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Corticospinal Coherence During Frequency-Modulated Isometric Ankle Dorsiflexion

  • A. ÚbedaEmail author
  • A. Del Vecchio
  • M. Sartori
  • U. Ş. Yavuz
  • F. Negro
  • F. Felici
  • J. M. Azorín
  • D. Farina
Conference paper
Part of the Biosystems & Biorobotics book series (BIOSYSROB, volume 15)

Abstract

In this paper we analyze the role of corticomuscular transmission for the time-varying force control. Corticospinal coherence is assessed during frequency-modulated isometric ankle dorsiflexions. Our preliminary results show a significant coupling between EEG signals and motor unit spike trains at the target frequency, suggesting that low-frequency cortical oscillations may have an important functional role in force control.

Keywords

Motor Unit Maximum Voluntary Contraction Tibialis Anterior Spike Train Target Frequency 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

This research has been supported by Conselleria d’Educació, Cultura i Esport of Generalitat Valenciana of Spain through grant APOSTD/2015/104 and by the European Research Council Advanced Grant DEMOVE (grant agreement 267888).

References

  1. 1.
    F. Negro, D. Farina, Linear transmission of cortical oscillations to the neural drive to muscles is mediated by common projections to populations of motoneurons in humans. J. Physiol. 589, 629–637 (2011)CrossRefGoogle Scholar
  2. 2.
    T.H. Petersen, M. Willerslev-Olsen, B.A. Conway, J.B. Nielsen, The motor cortex drives the muscles during walking in human subjects. J. Physiol. 590(10), 2443–2452 (2012)CrossRefGoogle Scholar
  3. 3.
    D. Farina, F. Negro, Common synaptic input in motor neurons, motor unit synchronization, and force control. Exerc. Sport Sci. Rev. 43(1), 23–33 (2015)CrossRefGoogle Scholar
  4. 4.
    S. Erimaki, O.M. Agapaki, C.N. Christakos, Neuromuscular mechanisms and neural strategies in the control of time-varying muscle contractions. J. Neurophysiol. 110, 1404–1414 (2013)CrossRefGoogle Scholar
  5. 5.
    J. Raethjen, R.B. Govindan, S. Binder, K.E. Zeuner, G. Deuschl, H. Stolze, Cortical representation of rhythmic foot movements. Brain Res. 1236, 79–84 (2008)CrossRefGoogle Scholar
  6. 6.
    I. Mendez-Balbuena, J.R. Naranjo, X. Wang, A. Andrykiewicz, F. Huethe, J. Schulte-Mönting, M.-C. Hepp-Reymond, R. Kristeva, The strength of the corticospinal coherence depends on the predictability of modulated isometric forces. J. Neurophysiol. 109(6), 1579–1588 (2013)CrossRefGoogle Scholar
  7. 7.
    F. Negro, S. Muceli, A.M. Castronovo, A. Holobar, D. Farina, Multi-channel intramuscular and surface EMG decomposition by convolutive blind source separation. J. Neural Eng. 13(2) (2016)Google Scholar
  8. 8.
    A. Holobar, M.A. Minetto, D. Farina, Accurate identification of motor unit discharge patterns from high-density surface EMG and validation with a novel signal-based performance metric. J. Neural Eng. 11, 016008 (2014)CrossRefGoogle Scholar
  9. 9.
    P.D. Welch, The use of fast Fourier transform for the estimation of power spectra: a method based on time averaging over short, modified periodograms. IEEE Trans. Audio Electroacoust. 15(2), 70–73 (1967)CrossRefGoogle Scholar
  10. 10.
    J.R. Rosenberg, A.M. Amjad, P. Breeze, D.R. Brillinger, D.M. Halliday, The Fourier approach to the identification of functional coupling between neuronal spike trains. Progr. Biophys. Mol. Biol. 53(1), 1–31 (1989)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • A. Úbeda
    • 1
    Email author
  • A. Del Vecchio
    • 2
  • M. Sartori
    • 3
  • U. Ş. Yavuz
    • 3
  • F. Negro
    • 3
  • F. Felici
    • 2
  • J. M. Azorín
    • 1
  • D. Farina
    • 3
  1. 1.Brain-Machine Interface LabMiguel Hernández University of ElcheElcheSpain
  2. 2.Department of Movement, Human and Health SciencesUniversity of Rome “Foro Italico”RomeItaly
  3. 3.Institute of Neurorehabilitation Systems, Bernstein Center for Computational NeuroscienceUniversity Medical Center GöttingenGöttingenGermany

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