Thibault Warlop

Gait Complexity and Regularity Are Differently Modulated by Treadmill Walking in Parkinson's Disease and Healthy Population

Variability raises considerable interest as a promising and sensitive marker of dysfunction in physiology, in particular in neurosciences. Both internally (e.g., pathology) and/or externally (e.g., environment) generated perturbations and the neuro-mechanical responses to them contribute to the fluctuating dynamics of locomotion. Defective internal gait control in Parkinsons disease (PD), resulting in typical timing gait disorders, is characterized by the breakdown of the temporal organization of stride duration variability. Influence of external cue on gait pattern could be detrimental or advantageous depending on situations (healthy or pathological gait pattern, respectively). As well as being an interesting rehabilitative approach in PD, treadmills are usually implemented in laboratory settings to perform instrumented gait analysis including gait variability assessment. However, possibly acting as an external pacemaker, treadmill could modulate the temporal organization of gait variability of PD patients which could invalidate any gait variability assessment. This study aimed to investigate the immediate influence of treadmill walking (TW) on the temporal organization of stride duration variability in PD and healthy population. Here, we analyzed the gait pattern of 20 PD patients and 15 healthy age-matched subjects walking on overground and on a motorized-treadmill (randomized order) at a self-selected speed. The temporal organization and regularity of time series of walking were assessed on 512 consecutive strides and assessed by the application of non-linear mathematical methods (i.e., the detrended fluctuation analysis and power spectral density; and sample entropy, for the temporal organization and regularity of gait variability, respectively). A more temporally organized and regular gait pattern seems to emerge from TW in PD while no influence was observed on healthy gait pattern. Treadmill could afford the necessary framework to regulate gait rhythmicity in PD. Overall, the results support the hypothesis of a greater dependence to regulatory inputs as an explanatory factor of treadmill influence observed in PD. Also, since treadmill misrepresents the gait as more healthy than it is, the present findings underline that gait analysis using treadmill devices should be cautiously considered in PD and especially for gait variability assessment in gait lab.

Locus Coeruleus atrophy doesn’t relate to fatigue in Parkinson’s disease

Fatigue is a frequent complaint among healthy population and one of the earliest and most debilitating symptoms in Parkinson’s disease (PD). Earlier studies have examined the role of dopamine and serotonin in pathogenesis of fatigue, but the plausible role of noradrenalin (NA) remains underexplored. We investigated the relationship between fatigue in Parkinsonian patients and the extent of degeneration of Locus Coeruleus (LC), the main source of NA in the brain. We quantified LC and Substantia Nigra (SN) atrophy using neuromelanin-sensitive imaging, analyzed with a novel, fully automated algorithm. We also assessed patients’ fatigue, depression, sleep disturbance and vigilance. We found that LC degeneration correlated with the levels of depression and vigilance but not with fatigue, while fatigue correlated weakly with atrophy of SN. These results indicate that LC degeneration in Parkinson’s disease is unlikely to cause fatigue, but may be involved in mood and vigilance alterations.

Impact of series length on statistical precision and sensitivity of autocorrelation assessment in human locomotion

Long-range autocorrelations (LRA) are a robust feature of rhythmic movements, which may provide important information about neural control and potentially constitute a powerful marker of dysfunction. A clear difficulty associated with the assessment of LRA is that it requires a large number of cycles to generate reliable results. Here we investigate how series length impacts the reliability of LRA assessment. A total of 94 time series extracted from walking or cycling tasks were re-assessed with series length varying from 64 to 512 data points. LRA were assessed using an approach combining the rescaled range analysis or the detrended fluctuation analysis (Hurst exponent, H), along with the shape of the power spectral density (α exponent). The statistical precision was defined as the ability to obtain estimates for H and α that are consistent with their theoretical relationship, irrespective of the series length. The sensitivity consisted of testing whether significant differences between experimental conditions found in the original studies when considering 512 data points persisted with shorter series. We also investigate the use of evenly-spaced diffusion plots as a methodological improvement of original version of methods for short series. Our results show that the reliable assessment of LRA requires 512 data points, or no shorter than 256 data points provided that more robust methods are considered such as the evenly-spaced algorithms. Such series can be reasonably obtained in clinical populations with moderate, or even more severe, gait impairments and open the perspective to extend the use of LRA assessment as a marker of gait stability applicable to a broad range of locomotor disorders.

Analysis of long-range autocorrelation series: effect of the number of cycles on statistical precision and sensitivity

Analysis of long-range autocorrelation series: effect of the number of cycles on statistical precision and sensitivity

Analysis of revolution time variability in cycling pattern

In human beings, physiological signals are characterised by their complexity. Even under resting conditions, most of their features continuously fluctuate in a complex manner over the long-term, exhibiting long-range autocorrelations. Largely studied in stride duration variability and perturbed in walking of neurodegenerative disorders (Parkinson’s, Huntington’s diseases and amyotrophic lateral sclerosis) and under constrained conditions (metronome), long-range autocorrelations could result from a centrally mediated process (Hausdorff 2007). Walking and cycling represent two rhythmic tasks, involving similar neuronal and biomechanical processes and using the same peripheral structures. Nevertheless, contrary to stride duration variability, revolution time variability had received little attention. This study was designed in order to assess the magnitude and the dynamics of revolution time variability during cycling.