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

International audienc

Studying the influence of a solid shell on lava dome growth and evolution using the level set method

A finite element formulation of the level set method, a technique to trace flow fronts and interfaces without element distortion, is presented to model the evolution of the free surface of a spreading flow for a highly viscous medium on a horizontal surface. As an example for this class of problem we consider the evolution of an axisymmetric lava dome. Equilibrium configurations of lava domes have been modelled analytically as brittle shells enclosing pressurized magma. The existence of the brittle shell may be viewed as a direct consequence of the strong temperature dependence of the viscosity. The temperature dependence leads to the formation of a thin predominantly elastic-plastic boundary layer along the free surface and acts as a constraint for the shape and flow of the lava dome. In our model, we adopt Iverson's assumption that the thin boundary layer behaves like an ideal plastic membrane shell enclosing the ductile interior of the lava dome. The effect of the membrane shell is then formally identical to a surface tension-like boundary condition for the normal stress at the free surface. The interior of the dome is modelled as a Newtonian fluid and the axisymmetry equations of motion are formulated in a Eulerian framework. We show that the level set is an effective tool to trace and model deforming interfaces for the example of the free surface of a lava dome. We demonstrate that Iverson's equilibrium dome shapes are indeed steady states of a transient model. We also show how interface conditions in the form of surface tension involving higher order spatial derivative (curvature) can be considered within a standard finite element framework

Multifractality in the Movement System When Adapting to Arm Cranking in Wheelchair Athletes, Able-Bodied Athletes, and Untrained People

Complexity science has helped neuroscientists shed new light on brain-body coordination during movement performance and motor learning in humans. A critical intuition based on monofractal approaches has been a fractal-like coordination in the movement system, more marked in motor-skilled people. Here we aimed to show that heterogeneity in scaling exponents of movements series, literally multifractality, may reflect a special kind of interactions spanning multiple temporal scales at once, which can be grasped by a focus-based multifractal detrended fluctuation analysis. We analyzed multifractality in the variability structure of a 10-min arm cranking movement series repeated as 3 sets a day for 3 days, comparatively with their linearized (phase-randomized) surrogate series in sedentary (SED) untrained people, wheelchair athletes (WATH), and able-bodied athletes (ATH). Arm cranking exercise was chosen to minimize external variations, which tend to interfere with internal origin of variability. Participants were asked to maintain a regular effort and torque output served as the performance variable. Our first hypothesis suggests greater multiscale interactions in trained (WATH, ATH) versus untrained (SED) people, reflected in a wider range of scaling exponents characterizing movement series, providing the system with significant robustness. As a second hypothesis, we addressed a possible advantage in WATH over ATH due to greater motor skills in upper-limbs. Multifractal metrics in original and surrogate series showed ubiquitous, but different, multifractal behaviors in expert (ATH and WATH indistinctively) versus novice (SED) people. Experts exhibited high multifractality during the first execution of the task; then multifractality dropped in following repetitions. We suggest an exacerbated robustness of the movement system coordination in experts when discovering the task. Once task novelty has worn off, poor external sources of variability and limited risks of task failure have been identified, which is reflected in the narrower range of scale interactions, possibly as an energy cost effective adaptation. Multifractal corollaries of movement adaptation may be helpful in sport training and motor rehabilitation programs

Influence of individual energy cost on running capacity in warm, humid environments

International audienc

Impact of a cognitive task on cycling fractal properties

International audienc

Feedback on the Use of Matb-Ii Task for Modeling of Cognitive Control Levels Through Psycho-Physiological Biosignals

Modeling individuals’ cognitive control levels in operational situations is a major challenge for safety in aeronautical industry. Standardized experimental tasks - as the Multi-Attribute Task Battery II (MATB-II) - are dedicated to such a challenge that can be faced using psycho-physiological biosignals. These biosignals are known to be sensitive to cognitive workload, performance, and expertise that are intricate features of MATB-II subtasks. Thus, it remained necessary to investigate whether these features could be set to ensure controlled experimental conditions. Two groups (15 experts in time-pressured decision making and 13 novices) completed 3 MATB-II sub-tasks (tracking, monitoring, and resource management tasks). Biosignals accounting for autonomic nervous system activity were measured continuously, as objective markers of cognition. Confrontation between performance data and (objective and subjective) cognitive markers reported contrasting perspectives regarding the exploitation of MATB-II as a pertinent tool to insure controlled experimental conditions in the context of cognitive control characterization

Multifractal Multiscale Analysis of Human Movements during Cognitive Tasks

Continuous adaptations of the movement system to changing environments or task demands rely on superposed fractal processes exhibiting power laws, that is, multifractality. The estimators of the multifractal spectrum potentially reflect the adaptive use of perception, cognition, and action. To observe time-specific behavior in multifractal dynamics, a multiscale multifractal analysis based on DFA (MFMS-DFA) has been recently proposed and applied to cardiovascular dynamics. Here we aimed at evaluating whether MFMS-DFA allows identifying multiscale structures in the dynamics of human movements. Thirty-six (12 females) participants pedaled freely, after a metronomic initiation of the cadence at 60 rpm, against a light workload for 10 min: in reference to cycling (C), cycling while playing “Tetris” on a computer, alone (CT) or collaboratively (CTC) with another pedaling participant. Pedal revolution periods (PRP) series were examined with MFMS-DFA and compared to linearized surrogates, which attested to a presence of multifractality at almost all scales. A marked alteration in multifractality when playing Tetris was evidenced at two scales, τ ≈ 16 and τ ≈ 64 s, yet less marked at τ ≈ 16 s when playing collaboratively. Playing Tetris in collaboration attenuated these alterations, especially in the best Tetris players. This observation suggests the high sensitivity to cognitive demand of MFMS-DFA estimators, extending to the assessment of skill/demand interplay from individual behavior. So, by identifying scale-dependent multifractal structures in movement dynamics, MFMS-DFA has obvious potential for examining brain-movement coordinative structures, likely with sufficient sensitivity to find echo in diagnosing disorders and monitoring the progress of diseases that affect cognition and movement control