HE Louvain en Hainaut

Between gait and cognition: an exploratory mixed-methods study of cognitive—motor dual-task profiles and lived experience

2026-09-22T00:00:00Z

Between gait and cognition: an exploratory mixed-methods study of cognitive—motor dual-task profiles and lived experience Fabien, Buisseret; Frederic, Dierick; Eva, Houdart; Florence, Jonckheere; Samir, Beggache; Jennifer, Denis Background: Cognitive-motor dual tasking is widely studied. However, the results remain heterogeneous depending on the type of tasks and individual psychological factors. To address this variability, dual-task cost (DTC) frameworks allow classification of behavioral profiles. This study aimed to propose a method designed to identify individual determinants of dual-task (DT) behavior by combining quantitative gait and cognitive measures with qualitative analyses of lived experience. Methods: Thirty-three young healthy adults performed Raven’s Progressive Matrices Test (RPMT) and treadmill walking in both single-task and DT conditions. Participants were classified into DT profiles according to DTC. Statistical tests were performed to assess whether the DTCs differed from zero and whether they differed between participants who reported having answered some items randomly and those who did not. Explicitation interviews were then conducted and analyzed independently of participants’ quantitative DT profiles. Qualitative findings were subsequently integrated with the quantitative profiles at the interpretive stage to characterize individual DT behaviors. Results: Dual tasking significantly reduced RPMT response time (p < 0.001) without affecting gait parameters. All four DT profiles were represented, and explicitation interviews revealed distinct experiential strategies within each profile. Discussion: Distress and cognitive overload characterized mutual interference, analytical or automatized strategies supported cognitive-priority trade-offs, and relaxed immersion and positive affect facilitated mutual facilitation. Gait-priority participants reported bodily immersion and sensory detachment. Conclusion: Our mixed-method approach may offer a transferable methodology for clinical contexts,

Casimir scaling in glueballs in SU(��) and Sp(2��) gauge theories: Hints from constituent approaches

2026-01-10T00:00:00Z

Casimir scaling in glueballs in SU(��) and Sp(2��) gauge theories: Hints from constituent approaches Buisseret, Fabien; Semay, Claude; Mathieu, Vincent; Chevalier, Cyrille Xe have shown that the ratio of the glueball masses on their large N mass in SU(N) and Sp(2N) gauge theories dominantly scales according to the Casimir scaling hypothesis. This result is in agreement with previous findings in the mesonic sector. Such scaling laws may help to put constraints on effective models parameters, as we have shown in the case of constituent gluons approaches, where the observed scaling law favours adjoint strings as the best candidate to model interactions between constituent gluons. A simple two-body spinless Salpeter Hamiltonian with funnel potential is able to model the SU(∞) and Sp(∞) ��=+ low-lying spectrum provided constituent gluons are seen as transverse particles. A three-body Y-junction generalization of this Hamiltonian leads to a ��=− low-lying spectrum with the expected global features but show-ing extra states with respect to the lattice QCD spectrum.

t si le cerveau utilisait la physique fondamentale pour piloter nos gestes ?

2026-05-08T00:00:00Z

t si le cerveau utilisait la physique fondamentale pour piloter nos gestes ? Du Brulle, Christian; Boulanger, Nicolas; Buisseret, Fabien; Dierick, Frédéric; White, Olivier Saisir une tasse, écrire son prénom, tendre la main. Des gestes simples, presque automatiques. Derrière cette apparente évidence se cache une question : comment le cerveau choisit-il un mouvement précis parmi une infinité de possibilités pour réaliser ces tâches ?

From brain to motion: harnessing higher-derivative mechanics for neural control

2025-11-25T00:00:00Z

From brain to motion: harnessing higher-derivative mechanics for neural control White, Olivier; BUISSERET, Fabien; DIERICK, Frédéric; Boulanger, Nicolas Optimal Feedback Control provides a theoretical framework for goal-directed movements, where the nervous system adjusts actions based on sensory feedback. This theory assumes that there exists a cost function that is optimized throughout one's movement. It is natural to assume that mechanical quantities should be involved in cost functions, but this does not imply that the mechanical principles that govern human voluntary movements are necessarily Newtonian. We argue that integrating principles from Lagrangian and Hamiltonian higher-derivative mechanics, i.e. dynamical models relying on a Lagrangian of the form $L\left(\vec x,\dot{\vec x},\ddot{\vec x},\dots,\vec x^{\, (N)}\right)$, with $N\geq 2$ and where $\vec x^{\, (i)}$ denotes the $i^{\rm th}$ time-derivative of the position $\vec x$, provides a more natural framework to study the constraints hidden in human voluntary movement within Optimal Feedback Control theory.