Verhaltensbiologie, Freie Universität Berlin, Takustrasse 6, 14195 Berlin, Germany.
BMC Biol. 2013 Jan 8;11:1. doi: 10.1186/1741-7007-11-1.
Like human infants, songbirds learn their species-specific vocalizations through imitation learning. The birdsong system has emerged as a widely used experimental animal model for understanding the underlying neural mechanisms responsible for vocal production learning. However, how neural impulses are translated into the precise motor behavior of the complex vocal organ (syrinx) to create song is poorly understood. First and foremost, we lack a detailed understanding of syringeal morphology.
To fill this gap we combined non-invasive (high-field magnetic resonance imaging and micro-computed tomography) and invasive techniques (histology and micro-dissection) to construct the annotated high-resolution three-dimensional dataset, or morphome, of the zebra finch (Taeniopygia guttata) syrinx. We identified and annotated syringeal cartilage, bone and musculature in situ in unprecedented detail. We provide interactive three-dimensional models that greatly improve the communication of complex morphological data and our understanding of syringeal function in general.
Our results show that the syringeal skeleton is optimized for low weight driven by physiological constraints on song production. The present refinement of muscle organization and identity elucidates how apposed muscles actuate different syringeal elements. Our dataset allows for more precise predictions about muscle co-activation and synergies and has important implications for muscle activity and stimulation experiments. We also demonstrate how the syrinx can be stabilized during song to reduce mechanical noise and, as such, enhance repetitive execution of stereotypic motor patterns. In addition, we identify a cartilaginous structure suited to play a crucial role in the uncoupling of sound frequency and amplitude control, which permits a novel explanation of the evolutionary success of songbirds.
与人类婴儿一样，鸣禽通过模仿学习来学习其特定物种的叫声。鸟类鸣叫系统已成为一种广泛使用的实验动物模型，用于理解负责发声学习的潜在神经机制。然而，神经冲动如何转化为复杂发声器官（鸣管）的精确运动行为以产生鸣叫声，这一点我们还知之甚少。首先，我们对鸣管的形态缺乏详细的了解。
为了填补这一空白，我们结合了非侵入性（高磁场磁共振成像和微计算机断层扫描）和侵入性技术（组织学和微解剖），构建了斑马雀（Taeniopygia guttata）鸣管的注释高分辨率三维数据集，或形态组。我们以前所未有的细节原位识别和注释了鸣管软骨、骨骼和肌肉。我们提供了交互式三维模型，极大地改善了复杂形态数据的交流，并提高了我们对鸣管功能的总体理解。
我们的研究结果表明，鸣管骨骼的优化是为了满足歌唱产生的生理限制而降低重量。目前肌肉组织和身份的细化阐明了拮抗肌如何驱动不同鸣管元素的运动。我们的数据集可以更精确地预测肌肉的协同激活和协同作用，并对肌肉活动和刺激实验具有重要意义。我们还展示了鸣管如何在歌唱过程中稳定下来，以减少机械噪音，从而增强了刻板运动模式的重复执行。此外，我们确定了一个适合在声音频率和幅度控制解耦中发挥关键作用的软骨结构，这为鸣禽的进化成功提供了一个新的解释。
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