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肌电图作为一种鉴别小鼠肌张力障碍的方法。

Electromyography as a Method for Distinguishing Dystonia in Mice.

机构信息

Department of Pathology & Immunology, Baylor College of Medicine, Houston, TX, USA.

Jan and Dan Duncan Neurological Research Institute at Texas Children's Hospital, Houston, TX, USA.

出版信息

Adv Neurobiol. 2023;31:71-91. doi: 10.1007/978-3-031-26220-3_5.

Abstract

Electromyography (EMG) methods allow quantitative analyses of motor function. The techniques include intramuscular recordings that are performed in vivo. However, recording muscle activity in freely moving mice, particularly in models of motor disease, often creates challenges that prevent the acquisition of clean signals. Recording preparations must be stable enough for the experimenter to collect an adequate number of signals for statistical analyses. Instability results in a low signal-to-noise ratio that prohibits proper isolation of EMG signals from the target muscle during the behavior of interest. Such insufficient isolation prevents the analysis of full electrical potential waveforms. In this case, resolving the shape of a waveform to differentiate individual spikes and bursts of muscle activity can be difficult. A common source of instability is an inadequate surgery. Poor surgical techniques cause blood loss, tissue damage, poor healing, encumbered movement, and unstable implantation of the electrodes. Here, we describe an optimized surgical procedure that ensures electrode stability for in vivo muscle recordings. We implement our technique to obtain recordings from agonist and antagonist muscle pairs in the hindlimbs of freely moving adult mice. We validate the stability of our method by holding EMG recordings during dystonic behavior. Our approach is ideal for studying normal and abnormal motor function in actively behaving mice and valuable for recording intramuscular activity when considerable motion is expected.

摘要

肌电图(EMG)方法可实现对运动功能的定量分析。这些技术包括在体进行的肌内记录。然而,在自由活动的小鼠中记录肌肉活动,特别是在运动疾病模型中,常常会遇到各种挑战,这些挑战会妨碍获得干净的信号。记录准备工作必须足够稳定,以便实验者能够收集足够数量的信号进行统计分析。如果不稳定,就会导致信噪比低,从而无法在感兴趣的行为期间从目标肌肉中正确分离 EMG 信号。这种不充分的隔离会阻止对全电潜力波形的分析。在这种情况下,解析波形的形状以区分单个肌电活动的尖峰和爆发可能会很困难。不稳定的一个常见来源是手术不当。糟糕的手术技术会导致失血、组织损伤、愈合不良、运动受限以及电极不稳定植入。在这里,我们描述了一种优化的手术程序,可确保体内肌肉记录中电极的稳定性。我们实施我们的技术,以从自由活动的成年小鼠后肢的拮抗剂和拮抗剂肌肉对中获得记录。我们通过在扭曲行为期间保持肌电图记录来验证我们方法的稳定性。我们的方法非常适合研究活跃行为的小鼠的正常和异常运动功能,并且在预期会有大量运动时,对于记录肌内活动也非常有价值。

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