Multi-Scale Models of Neural Mechanisms Controlling Breathing in Mammals

控制哺乳动物呼吸的神经机制的多尺度模型

• 批准号: 7969709
• 负责人: Jeffrey c Smith
• 金额: $ 74.51万
• 依托单位: NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/7969709
• 关键词: Architecture; Behavior; Biological Neural Networks; Blood; Brain; Brain Hypoxia; Brain Stem; Breathing; Carbon Dioxide; Cell model; Cells; Computer Architectures; Computer Simulation; Databases; Development; Elements; Feedback; Generations; Goals; Homeostasis; In Situ; In Vitro; Life; Mammals; Methods; Modeling; Motor; Motor Activity; Movement; Nervous system structure; Neurons; Operative Surgical Procedures; Oxygen; Pattern; Peripheral; Phase; Physiological; Physiological Processes; Population; Preparation; Property; Rattus; Regulation; Research; Respiration; Respiratory Transport; Rodent; Role; Signal Transduction; Slice; Spinal Cord; Study models; Synapses; System; Systems Theory; Testing; Time; design; experimental analysis; expiration; insight; multi-scale modeling; multidisciplinary; network models; neural circuit; neurogenesis; neuromechanism; neurophysiology; neuroregulation; novel; reconstruction; relating to nervous system; research study; respiratory; respiratory gas; simulation

Research involved the development of novel neurodynamical models of neurons and networks comprising the respiratory neural control system as studied experimentally in parallel in the rodent brain. Data-based models developed included (1) biophysically realistic cellular-level computational models of respiratory neurons incorporating current information on cellular architecture and biophysical properties such as ionic conductance mechanisms underlying neuronal activity, and (2) large-scale models of brainstem respiratory neural networks incorporating available information on network functional and structural architecture. The overall objective of these modeling studies was to gain mechanistic insights into the manner in which cellular- and circuit-level properties are integrated into microcircuits as well as large-scale respiratory networks for dynamical operation of the mammalian respiratory neural control system. A new model of respiratory central pattern generation (CPG) networks in the rodent brainstem was developed consisting of interacting excitatory and inhibitory subnetworks distributed in serially arranged brainstem structural compartments, each with distinct functional roles in generation and control of the respiratory neural activity patterns that evolve during the normal breathing cycle of inspiration followed by expiration. The basic network architecture and cellular properties used in this CPG model were derived from electrophysiological and neuroanatomical reconstruction studies conducted in the rat brainstem-spinal cord in situ and on subnetworks isolated in living brainstem slice preparations in vitro with active circuits. These models also incorporated for the first time regulation of different circuit components by modeled afferent input signals from several critical neuromodulatory control systems that are known to be involved in regulation of respiratory pattern generation. For dynamical analysis of CPG network operation, methods from dynamical systems theory were also applied to identify critical dynamical variables and parameters of circuit operation that underlie respiratory rhythm and pattern generation and control the orderly transitions between the functionally distinct phases of inspiratory and expiratory neural activity. Computer simulations with the microcircuit and large-scale models mimicked many features of the single-cell and neuron population activity patterns found experimentally under different in vitro and in situ conditions. A major new hypothesis derived from experimental studies and tested with these models was that the capability to generate oscillatory activity exists within the respiratory CPG at multiple levels of cellular and network organization. Thus different mechanisms of respiratory rhythm generation can be functionally expressed in a brain state-dependent manner and underlie multiple respiratory motor behaviors, some of which occur under normal physiological conditions and others of which emerge under pathophysiological conductions such as during severe brain hypoxia (conditions of abnormally low oxygen). Simulations with models of different levels of cellular and network complexity confirmed the plausibility of this new concept and have provided insights into the essential cellular and network mechanisms involved. At the system level, models of the respiratory neural control system have been developed that couple these essential neural circuit dynamics with peripheral oxygen and carbon dioxide exchange, blood gas transport, and physiological feedback regulation of central respiratory circuits by signals such as blood/brain levels of oxygen and carbon dioxide. These latter models represent the first generation of system-level control models that integrate essential elements of nervous system structural-functional properties and realistic features of the respiratory gas exchange and transport system. All of these models are currently being applied to further explore principles of operation of brainstem respiratory circuits and control of respiratory activity including under various (patho)physiological conditions associated with disturbances of brain and body oxygen/carbon dioxide homeostasis.

研究涉及在啮齿动物大脑中并行研究的神经元和网络的新型神经动力学模型和网络的开发。开发的基于数据的模型包括（1）呼吸神经元的生物物理逼真的细胞水平计算模型，这些计算模型结合了有关细胞结构和生物物理特性的当前信息，例如神经元活动的离子电导机制，以及（2）包含网络功能和结构架构的可用信息的大型脑系统呼吸神经网络的大尺度模型。这些建模研究的总体目的是获得机械洞察力，以了解细胞和电路级特性集成到微电路中的方式以及大规模呼吸网络，以进行哺乳动物呼吸神经控制系统的动力运行。开发了啮齿动物脑干中的呼吸中心模式产生（CPG）网络的新模型，该模型包括分布在串行布置的脑干结构隔室中的相互作用和抑制性子网组成，每个工作都在呼吸神经活动模式中具有独特的功能，在正常的呼吸周期中，在呼吸道神经活动模式中具有独特的功能。该CpG模型中使用的基本网络结构和细胞性能源自在大鼠脑干脊髓原位和在活性电路中体外的活脑干切片制备中分离的亚分离的大鼠脑茎脊髓和亚网络中进行的电生理和神经解剖学重建研究。这些模型还通过建模的几个关键神经调节控制系统的建模传入输入信号对不同电路组件进行了调节，这些信号已知与呼吸模式的调节有关。为了对CPG网络操作进行动态分析，还采用了动态系统理论的方法来识别临界动力学变量和电路操作的参数，这些变量是呼吸节奏和模式产生和模式生成并控制灵感和呼气神经活动功能上不同阶段之间的有序过渡的基础。具有微电路和大规模模型的计算机模拟模仿了单细胞和神经元种群活动模式的许多特征，在不同的体外和原位条件下实验发现。从实验研究中得出的一个主要的新假设并对这些模型进行了测试是，在细胞和网络组织的多个级别上，呼吸道CPG内存在振荡活性的能力。因此，呼吸节奏产生的不同机制可以在功能上以脑状态依赖性方式表达，并且是多种呼吸运动行为的基础，其中一些发生在正常的生理条件下，而另一些则发生在病理生理导电下，例如在严重的脑缺氧期间（异常低氧气的条件）。具有不同级别的细胞和网络复杂性模型的模拟证实了这一新概念的合理性，并提供了对所涉及的基本细胞和网络机制的见解。在系统级别上，已经开发了呼吸神经控制系统的模型，使这些必不可少的神经回路动力学与周围氧和二氧化碳交换，血液传输以及中枢呼吸道回路的生理反馈调节，这是通过氧气和氧化二氧化碳的血液/大脑水平等信号。这些后一种模型代表了系统级控制模型的第一代，该模型整合了神经系统结构功能的基本要素以及呼吸气体交换和运输系统的现实特征。目前，所有这些模型都用于进一步探索脑干呼吸回路运行原理，并控制呼吸活动，包括在各种（病情）生理条件下与大脑和人体氧气/二氧化碳稳态的障碍相关的各种生理条件。