Characterization of chaotic dynamics in the human menstrual cycle.

Gn Derry, Ps Derry
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引用次数: 16

Abstract

Background: The human menstrual cycle is known to exhibit a significant amount of unexplained variability. This variation is typically dismissed as random fluctuations in an otherwise periodic and predictable system. Given the many delayed nonlinear feedbacks in the multiple levels of the reproductive endocrine system, however, the menstrual cycle can properly be construed as the output of a nonlinear dynamical system, and such a system has the possibility of being in a chaotic trajectory. We hypothesize that this is in fact the case and that it accounts for the observed variability.

Results: Here, we test this hypothesis by performing time series analyses on data for 7749 menstrual cycles from 40 women in the 20-40 year age range, using the database maintained by the Tremin Research Program on Women's Health. Both raw menstrual cycle length data and a formal time series constructed from this data are utilized in these analyses. Employing phase space reconstruction techniques with a maximum embedding dimension of 12, we find appropriate scaling behavior in the correlation sums for these data, indicating low dimensional deterministic dynamics. A correlation dimension of Dc ≈ 5.2 is measured in the scaling regime. This result is confirmed by recalculation using the Takens estimator and by surrogate data tests. We interpret this result as an approximation to the fractal dimension of a strange attractor governing chaotic dynamics in the menstrual cycle. We also use the time series to calculate the correlation entropy (K2 ≈ 0.008/τ) and the maximal Lyapunov exponent (λ ≈ 0.005/τ) for the system, where τ is the sampling time of the series.

Conclusions: Taken collectively, these results constitute significant evidence that the menstrual cycle is the result of chaos in a nonlinear dynamical system. This view of the menstrual cycle has potential implications for clinical practice, modelling of the endocrine system, and the interpretation of the perimenopausal transition.

Abstract Image

Abstract Image

Abstract Image

人类月经周期混沌动力学的表征。
背景:已知人类月经周期表现出大量无法解释的变异性。这种变化通常被认为是周期性和可预测系统中的随机波动。然而,考虑到生殖内分泌系统在多个层次中存在许多延迟的非线性反馈,月经周期可以恰当地解释为一个非线性动力系统的输出,这个系统有可能处于混沌轨道。我们假设事实就是如此,它解释了观察到的变化。结果:在这里,我们使用Tremin女性健康研究项目维护的数据库,对40名20-40岁女性的7749个月经周期数据进行时间序列分析,验证了这一假设。在这些分析中使用了原始月经周期长度数据和从这些数据构建的正式时间序列。采用最大嵌入维数为12的相空间重构技术,我们发现这些数据的相关和具有适当的标度行为,表明了低维确定性动态。在标度区测得相关维数为Dc≈5.2。该结果通过使用Takens估计器和替代数据测试重新计算得到证实。我们把这个结果解释为一个近似的分形维数的一个奇怪的吸引控制混沌动力学在月经周期。我们还使用时间序列计算了系统的相关熵(K2≈0.008/τ)和最大Lyapunov指数(λ≈0.005/τ),其中τ为序列的采样时间。结论:总的来说,这些结果构成了重要的证据,证明月经周期是一个非线性动力系统混沌的结果。这种关于月经周期的观点对临床实践、内分泌系统的建模以及对围绝经期过渡的解释具有潜在的意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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