Estimating the active dimension of cardiac pacemaking dynamics

Abstract

Although there exist several different models for the excitability of cardiac and nerve cells, the number of ionic currents that determine this excitability is not clearly known. On the other hand, the chaotic behavior of excitable cells has recently been demonstrated. The science of complex dynamics provides tools for the reconstruction of the original dynamics from a time series of observed data. We determined the degrees of freedom for the excitability of a single cardiac pacemaker cell by chaotic analysis of a time series of action potentials (APs) recorded from the rabbit sinus node. We provide evidence that at least 12 variables are needed to determine the AP. From our findings, we conclude that a new model for the cardiac pacemaker mechanism may be needed, because previous models could deal only with fewer than 12 variables. Our approach based on our observation of a time series offers a powerful tool for constructing a model for the underlying biological mechanism.