Department of Neurophysiology, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands.
Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands.
Sci Rep. 2023 Mar 30;13(1):5219. doi: 10.1038/s41598-023-31554-3.
Mice display a wide repertoire of vocalizations that varies with sex, strain, and context. Especially during social interaction, including sexually motivated dyadic interaction, mice emit sequences of ultrasonic vocalizations (USVs) of high complexity. As animals of both sexes vocalize, a reliable attribution of USVs to their emitter is essential. The state-of-the-art in sound localization for USVs in 2D allows spatial localization at a resolution of multiple centimeters. However, animals interact at closer ranges, e.g. snout-to-snout. Hence, improved algorithms are required to reliably assign USVs. We present a novel algorithm, SLIM (Sound Localization via Intersecting Manifolds), that achieves a 2-3-fold improvement in accuracy (13.1-14.3 mm) using only 4 microphones and extends to many microphones and localization in 3D. This accuracy allows reliable assignment of 84.3% of all USVs in our dataset. We apply SLIM to courtship interactions between adult C57Bl/6J wildtype mice and those carrying a heterozygous Foxp2 variant (R552H). The improved spatial accuracy reveals that vocalization behavior is dependent on the spatial relation between the interacting mice. Female mice vocalized more in close snout-to-snout interaction while male mice vocalized more when the male snout was in close proximity to the female's ano-genital region. Further, we find that the acoustic properties of the ultrasonic vocalizations (duration, Wiener Entropy, and sound level) are dependent on the spatial relation between the interacting mice as well as on the genotype. In conclusion, the improved attribution of vocalizations to their emitters provides a foundation for better understanding social vocal behaviors.
老鼠表现出广泛的发声行为,这些行为因性别、品系和环境而异。特别是在社交互动中,包括性动机的对偶互动,老鼠会发出复杂程度很高的超声波发声序列。由于雌雄动物都会发声,因此可靠地将超声波发声归因于其发声者至关重要。用于 2D 中超声波发声的声音定位的最新技术可以以多个厘米的分辨率进行空间定位。然而,动物在更近的距离上相互作用,例如,口鼻对口鼻。因此,需要改进算法来可靠地分配超声波发声。我们提出了一种新的算法,SLIM(通过相交流形进行声音定位),该算法仅使用 4 个麦克风即可将准确性提高 2-3 倍(13.1-14.3 毫米),并扩展到许多麦克风和 3D 定位。这种准确性允许可靠地分配我们数据集内 84.3%的所有超声波发声。我们将 SLIM 应用于成年 C57Bl/6J 野生型小鼠与携带杂合 Foxp2 变体(R552H)的小鼠之间的求偶相互作用。改进的空间准确性表明,发声行为取决于相互作用的小鼠之间的空间关系。当雌性小鼠的口鼻对近时,雌性小鼠的发声更多,而当雄性小鼠的口鼻接近雌性的肛门生殖器区域时,雄性小鼠的发声更多。此外,我们发现超声波发声的声学特性(持续时间、维纳熵和声音水平)不仅取决于相互作用的小鼠之间的空间关系,还取决于基因型。总之,将发声更准确地归因于其发声者为更好地理解社交发声行为提供了基础。