Fig 2 - uploaded by Michal Teplan
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Drift of main circadian periods from 24 h period represented by zero value on Y-axis. X-items represent week intervals under shift, light/dark and light/light regime. Mean data from all rats with standard deviations in a form of error bars are presented.
Contexts in source publication
Context 1
... during LL conditions circadian contribution is highly suppressed, during Shift conditions 24 h peak is elongated to longer periods. In Fig.2 the shift of circadian peak of 24 h is evaluated. ...
Context 2
... shift of SP and DP during LD conditions could be affected by tightly preceding of Shift conditions, while HR and LA seemed to be more flexible according to their reaction in this particular time point of the experiment. Whereas from the point of view of Fig.2 there were two vertexes in deviation of 24 h peak -in Shift week no. 2 and 12, in Fig.3 there is substantial difference between these 2 weeks. ...
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Citations
... The Lomb-Scargle periodogram (LS) [2] is a method especially designed for nonuniformly acquired samples. This method was originally proposed for the analysis of astronomic time series and also found successful application in the analysis of cardiovascular data, such as those in the analyses of the heart rate variability [7, 8], circadian rhythms [9], and gene sequence analysis. Results of LP are in many situations almost identical to the classical (Schuster) periodogram generalized to nonuniform samples [10] and thus they can be inferred from the FT of nonuniformly sampled data. ...
Identification of a signal component with the frequency exceeding the Nyquist limit is a challenging problem in signal theory as well as in some specific applications areas like astronomy and biosciences. A consequence of the well-known sampling theorem for a uniformly sampled signal is that the spectral component above the Nyquist limit is aliased into lower frequency range, making a distinction between true and aliased components impossible. The nonuniform sampling, however, offers a possibility to reduce aliased components and uncover information above the Nyquist limit. In this paper, we provide a theoretical analysis of the aliased components reduction in the nonparametric periodogram for two sampling schemes: the random sampling pattern and the sampling pattern generated by the integral pulse frequency modulation (IPFM), the latter widely accepted as the heart rate timing model. A general formula that relates the variance of timing deviations from a regular scheme with the aliased component suppression is proposed. The derived relation is illustrated by Lomb-Scargle periodograms applied on simulated data. Presented experimental data consisting of the respiration signal derived from the electrocardiogram and the heart rate signal also support possibility to detect frequencies above the Nyquist limit in the condition known as the cardiac aliasing.
... The Lomb-Scargle periodogram [2] is a method especially designed for nonuniformly acquired samples. This method was originally proposed for the analysis of astronomic time series and it also found successful application in cardiovascular data analyses, such as analysis of heart rate variability [4] and circadian rhythms [5]. Section 3 treats the aliasing effect in both of the above spectral representations. ...
Aliasing is a well known phenomenon in spectral analysis of sampled signal and it can be clearly described when the sampling interval remains constant. The situation is more complicated in nonuniform sampling that found its use in some kinds of measurements, such as those in radio-astronomy and biological sciences. In this paper we have derived the formula for power spectral density of nonuniformly randomly sampled sinusoid based on the uniform sampling approximation and Lomb-Scargle periodogram. The obtained results are analyzed with special attention to the aliasing effect. The detectability of a component beyond the Nyquist limit has been proven theoretically and also demonstrated on experimental data: the respiration signal derived from electrocardiogram and the heart rate signal in the condition referred to as cardiac aliasing.
