Experimental Brain Research

, Volume 236, Issue 11, pp 3065–3075 | Cite as

Beta, gamma band, and high-frequency coherence of EMGs of vasti muscles caused by clustering of motor units

  • Vinzenz von TscharnerEmail author
  • Martin Ullrich
  • Maurice Mohr
  • Daniel Comaduran Marquez
  • Benno M. Nigg
Research Article


The vasti muscles stabilize the knee joint during the running movement. This requires some motor units to synchronize. Test the hypothesis that EMGs from the vasti muscles (VM and VL) are coherent in four frequency bands, one below 30 Hz, the 40 Hz (30–45 Hz), the middle band up to 120 Hz, and the high-frequency band (135–280 Hz). Because the VM during one step and the VL during another step contain common EMG signal parts the inter-step coherence at low frequencies does not disappear when the coherence is computed between the EMGVM obtained from one step and the EMGVL of the previous step. Twelve participants ran on a treadmill at 2.9 m/s for 15 min. EMGs were recorded from the vasti muscles using bipolar current amplifiers. Ordinary coherence was computed between the EMGVM and EMGVL and for the inter-step-condition. Significant coherence was observed in all frequency bands. In the mid- and high-frequency range, coherence disappears for the inter-step condition, whereas the low-frequency coherence is still present. Four frequency bands must be considered. It was proposed that coherence at low frequencies reflects cortico-muscular interactions. However, the clustering of motor unit action potentials is sufficient to generate the low-frequency coherence as well. There is a low-frequency coherence resulting from EMGs of the vasti muscles that are similar in different steps. Therefore, at least these three effects must be considered to draw conclusions from the coherence of the vasti muscles at low frequencies that occur while running.


Running Synchronization of vasti muscles Current amplifier Clustering of motor units Power spectral density of electromyograms 



There was no Grant supporting this project. The project was supported by Biomechanigg Sport and Health Research Inc. (BSHR) who provided support in the form of salaries for authors MM and BMN. The National Council of Science and Technology of Mexico (CONACYT) provided support in the form of salary for DCM. The funders did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. MU was a visiting student from Friedrich Alexander University Erlangen-Nuremberg, Germany, supervised by VVT and was supported by the German Academic Scholarship Foundation (Studienstiftung des deutschen Volkes).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Faculty of Kinesiology, Human Performance LaboratoryUniversity of CalgaryCalgaryCanada
  2. 2.Machine Learning and Data Analytics Lab, Department of Computer ScienceFriedrich-Alexander-University Erlangen-Nürnberg (FAU)ErlangenGermany
  3. 3.ICT-417, Integrated Circuits and Optical Imaging LabSchulich School of Engineering, University of CalgaryCalgaryCanada

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