Mapping the neural circuitry underlying walking

绘制行走背后的神经回路

• 批准号: 10201434
• 负责人: Sumaira Zamurrad
• 金额: $ 7.39万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-06-01 至 2023-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10201434
• 关键词: ARNT gene; Address; Affect; Afferent Neurons; Anatomy; Animal Model; Animals; Anions; Artificial Intelligence; Behavior; Behavioral; Biological Assay; Brain; Chest; Cloning; Color; Communities; Complex; Data; Disease; Drosophila genus; Environment; Functional disorder; Gait; Generations; Genetic; Genetic Epistasis; Individual; Knowledge; Label; Lead; Leg; Limb structure; Link; Maps; Methods; Morphology; Motor; Motor output; Movement; Nerve; Neural Pathways; Neurodegenerative Disorders; Neurons; Neuropil; Output; Pattern; Play; Resolution; Resources; Rhodopsin; Role; Running; Sensory; Synapses; Techniques; Testing; Walking; design; experimental study; flexibility; fly; interest; kinematics; mind control; motor behavior; motor control; motor disorder; neural circuit; neural network; optogenetics; relating to nervous system; tool

Project Summary Walking is an essential and conserved behavior across the animal kingdom. The ability to move in a coordinated, robust yet flexible manner is a crucial for an animal’s survival in the ever changing environment. Motor behaviors are controlled by sensory neuropils in the brain which talk to motor centers such as the ventral nerve cord (VNC) in the thorax to execute precise motor outputs. Descending neurons are the primary conduits of information that accomplish this connection between the brain and the VNC. However the downstream target neurons and complex circuits that precisely govern the execution of a specific kind of limbed motor output such as running, turning, slowing down, switching gait, climbing, stepping etc remain individually undefined. This project aims to map these individual circuits that control different walking kinematics. In aim 1, we will map the post-synaptic targets of descending neurons using a translabeling technique called Trans Tango. We already know from previous studies that have characterized the morphology of all the descending neurons in Drosophila, which DNs target the leg neuropils in the ventral nerve chord. These descending neurons are very likely to be directly implicated in controlling walking behavior. Additionally, we also have broad behavioral information for a subset of the DNs. Using this existing morphological and behavioral data, we can start to map out the motor and premotor circuits that are downstream of these DNs and reveal the distinct circuit components that control specific walking kinematics. Some of the DNs we plan to screen, affect similar behaviors hence it will be interesting to reveal whether they converge onto similar or different targets. In the second aim, we aim to use a computational approach search for generation Gal4 lines whose neuronal expression patterns match the downstream target neurons we want to study. Existing split Gal4 lines will be identified or new ones will be generated in order to gain genetic access to the downstream circuit neurons of interest. In the third aim, we will use three behavior setups: Flywalker, the Arena and the fly-on-ball setup to study a range of walking parameters in high resolution using optogenetics intersectional strategies. We will use optogenetic activation, silencing and also epistasis experiments to map out which components of the circuit are sufficient or necessary for a particular walking kinematic.

项目摘要 行走是动物王国中必不可少的保守行为。能够在一个 协调、稳健而又灵活的方式是动物在不断变化的环境中生存的关键。 运动行为是由大脑中的感觉神经柱控制的，感觉神经柱与运动中心（如腹侧中枢）对话。 神经索（VNC）在胸部执行精确的运动输出。下行神经元是 完成大脑和VNC之间的连接。然而，下游 目标神经元和复杂的电路，精确地控制一种特定的肢体运动的执行 输出，如跑步，转弯，减速，切换步态，攀爬，踏步等保持独立 未定义。该项目旨在绘制这些控制不同行走运动学的单独电路。在目标1中， 我们将使用一种称为“跨膜”的转标记技术， 探戈我们已经从以前的研究中了解到，所有下行的形态特征 DNs靶向腹神经索中的腿部神经柱。这些下降 神经元很可能直接参与控制行走行为。此外，我们还有 DN的子集的广泛行为信息。利用现有的形态和行为数据， 我们可以开始绘制出这些DN下游的运动和前运动回路， 控制特定行走运动学的不同电路组件。我们计划筛选的一些DN， 因此，揭示它们是否收敛于相似或不同的目标将是有趣的。在 第二个目，我们的目的是使用计算方法来搜索其神经元 表达模式与我们想要研究的下游靶神经元相匹配。现有的Gal4分离线将 识别或新的将产生，以获得遗传访问下游电路神经元的神经元， 兴趣在第三个目标中，我们将使用三种行为设置：飞行者，竞技场和飞行球设置， 使用光遗传学交叉策略以高分辨率研究一系列行走参数。我们将使用 光遗传学激活，沉默和上位性实验，以绘制出电路的哪些组件， 对于特定的行走运动学来说是足够的或必要的。