Interfacing the neural output of the spinal cord: robust and reliable longitudinal identification of motor neurons in humans
File(s)
Published version
Author(s)
Del Vecchio, A
Farina, D
Type
Journal Article
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.
Date Issued
2019-12-05
Date Acceptance
2019-10-11
Citation
Journal of Neural Engineering, 2019, 17 (1), pp.1-11
ISSN
1741-2552
Publisher
IOP Publishing
Start Page
1
End Page
11
Journal / Book Title
Journal of Neural Engineering
Volume
17
Issue
1
Copyright Statement
© 2019 IOP Publishing Ltd. Original content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence http://creativecommons.org/licenses/by/3.0. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
License URL
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000537460300003&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Subjects
Science & Technology
Technology
Life Sciences & Biomedicine
Engineering, Biomedical
Neurosciences
Engineering
Neurosciences & Neurology
spinal Interfacing
motor neurons
EMG
neural control
SURFACE EMG
RECRUITMENT THRESHOLD
CONDUCTION-VELOCITY
MUSCLE
UNITS
FORCE
CONTRACTIONS
DISCHARGE
BEHAVIOR
Publication Status
Published
Article Number
ARTN 016003
Date Publish Online
2019-10-11