Connecting Empirical and Mathematical Approaches to Collective Behaviour

跨尺度，生物聚集体形成惊人的模式，显示协调，凝聚力的运动，并通过自组织的原则功能，但在组水平的复杂性可以掩盖的基本机制。确定这种群体行为是如何出现和持续的，既涉及对这种群体的直接观察，也涉及测试假设行为制度的数学模型。 我的研究计划就在这个界面上。我设计和实施集体的观察和实验研究，从鸟类到人类。我开发算法来处理和分析这些数据，总结相互作用的重要统计标记，并提供跨物种和条件的比较测试。我开发，测试和模拟基于个人的微分方程模型来评估什么样的个人互动解释观察到的组级结构的假设。通过经验数据来告知这些模型的构建和验证，我将模型预测直接与自然现象联系起来。我用这种理论方法研究了野外的大群冲浪者，从重建的轨迹中推断出个体的相互作用规则。进一步的分析揭示了对有序/无序转变的动态、捕食回避模式和对环境的集体反应的见解。 我将把我的分析方法扩展到集体运动的新数据集。与澳大利亚悉尼的一位新合作者一起，我将在现场和实验室中分析一系列基于自动分类的鱼类数据集。这些数据集包括大堡礁雀鲷对风险的集体防御反应，鱼间熟悉对食蚊鱼集体行为的影响，以及行为参数如何通过彩虹鱼家族内的物种形成和环境形成。实验室数据所允许的控制程度将允许开发更新的逐步建模方法，从个体到配对，再到大型集体。 在第二个主要方向，我将通过听觉互动研究人类的集体行为。本研究基于已经完成的试点工作，使用人类同步鼓掌的实验系统（2至数百人的组）来研究什么类型的交互允许同步鼓掌出现，以及如何通过耦合振荡器建模框架实现同步后顺序参数（组频率，组同步）的演变。这项研究将人类感觉运动同步的工作从个人扩展到集体。此外，将研究诸如组大小、节奏初始化和空间信息传递的影响。 这些举措有助于我的总体研究目标的测量，并解释模式在有组织的集体。

Across scales, biological aggregates form striking patterns, display coordinated, cohesive motion, and function via principles of self-organization, yet complexity at the group level can obscure the underlying mechanisms. Determining how such group behaviour emerges and is sustained involves both direct observation of such groups, and mathematical models to test hypothetical behaviour regimes. My research program lies at this interface. I design and implement observational and experimental studies of collectives, from birds to humans. I develop algorithms to process and analyze these data, to summarize important statistical markers of interaction, and provide tests for comparison across species and condition. I develop, test, and simulate individual based differential-equation models to evaluate hypotheses of what individual interactions explain the observed group-level structure. By informing the construction and validation of these models via empirical data, I tie model predictions directly to the natural phenomena. I have used this empirical-theoretical approach to study large flocks of surf scoters in the field, to infer individual rules of interaction from reconstructed trajectories. Further analysis has revealed insights into the dynamics of order/disorder transitions, patterns of predation avoidance, and collective response to the environment. I will extend my analytical methods to new datasets of collective motion. With a new collaborator in Sydney, Australia, I will analyze a collection of trajectory-based datasets of fish, both in the field and in the lab. These datasets include the collective defensive response to risk in damselfish in the Great Barrier Reef, the effects of inter-fish familiarity on collective behaviour of mosquitofish, and how behavioural parameters are shaped by speciation and environment within the family of Rainbowfish. The degree of control permitted by the laboratory data will allow for the development of an updated, stepwise modelling approach from individuals, to pairs, up to large collectives. In the second main direction, I will study human collective behaviour via aural interactions. This research, based on pilot work already completed, uses an experimental system of humans clapping synchronously (groups of 2 to hundreds) to study what type of interactions allow synchronous clapping to arise, and how order parameters (group frequency, group synchrony) evolve after synchrony is achieved, via a coupled-oscillator modelling framework. This research extends work on human sensorimotor synchronization from the individual to the collective. Furthermore, effects such as group size, rhythmic initialization, and spatial information transfer will be studied. These initiatives contribute to my overall research goal of measuring, and explaining pattern in organized collectives.