We present the first systematic evidence for the origins and breakdown
of 1/f scaling in human heart rate. We confirm a previously posed conjecture that 1/f scaling in heart rate is caused by the intricate balance between antagonistic activity of sympathetic (SNS) and parasympathetic (PNS) nervous systems. We demonstrate that modifying the relative importance of either of the two branches leads to a substantial decrease of 1/f scaling. In particular, the relative PNS suppression both by congestive heart failure (CHF) and by the parasympathetic blocker atropine results in a substantial increase in the Hurst exponent H and a shift of the multifractal spectrum f(α) from 1/f towards random walk scaling 1/f2. Surprisingly, we observe a similar breakdown in the case of relative and neurogenic SNS suppression by primary autonomic failure (PAF). Further, we observe an intriguing interaction between multifractality of heart rate and absolute variability. While it is generally believed that lower absolute variability results in monofractal behaviour, as has been demonstrated both for CHF and the parasympathetic blockade, in PAF
patients we observe conservation of multifractal properties at
substantially reduced absolute variability to levels closer to
CHF. This novel and intriguing result leads us to the conjecture that
the multifractality of the heart rate can be traced back to the
intrinsic dynamics of the parasympathetic nervous system.
The noise of the current of a driven classical one-dimensional
charge density wave system is studied in the weak pinning regime
using the overdamped equation of motion and the Wavelet Transform
Modulus Maxima method. Above the zero temperature depinning
transition at low temperatures, the power spectrum of the current
noise S(f) scales with frequency f as S(f) ~ f-γ, where γ≈1, which suggests the existence of flicker. Experimental measurements for quasi-one-dimensional charge density wave materials are in agreement with our findings, providing the first evidence of 1/f behaviour obtained from first principles.
Using the method of local Continuous Detrended Fluctuation Analysis CDFA) we analyze the correlations of ventricular interbeat intervals of patients with Atrial Fibrillation (AF). CDFA yields a local Hoelder exponent h for a neighborhood around each point in the time series by determining the scaling of fluctuations with window size after detrending. We compare the histograms of Hoelder exponents for original data with those of randomly shuffled data and find some correlations not only in long-range windows but also at short time scales where interbeat intervals during AF have been believed to be random in nature. Furthermore, we find unique temporal correlation structures to occur only in the heart rate of patients who were in the survivor group when a follow up was conducted at least one year after data acquisition. We conclude that ventricular interbeat intervals during AF contain richer information than previously considered and the study of the local correlations may be useful in predicting mortality of the patients.