CAREER: Principles of Firefly Rhythmic Synchronization

在大型动物群体中，由于存在多种信号和环境干扰，生物交流常常伴随着巨大的噪音水平。处理噪声的一种常用方法是同步信号，使个体发出一致的信号。在广泛的生物（青蛙、鱼类、鸟类和灵长类动物）中，同步动物群体的交流以复杂的信号为特征。相比之下，PI将与一个易于处理的萤火虫群模型系统一起工作，其中通信信号是可视的，以近似数字闪光的形式，并且在三维空间中具有视觉可追溯性，甚至在大型移动个体群中也是如此。PI将结合现场和实验室实验与物理和信息论理论的信号同步，使用萤火虫群作为模型系统。这将使我们对通信策略的理解取得根本性的进步，并使PI能够在广泛的长度和时间尺度上集成模型和实验。PI将侧重于信号同步的基本方面。PI将使用创新的萤火虫现场记录技术和虚拟现实（VR）系统，获得萤火虫闪光的定量时空记录，并通过将萤火虫暴露在精心设计的视觉刺激下，测试关于同步通信的假设。这些信息丰富的数据集将促进基于主体的潜在机制模型的开发和验证。反过来，建模可以为实验设计提供反馈，并作为设计VR刺激的工具，其反应将验证或反驳给定的假设。这种相互交织的理论-实验方法将通过同时改进模型和实验，使模型验证达到前所未有的水平，直到提取和澄清基本原理。同样的方法将直接告知PI的教育目标，因为他们开发的课程将通过计算和实验数据的可视化来吸引学生参与动物交流的概念。因此，这个职业奖将从根本上推进PI的长期目标，提供对实现同步的原则的见解，并将获得的萤火虫数据纳入STEM教育。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Biological communication in large animal groups is often accompanied by immense noise levels due to the presence of multiple signals and interference from the environment. One common way to deal with noise is to synchronize the signals, so that individuals signal in unison. Communication in well-studied synchronous animal groups across a broad range of organisms (frogs, fish, birds, and primates) is characterized by complex signals. In contrast, the PI will work with a tractable model system of firefly swarms where communication signals are visual, in the form of approximately digital light flashes, and visually traceable in three dimensions, even throughout large swarms of motile individuals. The PI will combine field and lab experiments with physical and information-theoretic theories for signal synchronization, using firefly swarms as a model system. This will enable fundamental advances in our understanding of communication strategies and enable the PI to integrate models and experiments across a wide range of length and time scales. The PI will focus on fundamental aspects of signal synchronization. The PI will use innovative field-recording technologies for fireflies and Virtual Reality (VR) systems to obtain quantitative spatiotemporal recordings of firefly flashes and test hypotheses about synchronous communication by exposing the fireflies to carefully designed visual stimulus. These information-rich datasets will facilitate the development and validation of agent-based models of possible underlying mechanisms. In turn, modeling can provide feedback on experiment design and serve as a tool to design VR stimuli whose responses will either validate or disprove a given hypothesis. This interwoven theory-experiment approach will allow an unprecedented level of model validation via simultaneous refinement of both models and experiments until the underlying principles are extracted and clarified. The same approach will directly inform the PI's educational goals as they develop a class that will engage students in concepts of animal communication via visualization of computational and experimental data. Therefore, this CAREER award will fundamentally advance the PI's long-term goals by providing insight into the principles that enable synchronization and incorporating the acquired firefly data in STEM education.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.