Mapping the neural circuitry underlying walking

绘制行走背后的神经回路

• 批准号: 10388902
• 负责人: Sumaira Zamurrad
• 金额: $ 0.25万
• 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/10388902
• 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 步行是整个动物界的必不可少的行为。进入的能力 协调，健壮但灵活的方式对于在不断变化的环境中生存至关重要。 运动行为由大脑中的感觉神经胶体控制，这些神经胶质与腹侧的运动中心交谈 胸腔中的神经线（VNC）执行精确的电动机输出。降序神经元是主要导管 在大脑与VNC之间达到这种联系的信息。但是下游 靶向神经元和复杂电路，这些电路精确控制了特定类型的肢体电机的执行 输出，例如跑步，转弯，放慢速度，切换，攀爬，踏脚等，仍然单独 不明确的。该项目旨在绘制控制不同行走运动学的单个电路。在AIM 1中， 我们将使用称为trans的转换技术来绘制降降神经元的突触后靶标 探戈。我们已经从以前的研究中知道所有降级的形态 果蝇中的神经元DNS靶向腹神经和弦中的腿神经胶质。这些下降 神经元很可能直接与控制步行行为有关。此外，我们也有 DNS子集的广泛行为信息。使用这种现有的形态和行为数据， 我们可以开始绘制这些DN下游的电动机和前圆圈，并揭示 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，影响 因此，类似的行为因此很有趣，是揭示它们是否融合到相似或不同的目标上。在 第二个目的，我们的目标是使用计算方法搜索神经元的GAL4系 表达模式与我们要研究的下游目标神经元相匹配。现有的拆分gal4线将是 为了获得对下游电路神经元的遗传访问的确定或新的 兴趣。在第三个目标中，我们将使用三种行为设置：Flywalker，竞技场和球式赛场设置 使用光遗传学交叉策略研究一系列高分辨率的步行参数。我们将使用 光遗传激活，沉默以及上科学实验，以绘制出电路的哪些组成部分 特定行走运动学的足够或必要。