Frédéric Crevecoeur

The paper investigates how behavioral markers of essential tremor correlate with changes in brain functional connectivity using resting-state fMRI and kinematic data.

This study shows that phasic arousal selectively sharpens goal-dependent feedback control during movement by amplifying task-relevant responses and suppressing irrelevant ones.

This study examines how the central nervous system uses different feedback control strategies during reaching tasks in varying environments, finding that robust control and online adaptation are used differently depending on predictability.

This paper introduces a linear model that explains how neural population dynamics in the motor cortex can flexibly control multiple behaviors through optimal sensory feedback mapping.

This paper shows that movement duration in reaching tasks can be explained by infinite horizon optimal feedback control, capturing tradeoffs between duration, accuracy, and task parameters.

The paper measures how long-range autocorrelations in stride durations change during transitions between self-paced walking and synchronization with a metronome, and validates these findings with a computational model.

The paper investigates how flexible control and motor adaptation interact during movement, finding that concurrent perturbations reduce target redundancy exploitation and motor adaptation.

This study investigates how urgency and evidence accumulation affect multisensory integration during reaching, showing that visual feedback contributions vary with uncertainty and movement speed.

This study shows that sequence production can be either separate or coarticulated based on task-dependent control, validated through simulations and human experiments.

The paper demonstrates that increased spinal reflex responses to loads reduce motor cortex activity, using a neural network model to show how lower-level feedback influences goal-directed motor corrections.

The paper investigates Essential Tremor by testing a hypothesis that impaired delay compensation in feedback control mechanisms causes the tremor, using experimental and computational methods.

This study investigates motor adaptation impairments in Essential Tremor patients and finds deficits in movement execution, while anticipatory components remain intact.

This study investigates interlimb differences in reaching movement adaptation, finding greater adaptation in the dominant arm and a more robust, model-free control strategy in the non-dominant arm.

The paper develops a model that continuously monitors cost-to-go during reaching movements to enable online control adjustments and decision-making in response to perturbations.

This study investigates how humans can form and separate multiple motor memories during reaching tasks with force cues, showing that direction-based cues enable dual adaptation but magnitude-based cues lead to interference.

This study investigates how humans adjust their reaching control in response to dynamic changes in target width, showing continuous online tuning of task parameters rather than discrete policy switches.

This study investigates how target reward influences feedback control during motor tasks, finding increased feedback gains and changes in movement flexibility based on reward context.

The paper investigates savings in human force field learning, finding that feedback adaptation accelerates relearning without explicit strategy.

The paper shows humans adapt grip force to friction changes within 370ms by using skin deformation patterns detected by mechanoreceptive afferents.

This study shows reward enhances motor learning beyond reinforcement feedback by specifically strengthening reinforcement-related motor adjustments, with effects lasting beyond the training session.

This study shows that human reaching movements adjust control strategies online in response to changes in task goals or environmental constraints within ~150 ms.

The paper introduces a model to explain functional connectivity in the brain by identifying control regions that drive state-specific coactivation patterns through anatomical wiring.

This study shows that humans can adapt to unpredictable force fields within 250ms, with feedback responses finely tuned to ongoing perturbations.

The paper shows that humans adapt to unexpected force field disturbances during reaching movements, with within-movement feedback corrections improving and inducing after-effects, suggesting a fast time-scale of motor learning.

This study shows that human arm movement control and adaptation reflect differences in internal models, with some behaviors resembling stochastic and robust optimal control strategies.

This study simulates how sensorimotor deficits affect reaching performance in post-stroke hemiparesis by modeling neural control with specific impairments.

The paper proposes that saccadic suppression results from efficient sensorimotor estimation, where Bayesian inference reduces sensory weighting during eye movements.