Measuring regularity by means of a corrected conditional entropy in sympathetic outflow

Abstract

A new method for measuring the regularity of a process over short data sequences is reported. This method is based on the definition of a new function (the corrected conditional entropy) and on the extraction of its minimum. This value is taken as an index in the information domain quantifying the regularity of the process. The corrected conditional entropy is designed to decrease in relation to the regularity of the process (like other estimates of the entropy rate), but it is able to increase when no robust statistic can be performed as a result of a limited amount of available samples. As a consequence of the minimisation procedure, the proposed index is obtained without an a-priori definition of the pattern length (i.e. of the embedding dimension of the reconstructed phase space). The method is validated on simulations and applied to beat-to-beat sequences of the sympathetic discharge obtained from decerebrate artificially ventilated cats. At control, regular, both quasiperiodic and periodic (locked to ventilation) dynamics are observed. During the sympathetic activation induced by inferior vena cava occlusion, the presence of phase-locked patterns and the increase in regularity of the sympathetic discharge evidence an augmented coupling between the sympathetic discharge and ventilation. The reduction of complexity of the neural control obtained by spinalization decreases the regularity in the sympathetic outflow, thus pointing to a weaker coupling between the sympathetic discharge and ventilation.

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