Frequency-Specific Fractal Analysis of Postural Control Accounts for Control Strategies

Diverse indicators of postural control in Humans have been explored for decades, mostly based on the trajectory of the center-of-pressure. Classical approaches focus on variability, based on the notion that if a posture is too variable, the subject is not stable. Going deeper, an improved understanding of underlying physiology has been gained from studying variability in different frequency ranges, pointing to specific short-loops (proprioception), and long-loops (visuo-vestibular) in neural control. More recently, fractal analyses have proliferated and become useful additional metrics of postural control. They allowed identifying two scaling phenomena, respectively in short and long timescales. Here, we show that one of the most widely used methods for fractal analysis, Detrended Fluctuation Analysis, could be enhanced to account for scalings on specific frequency ranges. By computing and filtering a bank of synthetic fractal signals, we established how scaling analysis can be focused on specific frequency components. We called the obtained method Frequency-specific Fractal Analysis (FsFA) and used it to associate the two scaling phenomena of postural control to proprioceptive-based control loop and visuo-vestibular based control loop. After that, convincing arguments of method validity came from an application on the study of unaltered vs. altered postural control in athletes. Overall, the analysis suggests that at least two timescales contribute to postural control: a velocity-based control in short timescales relying on proprioceptive sensors, and a position-based control in longer timescales with visuo-vestibular sensors, which is a brand-new vision of postural control. Frequency-specific scaling exponents are promising markers of control strategies in Humans.

Repair of Physiologic Time Series: Replacement of Anomalous Data Points to Preserve Fractal Exponents

Extraction of fractal exponents via the slope of the power spectrum is common in the analysis of many physiological time series. The fractal structure thus characterized is a manifestation of long-term correlations, for which the temporal order of the sample values is crucial. However, missing data points due to artifacts and dropouts are common in such data sets, which can seriously disrupt the computation of fractal parameters. We evaluated a number of methods for replacing missing data in time series to enable reliable extraction of the fractal exponent and make recommendations as to the preferred replacement method depending on the proportion of missing values and any a priori estimate of the fractal exponent.

Hypothesizing the body's genius to trigger and self-organize its healing: 25 years using a standardized neurophysics therapy

We aim for this contribution to operate bi-directionally, both as a "bedside to bench" reverse-translational fractal physiological hypothesis and as a methodological innovation to inform clinical practice. In 25 years using gym equipment therapeutically in non-research settings, the standardized therapy is consistently observed to trigger universal responses of micro to macro waves of system transition dynamics in the human nervous system. These are associated with observably desirable impacts on disorders, injuries, diseases, and athletic performance. Requisite conditions are therapeutic coaching, erect posture, extremely slow movements in mild resistance exercises, and executive control over arousal and attention. To motivate research into the physiological improvements and in validation studies, we integrate from across disciplines to hypothesize explanations for the relationships among the methods, the system dynamics, and evident results. Key hypotheses include: (1) Correctly-directed system efforts may reverse a system's heretofore misdirected efforts, restoring healthier neurophysiology. (2) The enhanced information processing accompanying good posture is an essential initial condition. (3) Behaviors accompanying exercises performed with few degrees of freedom amplify information processing, triggering destabilization and transition dynamics. (4) Executive control over arousal and attention is essential to release system constraints, amplifying and complexifying information. (5) The dynamics create necessary and in many cases evidently sufficient conditions for the body to resolve or improve its own conditions within often short time periods. Literature indicates how the human system possesses material self-awareness. A broad explanation for the nature and effects of the therapy appears rooted in the cascading recursions of the systems' dynamics, which appear to trigger health-fostering self-reorganizing processes when this therapy provides catalytic initial conditions.

The role of the circadian system in fractal neurophysiological control

Many neurophysiological variables such as heart rate, motor activity, and neural activity are known to exhibit intrinsic fractal fluctuations - similar temporal fluctuation patterns at different time scales. These fractal patterns contain information about health, as many pathological conditions are accompanied by their alteration or absence. In physical systems, such fluctuations are characteristic of critical states on the border between randomness and order, frequently arising from nonlinear feedback interactions between mechanisms operating on multiple scales. Thus, the existence of fractal fluctuations in physiology challenges traditional conceptions of health and disease, suggesting that high levels of integrity and adaptability are marked by complex variability, not constancy, and are properties of a neurophysiological network, not individual components. Despite the subject's theoretical and clinical interest, the neurophysiological mechanisms underlying fractal regulation remain largely unknown. The recent discovery that the circadian pacemaker (suprachiasmatic nucleus) plays a crucial role in generating fractal patterns in motor activity and heart rate sheds an entirely new light on both fractal control networks and the function of this master circadian clock, and builds a bridge between the fields of circadian biology and fractal physiology. In this review, we sketch the emerging picture of the developing interdisciplinary field of fractal neurophysiology by examining the circadian system's role in fractal regulation.

A tutorial introduction to adaptive fractal analysis

The authors present a tutorial description of adaptive fractal analysis (AFA). AFA utilizes an adaptive detrending algorithm to extract globally smooth trend signals from the data and then analyzes the scaling of the residuals to the fit as a function of the time scale at which the fit is computed. The authors present applications to synthetic mathematical signals to verify the accuracy of AFA and demonstrate the basic steps of the analysis. The authors then present results from applying AFA to time series from a cognitive psychology experiment on repeated estimation of durations of time to illustrate some of the complexities of real-world data. AFA shows promise in dealing with many types of signals, but like any fractal analysis method there are special challenges and considerations to take into account, such as determining the presence of linear scaling regions.