Alessandro Del Vecchio

The paper examines how motor unit recruitment and firing rates change with different hand tasks, showing task-dependent variations in neural drive distribution.

The paper investigates neural control of movement by analyzing common synaptic inputs in human quadriceps muscles during isometric leg extensions, finding that rectus femoris receives an independent input.

This study shows that unilateral resistance training increases maximal force through enhanced rate coding in high-threshold motor units during maximal voluntary contractions.

CRD improves MU yield from HD-sEMG by decomposing residual signals, identifying previously undetected low-amplitude MUs across multiple datasets.

The paper investigates motor unit recruitment and derecruitment dynamics in individuals with chronic cervical SCI, revealing coexisting phenotypes within motor pools.

The paper shows that humans can dissociate motor unit activation between proximal vastus medialis and vastus lateralis during isometric contractions, but not in distal regions.

NeuromechaniX automates extraction and meta-analysis of motor-unit research, revealing muscle-specific discharge rate differences and sex-based variations.

The paper investigates how motor neuron excitability and identity affect cutaneous reflexes by analyzing individual motor unit responses during isometric contraction.

MyoGen is a unified biophysical model of human neuromotor activity that matches experimental data and enables analysis of motor control principles.

This study investigates neural adaptations in muscle strength and force steadiness in untrained limbs after unilateral training, finding reduced synaptic input variability and increased neural drive in trained and contralateral limbs.

NeuroNella is an automated algorithm for identifying neuronal activity from multielectrode arrays, achieving less than 1% error rate in rodent and primate recordings.

This study shows that short-term skill acquisition in a force-matching task involves reduced alpha band neural oscillations and increased coupling between force and target oscillations.

The paper investigates motor unit control during hand movements, finding that synergistic grasps are controlled non-synergistically by distinct motor units.

The paper shows that surface electromyography (sEMG) underestimates motor pool responses during sensory stimulation, affecting both inhibition and excitation, with inaccuracies beyond signal cancellation.

The paper tracks motor units in non-human primates during force contractions, finding stable recruitment order and a dominant neural component for force control.

This paper develops a deep learning method to predict hand kinematics and forces from EMG signals, showing accurate prediction of unseen movements and learned anatomical neural features.

The study identifies two neural modules underlying motor unit discharge rates in synergistic muscles, showing heterogeneous distribution of common synaptic inputs among motor neurons.

This study investigates whether TACS modulates corticospinal beta entrainment in humans using simulations and electromyography, finding no consistent effect.

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.

This study shows that isometric strength training increases maximal force but not rate of force development (RFD) due to unchanged motor unit recruitment speed, despite increased discharge rates during plateau phases.

The paper introduces improved methods to measure corticospinal transmission delays of beta rhythms and shows they align with fastest axon speeds, suggesting two possible mechanisms for fast transmission.