Emergence and Coordination of Rhythmic Activity in Respiratory Neurons and Networks

呼吸神经元和网络节律活动的出现和协调

• 批准号: 1951095
• 负责人: Jonathan Rubin
• 金额: $ 46.12万
• 依托单位: University of Pittsburgh
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1951095&HistoricalAwards=false
• 关键词: Emergence; Coordination; Rhythmic; Activity; Respiratory

Breathing in mammals occurs regularly throughout life without the need for conscious control. This remarkably robust behavior results from the activity of networks of neurons deep in the brain that interact to produce coordinated, rhythmic outputs that drive breathing. Although certain aspects of this process are well understood, experiments have revealed features that go beyond existing theories, and this project will apply new modeling and analysis approaches to investigate these effects. A first set of issues that will be studied relates to the ways that specific patterns of respiratory neuron outputs emerge, change across development, and are affected by feedback signals. A second direction of investigation will focus on how activity spreads and becomes coordinated across a population of respiratory neurons, as needed to effectively drive the muscles that initiate each breathing cycle. Additional avenues for research will involve the mechanisms of system-wide coordination across multiple populations of neurons that interact to produce the full breathing cycle over a range of conditions. The work will be completed in collaboration with experimentalists, and results of the project will lead to improved models to explain results of respiratory experiments and will generate new predictions. In addition to enhancing understanding of respiratory function and dysfunction, this project will have broad implications: theoretical methods developed to study the spread of coordinated activity will be relevant to other neural networks and to the spread of disease, opinion and information, while approaches for analyzing processes that evolve at very different rates will apply to other settings as well. Trainees contributing to this research will gain experience in using computational methods to address data-driven questions in neuroscience. Methods and findings developed will contribute to the training of students via local group meetings and courses and will be disseminated more broadly via publications, presentations, and model sharing.Rhythmic activity of networks of neurons underlies a wide range of repetitive behaviors such as walking, scratching, and breathing. This project will address rhythm generation, coordination, and control via a focus on neuronal networks in the mammalian brainstem associated with respiration. In the rhythms that these networks produce, multiple populations of neurons take turns activating at specific relative times and with specific activity patterns within each breathing cycle, and the activity within each population rapidly synchronizes when it arises. This work will analyze how activity with complex dynamic features, called bursting, arises in specific neurons and subsequently spreads across the population in a particular brainstem region during the inspiratory phase of breathing. Analysis of the bursting patterns, which will be done across multiple stages of development, will involve novel mathematical analysis of the dynamics of systems with components that evolve on several distinct timescales. The resulting theoretical advances will have implications for the study of other biological and physical systems with multiple timescale dynamics. New results will also be attained, using mathematical and computational methods, about how the coordination of bursting across the network depends on the pattern of connections across the neurons involved and the properties of the synapses through which these neurons communicate. These advances will also have broader applicability to other processes involving the spread of activity in a network from a small set of local initiation sites. Finally, this project will include investigation of coordination of activity across multiple neuronal populations to produce functional respiratory outputs, including issues of flexibility and robustness under changes in feedback signals due to environmental or metabolic demands. These steps will be guided by novel experimental data, will involve collaboration with experimentalists, and will result in advances in basic understanding as well as predictions about alterations underlying certain respiratory dysfunctions. The project will include diverse graduate students and undergraduates who will gain valuable research training, will impact educational efforts, and will lead to dissemination of results and model sharing.This award is funded jointly by the MPS Division of Mathematical Sciences (DMS) through the Mathematical Biology Program and BIO/IOS through the Neural Systems Cluster.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.

哺乳动物的呼吸在整个生命中定期发生，而不需要有意识的控制。这种非常强大的行为是大脑深处神经元网络活动的结果，这些神经元相互作用，产生协调的、有节奏的输出，驱动呼吸。 虽然这一过程的某些方面已经很好地理解，但实验揭示了超越现有理论的特征，本项目将采用新的建模和分析方法来研究这些影响。将研究的第一组问题涉及呼吸神经元输出的特定模式出现的方式，在发育过程中的变化，以及受反馈信号的影响。第二个研究方向将集中在活动如何在呼吸神经元群体中传播和协调，以有效地驱动启动每个呼吸周期的肌肉。 其他研究途径将涉及多个神经元群体之间的系统协调机制，这些神经元群体相互作用，在一系列条件下产生完整的呼吸周期。这项工作将与实验学家合作完成，该项目的结果将导致改进模型来解释呼吸实验的结果，并将产生新的预测。除了增强对呼吸功能和功能障碍的理解外，该项目还将产生广泛的影响：为研究协调活动的传播而开发的理论方法将与其他神经网络以及疾病，意见和信息的传播相关，而分析以非常不同的速度演变的过程的方法也将适用于其他环境。 参与这项研究的学员将获得使用计算方法解决神经科学中数据驱动问题的经验。方法和研究结果将有助于通过当地小组会议和课程的学生的培训，并将通过出版物，演示文稿和模型共享更广泛地传播。神经元网络的节律性活动是一系列重复行为的基础，如行走，抓挠和呼吸。这个项目将通过关注哺乳动物脑干中与呼吸相关的神经元网络来解决节律的产生、协调和控制。在这些网络产生的节律中，多个神经元群体在特定的相对时间轮流激活，并在每个呼吸周期内以特定的活动模式激活，并且每个群体内的活动在出现时迅速恢复。 这项工作将分析具有复杂动态特征的活动（称为爆发）如何在特定神经元中产生，并随后在呼吸的吸气阶段在特定脑干区域的人群中传播。对爆发模式的分析将在多个发展阶段进行，将涉及对系统动态的新数学分析，这些系统的组件在几个不同的时间尺度上演变。 由此产生的理论进展将对其他具有多时间尺度动力学的生物和物理系统的研究产生影响。利用数学和计算方法，我们还将获得新的结果，即网络中的突发协调如何取决于所涉及的神经元之间的连接模式以及这些神经元进行通信的突触的特性。 这些进展也将有更广泛的适用性，涉及网络中的活动从一小部分局部起始点的传播。最后，该项目将包括研究多个神经元群体之间的活动协调，以产生功能性呼吸输出，包括由于环境或代谢需求而引起的反馈信号变化下的灵活性和鲁棒性问题。这些步骤将以新的实验数据为指导，将涉及与实验学家的合作，并将导致对某些呼吸功能障碍潜在变化的基本理解和预测的进步。该项目将包括不同的研究生和本科生谁将获得宝贵的研究培训，将影响教育工作，并将导致结果的传播和模型共享。该奖项是由数学科学部（DMS）通过数学生物学计划和BIO/IOS通过神经系统集群。该奖项反映了NSF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进行评估，被认为值得支持审查标准。

项目成果

Activity Patterns of a Two-Timescale Neuronal Ring Model with Voltage-Dependent, Piecewise Smooth Inhibitory Coupling

具有电压依赖性分段平滑抑制耦合的两时间尺度神经元环模型的活动模式

• DOI: 10.1137/21m1431679
• 发表时间: 2022
• 期刊: SIAM Journal on Applied Dynamical Systems
• 影响因子: 2.1
• 作者: Park, Choongseok;Rubin, Jonathan E.
• 通讯作者: Rubin, Jonathan E.

The roles of ascending sensory signals and top-down central control in the entrainment of a locomotor CPG

上行感觉信号和自上而下的中央控制在运动 CPG 的夹带中的作用

• DOI: 10.1007/s00422-020-00852-8
• 发表时间: 2020
• 期刊: Biological Cybernetics
• 影响因子: 1.9
• 作者: Codianni, Marcello G.;Daun, Silvia;Rubin, Jonathan E.
• 通讯作者: Rubin, Jonathan E.

Rigorous Mapping of Data to Qualitative Properties of Parameter Values and Dynamics: A Case Study on a Two-Variable Lotka–Volterra System

数据到参数值和动态的定性属性的严格映射：二变量 Lotka–Volterra 系统的案例研究

• DOI: 10.1007/s11538-023-01165-0
• 发表时间: 2023
• 期刊: Bulletin of Mathematical Biology
• 影响因子: 3.5
• 作者: Duan, Xiaoyu;Rubin, Jonathan E.;Swigon, David
• 通讯作者: Swigon, David

On the Nonexistence of Terrestrial Canards: Linking Canards and Rivers

论陆地鸭翼的不存在：连接鸭翼和河流

• DOI: 10.1137/21m1421957
• 发表时间: 2022
• 期刊: SIAM Journal on Applied Dynamical Systems
• 影响因子: 2.1
• 作者: Letson, Benjamin;Rubin, Jonathan E.
• 通讯作者: Rubin, Jonathan E.

Dynamics of ramping bursts in a respiratory neuron model

• DOI: 10.1007/s10827-021-00800-w
• 发表时间: 2021-05
• 期刊: Journal of Computational Neuroscience
• 影响因子: 1.2
• 作者: Muhammad U. Abdulla;Ryan S. Phillips;J. Rubin