Vincent Wens

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Learning the functional properties of objects is a core mechanism in the development of conceptual, cognitive and linguistic knowledge in children. The cerebral processes underlying these learning mechanisms remain unclear in adults and unexplored in children. Here, we investigated the neurophysiological patterns underpinning the learning of functions for(More)
We introduce a novel multimodal scheme for primary sensorimotor hand area (SM1ha) mapping integrating multiple functional indicators from functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG). Ten right-handed healthy subjects (19–33 years; 5 females, 5 males) and four patients (24–64 years; 2 females, 2 males) suffering from(More)
UNLABELLED Using a continuous listening task, we evaluated the coupling between the listener's cortical activity and the temporal envelopes of different sounds in a multitalker auditory scene using magnetoencephalography and corticovocal coherence analysis. Neuromagnetic signals were recorded from 20 right-handed healthy adult humans who listened to five(More)
The aim of this study was to investigate the age-related changes in resting-state neurometabolic connectivity from childhood to adulthood (6-50 years old). Fifty-four healthy adult subjects and twenty-three pseudo-healthy children underwent [(18) F]-fluorodeoxyglucose positron emission tomography at rest. Using statistical parametric mapping (SPM8), age and(More)
Behavioral evidence shows that sleep is crucial for the consolidation of declarative memories in children as in adults. However, the underlying cerebral mechanisms remain virtually unexplored. Using magnetoencephalography, we investigated in children (8.0-12.5years) the impact of sleep (90-minute nap) on the neurophysiological processes underlying the(More)
Humans are highly sensitive to statistical regularities in their environment. This phenomenon, usually referred as statistical learning, is most often assessed using post-learning behavioural measures that are limited by a lack of sensibility and do not monitor the temporal dynamics of learning. In the present study, we used magnetoencephalographic(More)
Using magnetoencephalography (MEG), this study investigates the spatio-temporal dynamics of the multilevel cortical processing of somatosensory change detection. Neuromagnetic signals of 16 healthy adult subjects (7 females and 9 males, mean age 29 ± 3 years) were recorded using whole-scalp-covering MEG while they underwent an oddball paradigm based on(More)
Modulation of the mu-alpha and mu-beta spontaneous rhythms reflects plastic neural changes within the primary sensorimotor cortex (SM1). Using magnetoencephalography (MEG), we investigated how aging modifies experience-induced plasticity after learning a motor sequence, looking at post- vs. pre-learning changes in the modulation of mu rhythms during the(More)
Network theory and inverse modeling are two standard tools of applied physics, whose combination is needed when studying the dynamical organization of spatially distributed systems from indirect measurements. However, the associated connectivity estimation may be affected by spatial leakage, an artifact of inverse modeling that limits the interpretability(More)
Motor information conveyed by viewing the kinematics of an agent's action helps to predict how the action will unfold. Still, how observed movement kinematics is processed in the brain remains to be clarified. Here, we used magnetoencephalography (MEG) to determine at which frequency and where in the brain, the neural activity is coupled with the kinematics(More)