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

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
批准号:
1555643
负责人:
Lucia Jacobs
金额:
$78.09万
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
项目状态:
已结题
起止时间:
2015-11-01 至 2021-06-30

项目摘要

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中文摘要
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英文摘要
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).
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DISSERTATION RESEARCH: The Consequences of Food Assessment and Cache Placement on Social Competition and Cache Pilfering in a Scatter-hoarding Tree Squirrel
  • 批准号:
    1501892
  • 项目类别:
    Standard Grant
  • 资助金额:
    $2.04万
  • 财政年份:
    2015
  • 负责人:
    Lucia Jacobs
  • 依托单位:
CAA: Comparative Studies of Spatial and Nonspatial Memory inMammals
  • 批准号:
    9307317
  • 项目类别:
    Standard Grant
  • 资助金额:
    $5.0万
  • 财政年份:
    1993
  • 负责人:
    Lucia Jacobs
  • 依托单位:
PRF: Behavioral and Morphological Adaptations of Heteromyid Rodents to a Variable Environment
  • 批准号:
    8800271
  • 项目类别:
    Fellowship Award
  • 资助金额:
    $5.28万
  • 财政年份:
    1989
  • 负责人:
    Lucia Jacobs
  • 依托单位:
NATO Postdoctoral Fellow
  • 批准号:
    8651707
  • 项目类别:
    Standard Grant
  • 资助金额:
    $2.2万
  • 财政年份:
    1986
  • 负责人:
    Lucia Jacobs
  • 依托单位:
国内基金
海外基金
Research on Quantum Field Theory without a Lagrangian Description
  • 批准号:
    24ZR1403900
  • 项目类别:
    省市级项目
  • 资助金额:
    --
  • 批准年份:
    2024
  • 负责人:
    SATOSHI NAWATA
  • 依托单位:
Cell Research
Cell Research
Cell Research (细胞研究)