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

合作研究:嗅觉导航:自然环境中的动态计算

基本信息

  • 批准号:
    1555916
  • 负责人:
  • 金额:
    $ 181.85万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2015
  • 资助国家:
    美国
  • 起止时间:
    2015-11-01 至 2020-10-31
  • 项目状态:
    已结题

项目摘要

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).
该项目由美国国家科学基金会“破解嗅觉密码”创意实验室开发,由物理部生命系统物理学项目、数学科学部数学生物学项目、化学部生命过程化学项目和综合有机系统部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,将使人们更好地了解动物如何在现实世界中利用嗅觉导航。从苍蝇到老鼠再到狗,几乎所有的动物都利用气味来寻找重要的资源,比如食物、住所和配偶。迄今为止,没有任何工程设备可以复制这种功能,了解大脑使用的代码将导致许多新颖的应用。破译密码,从神经密码到二战的恩尼格玛密码,都需要深入了解正在传输的信息的内容,以及它们将如何被预期的接收者使用。为了破解嗅觉密码,研究小组将重点研究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,以及它们在朝着目标前进时如何利用运动来增强这些线索。提议的工作包括气味羽流的物理测量,动物通过嗅觉环境路径的行为测量,嗅觉导航过程中神经活动的电生理和光学测量,通过虚拟现实对环境的扰动,通过遗传学对神经元硬件的扰动,以及多层次数学建模。pi将与本科生、研究生和博士后一起教学和工作,特别是从科学领域代表性不足的群体中招募学生。该项目的结果可能会改进爆炸物探测方法,新的嗅觉机器人取代训练有素的动物,并在机器人控制方面取得新的理论基础进展。该项目将为开发干扰飞虫(包括病媒和作物害虫)定位其气味目标的能力的技术提供信息,从而为开发“绿色”技术来解决具有全球经济和人道主义重要性的问题打开一扇新的大门。这个建议是实验室实验和计算模型的协同结合,将探索动物如何利用嗅觉在其环境中导航。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)产生和量化可用于对导航策略进行经验和理论测试的标准化、自然的气味环境;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执行这些过程的假定神经回路,确定导航气味线索是如何在神经系统中编码和使用的;(iv)操纵嗅觉环境和神经回路,以评估模型的鲁棒性。与以往研究嗅觉导航的尝试不同,目前的研究重点是生物学上可行的机制,并探索了动物成功导航的时间和空间尺度。该项目将产生对理论生物学和数学、工程学(流体力学、电子嗅觉和机器人)和生物学(神经科学、生态学和进化)的科学家立即使用和重要的数据集。

项目成果

期刊论文数量(3)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Olfactory navigation in the real world: Simple local search strategies for turbulent environments
现实世界中的嗅觉导航:针对动荡环境的简单本地搜索策略
  • DOI:
    10.1016/j.jtbi.2021.110607
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    2
  • 作者:
    Hengenius, James B.;Connor, Erin G.;Crimaldi, John P.;Urban, Nathaniel N.;Ermentrout, G. Bard
  • 通讯作者:
    Ermentrout, G. Bard
Information-theoretic analysis of realistic odor plumes: What cues are useful for determining location?
  • DOI:
    10.1371/journal.pcbi.1006275
  • 发表时间:
    2018-07
  • 期刊:
  • 影响因子:
    4.3
  • 作者:
    Boie SD;Connor EG;McHugh M;Nagel KI;Ermentrout GB;Crimaldi JP;Victor JD
  • 通讯作者:
    Victor JD
The Dynamics of Bilateral Olfactory Search and Navigation
  • DOI:
    10.1137/19m1265934
  • 发表时间:
    2021-03-01
  • 期刊:
  • 影响因子:
    10.2
  • 作者:
    Riman, Nour;Victor, Jonathan D.;Ermentrout, Bard
  • 通讯作者:
    Ermentrout, Bard
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Nathan Urban其他文献

Julia for HPC: In Situ Data Analysis with Julia for Climate Simulations at Large Scale
Julia for HPC:使用 Julia 进行大规模气候模拟的现场数据分析
  • DOI:
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Li Tang;Soumya Dutta;Natalie Klein;Wayne Wang;Jonathan D. Wolfe;Luke Van Roekel;Nathan Urban;Ayan Biswas;Earl Lawrence
  • 通讯作者:
    Earl Lawrence

Nathan Urban的其他文献

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{{ truncateString('Nathan Urban', 18)}}的其他基金

CRCNS US-Israel Research Proposal: Understanding single neuron computation by combining biophysical and statistical models
CRCNS 美国-以色列研究提案:通过结合生物物理和统计模型来理解单神经元计算
  • 批准号:
    1622977
  • 财政年份:
    2015
  • 资助金额:
    $ 181.85万
  • 项目类别:
    Standard Grant
Patriot League Institutions Mentor Associate Professors WISEly
爱国者联盟机构导师WISEly副教授
  • 批准号:
    1464048
  • 财政年份:
    2015
  • 资助金额:
    $ 181.85万
  • 项目类别:
    Standard Grant
CRCNS US-Israel Research Proposal: Understanding single neuron computation by combining biophysical and statistical models
CRCNS 美国-以色列研究提案:通过结合生物物理和统计模型来理解单神经元计算
  • 批准号:
    1430208
  • 财政年份:
    2014
  • 资助金额:
    $ 181.85万
  • 项目类别:
    Standard Grant
Collaborative Research in Computational Neuroscience (CRCNS) PI Meeting 2009
2009 年计算神经科学合作研究 (CRCNS) PI 会议
  • 批准号:
    0940728
  • 财政年份:
    2009
  • 资助金额:
    $ 181.85万
  • 项目类别:
    Standard Grant

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  • 项目类别:
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Collaborative Research: Olfactory learning and neuromodulation in the Aedes aegypti mosquito
合作研究:埃及伊蚊的嗅觉学习和神经调节
  • 批准号:
    2242603
  • 财政年份:
    2023
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CRCNS Research Proposal: Collaborative Research: Mechanisms and dynamics of retronasal olfactory coding
CRCNS 研究提案:合作研究:鼻后嗅觉编码的机制和动力学
  • 批准号:
    1912320
  • 财政年份:
    2019
  • 资助金额:
    $ 181.85万
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    Standard Grant
CRCNS Research Proposal: Collaborative Research: Mechanisms and dynamics of retronasal olfactory coding
CRCNS 研究提案:合作研究:鼻后嗅觉编码的机制和动力学
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CRCNS Research Proposal: Collaborative Research: Mechanisms and dynamics of retronasal olfactory coding
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Collaborative Research: NCS-FO: A Computational Neuroscience Framework for Olfactory Scene Analysis within Complex Fluid Environments
合作研究:NCS-FO:复杂流体环境中嗅觉场景分析的计算神经科学框架
  • 批准号:
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Collaborative Research: Olfactory Navigation: Dynamic Computing in the Natural Environment
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