Causal Relationships Underlying the Collective Dynamic Behavior of Swarms

生活在群体中为动物提供了几个好处，例如更好的进食机会和减少捕食风险。在这两种情况下觅食和捕食者回避关键信息是通过非语言方式在不同的时间尺度上在整个群体中传播的。虽然目前的动物行为方法允许在协调动作期间推断信息共享，但这些相互作用只是动物群体复杂行为库的一小部分。该奖项支持基础研究，通过整合动力系统理论和斑马鱼动物模型的行为研究，研究集体动物行为背后的定向信息流。这项研究的意义是潜在的变革在行为脑研究和神经心理生物学领域，斑马鱼正在迅速成为一个有效的临床前动物模型。补充研究是跨学科的教育和外展活动，将培养外盒和多学科的思想，在工程学中代表性不足的学生，并有利于贫困学生在布鲁克林公立学校的教育。这项研究计划旨在证明，信息理论的方法可以用来衡量社会动物的行为。具体而言，该奖项将建立一个严格的无模型框架，以研究动物相互作用中的因果关系。一系列的假设驱动的实验斑马鱼将进行强调单向的信息传递，通过控制同种之间的视觉反馈，并使用独立控制的机器人副本。随后，建议的无模型框架和建立的实验范式将被用来调查信息流在浅滩和学校的斑马鱼沿着与社会影响的个体差异对他们的集体行为。为了实现这一目标，基于机器人的平台，多目标跟踪软件和新的实验协议将用于工程和解剖因果关系，这是验证设想的方法的核心。来自这些实验室实验的独特数据集将支持多种理论动力系统方法的验证，以揭示复杂生物和技术系统中的因果关系。

Living in groups affords several benefits for animals such as better feeding opportunities and reduced predation risks. In both instances-foraging and predator avoidance-critical information is transmitted nonverbally throughout the group, at different time scales. While current methods in animal behavior allow for inferring information sharing during coordinated maneuvers, these interactions are only a small subset of the complex behavioral repertoire of animal groups. This award supports fundamental research to investigate directional information flow underlying collective animal behavior, through the integration of dynamical systems theory and behavioral studies on the zebra fish animal model. The implications of this research are potentially transformative in the area of behavioral brain research and neuropsychobiology, where zebra fish is rapidly emerging as a valid preclinical animal model. Complementing the research are interdisciplinary education and outreach activities that will foster outside-the-box and multidisciplinary thinking in underrepresented students in engineering, and benefit the education of underprivileged students in Brooklyn public schools.This research program seeks to demonstrate that an information-theoretic approach can be used to measure social animal behavior. Specifically, this award will establish a rigorous model-free framework to study causal relationships in animal interactions. A series of hypothesis-driven experiments on zebra fish will be conducted to emphasize unidirectional information transfer by controlling visual feedback between conspecifics and using independently controlled robotic replicas. Subsequently, the proposed model-free framework and established experimental paradigms will be used to investigate information flow in shoaling and schooling zebra fish along with the social implications of individual differences on their collective behavior. Toward this aim, robotics-based platforms, multi-target tracking software, and novel experimental protocols will be utilized for engineering and dissecting causal relationships that are central to the validation of the envisioned approach. The unique datasets from these laboratory experiments will support the validation of a multitude of theoretical dynamical-systems approaches toward unraveling causality in complex biological and technological systems.