美国杜克大学Timothy W. Dunn团队近日取得一项新成果。经过不懈努力，他们研究出描绘社会行为的图景。该研究于2025年3月4日发表于国际一流学术期刊《细胞》杂志上。

课题组人员提出了一种用于自由互动动物的姿势动态和社交触摸的高分辨率3D跟踪技术，解决了具有挑战性的主题遮挡和部分分配问题，主题为3D几何推理，图神经网络和半监督学习。该研究组在相互作用的大鼠和小鼠中收集了超过1.1亿个3D姿势样本，其中包括7个单基因自闭症大鼠系。使用多尺度嵌入方法，小组确定了刻板动作、交互、同步和身体接触的丰富景观。这种高分辨率的表型分析揭示了自闭症模型和对苯丙胺的反应的一系列变化，这是传统测量方法无法解决的。他们的框架和庞大的交互库将促进社会行为及其神经生物学基础的研究。

据悉，社会互动是动物行为不可或缺的一部分。然而，由于缺乏以定量和严格的方式描述它的工具，他们对它的结构、基本原理和神经精神疾病（如自闭症）的理解受到了限制。

附：英文原文

Title: Mapping the landscape of social behavior

Author: Ugne Klibaite, Tianqing Li, Diego Aldarondo, Jumana F. Akoad, Bence P. lveczky, Timothy W. Dunn

Issue&Volume: 2025-03-04

Abstract: Social interaction is integral to animal behavior. However, lacking tools to describe it in quantitative and rigorous ways has limited our understanding of its structure, underlying principles, and the neuropsychiatric disorders, like autism, that perturb it. Here, we present a technique for high-resolution 3D tracking of postural dynamics and social touch in freely interacting animals, solving the challenging subject occlusion and part-assignment problems using 3D geometric reasoning, graph neural networks, and semi-supervised learning. We collected over 110 million 3D pose samples in interacting rats and mice, including seven monogenic autism rat lines. Using a multi-scale embedding approach, we identified a rich landscape of stereotyped actions, interactions, synchrony, and body contacts. This high-resolution phenotyping revealed a spectrum of changes in autism models and in response to amphetamine not resolved by conventional measurements. Our framework and large library of interactions will facilitate studies of social behaviors and their neurobiological underpinnings.

DOI: 10.1016/j.cell.2025.01.044

Source: https://www.cell.com/cell/abstract/S0092-8674(25)00154-0