Collective biological motion: connecting empirical and theoretical approaches

从细胞到人类，聚集体形成了惊人的集体模式，显示出自组织的协调、凝聚力和集体智慧。由于这些聚集体的内在复杂性，推断决定个体运动路径的潜在相互作用和影响对大多数群体来说仍然是一个挑战。然而，最近在图像获取方面的技术进步导致了新的数据集，可以完全和准确地跟踪大型集体的每个个体成员(甚至在细胞规模上)，因此我们准备回答一系列问题，这些问题涉及形式如何与群体的功能相关，局部和全局信息如何协调，哪些精确的相互作用控制个体的运动，以及集体是如何由其存在的生态塑造的。 我的研究项目使用基于个人的数学模型，结合基于个人的集体生物运动的经验数据，来解决这些问题。我使用数据来生成统计方法，这些统计方法反过来又可以用作构建和验证理论模型的蓝图；相反，模型允许通过观察来验证假设的制定、探索和测试。在经验数据稀缺或缺失的情况下，我设计实验，收集和分析集体运动数据集。在一个应用中，我在几百个个体的觅食群中完全重建了水鸟(冲浪得分者)的轨迹(这是此类详细数据集中的第一个)，并利用这些观察结果准确地推断出控制相互作用的因素。使用经验-理论方法，我打算研究从细胞群体到鸟群的真实群体，观察相变和定向信息传递等现象，并在生物力学、环境、导航的背景下研究集体行为，以及生态环境如何在进化时间尺度上塑造这些行为。

From cells to humans, aggregates form striking collective patterns, displaying self-organized coordination, cohesion, and collective intelligence. Due to the inherent complexity in these aggregates, deducing the underlying interactions and effects that determine individual movement paths remains a challenge for most groups. However, recent technological advances in image acquisition have led to new datasets that can completely and accurately track each individual member of large collectives (even at the scale of cells), and so we are poised to answer a host of questions concerning how form relates to function of the group, how local and global information is reconciled, what precise interactions govern individual motion, and how the collective is shaped by the ecology in which it exists. My research program uses individual-based mathematical models, coupled with empirical data of individual-based collective biological motion, to address these questions. I use data to generate statistical measures that can, in turn, be used as a blueprint for constructing and validating theoretical models; conversely, models allow formulation, exploration and testing of hypotheses to be verified by observations. Where empirical data are scarce or missing, I design experiments, and collect and analyze collective motion datasets. In one application, I have completely reconstructed trajectories of aquatic birds (surf scoters) within foraging flocks of a few hundred individuals (among the first of such detailed data sets), and used these observations to precisely infer governing interactions. Using the empirical-theoretical approach, I intend to study real groups, ranging from cell colonies to bird flocks, to look at phenomena such as phase transitions and directional information transfer, and to investigate collective behaviour in the context of biomechanics, environment, navigation, and how ecological context shapes these behaviors on evolutionary timescales.