0
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      The peripheral origin of tap-induced muscle contraction revealed by multi-electrode surface electromyography in human vastus medialis

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          It is well established that muscle percussion may lead to the excitation of muscle fibres. It is still debated, however, whether the excitation arises directly at the percussion site or reflexively, at the end plates. Here we sampled surface electromyograms (EMGs) from multiple locations along human vastus medialis fibres to address this issue. In five healthy subjects, contractions were elicited by percussing the distal fibre endings at different intensities (5–50 N), and the patellar tendon. EMGs were detected with two 32-electrode arrays, positioned longitudinally and transversally to the percussed fibres, to detect the origin and the propagation of action potentials and their spatial distribution across vastus medialis. During muscle percussion, compound action potentials were first observed at the electrode closest to the tapping site with latency smaller than 5 ms, and spatial extension confined to the percussed strip. Conversely, during tendon tap (and voluntary contractions), action potentials were first detected by electrodes closest to end plates and at a greater latency (mean ± s.d., 28.2 ± 1.7 ms, p < 0.001). No evidence of reflex responses to muscle tap was observed. Multi-electrode surface EMGs allowed for the first time to unequivocally and quantitatively describe the non-reflex nature of the response evoked by a muscle tap.

          Related collections

          Most cited references35

          • Record: found
          • Abstract: found
          • Article: not found

          The extraction of neural strategies from the surface EMG: an update.

          A surface EMG signal represents the linear transformation of motor neuron discharge times by the compound action potentials of the innervated muscle fibers and is often used as a source of information about neural activation of muscle. However, retrieving the embedded neural code from a surface EMG signal is extremely challenging. Most studies use indirect approaches in which selected features of the signal are interpreted as indicating certain characteristics of the neural code. These indirect associations are constrained by limitations that have been detailed previously (Farina D, Merletti R, Enoka RM. J Appl Physiol 96: 1486-1495, 2004) and are generally difficult to overcome. In an update on these issues, the current review extends the discussion to EMG-based coherence methods for assessing neural connectivity. We focus first on EMG amplitude cancellation, which intrinsically limits the association between EMG amplitude and the intensity of the neural activation and then discuss the limitations of coherence methods (EEG-EMG, EMG-EMG) as a way to assess the strength of the transmission of synaptic inputs into trains of motor unit action potentials. The debated influence of rectification on EMG spectral analysis and coherence measures is also discussed. Alternatively, there have been a number of attempts to identify the neural information directly by decomposing surface EMG signals into the discharge times of motor unit action potentials. The application of this approach is extremely powerful, but validation remains a central issue.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Influence of anatomical, physical, and detection-system parameters on surface EMG.

            Many previous studies were focused on the influence of anatomical, physical, and detection-system parameters on recorded surface EMG signals. Most of them were conducted by simulations. Previous EMG models have been limited by simplifications which did not allow simulation of several aspects of the EMG generation and detection systems. We recently proposed a model for fast and accurate simulation of the surface EMG. It characterizes the volume conductor as a non-homogeneous and anisotropic medium, and allows simulation of EMG signals generated by finite-length fibers without approximation of the current-density source. The influence of thickness of the subcutaneous tissue layers, fiber inclination, fiber depth, electrode size and shape, spatial filter transfer function, interelectrode distance, length of the fibers on surface, single-fiber action-potential amplitude, frequency content, and estimated conduction velocity are investigated in this paper. Implications of the results on electrode positioning procedures, spatial filter design, and EMG signal interpretation are discussed.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              The mechanosensitive nature of TRPV channels.

              Transient receptor potential vanilloid (TRPV) channels are widely expressed in both sensory and nonsensory cells. Whereas the channels display a broad diversity to activation by chemical and physical stimuli, activation by mechanical stimuli is common to many members of this group in both lower and higher organisms. Genetic screening in Caenorhabditis elegans has demonstrated an essential role for two TRPV channels in sensory neurons. OSM-9 and OCR-2, for example, are essential for both osmosensory and mechanosensory (nose-touch) behaviors. Likewise, two Drosophila TRPV channels, NAN and IAV, have been shown to be critical for hearing by the mechanosensitive chordotonal organs located in the fly's antennae. The mechanosensitive nature of the channels appears to be conserved in higher organisms for some TRPV channels. Two vertebrate channels, TRPV2 and TRPV4, are sensitive to hypotonic cell swelling, shear stress/fluid flow (TRPV4), and membrane stretch (TRPV2). In the osmosensing neurons of the hypothalamus (circumventricular organs), TRPV4 appears to function as an osmoreceptor, or part of an osmoreceptor complex, in control of vasopressin release, whereas in inner ear hair cells and vascular baroreceptors a mechanosensory role is suggestive, but not demonstrated. Finally, in many nonsensory cells expressing TRPV4, such as vascular endothelial cells and renal tubular epithelial cells, the channel exhibits well-developed local mechanosensory transduction processes where both cell swelling and shear stress/fluid flow lead to channel activation. Hence, many TRPV channels, or combinations of TRPV channels, display a mechanosensitive nature that underlies multiple mechanosensitive processes from worms to mammals.
                Bookmark

                Author and article information

                Contributors
                silvestro.roatta@unito.it
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                10 February 2020
                10 February 2020
                2020
                : 10
                : 2256
                Affiliations
                [1 ]ISNI 0000 0004 1937 0343, GRID grid.4800.c, Laboratory for Engineering of the Neuromuscular System (LISiN), Department of Electronics and Telecommunications, , Politecnico di Torino, Corso Duca degli Abruzzi 24, ; 10129 Turin, Italy
                [2 ]ISNI 0000 0004 1937 0343, GRID grid.4800.c, PoliToBIOMed Lab, , Politecnico di Torino, ; Turin, Italy
                [3 ]ISNI 0000 0001 2151 3065, GRID grid.5606.5, Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), , University of Genova, Campus of Savona, via Magliotto 2, ; 17100 Savona, Italy
                [4 ]ISNI 0000 0001 2336 6580, GRID grid.7605.4, Integrative Physiology Lab, Dept. of Neuroscience, , University of Torino, Torino, c.so Raffaello 30, ; 10125 Torino, Italy
                Author information
                http://orcid.org/0000-0002-4797-0667
                http://orcid.org/0000-0002-6239-7301
                http://orcid.org/0000-0001-9198-900X
                http://orcid.org/0000-0001-7370-2271
                Article
                59122
                10.1038/s41598-020-59122-z
                7010771
                32041996
                d987349a-2234-455c-807a-5ad72c5fa503
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 24 September 2019
                : 21 January 2020
                Funding
                Funded by: FundRef https://doi.org/10.13039/100007388, Compagnia di San Paolo (Fondazione Compagnia di San Paolo);
                Award ID: Convenzione_CSP_2016_2018
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100006692, Università degli Studi di Torino (University of Turin);
                Award ID: ROAS_RILO_17_01
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2020

                Uncategorized
                neurophysiology,neurology
                Uncategorized
                neurophysiology, neurology

                Comments

                Comment on this article