Elucidating dynamic reorganization of whole-brain networks during anesthetic-induced unconsciousness

项目概要 尽管对各种麻醉剂的分子基础有了相当清楚的了解，但系统级 麻醉剂引起意识丧失的神经机制仍然难以捉摸。实质性证据 表明麻醉引起的无意识（AIU）是一种大脑网络现象。出现麻醉剂 通过破坏大规模大脑网络的信息交换来抑制意识。因此，要 理解AIU底层的系统级机制，关键一步是全面表征 全脑网络如何动态重组以支持不同的信息交换模式 在AIU期间。这个问题可以使用静息态功能磁共振成像（rsfMRI）来研究，如 它通过全脑视野测量区域间的功能连接（FC）。特别是， 将 rsfMRI 应用于动物模型为研究 AIU 提供了几个优势：1) 颅内电生理学 可以与动物体内的 rsfMRI 同时测量，以揭示特征性神经活动/连接性 AIU 期间的模式和相应的全球大脑网络动态； 2) 不同的麻醉剂可以 应用于同一组动物，以便不同动物共享 AIU 期间共同的大脑网络变化 可以识别麻醉剂（如果有）； 3) 麻醉深度易于控制。然而，一个主要的 充分实现这些潜力的障碍是动物功能磁共振成像实验通常使用麻醉来 首先固定动物。因此，很难揭示大脑网络如何从清醒状态发生变化。 状态进入无意识状态。为了弥合这一差距，我们小组制定了进行 在完全清醒的动物中进行 rsfMRI 实验。此外，我们还整合了清醒大鼠 rsfMRI 方法 具有多层电生理学记录和动物行为，这使我们能够直接连接大脑 网络重组以并发神经活动模式和动物意识状态。通过使用 rsfMRI、电生理学和行为测试，这笔赠款的主要目标是全面 阐明全脑功能网络的动态重组以支持不同的模式 从清醒状态到无意识状态的信息交换。四种麻醉剂，包括异氟烷、 将测试异丙酚、氯胺酮和右美托咪定。在目标 1 中，我们将识别特征神经网络 不同稳定意识水平下的活动和大脑连接模式。在目标 2 中，我们将 系统地表征 AIU 期间大脑网络的拓扑变化。在目标 3 中，我们将阐明 特定层的皮层活动和连接模式，以及丢失和丢失期间的大脑网络动态 意识恢复。成功完成拟议的研究将提供全面的 AIU 期间全脑网络如何动态重新配置的框架。鉴于FC之间的紧密联系 和意识状态，它将广泛揭示意识的神经基础，并帮助揭示 指示意识水平的生物标记。

Project Summary Despite fairly clear understanding on the molecular basis of various anesthetic agents, the systems-level neural mechanism by which anesthetics induce unconsciousness remains elusive. Substantial evidence suggests that anesthetic-induced unconsciousness (AIU) is a brain network phenomenon. Anesthetics appear to suppress consciousness by disrupting information exchange across large-scale brain networks. Therefore, to understand the systems-level mechanism underlying AIU, a critical step is to comprehensively characterize how whole-brain networks dynamically reorganize to support different patterns of information exchange during AIU. This issue can be studied using resting-state functional magnetic resonance imaging (rsfMRI), as it measures between-region functional connectivity (FC) with a whole-brain field of view. In particular, applying rsfMRI to animal models offers several advantages for studying AIU: 1) Intracranial electrophysiology can be concurrently measured with rsfMRI in animals to reveal characteristic neural activity/connectivity patterns and the corresponding global brain network dynamics during AIU; 2) distinct anesthetic agents can be applied to the same group of animals so that common brain network changes during AIU shared by different anesthetics, if any, can be identified; and 3) anesthetic depths can be easily manipulated. However, a major obstacle to fully realize these potentials is that animal fMRI experiments typically use anesthesia to immobilize animals first. Consequently, it is very difficult to reveal how brain networks change from the awake state into an unconscious state. To bridge this gap, our group has established the approach of conducting rsfMRI experiments in fully awake animals. In addition, we have integrated our awake rat rsfMRI approach with multi-laminar electrophysiology recording and animal behavior, which allows us to directly link brain network reorganization to concurrent neural activity patterns and animal’s consciousness states. By using rsfMRI, electrophysiology and behavioral tests, the primary objective of this grant is to comprehensively elucidate the dynamic reorganization of the whole-brain functional network to support different patterns of information exchange from the awake state into an unconscious state. Four anesthetics, including isoflurane, propofol, ketamine and dexmedetomidine will be tested. In Aim 1, we will identify characteristic neural activity and brain connectivity patterns at different steady consciousness levels. In Aim 2, we will systematically characterize topological changes of brain networks during AIU. In Aim 3, we will elucidate layer-specific cortical activity and connectivity patterns, as well as brain network dynamics during the loss and recovery of consciousness. Successful completion of the proposed research will provide a comprehensive framework of how whole-brain networks dynamically reconfigure during AIU. Given the tight link between FC and conscious states, it will broadly shed light onto the neural basis of consciousness, and help reveal biomarkers to indicate levels of consciousness.