Collaborative Research: Flexibility and Robustness of attack and evasion: reverse-engineering the mechanisms of behavioral control

动物如何在新的环境中产生有效的行为是行为科学长期以来的谜团之一。例如，网球运动员每次回发球时，情况都与他过去经历的情况不同：球的移动速度略有不同，或以不同的角度，或以不同的旋转。然而，神经系统能够在这些新的条件下产生有效的反应。这怎麽可能？这个项目将通过将新的数学方法与一种新颖的实验系统相结合来解决这个问题，该系统使用实时计算机视觉来跟踪动物，因为它们解决了连续的决策任务。作为这项研究更广泛影响的一部分，调查人员将与一个本科教育项目合作，旨在向传统上代表性较低的STEM学生介绍研究机会。跨学科学生团队将在开发和执行与更大项目主题相关的小型研究项目方面得到指导，目标是为基础科学专业的学生以及工程和数学专业的学生提供进入尖端、跨学科科学的门户。此外，调查人员将在指导佛罗里达大学惠特尼实验室REU项目(31年)的参与者时纳入这项研究。这项工作的结果将揭示动物如何在新的环境中产生如此多样化的行为来生存，并将带来新的问题和方法，可以用来理解脊椎动物神经系统的功能，以及动物承担的一些最重要的任务中行为控制的起源。与长期以来一直作为动物决策模型的二元选择任务不同，更复杂的感觉-运动行为，如躲避捕食者或捕获猎物，通常涉及对动态感官刺激流做出的一系列决定。这类行为的一个关键要求是它们是健壮的。例如，逃脱捕食者所需的确切决策链在不同的环境中会有所不同，但动物必须产生一系列独特的反应，以适应手头的情况。这突显了关于动物行为的一个长期存在的问题：在一个背景下学习或进化的行为如何概括为动物可能遇到的大量可能情况？这个项目采用数学建模和高分辨率的闭环实验相结合的方法来解决这个问题，该实验使用虹鳟鱼(Oncorhynchus MykISS)的猎物攻击和捕食者逃避行为作为模型，以研究动物如何产生灵活、健壮的行为序列。特别是，研究人员将检验正在出现的假设，即这些强大的、更高水平的行为反应是通过一种名为行为获得控制的机制实现的。研究将探索行为获得控制如何参与在正确的时间启动行为序列，平衡多个相互竞争的目标，沿多个行为维度协调控制(例如，加速、转弯)，以及在不断变化的环境条件下保持性能。这项工作有可能阐明复杂行为是如何在生态和进化相关任务的背景下产生的。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

How animals generate effective behavior in new situations is one of the longstanding mysteries of behavioral science. For example, every time a tennis player returns a serve, conditions are different from those the player has experienced in the past: the ball is travelling at a slightly different speed, or at a different angle, or with a different rotation. Yet, the nervous system is able to generate a response that is effective under these novel conditions. How is this possible? This project will address this question by combining new mathematical methods with a novel experimental system that uses real-time computer vision to track animals as they solve sequential decision tasks. As part of the broader impacts of the study, the investigators will partner with an undergraduate education program intended to introduce research opportunities to traditionally underrepresented STEM students. Interdisciplinary teams of students will be mentored in developing and executing small research projects related to the theme of the larger project with the goal providing a gateway for both basic science majors, and also engineering and mathematics majors into cutting-edge, interdisciplinary science. In addition, the investigators will incorporate this research when mentoring participants in the University of Florida's longstanding Whitney Lab REU program (31 years). The results of this work will shed light on how animals generate such a diverse range of behaviors to survive in novel situations, and will lead to new questions and approaches that can be used to understand the function of the vertebrate nervous system and the origins of behavioral control in some of the most important tasks animals undertake.Unlike binary choice tasks, which have long served as the model for animal decision-making, more complex sensory-motor behaviors such as avoiding predators or capturing prey often involve sequences of decisions made in response to dynamic streams of sensory stimuli. A key requirement of such behaviors is that they be robust. For example, the exact chain of decisions required to escape a predator will differ from one setting to another, yet an animal must generate a sequence of responses uniquely suited to the situation at hand. This highlights a perennial question about animal behavior: how can behaviors that are learned or evolved in one context generalize to the enormous set of possible situations an animal might encounter? This project attacks this question using a combination of mathematical modeling and high-resolution, closed loop experiments using the prey attack and predator evasion behaviors of rainbow trout (Oncorhynchus mykiss) as a model for studying how animals generate flexible, robust behavioral sequences. In particular, the investigators will test the emerging hypothesis that these robust, higher-level behavioral responses are achieved through a mechanism called behavioral gain control. Research will explore how behavioral gain control is involved in initiating behavioral sequences at the right time, balancing multiple competing objectives, coordinating control along multiple behavioral dimensions (e.g., acceleration, turning), and maintaining performance across changing environmental conditions. This work has the potential to shed new light on how complex behaviors are generated in the context of ecologically and evolutionarily relevant tasks.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.