脾后皮质
皮质(解剖学)
异氟醚
无意识
神经科学
染色质结构重塑复合物
医学
体感系统
氯胺酮
视皮层
大脑皮层
麻醉剂
拟精神病
异丙酚
细胞结构
扣带回前部
麻醉
生物
内科学
NMDA受体
认知
受体
基因
核小体
组蛋白
生物化学
作者
Mu-Chao Xia,Chengyu Wang,Ling Jiang,Kai Wang,Changhong Miao,Chao Liang
标识
DOI:10.1213/ane.0000000000007649
摘要
BACKGROUND: Anesthesia-induced loss of consciousness (LOC) is associated with alterations in cortical synchronization and desynchronization in various cortical regions. However, the precise spatiotemporal dynamics across the entire cortex and their role in the LOC remain unclear. This study utilized advanced imaging techniques to investigate these cortical dynamics under the action of different anesthetics. METHODS: We used Thy1-GCaMP6s mice with surgically prepared transparent skulls to observe cortical Ca 2+ signals using widefield microscopy. Functional connectivity analysis was performed, and the primary spatial representations of the different frequency signal components were examined under anesthesia induced by ketamine, propofol, and isoflurane. RESULTS: All drugs enhanced 1.5 to 2.5 Hz signal oscillations in the retrosplenial cortex (RSC), making the 1.5 to 2.5 Hz signal oscillation power in the retrosplenial cortex significantly higher than that in other cortical regions (ketamine (mean ± SD: 1. 58 ± 0.06 vs 0. 27 ± 0.10, -0. 44 ± 0.02 and -0. 36 ± 0.06 for the retrosplenial cortex (RSC) vs the primary motor cortex (MOp), the primary somatosensory cortex (SSp) and the primary visual cortex (VISp), P < .001; propofol: 1. 36 ± 0.06 vs 0. 50 ± 0.09, -0. 34 ± 0.04 and -0. 20 ± 0.11 isoflurane: 1. 39 ± 0.12 vs 0. 30 ± 0.07, -0. 14 ± 0.19 and -0. 20 ± 0.14). Moreover, ketamine and isoflurane was associated with a structured signaling pattern. CONCLUSIONS: The general anesthetics induced unique cortical signal patterns, with the RSC emerging as a key region in which specific oscillatory patterns manifested. The observed 1.5 to 2.5 Hz oscillations in the RSC under different anesthetic conditions suggest a common underlying mechanism for anesthesia-induced LOC. Understanding these spatiotemporal patterns can help improve the monitoring and management of anesthesia.
科研通智能强力驱动
Strongly Powered by AbleSci AI