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Borzelli D, Vieira TMM, Botter A, Gazzoni M, Lacquaniti F, d'Avella A. Synaptic inputs to motor neurons underlying muscle coactivation for functionally different tasks have different spectral characteristics. J Neurophysiol 2024; 131:1126-1142. [PMID: 38629162 DOI: 10.1152/jn.00199.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 04/11/2024] [Accepted: 04/11/2024] [Indexed: 06/01/2024] Open
Abstract
The central nervous system (CNS) may produce the same endpoint trajectory or torque profile with different muscle activation patterns. What differentiates these patterns is the presence of cocontraction, which does not contribute to effective torque generation but allows to modulate joints' mechanical stiffness. Although it has been suggested that the generation of force and the modulation of stiffness rely on separate pathways, a characterization of the differences between the synaptic inputs to motor neurons (MNs) underlying these tasks is still missing. In this study, participants coactivated the same pair of upper-limb muscles, i.e., the biceps brachii and the triceps brachii, to perform two functionally different tasks: limb stiffness modulation or endpoint force generation. Spike trains of MNs were identified through decomposition of high-density electromyograms (EMGs) collected from the two muscles. Cross-correlogram showed a higher synchronization between MNs recruited to modulate stiffness, whereas cross-muscle coherence analysis revealed peaks in the β-band, which is commonly ascribed to a cortical origin. These peaks did not appear during the coactivation for force generation, thus suggesting separate cortical inputs for stiffness modulation. Moreover, a within-muscle coherence analysis identified two subsets of MNs that were selectively recruited to generate force or regulate stiffness. This study is the first to highlight different characteristics, and probable different neural origins, of the synaptic inputs driving a pair of muscles under different functional conditions. We suggest that stiffness modulation is driven by cortical inputs that project to a separate set of MNs, supporting the existence of a separate pathway underlying the control of stiffness.NEW & NOTEWORTHY The characterization of the pathways underlying force generation or stiffness modulation are still unknown. In this study, we demonstrated that the common input to motor neurons of antagonist muscles shows a high-frequency component when muscles are coactivated to modulate stiffness but not to generate force. Our results provide novel insights on the neural strategies for the recruitment of multiple muscles by identifying specific spectral characteristics of the synaptic inputs underlying functionally different tasks.
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Affiliation(s)
- Daniele Borzelli
- Department of Biomedical, Dental, Morphological and Functional Imaging Sciences, University of Messina, Messina, Italy
- Laboratory of Neuromotor Physiology, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Taian M M Vieira
- Laboratory for Engineering of the Neuromuscular System, Department of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy
- PoliToBIOMed Lab, Politecnico di Torino, Turin, Italy
| | - Alberto Botter
- Laboratory for Engineering of the Neuromuscular System, Department of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy
- PoliToBIOMed Lab, Politecnico di Torino, Turin, Italy
| | - Marco Gazzoni
- Laboratory for Engineering of the Neuromuscular System, Department of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy
- PoliToBIOMed Lab, Politecnico di Torino, Turin, Italy
| | - Francesco Lacquaniti
- Laboratory of Neuromotor Physiology, IRCCS Santa Lucia Foundation, Rome, Italy
- Department of Systems Medicine and Center of Space BioMedicine, University of Rome Tor Vergata, Rome, Italy
| | - Andrea d'Avella
- Department of Biomedical, Dental, Morphological and Functional Imaging Sciences, University of Messina, Messina, Italy
- Laboratory of Neuromotor Physiology, IRCCS Santa Lucia Foundation, Rome, Italy
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Valli G, Ritsche P, Casolo A, Negro F, De Vito G. Tutorial: Analysis of central and peripheral motor unit properties from decomposed High-Density surface EMG signals with openhdemg. J Electromyogr Kinesiol 2024; 74:102850. [PMID: 38065045 DOI: 10.1016/j.jelekin.2023.102850] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 10/05/2023] [Accepted: 11/28/2023] [Indexed: 01/29/2024] Open
Abstract
High-Density surface Electromyography (HD-sEMG) is the most established technique for the non-invasive analysis of single motor unit (MU) activity in humans. It provides the possibility to study the central properties (e.g., discharge rate) of large populations of MUs by analysis of their firing pattern. Additionally, by spike-triggered averaging, peripheral properties such as MUs conduction velocity can be estimated over adjacent regions of the muscles and single MUs can be tracked across different recording sessions. In this tutorial, we guide the reader through the investigation of MUs properties from decomposed HD-sEMG recordings by providing both the theoretical knowledge and practical tools necessary to perform the analyses. The practical application of this tutorial is based on openhdemg, a free and open-source community-based framework for the automated analysis of MUs properties built on Python 3 and composed of different modules for HD-sEMG data handling, visualisation, editing, and analysis. openhdemg is interfaceable with most of the available recording software, equipment or decomposition techniques, and all the built-in functions are easily adaptable to different experimental needs. The framework also includes a graphical user interface which enables users with limited coding skills to perform a robust and reliable analysis of MUs properties without coding.
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Affiliation(s)
- Giacomo Valli
- Department of Biomedical Sciences, University of Padova, Padova, Italy; Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy.
| | - Paul Ritsche
- Department of Sport, Exercise and Health, University of Basel, Basel, Switzerland.
| | - Andrea Casolo
- Department of Biomedical Sciences, University of Padova, Padova, Italy.
| | - Francesco Negro
- Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy.
| | - Giuseppe De Vito
- Department of Biomedical Sciences, University of Padova, Padova, Italy.
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De SD, Ricotta JM, Benamati A, Latash ML. Two classes of action-stabilizing synergies reflecting spinal and supraspinal circuitry. J Neurophysiol 2024; 131:152-165. [PMID: 38116603 DOI: 10.1152/jn.00352.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Revised: 11/30/2023] [Accepted: 12/19/2023] [Indexed: 12/21/2023] Open
Abstract
We explored force-stabilizing synergies during accurate four-finger constant force production tasks in spaces of finger modes (commands to fingers computed to account for the finger interdependence) and of motor unit (MU) firing frequencies. The main specific hypothesis was that the multifinger synergies would disappear during unintentional force drifts without visual feedback on the force magnitude, whereas MU-based synergies would be robust to such drifts. Healthy participants performed four-finger accurate cyclical force production trials followed by trials of constant force production. Individual MUs were identified in the flexor digitorum superficialis (FDS) and extensor digitorum communis (EDC). Principal component analysis was applied to motor unit frequencies to identify robust MU groups (MU-modes) with parallel scaling of the firing frequencies in FDS, in EDC, and the combined MUs of FDS + EDC. The framework of the uncontrolled manifold hypothesis was used to quantify force-stabilizing synergies when visual feedback on the force magnitude was available and 15 s after turning the visual feedback off. Removing visual feedback led to a force drift toward lower magnitudes, accompanied by the disappearance of multifinger synergies. In contrast, MU-mode synergies were minimally affected by removing visual feedback off and continued to be robust for the FDS and for the EDC, while being absent for the (FDS + EDC) analysis. We interpret the findings within the theory of hierarchical control of action with spatial referent coordinates. The qualitatively different behavior of the multifinger and MU-mode-based synergies likely reflects the difference in the involved neural circuitry, supraspinal for the former and spinal for the latter.NEW & NOTEWORTHY Two types of synergies, in the space of commands to individual fingers and in the space of motor unit groups, show qualitatively different behaviors during accurate multifinger force-production tasks. After removing visual feedback, finger force synergies disappear, whereas motor unit-based synergies persist. These results point at different neural circuitry involved in these two basic classes of synergies: supraspinal for multieffector synergies, and spinal for motor unit-based synergies.
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Affiliation(s)
- Sayan Deep De
- Department of Kinesiology, The Pennsylvania State University, University Park, Pennsylvania, United States
| | - Joseph M Ricotta
- Department of Kinesiology, The Pennsylvania State University, University Park, Pennsylvania, United States
| | - Anna Benamati
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Mark L Latash
- Department of Kinesiology, The Pennsylvania State University, University Park, Pennsylvania, United States
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Cohen JW, Vieira TM, Ivanova TD, Garland SJ. Regional recruitment and differential behavior of motor units during postural control in older adults. J Neurophysiol 2023; 130:1321-1333. [PMID: 37877159 PMCID: PMC10972635 DOI: 10.1152/jn.00068.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Revised: 10/23/2023] [Accepted: 10/23/2023] [Indexed: 10/26/2023] Open
Abstract
Aging is associated with neuromuscular system changes that may have implications for the recruitment and firing behaviors of motor units (MUs). In previous studies, we observed that young adults recruit subpopulations of triceps surae MUs during tasks that involved leaning in five directions: common units that were active during different leaning directions and unique units that were active in only one leaning direction. Furthermore, the MU subpopulation firing behaviors [average firing rate (AFR), coefficient of variation (CoVISI), and intermittent firing] modulated with leaning direction. The purpose of this study was to examine whether older adults exhibited this regional recruitment of MUs and firing behaviors. Seventeen older adults (aged 74.8 ± 5.3 yr) stood on a force platform and maintained their center of pressure leaning in five directions. High-density surface electromyography recordings from the triceps surae were decomposed into single MU action potentials. A MU tracking analysis identified groups of MUs as being common or unique across the leaning directions. Although leaning in different directions did not affect the AFR and CoVISI of common units (P > 0.05), the unique units responded to the leaning directions by increasing AFR and CoVISI, albeit modestly (F = 18.51, P < 0.001). The unique units increased their intermittency with forward leaning (F = 9.22, P = 0.003). The mediolateral barycenter positions of MU activity in both subpopulations were found in similar locations for all leaning directions (P > 0.05). These neuromuscular changes may contribute to the reduced balance performance seen in older adults.NEW & NOTEWORTHY In this study, we observed differences in motor unit recruitment and firing behaviors of distinct subpopulations of motor units in the older adult triceps surae muscle from those observed in the young adult. Our results suggest that the older adult central nervous system may partially lose the ability to regionally recruit and differentially control motor units. This finding may be an underlying cause of balance difficulties in older adults during directionally challenging leaning tasks.
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Affiliation(s)
- Joshua W Cohen
- School of Kinesiology, Western University, London, Ontario, Canada
- Faculty of Health Sciences, School of Physical Therapy, Western University, London, Ontario, Canada
| | - Taian M Vieira
- Department of Physiology and Pharmacology, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada
| | - Tanya D Ivanova
- Faculty of Health Sciences, School of Physical Therapy, Western University, London, Ontario, Canada
| | - S Jayne Garland
- Faculty of Health Sciences, School of Physical Therapy, Western University, London, Ontario, Canada
- Collaborative Specialization in Musculoskeletal Health Research, Bone and Joint Institute, Western University, London, Ontario, Canada
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