In vitro arrhythmia generation by mild hypothermia: a pitchfork bifurcation type process.

The neurological damage after cardiac arrest presents a huge challenge for hospital discharge. Therapeutic hypothermia (34 °C - 32 °C) has shown its benefits in reducing cerebral oxygen demand and improving neurological outcomes after cardiac arrest. However, it can have many adverse effects, among them cardiac arrhythmia generation which represents an important part (up to 34%, according different clinical studies). A monolayer cardiac culture is prepared with cardiomyocytes from a newborn rat, directly on a multi-electrode array, which allows the acquisition of the extracellular potential of the culture. The temperature range is 37 °C - 30 °C-37 °C, representing the cooling and rewarming process of therapeutic hypothermia. Experiments showed that at 35 °C, the acquired signals are characterized by period-doubling phenomenon, compared with signals at other temperatures. Spiral waves, commonly considered to be a sign of cardiac arrhythmia, are observed in the reconstructed activation map. With an approach from nonlinear dynamics, phase space reconstruction, it is shown that at 35 °C, the trajectories of these signals formed a spatial bifurcation, even trifurcation. Another transit point is found between 30 °C-33 °C, which agreed with other clinical studies that induced hypothermia after cardiac arrest should not fall below 32 °C. The process of therapeutic hypothermia after cardiac arrest can be represented by a pitchfork bifurcation type process, which could explain the different ratios of arrhythmia among the adverse effects after this therapy. This nonlinear dynamic suggests that a variable speed of cooling/rewarming, especially when passing 35 °C, would help to decrease the ratio of post-hypothermia arrhythmia and then improve the hospital output.

Arrhythmic dynamics from singularity analysis of electrocardiographic maps.

From a point view of nonlinear dynamics, the electrical activity of the heart is a complex dynamical system, whose dynamics reflects the actual state of health of the heart. Nonlinear signal-processing methods are needed in order to accurately characterize these signals and improve understanding of cardiac arrhythmias. Recent developments on reconstructible signals and multiscale information content show that an analysis in terms of singularity exponents provides compact and meaningful descriptors of the structure and dynamics of the system. Such approach gives a compact representation atrial arrhythmic dynamics, which can sharply highlight regime transitions and arrhythmogenic areas.

Application of the microcanonical multifractal formalism to monofractal systems.

The design of appropriate multifractal analysis algorithms, able to correctly characterize the scaling properties of multifractal systems from experimental, discretized data, is a major challenge in the study of such scale invariant systems. In the recent years, a growing interest for the application of the microcanonical formalism has taken place, as it allows a precise localization of the fractal components as well as a statistical characterization of the system. In this paper, we deal with the specific problems arising when systems that are strictly monofractal are analyzed using some standard microcanonical multifractal methods. We discuss the adaptations of these methods needed to give an appropriate treatment of monofractal systems.