Department of Biomedical, Dental, Morphological and Functional Imaging Sciences, University of Messina, Messina, Italy.
Laboratory of Neuromotor Physiology, IRCCS Santa Lucia Foundation, Rome, Italy.
J Neurophysiol. 2024 Jun 1;131(6):1126-1142. doi: 10.1152/jn.00199.2023. Epub 2024 Apr 17.
The central nervous system (CNS) may produce the same endpoint trajectory or torque profile with different muscle activation patterns. What differentiates these patterns is the presence of cocontraction, which does not contribute to effective torque generation but allows to modulate joints' mechanical stiffness. Although it has been suggested that the generation of force and the modulation of stiffness rely on separate pathways, a characterization of the differences between the synaptic inputs to motor neurons (MNs) underlying these tasks is still missing. In this study, participants coactivated the same pair of upper-limb muscles, i.e., the biceps brachii and the triceps brachii, to perform two functionally different tasks: limb stiffness modulation or endpoint force generation. Spike trains of MNs were identified through decomposition of high-density electromyograms (EMGs) collected from the two muscles. Cross-correlogram showed a higher synchronization between MNs recruited to modulate stiffness, whereas cross-muscle coherence analysis revealed peaks in the β-band, which is commonly ascribed to a cortical origin. These peaks did not appear during the coactivation for force generation, thus suggesting separate cortical inputs for stiffness modulation. Moreover, a within-muscle coherence analysis identified two subsets of MNs that were selectively recruited to generate force or regulate stiffness. This study is the first to highlight different characteristics, and probable different neural origins, of the synaptic inputs driving a pair of muscles under different functional conditions. We suggest that stiffness modulation is driven by cortical inputs that project to a separate set of MNs, supporting the existence of a separate pathway underlying the control of stiffness. The characterization of the pathways underlying force generation or stiffness modulation are still unknown. In this study, we demonstrated that the common input to motor neurons of antagonist muscles shows a high-frequency component when muscles are coactivated to modulate stiffness but not to generate force. Our results provide novel insights on the neural strategies for the recruitment of multiple muscles by identifying specific spectral characteristics of the synaptic inputs underlying functionally different tasks.
中枢神经系统 (CNS) 可能会通过不同的肌肉激活模式产生相同的末端轨迹或扭矩曲线。这些模式的区别在于存在协同收缩,它不会有助于有效产生扭矩,但可以调节关节的机械刚度。尽管有人提出,力的产生和刚度的调节依赖于独立的途径,但对于这些任务中运动神经元 (MNs) 的突触输入之间的差异特征仍然缺乏描述。在这项研究中,参与者共同激活同一对上肢肌肉,即肱二头肌和肱三头肌,以执行两个功能不同的任务:肢体刚度调节或末端力生成。通过对从这两块肌肉采集的高密度肌电图 (EMG) 进行分解,识别出 MNs 的尖峰活动。互相关图显示,用于调节刚度的 MNs 之间的同步性更高,而跨肌肉相干性分析显示β频带中的峰值,这通常归因于皮质起源。这些峰值在进行力生成的共激活时并未出现,这表明刚度调节具有独立的皮质输入。此外,肌肉内相干性分析确定了两组 MNs,它们分别被选择性募集来产生力或调节刚度。这项研究首次强调了在不同功能条件下驱动一对肌肉的突触输入的不同特征,并且可能具有不同的神经起源。我们认为,刚度调节是由投射到一组不同 MNs 的皮质输入驱动的,这支持了刚度控制的存在独立的途径。力生成或刚度调节的途径的特征仍然未知。在这项研究中,我们证明了当肌肉共同激活以调节刚度而不是产生力时,拮抗肌肉的运动神经元的共同输入会显示出高频成分。通过识别功能不同任务的突触输入的特定频谱特征,我们的结果为识别多个肌肉的神经募集策略提供了新的见解。