Non-invasive analysis of motor neurons controlling the intrinsic and extrinsic muscles of the hand

Tanzarella S, Muceli S, Del Vecchio A, Casolo A, Farina D (2020)

Publication Type: Journal article

Publication year: 2020

Journal

Journal of Neural Engineering Institute of Physics: Hybrid Open Access

Book Volume: 17

Article Number: 046033

Journal Issue: 4

DOI: 10.1088/1741-2552/aba6db

Abstract

Objective. We present a non-invasive framework for investigating efferent commands to 14 extrinsic and intrinsic hand muscles. We extend previous studies (limited to a few muscles) on common synaptic input among pools of motor neurons in a large number of muscles. Approach. Seven subjects performed sinusoidal isometric contractions to complete seven types of grasps, with each finger and with three combinations of fingers in opposition with the thumb. High-density surface EMG (HD-sEMG) signals (384 channels in total) recorded from the 14 muscles were decomposed into the constituent motor unit action potentials. This provided a non-invasive framework for the investigation of motor neuron discharge patterns, muscle coordination and efferent commands of the hand muscles during grasping. Moreover, during grasping tasks, it was possible to identify common neural information among pools of motor neurons innervating the investigated muscles. For this purpose, principal component analysis (PCA) was applied to the smoothed discharge rates of the decoded motor units. Main results. We found that the first principal component (PC1) of the ensemble of decoded motor neuron spike trains explained a variance of (53.0 ± 10.9) % and was positively correlated with force (R = 0.67 ± 0.10 across all subjects and tasks). By grouping the pools of motor neurons from extrinsic or intrinsic muscles, the PC1 explained a proportion of variance of (57.1 ± 11.3) % and (56.9 ± 11.8) %, respectively, and was correlated with force with R = 0.63 ± 0.13 and 0.63 ± 0.13, respectively. Significance. These observations demonstrate a low dimensional control of motor neurons across multiple muscles that can be exploited for extracting control signals in neural interfacing. The proposed framework was designed for hand rehabilitation perspectives, such as post-stroke rehabilitation and hand-exoskeleton control.

Authors with CRIS profile

Alessandro Del Vecchio

Involved external institutions

Chalmers University of Technology / Chalmers tekniska högskola SE Sweden (SE) Imperial College London / The Imperial College of Science, Technology and Medicine GB United Kingdom (GB)

How to cite

APA:

Tanzarella, S., Muceli, S., Del Vecchio, A., Casolo, A., & Farina, D. (2020). Non-invasive analysis of motor neurons controlling the intrinsic and extrinsic muscles of the hand. Journal of Neural Engineering, 17(4). https://dx.doi.org/10.1088/1741-2552/aba6db

MLA:

Tanzarella, Simone, et al. "Non-invasive analysis of motor neurons controlling the intrinsic and extrinsic muscles of the hand." Journal of Neural Engineering 17.4 (2020).

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