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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：
1631864
负责人：
Matthew Reidenbach
金额：
$ 24.92万
依托单位：
University of Virginia Main Campus
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 2021-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1631864&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 major objective 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. This work will enhance 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.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. 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 with the goal of equipping autonomous underwater vehicles with the ability to navigate in turbulent chemical plumes. This will increase our understanding of how bursting olfactory neuron responses are exploited by the olfactory lobe, the first olfactory relay, and how this information is integrated with the odor specific information in the olfactory bulb. Moreover, this work will enhance our understanding of turbulent plume dynamics in order to develop a new neurobiology-based theory in the search for odor sources. Using information obtained from a large-scale plume, the researchers will use the olfactory organs of the lobster as a model system to understand the physical constraints placed on these chemosensors and examine the role of spatial and temporal relationships of odor inputs in the excitation of olfactory receptor neurons. The work will provide a conceptual substrate for olfactory scene analysis informed by neurobiology, which is still in its infancy compared with vision and audition.

大多数动物在湍急的空气或水环境中存活，是可以在复杂的湍流条件下量化气味信号以跟踪和找到气味来源(如食物、配偶等)的活生生的证据。然而，我们的工程知识仍然不能制定简单而有效的测量方法，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排放源。该项目建立在发起人最近对生物体神经生物学进行的令人兴奋的计算模型的基础上，该模型预测，龙虾不仅能够估计气味的浓度，而且能够估计自最后一次遇到气味以来的时间。龙虾通过在一群嗅觉感受器神经元(ON)之间进行整体竞争来实现这一点，这种ON被称为“爆裂ON”。爆破角功能可以计算自上次遇到气味以来的时间，与浓度一起，可以提供到气味来源的距离的测量。这项研究将寻求增加对龙虾如何感知气味浓度和气味羽流中测量的间歇性的理解，以及这些信息如何整合到龙虾的大脑中。另一个主要目标是在寻找气味来源方面开发基于神经生物学的新理论，这些气味来源可以在人类工程的自动水下机器人中实施，这些水下机器人能够在湍急的化学羽流中导航。这项工作将加强新一代电子鼻在自然灾害或人为灾害中跟踪化学品的国防和民用应用。通过该项目，还为流体动力学、神经科学、计算机工程和信息处理等学科的学生进行综合教育和培训提供了极好的资源和外展机会。外展将通过佛罗里达大学创新脑机接口中心进行协调，将为本科生和研究生提供研究机会，促进神经技术创新，并促进创业活动，以创造潜在的未来创业公司。这项研究汇集了一支多学科和互补的专家团队，包括一名流体动力学家、一名神经生物学家和一名电气工程师，他们的目标非常明确，即理解和利用湍流中的嗅觉场景分析。这项研究将包括化学羽流混合和ORN对龙虾气味的响应的实验室实验，搜索优化的理论分析，以及电子鼻的数值模拟和新颖的系统架构，目的是使自主水下航行器能够在湍急的化学羽流中导航。这将增加我们对嗅叶(第一个嗅觉继电器)如何利用爆发性嗅觉神经元反应的理解，以及这些信息如何与嗅球中的气味特定信息相结合。此外，这项工作将加深我们对湍流羽流动力学的理解，以便发展一种新的基于神经生物学的理论来寻找气味来源。利用从大规模羽流中获得的信息，研究人员将以龙虾的嗅觉器官作为模型系统，了解施加在这些化学传感器上的物理限制，并检查气味输入的空间和时间关系在嗅觉感受器神经元兴奋中的作用。这项工作将为神经生物学提供嗅觉场景分析的概念基础，与视觉和听觉相比，神经生物学仍处于起步阶段。