眼球运动
扁桃形结构
快速眼动睡眠
非快速眼动睡眠
心理学
多导睡眠图
神经科学
睡眠阶段
睡眠神经科学
睡眠(系统调用)
睡眠开始
慢波睡眠
听力学
睡眠纺锤
K-络合物
脑电图
医学
精神科
失眠症
操作系统
计算机科学
作者
María Corsi‐Cabrera,Francisco Velasco,Yolanda del Río‐Portilla,Jorge L. Armony,David Trejo‐Martínez,Miguel Ángel Guevara,Ana Luisa Velasco
摘要
The amygdaloid complex plays a crucial role in processing emotional signals and in the formation of emotional memories. Neuroimaging studies have shown human amygdala activation during rapid eye movement sleep (REM). Stereotactically implanted electrodes for presurgical evaluation in epileptic patients provide a unique opportunity to directly record amygdala activity. The present study analysed amygdala activity associated with REM sleep eye movements on the millisecond scale. We propose that phasic activation associated with rapid eye movements may provide the amygdala with endogenous excitation during REM sleep. Standard polysomnography and stereo-electroencephalograph (SEEG) were recorded simultaneously during spontaneous sleep in the left amygdala of four patients. Time-frequency analysis and absolute power of gamma activity were obtained for 250 ms time windows preceding and following eye movement onset in REM sleep, and in spontaneous waking eye movements in the dark. Absolute power of the 44-48 Hz band increased significantly during the 250 ms time window after REM sleep rapid eye movements onset, but not during waking eye movements. Transient activation of the amygdala provides physiological support for the proposed participation of the amygdala in emotional expression, in the emotional content of dreams and for the reactivation and consolidation of emotional memories during REM sleep, as well as for next-day emotional regulation, and its possible role in the bidirectional interaction between REM sleep and such sleep disorders as nightmares, anxiety and post-traumatic sleep disorder. These results provide unique, direct evidence of increased activation of the human amygdala time-locked to REM sleep rapid eye movements.
科研通智能强力驱动
Strongly Powered by AbleSci AI