Dynamics of Sleep-Wake Regulation

最近的实验结果已经确定了脑干和下丘脑神经元群体，它们的神经递质介导的相互作用被认为构成了控制睡眠和觉醒转换的调节网络。尽管在这个网络中特定的促进觉醒和促进睡眠的神经元群体的贡献和相互作用得到了广泛的支持，但关于参与调节快眼运动(REM)睡眠的网络组件一直存在着很大的争论。这个项目分析了相互竞争的睡眠-觉醒调节网络的结构如何决定睡眠-觉醒行为和行为状态转换的动态。研究人员开发了一种新的放电率模型形式主义，明确包括神经递质动力学，该模型唯一适合于对睡眠-觉醒调节网络的动力学进行建模。使用该形式论的简化，分析用于管理REM睡眠生成的子网络的当前竞争提出的结构的模型，以确定由网络结构指示的内在动力学以及这些动力学对子网络组件的依赖。此外，还研究了竞争提出的用于调节唤醒和睡眠状态的网络结构中的状态转移动力学。维持简化的模型形式主义，重点是确定相互竞争的网络结构产生人类睡眠模式的关键特征的机制，这些特征将从实验睡眠记录中得到表征。竞争模型网络的动力学，使用包括随机成分的完整模型形式主义，适合于在包括啮齿动物、猫科动物和人类在内的多种物种中记录的睡眠-觉醒模式的精细时间结构，重点是研究睡眠-觉醒模式的共同动态特征和跨物种睡眠-觉醒调节机制的可变性。研究人员与三位领先的睡眠实验科学家合作，他们为拟议的项目提供睡眠记录和咨询。在哺乳动物中，清醒和睡眠状态由位于脑干和下丘脑的神经元群体主动控制。目前，在实验睡眠科学中，这些人群之间的相互作用，由初级神经递质介导，被认为形成了一个控制睡眠和觉醒转换的调节网络。尽管在这个网络中特定的促进觉醒和促进睡眠的神经元群体的贡献和相互作用得到了广泛的支持，但关于参与调节快眼运动(REM)睡眠的网络组件一直存在着很大的争论。睡眠-觉醒调节的实验研究受到这样一个事实的限制，即结果测量，即睡眠-觉醒模式，只存在于完整的动物中。可用于探索神经元调节机制的实验技术仅限于那些可以在不干扰睡眠的情况下在体内进行的技术，或者死后研究，这些技术可以识别人群之间突触投射的解剖，但不能识别作为睡眠-觉醒转换基础的时变相互作用。这个项目使用数学建模作为一种调查工具，以弥补这些限制在实验研究中留下的空白。建模研究解决了哺乳动物睡眠-觉醒调节网络的结构这一生理学上令人信服且目前存在争议的问题。许多实验小组提出了网络结构的示意图，并对网络交互如何驱动行为状态转换提供了假设性描述。然而，静态概念模型缺乏复制睡眠-觉醒状态之间转换的时间动态或确定网络结构固有的动态交互的能力。对这些提出的网络的数学模型的构建和分析确定了组成群体和神经递质的动态相互作用，并提供了对网络动态如何产生睡眠-觉醒模式的良好时间结构的定量理解。将模型解决方案与啮齿动物、猫科动物和人类睡眠的实验记录进行比较，以确定在这些多个物种中观察到的睡眠-觉醒模式差异的机制。模拟研究的结果确定了每个提出的网络结构在解释睡眠-觉醒调节的不同特征方面的局限性，并将产生预测，表明实验方法如何改进我们对生理网络结构的知识。

Recent experimental results have identified brainstem and hypothalamic neuronal populations whose neurotransmitter-mediated interactions are proposed to compose a regulatory network for the control of sleep and wake transitions. While there is wide support for the contribution and interactions of specific wake-promoting and sleep-promoting neuronal populations in this network, by contrast, there has been much debate about the network components involved in the regulation of rapid-eye movement (REM) sleep. This project analyzes how the structure of competing proposed sleep-wake regulatory networks determines sleep-wake behavior and dynamics of behavioral state transitions. The researchers have developed a novel firing rate model formalism explicitly including neurotransmitter dynamics that is uniquely suited to model dynamics of the sleep-wake regulatory network. Using a reduction of this formalism, models of the current competing proposed structures for the subnetwork governing REM sleep generation are analyzed to determine intrinsic dynamics dictated by the network structure, and the dependence of those dynamics on subnetwork components. Additionally, state transition dynamics in competing proposed network structures for regulation of wake and sleep states are investigated. Maintaining the reduced model formalism, the focus is on determining the mechanisms by which the competing network structures generate key features of human sleep patterning that will be characterized from experimental sleep recordings. Dynamics of competing model networks, using the full model formalism including stochastic components, are fit to the fine temporal architecture of sleep-wake patterning recorded in multiple species, including rodent, feline, and human, with focus on investigating common dynamic features of sleep-wake patterning and variability in sleep-wake regulatory mechanisms across species. The researchers collaborate with three leading experimental sleep scientists who provide sleep recordings and consultation on the proposed projects.In mammals, states of waking and sleep are actively controlled by populations of neurons located in the brainstem and hypothalamus. Currently, in experimental sleep science, the interactions of these populations, mediated by primary neurotransmitters, are believed to form a regulatory network for the control of sleep and wake transitions. While there is wide support for the contribution and interactions of specific wake-promoting and sleep-promoting neuronal populations in this network, by contrast, there has been much debate about the network components involved in the regulation of rapid-eye movement (REM) sleep. Experimental investigation of the sleep-wake regulatory is limited by the fact that the outcome measurement, namely sleep-wake patterning, only exists in the intact animal. The experimental techniques available to probe the neuronal regulatory mechanisms are limited to those that can be conducted in vivo without disrupting sleep, or post-mortem studies that can identify anatomy of synaptic projections between populations but not their time-varying interactions that underlie sleep-wake transitions. This project uses mathematical modeling as an investigative tool to bridge the gaps left by these limitations in experimental studies. The modeling studies address the physiologically compelling and currently debated question of the structure of the mammalian sleep-wake regulatory network. Numerous experimental groups have proposed schematics of network structures and provided hypothetical descriptions of how network interactions drive behavioral state transitions. However, static conceptual models lack the ability to replicate time dynamics of transitions between sleep-wake states or to determine dynamic interactions inherent to network structure. Construction and analysis of mathematical models of these proposed networks identifies the dynamic interactions of constituent populations and neurotransmitters, and provides quantitative understanding of how network dynamics generate the fine temporal architecture of sleep-wake patterning. Model solutions are compared to experimental recordings of rodent, feline and human sleep to determine mechanisms contributing to the differences in sleep-wake patterning observed in these multiple species. Results of the modeling studies identify limitations of each of the proposed network structures in accounting for various characteristics of sleep-wake regulation and will generate predictions suggesting how experimental approaches can refine our knowledge of the physiological network structure.