Dynamic switching in the brainstem: a spatiotemporal mechanism for the neural control of breathing

脑干的动态切换:呼吸神经控制的时空机制

基本信息

  • 批准号:
    10594393
  • 负责人:
  • 金额:
    $ 6.95万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2022
  • 资助国家:
    美国
  • 起止时间:
    2022-02-18 至 2025-02-17
  • 项目状态:
    未结题

项目摘要

PROJECT SUMMARY Breathing is necessary for survival, and failure to breath results in death. Simultaneously, the precise and flexible control of breathing is crucial for maintaining homeostasis (e.g., blood oxygenation during exertion), and to serve higher order functions such as vocalization. The neural control for both the inexorable and the flexible capabilities of breathing arises from the activity of neurons in the brainstem. The intrinsically rhythmic pre-Bötzinger complex (preBötC) is thought to be the core or “kernel” driving rhythm generation, but a distributed network of neural centers that extend rostrally and caudally from the preBötC, known as the Ventral Respiratory Column (VRC), has been implicated in control of varied aspects of respiration (e.g., inspiration, expiration, sighing, gasping). Lesion experiments and isolated recordings from in-vitro brain slices have given insights into the roles of the different sub-nuclei that govern respiration. However, it remains unknown how the activity of these neuronal populations is dynamically coordinated to adjust respiratory behaviors during normal breathing and gasping. Here, we record simultaneously from large, spatially distributed populations of genetically identified single neurons across the VRC in-vitro and in-vivo. Based on our preliminary data, we propose a novel “dynamic switching” hypothesis: coordinated neural networks recruit discrete, but anatomically overlapping, populations of neurons to drive unique respiratory behaviors. Moreover, the respiratory role (e.g. inspiratory/expiratory) of individual neurons is not static, as is currently thought, but dynamic and changes with respiratory behavior. This hypothesis is analogous to phenomena observed in locomotor gaits in which discrete spatiotemporal muscle patterns give rise to discrete modes of movement (e.g. walking, trotting, galloping). This proposal tests the dynamic switching hypothesis through three specific aims: Aim 1 quantifies the dynamic and coordinated respiratory roles of single neurons in in-vitro brain slices and in-vivo in anesthetized, breathing mice. We employ state-of-the-art high-density electrophysiology (Neuropixels) with optogenetic techniques to identify the functional role and genetic identity of hundreds of simultaneously recorded neurons and compare the coordinated activity of these populations both between in-vitro and in-vivo preparations. Aim 2 describes how these dynamic networks reconfigure during gasping. Lastly, in Aim 3 we corroborate results in freely behaving animals where respiratory behaviors are highly flexible (e.g. sniffing) and are modulated by top-down centers.
项目概要 呼吸是生存所必需的,呼吸失败就会导致死亡。 呼吸的控制对于维持体内平衡(例如,运动期间的血液氧合)至关重要,并服务于 高阶功能,例如发声,对不可抗拒能力和灵活能力的神经控制。 呼吸的产生源于脑干中神经元的内在节律性前 Bötzinger 复合体。 (preBötC)被认为是驱动节奏生成的核心或“内核”,但神经网络的分布式网络 从 preBötC 向头侧和尾侧延伸的中心,称为腹侧呼吸柱 (VRC), 与呼吸的各个方面(例如吸气、呼气、叹气、喘气)的控制有关。 损伤实验和体外脑切片的孤立记录已经深入了解了 然而,这些神经元的活动如何仍然未知。 种群动态协调以调整正常呼吸和喘气期间的呼吸行为。 在这里,我们同时记录了大型、空间分布的基因识别单一群体 根据我们的初步数据,我们提出了一种新颖的“动态”神经元。 切换”假说:协调神经网络招募离散但在解剖学上重叠的群体 神经元驱动独特的呼吸行为此外,呼吸作用(例如吸气/呼气)。 单个神经元并不像目前认为的那样是静态的,而是动态的并且随着呼吸行为而变化。 假设类似于在运动步态中观察到的现象,其中离散的时空肌肉 模式产生离散的运动模式(例如步行、小跑、疾驰)。 动态切换假设通过三个具体目标: 目标 1 量化动态和协调 我们采用了体外脑切片和体内麻醉呼吸小鼠中单个神经元的呼吸作用。 最先进的高密度电生理学(Neuropixels)与光遗传学技术来识别 数百个同时记录的神经元的功能作用和遗传特性,并比较 目标 2 描述了这些群体在体外和体内制剂之间的协调活动。 这些网络在喘息期间动态重新配置。最后,在目标 3 中,我们证实了自由行为的结果。 呼吸行为高度灵活(例如嗅)并由自上而下的中心调节的动物。

项目成果

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Nicholas Edward Bush其他文献

Nicholas Edward Bush的其他文献

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{{ truncateString('Nicholas Edward Bush', 18)}}的其他基金

Dynamic switching in the brainstem: a spatiotemporal mechanism for the neural control of breathing
脑干的动态切换:呼吸神经控制的时空机制
  • 批准号:
    10313260
  • 财政年份:
    2022
  • 资助金额:
    $ 6.95万
  • 项目类别:
Spatiotemporal Integration of Mechanical Information in the Rat Brainstem
大鼠脑干机械信息的时空整合
  • 批准号:
    8909521
  • 财政年份:
    2015
  • 资助金额:
    $ 6.95万
  • 项目类别:

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