BRAIN EAGER: Using Optogenetic Techniques in Combination with Free Flight Perturbations to Elucidate Neural Structure Governing Flight Control in D. Melanogaster

BRAIN EAGER：利用光遗传学技术结合自由飞行扰动来阐明黑腹果蝇控制飞行控制的神经结构

• 批准号: 1546710
• 负责人: Itai Cohen
• 金额: $ 30万
• 依托单位: Cornell University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1546710&HistoricalAwards=false
• 关键词: BRAIN; EAGER; Using; Optogenetic; Techniques

Forging the link between individual neuron function and the behavior of collections of neurons that can produce complex behaviors is the central goal of contemporary neuroscience. The path towards achieving this goal is being revolutionized by genetic techniques that allow for manipulation of the activity of neurons and measurement of the effect on behavior. Flight behavior in the fruit fly, Drosophila, is highly suitable for this combined analysis, since flies can be genetically manipulated very easily and their rich set of free flight behaviors can be quantitatively characterized in great detail. This project will use this approach to unravel the design and operation of a remarkable neural circuit responsible for giving flies one of the fastest response times in the animal kingdom and controlling their high speed maneuvering capabilities. Using small magnets attached to the flies and applied magnetic fields, flies will be subjected to forces in midair that alter their flight. By turning on and off the neurons in the control circuit that governs their response to such forces and determining the resulting change in their wing motions, the role that each individual neuron plays in the neural circuit that governs the recovery of these insects to the experimental perturbation will be determined. More broadly this work will lay the framework for a general powerful approach for interrogating and building an understanding of many other complex neural circuits. Moreover, the discoveries made will inform design principles for the development of efficient control strategies that can be used in robots. This pipeline for discovery will be publicized through conference meetings, publications, and workshops. In addition, the analysis routines and resulting data will be made available through the Principal Investigator's group web site. The flight of fruit flies (Drosophila) provides a rich set of free flight behaviors that can be quantitatively characterized in great detail using methods recently developed by the PI. Towards this end, this project will develop a platform in which each neuron in this circuit can be manipulated using optogenetics and the altered behavioral response quantified, with the aim of dissecting with unprecedented detail a behaviorally vital yet poorly understood neural circuit. Crucially, the approach taken entails using large empirical data sets of flight kinematics in conjunction with the mathematical theory of dynamical systems to generate reduced order models. These models will be used to guide the experiment design and interpretation of the resulting kinematic data. Application of this approach to motor-neurons will be used to elucidate the role of specific steering muscles in the flight control process. Application of this approach to the inter-neurons, which relay sensory responses to the motor-neurons, is being used to elucidate the design and function of the neural control circuit that determines the fly's response to mid-air perturbations. More broadly the complexity and hierarchical layout of the machinery necessary for insect flight is typical of other complex neural circuits.

建立单个神经元功能与可以产生复杂行为的神经元集合的行为之间的联系是当代神经科学的中心目标。基因技术正在彻底改变实现这一目标的道路，这些技术允许操纵神经元的活动并测量对行为的影响。果蝇的飞行行为非常适合这种组合分析，因为果蝇可以非常容易地进行基因操纵，并且可以非常详细地定量描述它们丰富的自由飞行行为。该项目将利用这种方法来揭示一个非凡的神经回路的设计和操作，该神经回路负责为果蝇提供动物王国中最快的响应时间之一，并控制它们的高速机动能力。使用附着在苍蝇上的小磁铁并施加磁场，苍蝇将受到半空中的力，从而改变它们的飞行。通过打开和关闭控制电路中的神经元来控制它们对这种力的反应，并确定由此产生的翅膀运动的变化，每个单独的神经元在控制这些昆虫对实验扰动的恢复的神经电路中所扮演的角色将被确定。更广泛地说，这项工作将为询问和建立对许多其他复杂神经回路的理解的通用强大方法奠定框架。此外，所取得的发现将为开发可用于机器人的高效控制策略的设计原则提供信息。该发现渠道将通过会议、出版物和研讨会进行宣传。此外，分析程序和结果数据将通过首席研究员的小组网站提供。 果蝇（果蝇）的飞行提供了一系列丰富的自由飞行行为，可以使用 PI 最近开发的方法对其进行详细的定量表征。为此，该项目将开发一个平台，可以使用光遗传学来操纵该回路中的每个神经元，并对改变的行为反应进行量化，目的是以前所未有的细节剖析一个行为重要但知之甚少的神经回路。至关重要的是，所采用的方法需要使用飞行运动学的大型经验数据集结合动力系统的数学理论来生成降阶模型。这些模型将用于指导实验设计和对所得运动学数据的解释。这种方法对运动神经元的应用将用于阐明特定转向肌肉在飞行控制过程中的作用。这种方法应用于将感觉反应传递给运动神经元的中间神经元，用于阐明决定果蝇对空中扰动的反应的神经控制电路的设计和功能。 更广泛地说，昆虫飞行所需的机器的复杂性和分层布局是其他复杂神经回路的典型特征。