Synergistic organization of neural inputs from spinal motor neurons to extrinsic and intrinsic hand muscles
Artikel i vetenskaplig tidskrift, 2021

Our current understanding of synergistic muscle control is based on the analysis of muscle activities. Modules (synergies) in muscle coordination are extracted from electromyographic (EMG) signal envelopes. Each envelope indirectly reflects the neural drive received by a muscle; therefore, it carries information on the overall activity of the innervating motor neurons. However, it is not known whether the output of spinal motor neurons, whose number is orders of magnitude greater than the muscles they innervate, is organized in a low-dimensional fashion when performing complex tasks. Here, we hypothesized that motor neuron activities exhibit a synergistic organization in complex tasks and therefore that the common input to motor neurons results in a large dimensionality reduction in motor neuron outputs. To test this hypothesis, we factorized the output spike trains of motor neurons innervating 14 intrinsic and extrinsic hand muscles and analyzed the dimensionality of control when healthy individuals exerted isometric forces using seven grip types. We identified four motor neuron synergies, accounting for >70% of the variance of the activity of 54.1 ± 12.9 motor neurons, and we identified four functionally similar muscle synergies. However, motor neuron synergies better discriminated individual finger forces than muscle synergies and were more consistent with the expected role of muscles actuating each finger. Moreover, in a few cases, motor neurons innervating the same muscle were active in separate synergies. Our findings suggest a highly divergent net neural inputs to spinal motor neurons from spinal and supraspinal structures, contributing to the dimensionality reduction captured by muscle synergies.

Muscle synergies

Motor unit

Spinal modules

Synergistic motor control

Electromyography

Motor neuron

Författare

Simone Tanzarella

Imperial College London

Silvia Muceli

Chalmers, Elektroteknik, Signalbehandling och medicinsk teknik, Medicinska signaler och system

Marco Santello

Arizona State University

Dario Farina

Imperial College London

Journal of Neuroscience

0270-6474 (ISSN) 1529-2401 (eISSN)

Vol. 41 32 6878-6891

Ämneskategorier

Sjukgymnastik

Neurovetenskaper

Fysiologi

DOI

10.1523/JNEUROSCI.0419-21.2021

PubMed

34210782

Mer information

Senast uppdaterat

2021-08-24