非快速眼动睡眠的同步EEG-fMRI研究

Well sleep is essential part for a person's health and wellbeing. However, with the acceleration of life speed, millions of people suffer varied sleep disorders, especially the lack of deep sleep.The stage two of non-rapid eye movement sleep (S2) is an important transitions phase between light sleep and deep sleep. S2 has rich electrophysiological characteristics, such as sleep spindles and k-complex, but their physiological properties are unclear. By simultaneous EEG-fMRI recording of the normal subjects, this project studies the sleep stage transitions and the influence of sleep deprivation on visual attention task, and develops some suitable data-processing methods for state signal. This research will focuss on the resting-state networks of S2, especially the major brain regions affected by sleep deprivation.The lanching of this project has profound theoretical significance for elucidating the neural mechanism of conscious state conversion, and will provide new ideas for the diagnosis and treatment of the sleep disorders.

健康的身心需要良好的睡眠，而随着生活节奏加快，我国存在睡眠障碍的人群不断增加，深度睡眠的缺乏是其中一个重要原因。非快速眼动睡眠第二期是睡眠转换的十字路口：由此睡眠可能转浅或加深，意识状态也由此发生变化。该时相脑电信号多纺锤波、K复合波等，但各个成分的生理意义尚不清楚。本项目拟通过对正常被试睡眠过程的同步EEG-fMRI记录，并结合视觉注意任务、睡眠剥夺任务，发展适合于睡眠分析的数据处理方法，研究睡眠第二期特征脑电波产生的神经机理以及它们在时相转换过程中的作用，探寻睡眠剥夺作用的主要脑区和对注意等认知的影响。该项目的开展，对阐明意识状态转换的神经机制具有深刻的理论意义，并有可能为临床睡眠障碍的诊断和治疗提供全新的思路。

非快速眼动睡眠是意识转换的关键时期。本项目采用同步EEG-fMRI技术，探讨了该时期脑活动的无标度性，并结合睡眠剥夺研究了默认网络的结构改变。发现睡眠区别于清醒期的关键脑区是丘脑，而EEG信号的无标度性可反映丘脑fMRI信号的无标度性。观察到默认网络内部节点间功能连接在睡眠剥夺后的减弱，但从全脑网络来看剥夺后的局部效率和全局效率都有提高。在EEG/fMRI融合技术方面我们提出了大尺度网络连接与头表EEG节律相结合的分析思路，发展了基于独立成分分析的多模态融合框架。本项目的执行发表了包括NeuroImage, Hum Brain Mapp, Soc Cogn Affect Neurosci等杂志在内的SCI检索论文10篇，培养硕士生5名。发表专著一部，并获得国家发明专利一项。