默认网络是静息状态自发活动较强的大脑结构。它的子区域海马和内侧前额叶是记忆巩固的关键脑区，同时静息态也被证明伴随有记忆巩固现象，我们推测默认网络是睡眠依赖记忆巩固的核心。本项目拟借助同步EEG-fMRI在时空分辨率上的优势，研究默认网络参与睡眠依赖记忆巩固的神经机制。包括：1)构建默认网络活动的电生理指标，应用EEG源定位和跨频段耦合分析，揭示记忆巩固的动态过程；2)应用滑动时间窗和模块分析，研究默认网络参与静息态和睡眠过程记忆巩固的异同，揭示记忆在昼夜更迭中得以强化的基本原理；3)通过多模态信息融合，揭示记忆类型和睡眠阶段等因素对睡眠依赖记忆巩固的影响。该项目的开展将为脑功能探测开发新的动态分析技术，对阐明睡眠依赖记忆巩固的神经机制具有深刻的理论意义，并最终可能为治疗学习记忆相关障碍提供全新的思路。

The default mode network (DMN) is a brain structure persisting activity during the resting state. As resting state has been demonstrated with function of memory consolidation and sub-regions of DMN, the hippocampus and medial prefrontal cortex, are the key regions of memory consolidation, we hypothesize that the DMN is the core structure of sleep-dependent memory consolidation. With the high resolution in temporal and spatial domain of simultaneous EEG-fMRI, we will study the neural mechanisms of the DMN-involved memory consolidation, which includes: 1) describing the dynamic process of memory consolidation based on the EEG source localization and cross-frequency coupling analysis; 2) distinguishing the functional connectivity of DMN during resting and sleep states based on the sliding time-window and module analysis to reveal the basic principles of memory enhancement within the iteration of day and night; 3) revealing the influences of types of memory and sleep stages in memory consolidation by multimodel fusion. This project will not only develop new techniques for dynamic analysis of brain function, but it also has profound theory significance to elucidate the neural mechanisms of memory consolidation. Moreover it may ultimately provide new ideas for the treatment of the learning and memory related disorders.