NeuroNex: From Odor to Action: Discovering Principles of Olfactory-Guided Natural Behavior

NeuroNex：从气味到行动：发现嗅觉引导自然行为的原理

• 批准号: 2014217
• 负责人: John Crimaldi
• 金额: $ 1700万
• 依托单位: University of Colorado at Boulder
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2014217&HistoricalAwards=false
• 关键词: NeuroNex; Odor; Action; Discovering; Principles

The Odor2Action network consists of 16 investigators from 16 research institutions in the United States, the United Kingdom, and Canada. The composition and scientific goals of the effort are designed to leverage prior investments in neurotechnologies funded by the BRAIN Initiative, other domestic agencies and international partners. Specifically, Odor2Action will address a central question of neuroscience: How do animals use information from odor stimuli in their environment to guide natural behaviors? To synergistically study this problem, the network is subdivided into three interdisciplinary research groups (IRGs); each IRG contains experts in a wide range of experimental and theoretical approaches, and investigates how similar problems are solved by nervous systems in phylogenetically diverse species. IRG1 will test a novel framework for organizing olfactory stimulus space and olfactory codes around the statistical relationships among natural odors. IRG2 will work to understand how neural circuits translate odor signals into dynamic and adaptive behaviors, a critical component of our overall network goal of understanding how natural odors trigger natural behaviors. IRG3 will investigate the physical structure of odor environments and how animal motion and sensory capabilities interact with those environments to detect, discriminate and localize odor objects. Collectively, the network will determine how neural representations of odor are generated, how they are progressively reformatted across successive circuit layers, and how they support useful behaviors. While focusing on olfaction, this project will provide broad and fundamental insights into brain function. This compact circuit architecture associated with olfaction offers unique opportunities to achieve an end-to-end understanding of the core computational logic by which various brains organize and read out such high-dimensional, discrete variables to generate adaptive behaviors. This coordinated project on the neuroscience of olfaction across species will have important societal impacts in science, technology, health, and policy. Given the complexity and high dimensionality of chemical space and its primacy in driving behavior among most species, studying how odor leads to action promises to provide insight into optimal biological solutions for encoding complex information about the external world. Elucidating biological solutions to olfaction can inform the development of algorithms and engineered devices for detection and identification of chemicals in applications that span the range from homeland security to food safety.The Odor2Action network will address a central question of neuroscience: How do animals use information from odor stimuli in their environment to guide natural behaviors? The network will approach this problem in the context of olfactory-guided behavior as an instance of a much more general problem of many complex brain systems - how are high-dimensional, discrete, and combinatorial variables that are not simply ordered along easily discernible axes represented in brain circuits and mapped to actions? The compact olfactory circuit architecture offers unique opportunities to achieve an end-to-end understanding of the core computational logic by which brains organize and read out such high-dimensional, discrete variables to generate adaptive behaviors. This network will study olfactory systems of mammals and insects, which have independently evolved common structural elements at successive levels of olfactory processing in their central nervous systems. These common elements possibly reflect convergent evolution towards a set of similar solutions to shared olfactory problems. The network comprises three interdisciplinary research groups (IRGs) that are designed around specific elements of an end-to-end investigation of olfaction. IRG1 aims to understand the first stages of how neural representations of odor are generated, and how they are progressively reformatted across successive circuit layers to support meaningful behaviors. IRG2 aims to understand how neural circuits translate odor signals into dynamic and adaptive behaviors, a critical component of our overall network goal of understanding how natural odors trigger natural behaviors. IRG3 will investigate the physical structure of odor environments and how animal motion and sensory capabilities interact with those environments to detect, discriminate and localize odor objects. Each IRG integrates theory and experimental approaches in two or more species in ways that produce complementary, synergistic interactions across levels of biological analysis. This Neuronex award is co-funded by the Division of Emerging Frontiers and the Behavioral Systems Cluster within the Directorate for Biological Sciences, the Office of Advanced Cyberinfrastructure within the Directorate for Computer and Information Sciences, the Mathematical Biology Program and the Physics of Living Systems Program within the Directorate for Mathematical and Physical Sciences, as part of the BRAIN Initiative and NSF's Understanding the Brain activities.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.

Odor 2Action网络由来自美国、英国和加拿大16个研究机构的16名研究人员组成。这项工作的组成和科学目标旨在利用由BRAIN Initiative，其他国内机构和国际合作伙伴资助的神经技术的先前投资。具体来说，Odor 2Action将解决神经科学的一个核心问题：动物如何使用来自环境中气味刺激的信息来指导自然行为？为了协同研究这个问题，该网络被细分为三个跨学科研究小组（IRG）;每个IRG都包含广泛的实验和理论方法的专家，并研究神经系统如何解决类似的问题。IRG 1将测试一种新的框架，用于围绕自然气味之间的统计关系组织嗅觉刺激空间和嗅觉代码。IRG 2将致力于了解神经回路如何将气味信号转化为动态和自适应行为，这是我们理解自然气味如何触发自然行为的整体网络目标的关键组成部分。IRG 3将研究气味环境的物理结构，以及动物的运动和感觉能力如何与这些环境相互作用，以检测，区分和定位气味对象。总的来说，该网络将确定气味的神经表征是如何生成的，它们如何在连续的电路层中逐渐重新格式化，以及它们如何支持有用的行为。在专注于嗅觉的同时，该项目将提供对大脑功能的广泛和基本的见解。这种与嗅觉相关的紧凑电路架构提供了独特的机会，可以实现对核心计算逻辑的端到端理解，各种大脑通过这种核心计算逻辑组织和读出这种高维离散变量，以产生自适应行为。这个关于跨物种嗅觉神经科学的协调项目将在科学，技术，健康和政策方面产生重要的社会影响。鉴于化学空间的复杂性和高维性，以及它在大多数物种中驱动行为的首要地位，研究气味如何导致行动，有望为编码有关外部世界的复杂信息提供最佳生物解决方案。阐明嗅觉的生物解决方案可以为从国土安全到食品安全等应用中化学物质检测和识别的算法和工程设备的开发提供信息。Odor 2Action网络将解决神经科学的一个核心问题：动物如何使用来自气味的信息刺激他们的环境来指导自然行为？该网络将在嗅觉引导行为的背景下处理这个问题，作为许多复杂大脑系统的一个更普遍问题的实例--高维、离散和组合的变量，不是简单地沿着沿着容易识别的轴排列，它们是如何在大脑回路中表示并映射到动作的？紧凑的嗅觉电路架构提供了独特的机会，以实现对核心计算逻辑的端到端理解，大脑通过该核心计算逻辑组织和读出这种高维离散变量以产生自适应行为。该网络将研究哺乳动物和昆虫的嗅觉系统，这些系统在其中枢神经系统的嗅觉处理的连续水平上独立进化出共同的结构元件。这些共同的元素可能反映了趋同的进化，朝着一套类似的解决方案，共同的嗅觉问题。该网络由三个跨学科研究小组（IRG）组成，这些小组围绕嗅觉端到端调查的特定元素而设计。IRG 1旨在了解气味的神经表征如何产生的第一阶段，以及它们如何在连续的电路层中逐渐重新格式化以支持有意义的行为。IRG 2旨在了解神经回路如何将气味信号转化为动态和适应性行为，这是我们理解自然气味如何触发自然行为的整体网络目标的关键组成部分。IRG 3将研究气味环境的物理结构，以及动物的运动和感觉能力如何与这些环境相互作用，以检测，区分和定位气味对象。每个IRG将理论和实验方法集成在两个或更多个物种中，以产生跨生物分析水平的互补，协同相互作用的方式。这个Neuronex奖是由生物科学理事会内的新兴前沿和行为系统集群部门，计算机和信息科学理事会内的高级网络基础设施办公室，数学生物学计划和数学物理科学理事会内的生命系统计划物理共同资助的，该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Drift in a popular metal oxide sensor dataset reveals limitations for gas classification benchmarks

• DOI: 10.1016/j.snb.2022.131668
• 发表时间: 2022-03-15
• 期刊: SENSORS AND ACTUATORS B-CHEMICAL
• 影响因子: 8.4
• 作者: Dennler, Nik;Rastogi, Shavika;Schmuker, Michael
• 通讯作者: Schmuker, Michael

Decoding the olfactory map through targeted transcriptomics links murine olfactory receptors to glomeruli.

• DOI: 10.1038/s41467-022-32267-3
• 发表时间: 2022-09-01
• 期刊: NATURE COMMUNICATIONS
• 影响因子: 16.6
• 作者: Zhu, Kevin W.;Burton, Shawn D.;Nagai, Maira H.;Silverman, Justin D.;de March, Claire A.;Wachowiak, Matt;Matsunami, Hiroaki
• 通讯作者: Matsunami, Hiroaki

Odor encoding by signals in the olfactory bulb

• DOI: 10.1152/jn.00449.2022
• 发表时间: 2023-02-01
• 期刊: JOURNAL OF NEUROPHYSIOLOGY
• 影响因子: 2.5
• 作者: Verhagen，Justus V.;Baker，Keeley L.;Rolls，Edmund T.
• 通讯作者: Rolls，Edmund T.

Information about space from time: how mammals navigate the odour landscape

时间与空间的信息：哺乳动物如何驾驭气味景观

• DOI: 10.1515/nf-2022-0006
• 发表时间: 2022
• 期刊: Neuroforum
• 作者: Ackels T

A topological approach to inferring the intrinsic dimension of convex sensing data

推断凸传感数据内在维度的拓扑方法

• DOI: 10.1007/s41468-021-00081-3
• 发表时间: 2021
• 期刊: Journal of Applied and Computational Topology
• 作者: Wu, Min-Chun;Itskov, Vladimir
• 通讯作者: Itskov, Vladimir