3D functional modules of the facial muscles (3D FACE)

哺乳动物的一个重要特征是面部的可移动皮肤的发育。面部肌肉的形态和数量在进化过程中发生了变化，特别是在面部表情的社会功能过程中。在原始人类（类人猿）中，人类的面部表情变化最大，但为什么会这样，我们还不清楚。第一次，这里申请的项目旨在通过显微解剖学中不同技术的组合来从功能上了解人类面部肌肉。使用捐赠的身体制备。我们将联合收割机计算机断层扫描、磁共振断层扫描、显微计算机断层扫描检查与高分辨率超声检查相结合，并伴有3D肌束制备和组织化学肌纤维分型以及进一步的显微组织检查。我们最重要的假设是：a）不是单个面部肌肉形成面部表情和情绪表达的功能单位，而是肌肉中的亚单位，这些亚单位反过来可以跨肌肉发挥作用; B）这些功能亚单位不同; c）这些功能肌肉差异解释了人们面部表情和情绪表达的可能性; d）性别差异是可以预期的。这些基础知识是后续应用的先决条件，包括1）在后续检查中为面部运动和情感表达建模三维模型; 2）将这些数据集成到用于评估面部表情的自动图像分析方法中;和3）了解人类面部肌肉疾病中面部表情的变化，并能够开发个性化的改进方法，这些疾病的康复。

An important feature of mammals is the development of a movable skin in the face. The morphology and the number of facial muscles have changed evolutionarily, especially in the course of the social function of facial expressions. Among the hominids (great apes), the human face shows the greatest variety of facial expressions without it being ultimately clear why this is so. For the first time, the project applied for here aims to functionally understand the human facial muscles in a combination of different techniques in their microscopic anatomy. Preparations from body donations are used. We combine computed tomography, magnetic resonance tomography, micro-computed tomography examinations with high-resolution ultrasound examinations accompanied by 3D fascicle preparation and histochemical muscle fiber typing as well as further microscopic tissue examinations. Our most important hypotheses are: a) It is not individual facial muscles that form functional units for facial expressions and emotional expression, but rather sub-units in the muscles, which in turn can act across muscles; b) These functional subunits differ; c) These functional-muscular differences explain the possibilities of facial and emotional expression of people; d) gender differences are to be expected. This basic knowledge is a prerequisite for an follow-up application including then 1) modeling three-dimensional models for facial movements and emotional expressions in subsequent examinations; 2) integrate this data into automatic image analysis methods for evaluating facial expressions; and 3) to understand the changed facial expression in diseases of the facial muscles of humans and to be able to develop improved approaches for the personalized rehabilitation of these disorders.