Engineering Neural Motor Control: From Mechanisms to Neural Interfaces

A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Biomedical Engineering and Biomaterials".

Deadline for manuscript submissions: 30 June 2025 | Viewed by 644

Special Issue Editors


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Guest Editor
School of Life Science and Technology, Institute of Science Tokyo, Kanagawa 226-8501, Japan
Interests: systems neuroscience; motor control; motor learning; neural coding; neuromodulation

E-Mail Website
Guest Editor
Department of Mechanical Engineering, National Defense Academy of Japan, Yokosuka 239-8686, Japan
Interests: motor control; computational neuroscience; rehabilitation; robotics; cybernetics

Special Issue Information

Dear Colleagues,

Neural control of movements is a key issue in neuroscience. Researchers have adopted concepts and technologies from other disciplines to propose working hypotheses, as well as acquire data and analyze data. In particular, engineering provides powerful tools that can be used to unveil and describe the time dynamics of a system, which is an important characteristic of movement. One of the final goals of neuroscience is to understand how to generate appropriate motor commands by the nervous system so as to control the musculoskeletal system within an environment, in which the nervous system should adapt to changes in the body and the environment. Knowledge of this adaptive control mechanism by the nervous system is growing. Not only has this led to greater insights into the nervous system, but this knowledge has also been applied to therapeutics. Electrical stimulation, for example, is used to modulate the nervous system for the treatment of epilepsy and Parkinson’s disease. The brain–machine interface could be a potential prosthetic device for patients with some spinal cord injuries and diseases.

This Special Issue aims to collect recent studies focused on elucidating neural control mechanisms of the body and developing new methodologies translatable to research on the nervous system, as well as to further expand our knowledge that has potential applicability to therapeutics. We welcome authors to submit original papers, reviews, and other articles.

Dr. Eizo Miyashita
Dr. Yuki Ueyama
Guest Editors

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Keywords

  • systems neuroscience
  • computational neuroscience
  • motor control
  • motor learning
  • motor dysfunction
  • rehabilitation
  • neuromodulation
  • human argumentation

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Published Papers (1 paper)

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Research

33 pages, 10768 KiB  
Article
Analysis of Connectivity in Electromyography Signals to Examine Neural Correlations in the Activation of Lower Leg Muscles for Postural Stability: A Pilot Study
by Gordon Alderink, Diana McCrumb, David Zeitler and Samhita Rhodes
Bioengineering 2025, 12(1), 84; https://doi.org/10.3390/bioengineering12010084 - 17 Jan 2025
Viewed by 552
Abstract
In quiet standing, the central nervous system implements a pre-programmed ankle strategy of postural control to maintain upright balance and stability. This strategy comprises a synchronized common neural drive delivered to synergistically grouped muscles. This study evaluated connectivity between EMG signals of the [...] Read more.
In quiet standing, the central nervous system implements a pre-programmed ankle strategy of postural control to maintain upright balance and stability. This strategy comprises a synchronized common neural drive delivered to synergistically grouped muscles. This study evaluated connectivity between EMG signals of the unilateral and bilateral homologous muscle pairs of the lower legs during various standing balance conditions using magnitude-squared coherence (MSC). The leg muscles examined included the right and left tibialis anterior (TA), medial gastrocnemius (MG), and soleus (S). MSC is a frequency domain measure that quantifies the linear phase relation between two signals and was analyzed in the alpha (8–13 Hz), beta (13–30 Hz), and gamma (30–100 Hz) neural frequency bands for feet together and feet tandem, with eyes open and eyes closed conditions. Results showed that connectivity in the beta and lower and upper gamma bands (30–100 Hz) was influenced by standing balance conditions and was indicative of a neural drive originating from the motor cortex. Instability was evaluated by comparing less stable standing conditions with a baseline—eyes open feet together stance. Changes in connectivity in the beta and gamma bands were found to be most significant in the muscle pairs of the back leg during a tandem stance regardless of dominant foot placement. MSC identified the MG:S muscle pair as significant for the right and left leg. The results of this study provided insight into the neural mechanism of postural control. Full article
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