Interfacing the neural output of the spinal cord: robust and reliable longitudinal identification of motor neurons in humans.
A. Del Vecchio,Dario Farina +1 more
TLDR
It is shown that motor neuron activity can be identified in humans in the full muscle recruitment range with high accuracy and the potential of an accurate and reliable assessment of large populations of motor neurons in physiological investigations is shown.Abstract:
Objective: Non-invasive electromyographic techniques can detect action potentials from muscle units with high spatial dimensionality. These technologies allow the decoding of large samples of motor units by using high-density grids of electrodes that are placed on the skin overlying contracting muscles and therefore provide a non-invasive representation of the human spinal cord output. Approach: From a sample of >1200 decoded motor neurons, we show that motor neuron activity can be identified in humans in the full muscle recruitment range with high accuracy. Main results: After showing the validity of decomposition with novel test parameters, we demonstrate that the same motor neurons can be tracked over a period of one-month, which allows for the longitudinal analysis of individual human neural cells. Significance: These results show the potential of an accurate and reliable assessment of large populations of motor neurons in physiological investigations. We discuss the potential of this non-invasive neural interfacing technology for the study of the neural determinants of movement and man-machine interfacing.read more
Citations
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Tutorial: Analysis of motor unit discharge characteristics from high-density surface EMG signals
TL;DR: This tutorial includes a discussion of the differences between the extraction of global EMG signal features versus the identification of motor unit activity for physiological investigations followed by a comprehensive guide on how to acquire, inspect, and decompose HDEMG signals, and robust extraction ofMotor unit discharge characteristics.
Journal ArticleDOI
The knowns and unknowns of neural adaptations to resistance training.
Jakob Škarabot,Callum G. Brownstein,Andrea Casolo,Andrea Casolo,Alessandro Del Vecchio,Paul Ansdell +5 more
TL;DR: The purpose of this review is to clarify and critically discuss the literature concerning the site of putative neural adaptations to short-term resistance training, and to facilitate the estimation of the site(s) of neural adaptation to resistance training in the future.
Journal ArticleDOI
Spinal motoneurons of the human newborn are highly synchronized during leg movements
A. Del Vecchio,A. Del Vecchio,Francesca Sylos-Labini,Vito Mondì,Piermichele Paolillo,Yury Ivanenko,Francesco Lacquaniti,Dario Farina +7 more
TL;DR: The results suggest that motoneuron synchronization in human neonates might be an important mechanism for controlling fast limb movements, such as those of primitive reflexes, as well as monitor children at risk of developing motor disorders.
Journal ArticleDOI
Deep Learning for Robust Decomposition of High-Density Surface EMG Signals
Alexander Kenneth Clarke,Seyed Farokh Atashzar,Alessandro Del Vecchio,Deren Y. Barsakcioglu,Silvia Muceli,Paul Bentley,Filip Urh,Ales Holobar,Dario Farina +8 more
TL;DR: A gated recurrent unit (GRU) network was trained to decompose both simulated and experimental unwhitened HD-sEMG signal using the output of the gCKC algorithm, proving superior performance in generalising to new data.
Journal ArticleDOI
Only the fastest corticospinal fibers contribute to beta corticomuscular coherence
TL;DR: New methods to improve delay estimates in the corticomuscular transmission of beta rhythms are introduced and an improved methodology to measure the delay in the transmission of cortical beta activity to tonically active muscles is presented.
References
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