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Multi-muscle control during bipedal stance: an EMG–EMG analysis approach

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Abstract

Posture and postural reactions to mechanical perturbations require the harmonic modulation of the activity of multiple muscles. This precision can become suboptimal in the presence of neuromuscular disorders and result in higher fall risk and associated levels of comorbidity. This study was designed to investigate neurophysiological principles related to the generation and distribution of inputs to skeletal muscles previously recognized as a synergistic group. Specifically, we investigated the current hypothesis that correlated neural inputs, as measured by intermuscular coherence, are the mechanism used by the central nervous system to coordinate the formation of postural muscle synergies. This hypothesis was investigated by analyzing the strength and distribution of correlated neural inputs to postural muscles during the execution of a quiet stance task. Nine participants, 4 females and 5 males, mean age 29.2 years old (±6.1 SD), performed the task of standing while holding a 5-kg barbell in front of their bodies at chest level. Subjects were asked to maintain a standing position for 10 s while the activity of three postural muscles was recorded by surface electrodes: soleus (SOL), biceps femoris (BF), and lumbar erector spinae (ERE). EMG–EMG coherence was estimated for three muscle pairs (SOL/BF, SOL/ERE, and BF/ERE). Our choice of studying these muscles was made based on the fact that they have been reported as components of a functional (synergistic) muscle group that emerges during the execution of bipedal stance. In addition, an isometric contraction can be easily induced in this muscle group by simply adding a weight to the body’s anterior aspect. The experimental condition elicited a significant increase in muscle activation levels for all three muscles (p < 0.01 for all muscles). EMG–EMG coherence analysis revealed significant coherence within two distinct frequency bands, 0–5 and 5–20 Hz. Significant coherence within the later frequency band was also found to be significantly uniformly distributed across the three muscle pairs. These findings are interpreted as corroborative with the idea of a hierarchic system of control where the controller may use the generation of common neural inputs to reduce the number of variables it manipulates.

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Authors and Affiliations

  1. School of Physical Therapy and Rehabilitation Science, The University of Montana, 32 Campus Drive, Missoula, MT, 59812-4680, USA

    Alessander Danna-Dos-Santos, Adriana M. Degani & Charles T. Leonard

  2. School of Psychiatry, University of New South Wales, Sydney, Australia

    Tjeerd W. Boonstra

  3. Black Dog Institute, Sydney, Australia

    Tjeerd W. Boonstra

  4. Research Institute MOVE, VU University, Amsterdam, The Netherlands

    Tjeerd W. Boonstra

  5. Department of Physical Therapy, Federal University of Piauí, Parnaíba, Brazil

    Vinicius S. Cardoso & Alessandra T. Magalhaes

  6. School of Sports and Physical Education, University of Sao Paulo, São Paulo, Brazil

    Luis Mochizuki

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  1. Alessander Danna-Dos-Santos
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  2. Tjeerd W. Boonstra
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  3. Adriana M. Degani
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  5. Alessandra T. Magalhaes
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  6. Luis Mochizuki
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  7. Charles T. Leonard
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Correspondence to Alessander Danna-Dos-Santos.

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Danna-Dos-Santos, A., Boonstra, T.W., Degani, A.M. et al. Multi-muscle control during bipedal stance: an EMG–EMG analysis approach. Exp Brain Res 232, 75–87 (2014). https://doi.org/10.1007/s00221-013-3721-z

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  • DOI: https://doi.org/10.1007/s00221-013-3721-z

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