The last decade has seen a surge in the study of nonlinear dynamical behavior in physiologic systems. In this paper, some of the computational techniques most commonly used to investigate the nonlinear dynamics of these systems are described. Applications to eye movement analysis are included, including the validation of a mathematical model of optokinetic nystagmus (OKN) eye movements. OKN appears to have some nonlinear and deterministic component, along with significant randomness. Fast phase starting and ending points are somewhat predictable (deterministic), while so-called 'exceptional events' analysis shows that they also have a large random component. Surrogate data methods suggest that the population of slow and fast phases in OKN is more important than any specific relationship between adjacent slow and fast phases. Analysis of a statistical model for fast phase intervals indicates that the model data are slightly more random than the actual OKN.
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