mechanics. We demonstrate the emergence, even in a simplified one-dimensional model, of a spatial patterning of individuals and a right-skewed activity distribution, both of which are characteristics of division of labour in animal societies. We then show using a two-dimensional model that the work done by an individual within an activity bout is a sigmoidal function of its response threshold. Furthermore, there is an inverse relationship between the overall stimulus level and the skewness of the activity distribution. Therefore, the difference in the amount of work done by two individuals with different thresholds increases as the overall stimulus level decreases. Indeed, spatial fluctuations of task stimuli are minimised at these low stimulus levels. Hence, the more unequally labour is divided amongst individuals, the greater the ability of the colony to maintain homeostasis. Finally, we show that the non-random spatial distribution of individuals within biological and social systems could be caused by indirect (stigmergic) interactions, rather than direct agent-to-agent interactions. Our model links the principle of DoL with principles in the statistical mechanics and provides testable hypotheses for future experiments.
Expert P, Lambiotte R, Chialvo DR, et al., 2011, Self-similar correlation function in brain resting-state functional magnetic resonance imaging, JOURNAL OF THE ROYAL SOCIETY INTERFACE, Vol: 8, Pages: 472-479, ISSN: 1742-5689
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- Citations: 106
Richardson TO, Christensen K, Franks NR, et al., 2011, Group dynamics and record signals in the ant <i>Temnothorax albipennis</i>, JOURNAL OF THE ROYAL SOCIETY INTERFACE, Vol: 8, Pages: 518-528, ISSN: 1742-5689
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- Citations: 3
Richardson TO, Robinson EJH, Christensen K, et al., 2011, Comment on P. Nouvellet, JP Bacon, D. Waxman, "Testing the level of ant activity associated with quorum sensing: An empirical approach leading to the establishment and test of a null-model", JOURNAL OF THEORETICAL BIOLOGY, Vol: 269, Pages: 356-358, ISSN: 0022-5193
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- Citations: 3
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