Network-Level Mechanisms of Ketamine and Nitrous Oxide in the Primate Brain

 描述(申请人提供)：麻醉和止痛的神经机制是基本的科学问题，对外科患者具有深刻的临床意义。大多数普通麻醉药会增强GABA传递，从而抑制神经元功能，从而可预见地导致昏迷。然而，氯胺酮和一氧化二氮是具有麻醉和止痛特性的独特药物，值得注意的例外是：GABA受体不是主要的分子靶点，这两种药物都能增加脑电的高频活动。然而，尽管在分子和神经生理水平上存在这些差异，但我们实验室最近的数据表明，这些药物可能在大脑网络水平上与GABA能麻醉药在机制上有相似之处。我们的长期目标是发现可以在围手术期监测的麻醉和止痛的基本神经科学原理。这项应用的目的是利用功能磁共振成像(FMRI)、脑电(EEG)、皮质多电极阵列记录和图论分析来识别氯胺酮和一氧化二氮在止痛和麻醉剂量下的网络水平机制。我们的中心假设是氯胺酮和一氧化二氮改变了网络的模块化(即，大脑皮层“模块”的整合程度)和网络效率。我们特别假设，较低剂量的这些药物提高了网络效率，扰乱了疼痛处理--导致了镇痛--而较高剂量降低了网络效率，扰乱了大脑皮层的表征--导致麻醉。拟议中的研究的理论基础不仅仅是确定这些特定药物的作用方式。对这些独特药物的网络效应的更好理解可能会导致对一般麻醉和止痛机制的更基本的理解。我们计划通过实现以下具体目标来验证我们的中心假设：1.使用联合fMRI/EEG研究，确定接受氯胺酮或一氧化二氮治疗的健康志愿者脑网络中的剂量依赖性变化。我们已经成功地在接受麻醉药物的人类中开发了一种联合fMRI/EEG的范例，初步数据支持了我们的中心假设。在拟议的研究中，我们将评估氯胺酮或一氧化二氮在麻醉下和麻醉剂量下的大脑反应，重点放在网络测量上，如模块化、效率和中枢结构。2.在接受氯胺酮或一氧化二氮的非人灵长类动物中，使用皮质阵列记录评估感觉运动表征的剂量依赖性变化。我们已经获得了初步证据，表明在氯胺酮麻醉过程中，初级皮层表征可以持续存在，而通常在清醒时发现的跨模式感觉表征被取消(例如，消除M1中的次级感觉表征)。这项创新的研究设计是第一次测量麻醉药物暴露后大脑网络中的认知表征，而不是目前测量功能连接性等替代物的技术。

 DESCRIPTION (provided by applicant): The neural mechanisms of anesthesia and analgesia are fundamental scientific questions, with profound clinical relevance for surgical patients. Most general anesthetics potentiate GABA transmission and thus depress neuronal function, predictably inducing unconsciousness. However, ketamine and nitrous oxide are unique drugs with both anesthetic and analgesic properties that are noteworthy exceptions: GABA receptors are not the primary molecular target and both drugs increase high-frequency activity of the electroencephalogram. However, despite these differences at the molecular and neurophysiological level, recent data from our laboratory suggest that these drugs may have mechanistic similarities to GABAergic anesthetics at the level of brain networks. Our long-term goal is to discover fundamental neuroscientific principles of anesthesia and analgesia that can be monitored in the perioperative period. The objective for this application is to identify-using functional magnetic resonance imaging (fMRI), electroencephalography (EEG), cortical multielectrode array recordings, and graph-theoretical analysis-the network-level mechanisms of ketamine and nitrous oxide at analgesic and anesthetic doses. Our central hypothesis is that ketamine and nitrous oxide alter network modularity (i.e., the level of integration of cortical "modules") and network efficiency. We specifically hypothesize that lower doses of these drugs increase network efficiency and disrupt pain processing-resulting in analgesia-and that higher doses decrease network efficiency and disrupt cortical representation-resulting in anesthesia. The rationale for the proposed studies extends beyond determining how these particular drugs work. An improved understanding of the network effects of these unique agents could lead to a more fundamental understanding of general anesthetic and analgesic mechanisms. We plan to test our central hypothesis by accomplishing the following specific aims: 1. Identify dose-dependent changes in brain networks using combined fMRI/EEG studies in healthy volunteers receiving ketamine or nitrous oxide. We have successfully developed a paradigm of combined fMRI/EEG in humans receiving anesthetic drugs, with preliminary data supporting our central hypothesis. In the proposed studies we will assess brain responses to ketamine or nitrous oxide at subanesthetic and anesthetic doses, with a focus on network measures such as modularity, efficiency, and hub structure. 2. Assess dose-dependent changes in sensorimotor representations using cortical array recordings in nonhuman primates receiving ketamine or nitrous oxide. We have obtained preliminary evidence that primary cortical representations can persist during ketamine anesthesia, while the cross-modal sensory representation normally found during waking is abolished (e.g., elimination of secondary sensory representation in M1). This innovative study design is the first to measure cognitive representation in brain networks after exposure to anesthetic drugs, as opposed to current techniques of measuring surrogates such as functional connectivity.