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

阐明麻醉引起的无意识期间全脑网络的动态重组

• 批准号: 10621275
• 负责人: Nanyin Zhang
• 金额: $ 33.22万
• 依托单位: PENNSYLVANIA STATE UNIVERSITY, THE
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-02 至 2025-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10621275
• 关键词: Altered Level of Consciousness; Anesthesia procedures; Anesthetics; Animal Behavior; Animal Model; Animals; Biological Markers; Brain; Characteristics; Claustral structure; Conscious; Data; Development; Dexmedetomidine; Dose; Electrophysiology (science); Functional Magnetic Resonance Imaging; Goals; Grant; Graph; Immobilization; Individual; Isoflurane; Ketamine; Light; Link; Measures; Molecular; Parietal; Pattern; Property; Propofol; Rattus; Recovery; Reflex action; Research; Rest; Signal Transduction; Site; System; Testing; Thalamic structure; Unconscious State; Volatilization; Wakefulness; awake; behavior test; experimental study; flexibility; neural; neural circuit; neural network; neuromechanism; segregation; study characteristics; tool

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.

项目总结

项目成果

Gaining insight into the neural basis of resting-state fMRI signal.

• DOI: 10.1016/j.neuroimage.2022.118960
• 发表时间: 2022-04-15
• 期刊: NeuroImage
• 影响因子: 5.7
• 作者: Ma Z;Zhang Q;Tu W;Zhang N
• 通讯作者: Zhang N

Deriving causal relationships in resting-state functional connectivity using SSFO-based optogenetic fMRI.

• DOI: 10.1088/1741-2552/ac9d66
• 发表时间: 2022-11-08
• 期刊: Journal of neural engineering
• 影响因子: 4
• 作者: Han X;Cramer SR;Zhang N
• 通讯作者: Zhang N

High-frequency neuronal signal better explains multi-phase BOLD response.

• DOI: 10.1016/j.neuroimage.2023.119887
• 发表时间: 2023-03
• 期刊: NEUROIMAGE
• 影响因子: 5.7
• 作者: Zhang, Qingqing;Cramer, Samuel R.;Turner, Kevin L.;Neuberger, Thomas;Drew, Patrick J.;Zhang, Nanyin
• 通讯作者: Zhang, Nanyin

Neural underpinning of a respiration-associated resting-state fMRI network.

神经基础与呼吸相关的静止状态fMRI网络。

• DOI: 10.7554/elife.81555
• 发表时间: 2022-10-20
• 期刊: eLife
• 影响因子: 7.7
• 作者: Tu W;Zhang N
• 通讯作者: Zhang N

Brain-wide ongoing activity is responsible for significant cross-trial BOLD variability.

全脑持续活动是造成显着的跨试验 BOLD 变异的原因。

• DOI: 10.1093/cercor/bhac016
• 发表时间: 2022
• 期刊: Cerebral cortex (New York, N.Y. : 1991)
• 作者: Zhang,Qingqing;Cramer,SamuelR;Ma,Zilu;Turner,KevinL;Gheres,KyleW;Liu,Yikang;Drew,PatrickJ;Zhang,Nanyin
• 通讯作者: Zhang,Nanyin