Stednitz Sarah Josephine, Lesak Andrew, Fecker Adeline L, Painter Peregrine, Washbourne Phil, Mazzucato Luca, Scott Ethan K
Department of Anatomy & Physiology, University of Melbourne, Parkville, VIC, 3010, Australia.
Institute of Neuroscience, University of Oregon, Eugene, OR, 97403, USA.
Curr Biol. 2025 May 28. doi: 10.1016/j.cub.2025.05.031.
Social behavior across animal species ranges from simple pairwise interactions to thousands of individuals coordinating goal-directed movements. Regardless of the scale, these interactions are governed by the interplay between multimodal sensory information and the internal state of each animal. Here, we investigate how animals use multiple sensory modalities to guide social behavior in the highly social zebrafish (Danio rerio) and uncover the complex features of pairwise interactions early in development. To identify distinct behaviors and understand how they vary over time, we developed a hidden Markov model with constrained linear-model emissions to automatically classify states of coordinated interaction, using the movements of one animal to predict those of another. We discovered that social behaviors alternate between two interaction states within a single experimental session, distinguished by unique movements and timescales. Long-range interactions, akin to shoaling, rely on vision, while mechanosensation underlies rapid in-phase movements and parallel swimming. Altogether, we observe spontaneous interactions in pairs of fish, develop novel applications of hidden Markov modeling to reveal two fundamental interaction modes, and identify the sensory systems involved in each. Our modeling approach to pairwise social interactions is broadly applicable to a wide variety of naturalistic behaviors and species, and solves the challenge of detecting transient couplings between quasi-periodic time series.
动物物种间的社会行为范围广泛，从简单的两两互动到数千个体协调目标导向的运动。无论规模大小，这些互动都受多模态感官信息与每只动物内部状态之间相互作用的支配。在此，我们研究动物如何利用多种感官模态来引导高度社会化的斑马鱼（Danio rerio）的社会行为，并揭示发育早期两两互动的复杂特征。为了识别不同行为并了解它们如何随时间变化，我们开发了一种具有受限线性模型发射的隐马尔可夫模型，以自动分类协调互动的状态，利用一只动物的运动来预测另一只动物的运动。我们发现，在单个实验过程中，社会行为在两种互动状态之间交替，这两种状态由独特的运动和时间尺度区分。类似于聚群的远距离互动依赖视觉，而机械感觉是快速同相运动和平行游动的基础。总之，我们观察到成对鱼类的自发互动，开发了隐马尔可夫建模的新应用以揭示两种基本互动模式，并确定每种模式所涉及的感官系统。我们对两两社会互动的建模方法广泛适用于各种自然行为和物种，并解决了检测准周期时间序列之间瞬态耦合的挑战。
