Flight Stability and Neural Feedback Control in Genetically Modified Flies

转基因果蝇的飞行稳定性和神经反馈控制

基本信息

  • 批准号:
    2013934
  • 负责人:
  • 金额:
    $ 41.96万
  • 依托单位:
  • 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 2024-08-31
  • 项目状态:
    已结题

项目摘要

There is a new momentum in efforts across many fields to understand animal behavior, prompted by the new technology in acquiring large sets of behavioral data and the advancement in neural-genetics. Much needed is the development of sophisticated quantitive models that can explain behavior and can make testable predictions. Finding out how we can start from basic physical laws to explain parts of neural behavior of insect flight is the central theme of the proposed work. Insects were the first that evolved to fly, and to fly is not to fall. Understanding what insects must do so as not to fall provides a pathway to probe the connection between physics of flight and the neural feedback control. This project will test the PI's conjecture on the role of fly’s steering muscle on flight stability, using genetically modified fruit flies. In addition to experiments, the PI will construct computational models that can predict the observed free flight behavior of both intact and genetically modified flies. The proposed work will consist three core parts: 1) 3D tracking of free flight with high resolution, 2) computational studies of control algorithms, and 3) understanding the control and muscle activity by constructing effective models that can explain the experiments. The field of biology is dominated by experimental studies. This key contribution is the development of new methods for analyzing complex biological systems. The work will raise new questions and have a direct impact on research in physics of living organisms, mathematical modeling, neural science, entomology, evolutionary biology, and robotics. The proposed work offers an excellent opportunity for students to engage in interdisciplinary work. The findings on how nature works will provide a compelling case for sharing the value of basic science with the general public.The proposed work is fundamentally about integrating the physics of flight into our understanding of the neural circuitries for control. Direct neural recordings of flight circuitries require insects to be tethered. One challenge is to connect the internal control algorithms to the free flight behavior. Another challenge is to disentangle different control feedback schemes in intact flies. Using genetically modified flies with specified motor-neurons silenced allows us to single out the function of individual steering muscle. Analyses of the flight reflexes in intact and genetically modified flies will further lead to new models for control schemes that underlie the mechano-sensory feedback for flight equilibrium. This work will be the first to combine computational modeling of free flight with the progress in neuro-genetics to decipher a fly’s equilibrium reflex in free flight. The work will offer a new pathway for flight behavior guided by quantitive predictions, in addition to direct observations.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.
在获取大量行为数据的新技术和神经遗传学的进步的推动下,许多领域都在努力理解动物行为。目前迫切需要的是开发复杂的定量模型,以解释行为并做出可检验的预测。研究如何从基本的物理定律出发来解释昆虫飞行的部分神经行为是这项工作的中心主题。昆虫是最先进化出会飞的动物,而会飞并不意味着会掉下来。了解昆虫必须做什么才能不坠落,为探索飞行物理学和神经反馈控制之间的联系提供了一条途径。该项目将使用转基因果蝇来验证PI关于果蝇操纵肌肉在飞行稳定性中的作用的猜想。除了实验之外,PI还将构建计算模型,以预测观察到的完整和转基因果蝇的自由飞行行为。提出的工作将包括三个核心部分:1)高分辨率自由飞行的3D跟踪,2)控制算法的计算研究,以及3)通过构建可以解释实验的有效模型来理解控制和肌肉活动。生物学领域以实验研究为主。这一关键贡献是开发了分析复杂生物系统的新方法。这项工作将提出新的问题,并对生物体物理学、数学建模、神经科学、昆虫学、进化生物学和机器人技术的研究产生直接影响。建议的工作为学生从事跨学科工作提供了一个极好的机会。关于自然如何运作的发现将为与公众分享基础科学的价值提供一个令人信服的案例。这项提议的工作基本上是将飞行的物理原理整合到我们对控制神经回路的理解中。对飞行回路的直接神经记录需要把昆虫拴起来。其中一个挑战是将内部控制算法与自由飞行行为联系起来。另一个挑战是在完整的果蝇中解开不同的控制反馈方案。使用特定运动神经元沉默的转基因果蝇使我们能够单独找出单个转向肌的功能。对完整和转基因果蝇的飞行反射的分析将进一步导致新的控制方案模型,这些模型是飞行平衡的机械-感觉反馈的基础。这项工作将首次将自由飞行的计算模型与神经遗传学的进展结合起来,以破译苍蝇在自由飞行中的平衡反射。除了直接观察外,这项工作将为定量预测指导的飞行行为提供一条新的途径。该奖项反映了美国国家科学基金会的法定使命,并通过使用基金会的知识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

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Z. Jane Wang其他文献

APDF: An active preference-based deep forest expert system for overall survival prediction in gastric cancer
  • DOI:
    https://doi.org/10.1016/j.eswa.2023.123131
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
  • 作者:
    Qiucen Li;Yuheng Wang;Zedong Du;Qiu Li;Weihan Zhang;Fangming Zhong;Z. Jane Wang;Zhikui Chen
  • 通讯作者:
    Zhikui Chen
emSleeping Beauty/em mRNA-LNP enables stable rAAV transgene expression in mouse and NHP hepatocytes and improves vector potency
Emsleeping Beauty/EM MRNA-LNP在小鼠和NHP肝细胞中启用稳定的RAAV转基因表达,并改善矢量效力
  • DOI:
    10.1016/j.ymthe.2024.06.021
  • 发表时间:
    2024-10-02
  • 期刊:
  • 影响因子:
    12.000
  • 作者:
    Philip M. Zakas;Sharon C. Cunningham;Ann Doherty;Eva B. van Dijk;Raed Ibraheim;Stephanie Yu;Befikadu D. Mekonnen;Brendan Lang;Elizabeth J. English;Gang Sun;Miles C. Duncan;Matthew S. Benczkowski;Robert C. Altshuler;Malvenderjit Jagjit Singh;Emily S. Kibbler;Gulen Y. Tonga;Zi Jun Wang;Z. Jane Wang;Guangde Li;Ding An;William E. Salomon
  • 通讯作者:
    William E. Salomon
ESCAPE: Energy-based Selective Adaptive Correction for Out-of-distribution 3D Human Pose Estimation
逃逸:基于能量的离群 3D 人体姿态估计的选择性自适应校正
  • DOI:
    10.1016/j.neucom.2024.128605
  • 发表时间:
    2025-01-01
  • 期刊:
  • 影响因子:
    6.500
  • 作者:
    Luke Bidulka;Mohsen Gholami;Jiannan Zheng;Martin J. McKeown;Z. Jane Wang
  • 通讯作者:
    Z. Jane Wang
DA-IMRN: Dual-Attention-Guided Interactive Multi-Scale Residual Network for Hyperspectral Image Classification
DA-IMRN:用于高光谱图像分类的双注意力引导交互式多尺度残差网络
  • DOI:
    10.3390/rs14030530
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    5
  • 作者:
    Liang Zou;Zhifan Zhang;Haijia Du;Meng Lei;Yong Xue;Z. Jane Wang
  • 通讯作者:
    Z. Jane Wang
A Better Than Alamouti OSTBC for MIMO Backscatter Communications
优于 Alamouti OSTBC 的 MIMO 反向散射通信

Z. Jane Wang的其他文献

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{{ truncateString('Z. Jane Wang', 18)}}的其他基金

Flight Efficiency and Control in 12 Species of Drosophila and Their Mutants
12种果蝇及其突变体的飞行效率和控制
  • 批准号:
    0933332
  • 财政年份:
    2009
  • 资助金额:
    $ 41.96万
  • 项目类别:
    Standard Grant
Insects in Free Flight: Experiments, Computations, and Mathematical Analysis
自由飞行的昆虫:实验、计算和数学分析
  • 批准号:
    0841089
  • 财政年份:
    2008
  • 资助金额:
    $ 41.96万
  • 项目类别:
    Standard Grant
CAREER: Insect Flight: Computation, Biomimetic Design, and Control
职业:昆虫飞行:计算、仿生设计和控制
  • 批准号:
    0093792
  • 财政年份:
    2001
  • 资助金额:
    $ 41.96万
  • 项目类别:
    Standard Grant
Computation and Modeling of Insect Flight
昆虫飞行的计算与建模
  • 批准号:
    0075510
  • 财政年份:
    2000
  • 资助金额:
    $ 41.96万
  • 项目类别:
    Continuing grant
NSF-NATO POSTDOCTORAL FELLOWSHIPS
NSF-北约博士后奖学金
  • 批准号:
    9633916
  • 财政年份:
    1996
  • 资助金额:
    $ 41.96万
  • 项目类别:
    Fellowship Award

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随机激励下多稳态系统的临界过渡识别及Basin Stability分析
  • 批准号:
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