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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

基本信息

批准号：
1631787
负责人：
Barry Ache
金额：
$ 35.79万
依托单位：
University of Florida
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2016
资助国家：
美国
起止时间：
2016-09-01 至 2020-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1631787&HistoricalAwards=false
关键词：
Collaborative Research NCS FO Computational

项目摘要

Most animals survive in turbulent air or water environments and are living proof that it is possible to quantify odor signals in complex turbulent flow conditions to track and find sources of odors (such as food, mates, etc.). However, our engineering knowledge is still incapable of formulating simple and effective measurements that will enable man-made systems to predict, navigate and utilize properties of this turbulent flow to locate sources of chemical release. This project builds on recent exciting computational modeling of the neurobiology of organisms by the proposers, which predict that lobsters are capable of estimating not only the concentration of odors but also the time since the last odor was encountered. Lobsters accomplish this by using ensemble competition across a population of olfactory receptor neurons (ORNs), called "bursting ORNs". Bursting ORNs function to compute the time since last encounter of an odor that, along with concentration, can provide a measure of the distance to the odor source. This research will seek to increase understanding of how ORNs perceive odor concentration and intermittency measured within an odor plume, and how this information is integrated within the lobster?s brain. An additional goal is to develop new neurobiology-based theories in the search for odor sources that can be implemented within human-engineered autonomous underwater vehicles that have the ability to navigate in turbulent chemical plumes.The broader implications of this work stem from the large potential market for defense and civilian applications of a new generation of electronic noses for tracking chemicals in natural or man-initiated disasters. Through this project, there are also excellent resources and outreach opportunities for integrated education and training of students at the intersection of fluid dynamics, neuroscience, computer engineering and information processing. Outreach will be coordinated through the Center of Innovative Brain Machine Interfaces at the University of Florida and will provide opportunities for undergraduate and graduate research, promote neurotechnology innovations, and foster entrepreneurship activities in order to create potential future start-up companies.The research will include laboratory experiments of chemical plume mixing and ORN responses to odor encounters by lobsters, theoretical analysis of search optimization, as well as numerical simulations and novel system architecture for electronic noses. This research brings together a multidisciplinary and complementary team of experts, including a fluid dynamicist, a neurobiologist, and an electrical engineer with the very clear goal of understanding and exploiting olfactory scene analysis in turbulent flow. In this new light, neurobiologists will understand new sensing strategies for olfaction, and engineers can improve the quantification of turbulent mixing and replicate these sensory strategies to propose novel bio-inspired sensors capable of quantifying the dispersion of chemical plumes and improve the search for the source.

大多数动物在湍流空气或水环境中生存，并且是可以在复杂湍流条件下量化气味信号以跟踪和找到气味来源（例如食物，配偶等）的活生生的证据。然而，我们的工程知识仍然无法制定简单有效的测量方法，使人造系统能够预测，导航和利用这种湍流的特性来定位化学释放的来源。该项目建立在最近令人兴奋的生物体神经生物学计算模型的基础上，该模型预测龙虾不仅能够估计气味的浓度，还能够估计自上次遇到气味以来的时间。龙虾通过在一群嗅觉受体神经元（ORN）之间使用整体竞争来实现这一点，称为“爆裂ORN”。Bursting ORN用于计算自上次遇到气味以来的时间，其沿着浓度，可以提供到气味源的距离的测量。这项研究将寻求增加对ORN如何感知气味浓度和气味羽流内测量的气味浓度的理解，以及这些信息如何整合到龙虾中？的大脑。另一个目标是发展新的神经生物学为基础的理论，在寻找气味源，可以在人类工程的自主水下航行器，有能力在动荡的化学羽流中航行。这项工作的更广泛的影响源于巨大的潜在市场的国防和民用应用的新一代电子鼻跟踪化学品在自然或人为引发的灾难。通过这个项目，也有很好的资源和推广机会，在流体动力学，神经科学，计算机工程和信息处理的交叉点的学生的综合教育和培训。该项目将通过佛罗里达大学的创新脑机接口中心进行协调，并将为本科生和研究生提供研究机会，促进神经技术创新，培养创业活动，以创建潜在的未来初创公司。该研究将包括化学羽流混合和ORN对龙虾气味的反应的实验室实验，搜索优化的理论分析，以及数值模拟和电子鼻的新系统架构。这项研究汇集了一个多学科和互补的专家团队，包括流体动力学家，神经生物学家和电气工程师，其目标非常明确，即理解和利用湍流中的嗅觉场景分析。在这种新的视角下，神经生物学家将理解嗅觉的新传感策略，工程师可以改进湍流混合的量化，并复制这些传感策略，以提出能够量化化学羽流分散的新型生物启发传感器，并改进对源的搜索。