A nonlinear time-series analysis method is used to investigate the dynamic behavior of the estrous
cycle in female mice. Taking the daily changes in the cell types observed in the vaginal smears of
mice as a single-variable time series, we construct a multi-dimensional state space by using an
embedding scheme. The Lyapunov exponent and the correlation dimension of the trajectories in
the re-constructed state space are analyzed in order to understand the underlying dynamics of the
reproductive cycle of the mice. The time-series analysis results are found to be consistent with the
physiological description of the reproductive endocrine system. Moreover, the results suggest that
the variations in the estrous cycle of mice have a low-dimensional chaotic motion.
關聯:
Journal of the Korean Physical Society 55(4)：p. 1357-1362
