CNCS Center for Nonlinear and Complex Systems
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Publications [#282323] of Wanda K. Neu

Papers Published

  1. Kalb, SS; Tolkacheva, EG; Schaeffer, DG; Gauthier, DJ; Krassowska, W, Restitution in mapping models with an arbitrary amount of memory., Chaos (Woodbury, N.Y.), vol. 15 no. 2 (June, 2005), pp. 23701, ISSN 1054-1500 [16035891], [doi]
    (last updated on 2023/06/01)

    Abstract:
    Restitution, the characteristic shortening of action potential duration (APD) with increased heart rate, has been studied extensively because of its purported link to the onset of fibrillation. Restitution is often represented in the form of mapping models where APD is a function of previous diastolic intervals (DIs) and/or APDs, A(n+1)=F(D(n),A(n),D(n-1),A(n-1),...), where A(n+1) is the APD following a DI given by D(n). The number of variables previous to D(n) determines the degree of memory in the mapping model. Recent experiments have shown that mapping models should contain at least three variables (D(n),A(n),D(n-1)) to reproduce a restitution portrait (RP) that is qualitatively similar to that seen experimentally, where the RP shows three different types of restitution curves (RCs) [dynamic, S1-S2, and constant-basic cycle length (BCL)] simultaneously. However, an interpretation of the different RCs has only been presented in detail for mapping models of one and two variables. Here we present an analysis of the different RCs in the RP for mapping models with an arbitrary amount of memory. We determine the number of variables necessary to represent the different RCs in the RP. We also present a graphical visualization of these RCs. Our analysis reveals that the dynamic and S1-S2 RCs reside on two-dimensional surfaces, and therefore provide limited information for mapping models with more than two variables. However, constant-BCL restitution is a feature of the RP that depends on higher dimensions and can possibly be used to determine a lower bound on the dimensionality of cardiac dynamics.

    Keywords:
    cardiology;chaos;nonlinear dynamical systems;