Department of Radiation Sciences, Biomedical Engineering, Umeå University, Umeå, Sweden.
Department of Clinical Neurophysiology, Institute of Neuroscience, Uppsala University, Uppsala, Sweden.
Sci Rep. 2020 Dec 24;10(1):22382. doi: 10.1038/s41598-020-79863-1.
The central nervous system (CNS) controls skeletal muscles by the recruitment of motor units (MUs). Understanding MU function is critical in the diagnosis of neuromuscular diseases, exercise physiology and sports, and rehabilitation medicine. Recording and analyzing the MUs' electrical depolarization is the basis for state-of-the-art methods. Ultrafast ultrasound is a method that has the potential to study MUs because of the electrical depolarizations and consequent mechanical twitches. In this study, we evaluate if single MUs and their mechanical twitches can be identified using ultrafast ultrasound imaging of voluntary contractions. We compared decomposed spatio-temporal components of ultrasound image sequences against the gold standard needle electromyography. We found that 31% of the MUs could be successfully located and their firing pattern extracted. This method allows new non-invasive opportunities to study mechanical properties of MUs and the CNS control in neuromuscular physiology.
中枢神经系统（CNS）通过募集运动单位（MUs）来控制骨骼肌。了解 MU 的功能对于神经肌肉疾病的诊断、运动生理学和运动医学以及康复医学至关重要。记录和分析 MUs 的电去极化是最先进方法的基础。由于电去极化和随后的机械抽搐，超快速超声是一种有潜力研究 MUs 的方法。在这项研究中，我们评估了是否可以使用自愿收缩的超快速超声成像来识别单个 MUs 及其机械抽搐。我们将超声图像序列的分解时空分量与金标准针肌电图进行了比较。我们发现，31%的 MUs 可以成功定位并提取其发射模式。这种方法为研究神经肌肉生理学中的 MUs 的机械特性和中枢神经系统控制提供了新的非侵入性机会。
