Simon Avrillon

The paper uses motor neuron recordings and simulation-based inference to estimate homonymous and heteronymous recurrent inhibition in human muscles during contractions.

The paper shows that neuromodulation enables transient decorrelation of motoneurons with shared inputs, explaining flexible control through differential sensitivity to neuromodulation.

This study shows that persistent inward currents (PICs) in spinal motor neurons have a greater influence on discharge behavior in the late afternoon compared to the early morning.

This study examines motor unit control flexibility by analyzing dimensionality of motor unit activity in two muscles, finding that while some muscles exhibit multidimensional manifolds, their control remains limited.

The paper analyzes motor unit firing rates during isometric contractions to show diverse rate coding patterns across motor unit pools.

The paper investigates how inhibitory inputs to motor units vary during nociceptive stimulation and finds non-homogeneous inhibition patterns that are size-independent.

The paper introduces an open-source software for real-time decoding of motor unit activity from EMG signals using blind-source separation, validated on synthetic and real data from human lower limb muscles.

This study investigates the dimensionality of motor unit control during isometric contractions, finding that motor units are constrained by common inputs and form synergistic groups.

The paper introduces MUedit, an open-source software for decomposing EMG signals and analyzing motor unit discharge timing, with simulated and experimental data for benchmarking.

This paper shows that larger and denser EMG electrode grids improve the identification of more representative motor unit samples through computational and experimental analysis.

The paper identifies two motor neuron synergies in triceps surae muscles during plantarflexion that remain stable across ankle angles.

This study investigates high-frequency cortical inputs to muscles during movement cancellation, finding increased beta and gamma oscillations in brain and muscle activity during NO-GO trials without behavioral changes.

This paper introduces a deep CNN for estimating neural drive from HD-EMG signals, showing it generalizes across muscles, sessions, and participants without retraining.

This study finds that the dominant hand has less common synaptic input between motor neurons innervating different muscles during isometric rotation tasks compared to the non-dominant hand.

The paper identifies common synaptic inputs to spinal motor neurons during a multi-joint task, revealing neural synergies that partially decouple from muscle innervation.

The paper assesses inter-operator reliability in decomposing HDsEMG into motor unit spike trains, finding high agreement across operators.