Collaborative Research: Olfactory Navigation: Dynamic Computing in the Natural Environment

该项目是在NSF的想法实验室开发的“破解嗅觉密码”，并由物理学系的生命系统物理学计划，数学科学系的数学生物学计划，化学系的生命过程化学计划和综合有机系统系的神经系统集群共同资助。该项目是实验室实验和计算机建模的协同结合，将导致更好地了解动物如何使用嗅觉在真实的世界中导航。从苍蝇到老鼠再到狗，几乎所有的动物都利用气味来寻找关键资源，如食物、住所和配偶。到目前为止，还没有工程设备可以复制这种功能，理解大脑使用的代码将导致许多新的应用。破解代码，从神经代码到第二次世界大战的Enigma代码，都需要深入了解正在传输的消息的内容以及它们将如何被预期的接收者使用。为了破解嗅觉密码，该团队将专注于气味如何在景观中移动，动物如何从气味景观中提取空间和时间线索，以及它们如何在朝着目标前进的同时利用运动来增强这些线索。拟议的工作包括气味羽流的物理测量，动物通过嗅觉环境的路径的行为测量，嗅觉导航过程中神经活动的电生理和光学测量，通过虚拟现实环境的扰动和通过遗传学的神经元硬件，以及多级数学建模。PI将与本科生，研究生和博士后学生一起教学和工作，特别是从科学领域代表性不足的群体中招收学生。该项目的结果可能会带来爆炸物检测方法的改进、取代训练有素动物的新嗅觉机器人以及机器人控制方面新的理论基础进步。该项目将为干扰飞行昆虫（包括疾病媒介和作物害虫）定位其气味目标的能力的技术开发提供信息，从而为开发“绿色”技术打开新的大门，以解决具有全球经济和人道主义重要性的问题。这个提议是实验室实验和计算建模的协同结合，将探索动物如何使用嗅觉在环境中导航。具体而言，这项工作旨在通过以下目标解决嗅觉导航的难题：（i）生成和量化标准化的，自然的气味环境，可用于执行导航策略的经验和理论测试;（ii）通过不同动物物种的行为实验确定气味引导导航的现象学算法;（iii）通过记录神经元数据和模拟实现这些过程的假定神经回路，确定用于导航的气味线索如何在神经系统中编码和使用;（iv）操纵嗅觉环境和神经回路，以评估模型的鲁棒性。与以前试图了解嗅觉导航相反，本策略强调生物学上可行的机制，并探索了动物成功导航的广泛的时间和空间尺度。该项目将生成对理论生物学和数学、工程学（流体力学、电子嗅觉和机器人技术）和生物学（神经科学、生态学和进化）科学家立即使用和重要的数据集。

This project was developed at an NSF Ideas Lab on "Cracking the Olfactory Code" and is jointly funded by the Physics of Living Systems program in the Physics Division, the Mathematical Biology program in the Division of Mathematical Sciences, the Chemistry of Life Processes program in the Chemistry Division, and the Neural Systems Cluster in the Division of Integrative Organismal Systems. The project is a synergistic combination of laboratory experiments and computer modeling that will lead to better understanding of how animals use the sense of smell to navigate in the real world. Almost universally, from flies to mice to dogs, animals use odors to find critical resources, such as food, shelter, and mates. To date, no engineered device can replicate this function and understanding the code used by the brain will lead to many novel applications. Cracking codes, from neural codes to the Enigma code of WWII, is aided by a deep understanding of the content of messages that are being transmitted and how they will be used by their intended receivers. To crack the olfactory code, the team will focus on how odors move in landscapes, how animals extract spatial and temporal cues from odor landscapes, and how they use movement for enhancing these cues while progressing towards their targets. The proposed work encompasses physical measurement of odor plumes, behavioral measurement of animals' paths through olfactory environments, electrophysiological and optical measurement of neural activity during olfactory navigation, perturbations of the environment via virtual reality and of neuronal hardware via genetics, and multilevel mathematical modeling. The PIs will teach and work with undergraduate, graduate and postdoctoral students and especially recruit students from underrepresented groups in science. The project's results may lead to improved methods for the detection of explosives, new olfactory robots to replace trained animals, and new theoretically-grounded advances in robotic control. The project will inform the development of technologies that interfere with the ability of flying insects (including disease vectors and crop pests) to locate their odor target, thus opening a new door for developing 'green' technologies to solve problems that are of global economic and humanitarian importance. This proposal is a synergistic combination of laboratory experiments and computational modeling that will probe how animals use olfaction to navigate in their environment. Specifically, this effort seeks to solve the difficult problem of olfactory navigation through the following aims: (i) Generate and quantify standardized, naturalistic odor environments that can be used to perform empirical and theoretical tests of navigation strategies; (ii) Determine phenomenological algorithms for odor-guided navigation through behavioral experiments in diverse animal species; (iii) Determine how odor cues for navigation are encoded and used in the nervous system by recording neuronal data and simulating putative neural circuits that implement these processes; (iv) Manipulate olfactory environments and neural circuitry, to evaluate model robustness. In contrast to previous attempts to understand olfactory navigation, the present strategy emphasizes mechanisms that are biologically feasible and explores the wide range of temporal and spatial scales in which animals successfully navigate. The project will generate datasets of immediate use and importance to scientists in theoretical biology and mathematics, engineering (fluid mechanics, electronic olfaction, and robotics) and biology (neuroscience, ecology and evolution).