Division of Neuroscience and Experimental Psychology, School of Biological Science, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.
Division of Neuroscience and Experimental Psychology, School of Biological Science, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.
Curr Biol. 2020 Dec 7;30(23):4619-4630.e5. doi: 10.1016/j.cub.2020.09.007. Epub 2020 Oct 1.
Instinctive defensive behaviors, consisting of stereotyped sequences of movements and postures, are an essential component of the mouse behavioral repertoire. Since defensive behaviors can be reliably triggered by threatening sensory stimuli, the selection of the most appropriate action depends on the stimulus property. However, since the mouse has a wide repertoire of motor actions, it is not clear which set of movements and postures represent the relevant action. So far, this has been empirically identified as a change in locomotion state. However, the extent to which locomotion alone captures the diversity of defensive behaviors and their sensory specificity is unknown. To tackle this problem, we developed a method to obtain a faithful 3D reconstruction of the mouse body that enabled to quantify a wide variety of motor actions. This higher dimensional description revealed that defensive behaviors are more stimulus specific than indicated by locomotion data. Thus, responses to distinct stimuli that were equivalent in terms of locomotion (e.g., freezing induced by looming and sound) could be discriminated along other dimensions. The enhanced stimulus specificity was explained by a surprising diversity. A clustering analysis revealed that distinct combinations of movements and postures, giving rise to at least 7 different behaviors, were required to account for stimulus specificity. Moreover, each stimulus evoked more than one behavior, revealing a robust one-to-many mapping between sensations and behaviors that was not apparent from locomotion data. Our results indicate that diversity and sensory specificity of mouse defensive behaviors unfold in a higher dimensional space, spanning multiple motor actions.
本能防御行为由一系列刻板的动作和姿势组成,是老鼠行为组合的一个重要组成部分。由于防御行为可以被威胁性的感官刺激可靠地触发,因此选择最合适的动作取决于刺激的属性。然而,由于老鼠有广泛的运动动作组合,所以不清楚哪些动作和姿势代表了相关的动作。到目前为止,这已经被经验性地确定为运动状态的变化。然而,运动本身在多大程度上可以捕捉到防御行为的多样性及其感官特异性尚不清楚。为了解决这个问题,我们开发了一种方法来获得老鼠身体的忠实 3D 重建,从而能够量化各种各样的运动动作。这种更高维度的描述表明,防御行为比运动数据所指示的更具有刺激特异性。因此,即使在运动方面等效的不同刺激(例如,逼近和声音引起的冻结)也可以沿着其他维度进行区分。增强的刺激特异性可以用令人惊讶的多样性来解释。聚类分析显示,需要不同的动作和姿势组合来解释刺激特异性,这些组合至少产生了 7 种不同的行为。此外,每个刺激都会引发多种行为,这表明在感觉和行为之间存在稳健的一对多映射,而这种映射从运动数据中并不明显。我们的研究结果表明,老鼠防御行为的多样性和感官特异性在一个更高维度的空间中展开,涵盖了多种运动动作。