全身麻醉神经机制的脑网络研究

Currently，the therapeutic indexes of clinical drugs for general anesthesia are very low, and anesthetic accidents during surgery and intraoperative awareness occur occasionally. The root cause of these problems is that the brain mechanism of general anesthesia is not fully elucidated..By means of functional imaging and multi-modal information fusion technology, this project aims to explore the neural mechanism of general anesthesia by using brain network analysis. The research programs are designed to focus on different general anesthesia groups, and the human and animal experiments will be carried out respectively. The extracted EEG/fMRI information is integrated into spatial and temporal configurations in order to complete the brain functional network modeling in terms of different general anesthetic components: to reveal the neural mechanism of pain caused by mechanical stimulation and the analgesia of the opioid analgesic fentanyl; to analysis the characteristics of the brain network before and after the loss of consciousness caused by hypnotic sedative etomidate; to investigate the brain network performance of implicit memory and explicit memory affected by propofol in order to understand the brain mechanism caused by memory loss; to explore the neural network pathways during the process of anesthesia and awakening; to propose a new set of quantitative indicators based on the network analysis of the anesthetic component, which could express the components of general anesthesia respectively, including the analgesic index, consciousness disappear index and forgetting index to reflect the depth of anesthesia in a more scientific and comprehensive manner..The study of this project will provide a new perspective in exploring the nerve mechanism of general anesthesia, and it is also important to deepen our understanding of brain function and regulatory mechanism.

目前临床使用的全麻药物治疗指数很低，手术过程中麻醉意外和术中知晓时有发生。这些问题存在的根本原因是全身麻醉的脑机制没有完全阐明。.借助于功能影像和多模态信息融合技术，本项目旨在从脑网络分析的角度探讨全身麻醉的神经机制。拟以不同全麻组分为侧重点设计研究方案，分别开展人体与动物实验，将提取的EEG/fMRI信息时空融合，完成不同全麻组分的脑功能网络建模，揭示机械性刺激疼痛及阿片类药芬太尼镇痛的神经机制；分析催眠镇静药依托咪酯所致意识消失前后的脑网络特征；研究丙泊酚影响内隐记忆与外显记忆的脑网络表现，了解其致遗忘的脑机制；探究麻醉过程与苏醒过程的神经网络通路；基于全麻组分的脑网络分析，提出一组全新的能分别表达各全麻组分的定量指标，包括镇痛指数、意识消失指数和遗忘指数等，以期更科学全面地反映麻醉深度。.本项目的研究将为全身麻醉神经机制的探索提供新视角，对加深理解大脑的功能和调控机制也有重要意义。

借助于EEG、ERP等研究手段，开展了静息态与任务态实验，分析对比任务态多模态信号的特征确定网络节点，构建功能性、因效性脑网络，结合EEG/ERP时空信息融合的分析方法，探索了全身麻醉过程中麻醉药物作用的神经机制。主要完成了以下几点工作：.1）确定典型麻醉药丙泊酚发生作用的神经网络时空特征，确定了药物作用的相关靶点、网络连接及其变化规律；2）设计了听觉任务刺激下的麻醉作用机制研究的实验新模式，探讨了麻醉过程中听觉皮层的不同功能；3）从影像网络分析角度探究麻醉过程与苏醒过程的神经网络通路，从脑网络连接的角度为相关科学问题给出新论据。4）对脑网络分析方法进行了改进。.本项目研究有以下重要发现：.1）构建麻醉诱导与麻醉恢复在同一麻醉状态下的脑网络，并计算其典型测度，探讨麻醉现象的迟滞效应与麻醉诱导时间、麻醉恢复时间的关系。结果发现随着麻醉深度的变浅，迟滞效应逐渐变大。该结果可以帮助改进麻醉药物的注药模型使得靶控输注更精准。2）利用溯源脑电时间序列构建脑网络。通过清醒状态下两种刺激所诱发长短连接数目的比较，发现偏差刺激会在右侧额叶以及颞叶诱发更多的脑区间信息同步。通过与麻醉状态对比，发现偏差刺激会诱发双侧额叶、顶叶等高级皮层的信息同步。3）利用听觉Oddball实验范式的事件相关电位P300构建了基于互相关的功能性网络，探索各导联间两两序列之间最大互相关值与波幅的相关及最大互相关值对应的延时规律；提出了一个适用的ERP复杂网络构建方法，计算并分析了该网络的典型测度与P300波幅、潜伏期的相关性。4）建立一个利用术前脑网络特征实现对丙泊酚药物个体敏感性的预测模型。通过图论的方法分析大脑的网络水平，用网络典型测度反映大脑的全局和局部活动，结果发现术前的脑网络水平可以对丙泊酚诱导时间长短进行预测。麻醉师可以根据术前的脑网络指标对患者麻醉用药量进行调整，降低麻醉用药风险。