Multiscale Model of Neural Control of Breathing

描述(申请人提供)：哺乳动物的呼吸是一种原始的动态平衡过程，调节血液和组织中氧气(O2)和二氧化碳(CO2)的水平，对生命至关重要。有节奏的呼吸运动必须在一生中持续发生，并源于脑干中组成呼吸中枢模式生成器(CPG)的特殊组织电路产生的神经活动。呼吸性CPG产生有节奏的运动模式，产生呼吸泵(横隔膜、胸腔和腹部)的协调运动，控制肺充气和排气，以及上呼吸道肌肉，控制气流。这些协调的有节奏的运动推动O2和CO2的交换和运输，从而维持大脑和身体的生理动态平衡。揭示呼吸系统中复杂的多层次和多尺度机制，导致对呼吸的机械理解，包括不同疾病状态下的呼吸，需要一种生理学类型的方法，该方法依赖于特定器官和生理功能的多尺度计算模型的开发和明确实施。这个多机构项目的具体目标是：(1)开发一个生理学类型的、可预测的、多尺度的呼吸神经控制计算模型，该模型将呼吸的重要功能中涉及的多个生理机制和过程联系起来，但在不同的功能和结构组织尺度上运行，(2)在一系列补充的实验研究中验证该模型，以及(3)将该模型用作制定与心力衰竭相关的呼吸模式改变的可能来源和机制的预测的计算框架。该项目汇集了一支多学科的科学家团队，他们在呼吸生理学、神经科学和转化医学研究方面有着长期的合作和互补的专业知识(托马斯·E·迪克，凯斯西储大学；朱利安·F·R·佩顿，英国布里斯托尔大学；罗伯特·F·罗杰斯，德雷克塞尔大学；杰弗里·C·史密斯，NINDS，NIH，Intral)，数学、系统分析和生物工程(Alona Ben-Tal，梅西大学，新西兰)，以及计算神经科学和神经控制(Ilya A.Rybak，德雷克塞尔大学)。我们提出的跨学科建模和实验研究的最终结果将是基于当前的生理知识状态开发和实施一种新的、完全可操作的、多尺度的集成呼吸神经生理控制系统模型。然后，这个模型可以作为一个计算框架，用来制定对呼吸系统疾病可能的神经机制的预测，并建议可能的治疗方法。

DESCRIPTION (provided by applicant): Respiration in mammals is a primal homeostatic process, regulating levels of oxygen (O2) and carbon dioxide (CO2) in blood and tissues and is crucial for life. Rhythmic respiratory movements must occur continuously throughout life and originate from neural activity generated by specially organized circuits in the brain stem constituting the respiratory central pattern generator (CPG). The respiratory CPG generates rhythmic patterns of motor activity that produce coordinated movements of the respiratory pump (diaphragm, thorax, and abdomen), controlling lung inflation and deflation, and upper airway muscles, controlling airflow. These coordinated rhythmic movements drive exchange and transport of O2 and CO2 that maintain physiological homeostasis of the brain and body. Uncovering complex multilevel and multiscale mechanisms operating in the respiratory system, leading to mechanistic understanding of breathing, including breathing in different disease states requires a Physiome-type approach that relies on the development and explicit implementation of multiscale computational models of particular organs and physiological functions. The specific aims of this multi-institutional project are: (1) develop a Physiome-type, predictive, multiscale computational model of neural control of breathing that links multiple physiological mechanisms and processes involved in the vital function of breathing but operating at different scales of functional and structural organization, (2) validate this model in a series of complementary experimental investigations and (3) use the model as a computational framework for formulating predictions about possible sources and mechanisms of respiratory pattern alteration associated with heart failure. The project brings together a multidisciplinary team of scientists with long standing collaboration and complementary expertise in respiration physiology, neuroscience and translational medical studies (Thomas E. Dick, Case Western Reserve University; Julian F.R. Paton, University of Bristol, UK; Robert F. Rogers, Drexel University; Jeffrey C. Smith, NINDS, NIH, intramural), mathematics, system analysis and bioengineering (Alona Ben-Tal, Massey University, NZ), and computational neuroscience and neural control (Ilya A. Rybak, Drexel University). The end result of our proposed cross-disciplinary modeling and experimental studies will be the development and implementation of a new, fully operational, multiscale model of the integrated neurophysiological control system for breathing based on the current state of physiological knowledge. This model can then be used as a computational framework for formulating predictions about possible neural mechanisms of respiratory diseases and suggesting possible treatments.