Molkov Yaroslav I, Rubin Jonathan E, Rybak Ilya A, Smith Jeffrey C
Department of Mathematics and Statistics, Georgia State University, Atlanta, GA, USA.
Department of Mathematics, University of Pittsburgh, Pittsburgh, PA, USA.
Wiley Interdiscip Rev Syst Biol Med. 2017 Mar;9(2). doi: 10.1002/wsbm.1371. Epub 2016 Dec 23.
The ongoing process of breathing underlies the gas exchange essential for mammalian life. Each respiratory cycle ensues from the activity of rhythmic neural circuits in the brainstem, shaped by various modulatory signals, including mechanoreceptor feedback sensitive to lung inflation and chemoreceptor feedback dependent on gas composition in blood and tissues. This paper reviews a variety of computational models designed to reproduce experimental findings related to the neural control of breathing and generate predictions for future experimental testing. The review starts from the description of the core respiratory network in the brainstem, representing the central pattern generator (CPG) responsible for producing rhythmic respiratory activity, and progresses to encompass additional complexities needed to simulate different metabolic challenges, closed-loop feedback control including the lungs, and interactions between the respiratory and autonomic nervous systems. The integrated models considered in this review share a common framework including a distributed CPG core network responsible for generating the baseline three-phase pattern of rhythmic neural activity underlying normal breathing. WIREs Syst Biol Med 2017, 9:e1371. doi: 10.1002/wsbm.1371 For further resources related to this article, please visit the WIREs website.
持续的呼吸过程是哺乳动物生命所必需的气体交换的基础。每个呼吸周期都源于脑干中有节奏的神经回路的活动,这些活动受到各种调节信号的影响,包括对肺扩张敏感的机械感受器反馈以及依赖于血液和组织中气体成分的化学感受器反馈。本文综述了各种计算模型,这些模型旨在重现与呼吸神经控制相关的实验结果,并为未来的实验测试生成预测。综述从脑干核心呼吸网络的描述开始,该网络代表负责产生有节奏呼吸活动的中枢模式发生器(CPG),然后逐步涵盖模拟不同代谢挑战、包括肺部的闭环反馈控制以及呼吸和自主神经系统之间相互作用所需的额外复杂性。本综述中考虑的综合模型共享一个共同框架,包括一个分布式CPG核心网络,负责生成正常呼吸基础的有节奏神经活动的基线三相模式。WIREs系统生物学与医学2017年,9:e1371。doi:10.1002/wsbm.1371 有关本文的更多资源,请访问WIREs网站。