Publications (67) View all
-
Article: Minimum Information about a Cardiac Electrophysiology Experiment (MICEE): standardised reporting for model reproducibility, interoperability, and data sharing.
[show abstract] [hide abstract]
ABSTRACT: Cardiac experimental electrophysiology is in need of a well-defined Minimum Information Standard for recording, annotating, and reporting experimental data. As a step towards establishing this, we present a draft standard, called Minimum Information about a Cardiac Electrophysiology Experiment (MICEE). The ultimate goal is to develop a useful tool for cardiac electrophysiologists which facilitates and improves dissemination of the minimum information necessary for reproduction of cardiac electrophysiology research, allowing for easier comparison and utilisation of findings by others. It is hoped that this will enhance the integration of individual results into experimental, computational, and conceptual models. In its present form, this draft is intended for assessment and development by the research community. We invite the reader to join this effort, and, if deemed productive, implement the Minimum Information about a Cardiac Electrophysiology Experiment standard in their own work.Progress in Biophysics and Molecular Biology 07/2011; 107(1):4-10. · 3.20 Impact Factor -
Article: Detecting Space-Time Alternating Biological Signals Close to the Bifurcation Point
[show abstract] [hide abstract]
ABSTRACT: Time-alternating biological signals, i.e., alternans, arise in variety of physiological states marked by dynamic instabilities, e.g., period doubling. Normally, a sequence of large-small-large transients, they can exhibit variable patterns over time and space, including spatial discordance. Capture of the early formation of such alternating regions is challenging because of the spatiotemporal similarities between noise and the small-amplitude alternating signals close to the bifurcation point. We present a new approach for automatic detection of alternating signals in large noisy spatiotemporal datasets by exploiting quantitative measures of alternans evolution, e.g., temporal persistence, and by preserving phase information. The technique specifically targets low amplitude, relatively short alternating sequences and is validated by combinatorics-derived probabilities and empirical datasets with white noise. Using high-resolution optical mapping in live cardiomyocyte networks, exhibiting calcium alternans, we reveal for the first time early fine-scale alternans, close to the noise level, which are linked to the later formation of larger regions and evolution of spatially discordant alternans. This robust method aims at quantification and better understanding of the onset of cardiac arrhythmias and can be applied to general analysis of space-time alternating signals, including the vicinity of the bifurcation point.IEEE Transactions on Biomedical Engineering 03/2010; · 2.28 Impact Factor -
Article: Modeling and simulation of cardiac tissue using hybrid i/o automata
[show abstract] [hide abstract]
ABSTRACT: a b s t r a c t We propose a new biological framework based on the Lynch et al. theory of Hybrid I/O Automata (HIOAs) for modeling and simulating excitable tissue. Within this framework, we view an excitable tissue as a composition of two main kinds of component: a diffusion medium and a collection of cells, both modeled as an HIOA. This approach yields a notion of decomposition that allows us to describe a tissue as the parallel composition of several interacting tissues, a property that could be exploited to parallelize, and hence improve, the efficiency of the simulation process. We also demonstrate the feasibility of our HIOA-based framework to capture and mimic different kinds of wave-propagation behavior in 2D isotropic cardiac tissue, including normal wave propagation along the tissue; the creation of spiral waves; the break-up of spiral waves into more complex patterns such as fibrillation; and the recovery of the tissue to the rest via electrical defibrillation.Theoretical Computer Science. 01/2009; 410:3149-3165. -
Conference Proceeding: Symbolic Analysis of the Neuron Action Potential
[show abstract] [hide abstract]
ABSTRACT: We present a novel approach to investigating key behavioral properties of complex biological systems by first using automated techniques to learn a simplified Linear Hybrid Automaton model of the system under investigation, and then carrying out automatic reachability analysis on the resulting model. The specific biological system we consider is the neuronal Action Potential and the specific question of interest is bifurcation: the graded response of the neuron to stimulation of varying amplitude and duration. Reachability analysis in this case is performed using the d/dt analysis tool for hybrid systems. The results we so obtain reveal the precise conditions under which bifurcation manifests, when taking into consideration an infinite class of input stimuli of arbitrary shape, amplitude, and duration within given respective intervals. To the best of our knowledge, this represents the first time that formal (reachability) analysis has been applied to a computational model of excitable cells. The obvious advantage of symbolic reachability analysis over simulation - perhaps the only available analysis method when complex systems of coupled ODEs are used to model excitable-cell behavior, as has traditionally been the case - is that through the so-called reachable set computation, the system's reaction to an infinite set of possible inputs can be observed. Our results further demonstrate that Linear Hybrid Automata, as a formal language, is both expressive enough to capture interesting excitable-cell behavior, and abstract enough to render formal analysis possible.Bioinformatics and Biomedical Engineering, 2008. ICBBE 2008. The 2nd International Conference on; 06/2008 -
Article: Modelling excitable cells using cycle-linear hybrid automata.
[show abstract] [hide abstract]
ABSTRACT: Cycle-linear hybrid automata (CLHAs), a new model of excitable cells that efficiently and accurately captures action-potential morphology and other typical excitable-cell characteristics such as refractoriness and restitution, is introduced. Hybrid automata combine discrete transition graphs with continuous dynamics and emerge in a natural way during the (piecewise) approximation process of any nonlinear system. CLHAs are a new form of hybrid automata that exhibit linear behaviour on a per-cycle basis but whose overall behaviour is appropriately nonlinear. To motivate the need for this modelling formalism, first it is shown how to recast two recently proposed models of excitable cells as hybrid automata: the piecewise-linear model of Biktashev and the nonlinear model of Fenton-Karma. Both of these models were designed to efficiently approximate excitable-cell behaviour. We then show that the CLHA closely mimics the behaviour of several classical highly nonlinear models of excitable cells, thereby retaining the simplicity of Biktashev's model without sacrificing the expressiveness of Fenton-Karma. CLHAs are not restricted to excitable cells; they can be used to capture the behaviour of a wide class of dynamic systems that exhibit some level of periodicity plus adaptation.IET Systems Biology 02/2008; 2(1):24-32. · 1.35 Impact Factor
