Locomotion of Parkinsonian Patient: Are There Relations Between the Long Range Autocorrelations and the Neurological Impairments, Walking Abilities and the Practice of Physical Exercise?

BACKGROUND

One of the most common features of human movement is its variability across multiple repetition of the same rhythmic task (1). In humans, many periodic signals, such as gait, heartbeat, respiratory and neuronal activities are characterized by their temporal complexity, fluctuating in a complex manner over time. Although fluctuations between cycles could appear to vary randomly, without apparent correlations between cycles, healthy systems possess the memory of preceding values of the series displaying a complex temporal structure.

In order to assess variability in physiological time series, several mathematical methods can be used. On one hand, classical mathematical methods, usually applied on shorter time series (tens of data points), quantify the fluctuation magnitude in a set of values independently of their order in the distribution, by computing the standard deviation (SD) and the coefficient of variation (CV). On the other hand, more complex mathematical methods, applied on longer time series (≥512 cycles), can be used to assess the fluctuation dynamics over time (3). These latter methods have demonstrated that variability of numerous physiological signals (cardiac and respiratory rhythm or locomotor activities e.g.) exhibit long-range autocorrelations, whereby the statistical inter-dependency between cycles spans of a very large number of cycles (14).

This temporal organization of variability is thus an intrinsic property within numerous biological systems. Moreover, it could provide insight into the neurophysiological organization and into the regulation of these systems (32). Recent studies claimed that these fluctuations, included in an optimal range, would represent the underlying physiologic capability to make flexible adaptations to everyday stresses placed on the human body (32). Therefore, the presence of such temporal dynamics is thought to be a critical marker of health and their breakdown as an index of pathological condition (18, 25, 32). In human heart rate for instance, deviations from an optimum of variability in either the direction of randomness (atrial fibrillation e.g.) or the over-regularity (congestive heart failure e.g.) indicate the loss of the adaptive capabilities of the system (9, 32).

Alongside, some central nervous system diseases influence the variability, especially, of gait. Indeed, neurodegenerative disorders such as Parkinson and Huntington diseases are characterized, among others, by a modification of walking variability (observed by a breakdown of long-range autocorrelations) and a high risk of falling. Although the origin of long-range autocorrelation remains unknown, their breakdown in such diseases suggests a central control mechanism (8, 11, 13, 16, 17, 36).