Sleep and neuroplasticity in complex training

该研究项目的主要目标是更深入地了解睡眠中播放的声音是如何增强学习和记忆的。2013年，Ngo等人证明，睡眠期间慢振荡（so）的强度和纺锤波的密度可以通过精确定时的声音爆发来提高，这种技术被称为闭环听觉刺激（CLAS）。增强与第二天的记忆性能改善有关。因此，CLAS提供了一种探索睡眠记忆功能的方法，但声音影响大脑活动的机制尚不清楚，它对现实生活任务的影响（这比迄今为止研究的简单范例要复杂得多）也是未知的。我已经开发了一套独特的技能来理解这些过程：具有复杂训练任务的经验，CLAS，以及使用MEG对清醒和睡眠期间任务引起的振荡进行全脑源建模；这项工作将成为我新实验室研究方向的基础。我提出三个不同的目标：目标一：闭环听觉刺激（CLAS）如何增强慢振荡（SOs）？为了验证以下假设：1)信号从初级听觉皮层向次级听觉皮层的传播取决于正在进行的听觉皮层的阶段；并且，使用源定位连接分析，ii)诱发反应和内源性皮层SOs之间的关键相互作用通过唤醒过程发生在皮层而不是脑干。目的二：非快速眼动睡眠中复杂任务巩固的神经关联是什么？我们将在我们之前开发的基于钢琴的学习范式中建立睡眠依赖记忆巩固的影响（即序列，时间准确性），并使用EEG表征唤醒任务表现和睡眠巩固的时空特征。我们预测SO和纺锤体活动的增加与第二天任务的改善成正比。目标三：我们可以通过CLAS来提高复杂的学习吗？有了在I和II中获得的知识，我们将使用MEG的更高空间分辨率来检验CLAS以依赖于使用的方式增强整合的假设。我们假设与无刺激相比，CLAS会增加任务相关脑区的SO振幅和纺锤体密度。由于CLAS在健康应用方面具有相当大的潜力，因此有必要更深入地了解声音影响内源性大脑活动和记忆的机制。我们的研究结果将与许多试图利用睡眠依赖性巩固的团体直接相关，并可能最终导致更好的治疗方法的发展，以应对睡眠的认知益处，这些益处可能会因疾病和衰老而降低。我们的研究结果也将进一步加深我们对睡眠记忆功能的理解。

The principal goal of the research program is to gain a deeper understanding of how learning and memory can be enhanced by sound presented during sleep. In 2013, Ngo at al. demonstrated that the strength of slow oscillations (SOs) and the density of spindles during sleep could be boosted by precisely timed sound bursts, a technique known as closed-loop auditory stimulation (CLAS). Enhancement was related to memory performance improvements the following day. CLAS thus provides a means of probing the memory function of sleep, but the mechanism through which sound affects brain activity is not understood, and its effects on real-life tasks (which are far more complex than the simple paradigms studied to date) are unknown. I have developed a skill set that is uniquely suited to understanding these processes: experience with complex training tasks, CLAS, and whole-brain source modeling of oscillations induced by tasks during wakefulness and those during sleep, using MEG; this work will form the basis of my new lab's research direction. I propose three distinct aims: Aim I: How does closed-loop auditory stimulation (CLAS) enhance slow oscillations (SOs)?  We will deliver noise bursts during NREM sleep in the MEG to target phases of SOs, in order to test the hypotheses: i) that signal propagation from the primary auditory cortex to secondary regions depends on the phase of ongoing SOs; and, using source-localized connectivity analysis, ii) that the critical interaction between evoked responses and endogenous cortical SOs takes place in the cortex vs. in the brainstem via processes of arousal. Aim II: What are the neural correlates of complex task consolidation in NREM sleep?  We will establish an effect of sleep-dependent memory consolidation in a piano-based learning paradigm that we previously developed (i.e. on sequence, timing accuracy), and characterize spatiotemporal signatures of wake task performance and sleep consolidation using EEG. We predict an increase in SO and spindle activity which is proportional to next-day task improvement. Aim III: Can we enhance complex learning with CLAS? Armed with the knowledge gained in I and II, we will use MEG's higher spatial resolution to test the hypothesis that CLAS enhances consolidation in a use-dependent fashion. We hypothesize that CLAS as compared with no stimulation will increase SO amplitude and spindle density within task-related brain regions. Because CLAS has considerable potential for health applications, a deeper understanding of the mechanisms through which sound can influence endogenous brain activity and memory is necessary. Our results will be directly relevant to the many groups who are trying to harness sleep-dependent consolidation, and may eventually lead to the development of better therapies to the cognitive benefits of sleep that can be degraded by disease and aging. Our results will also further our understanding of the memory function of sleep.