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The first night effect of sleep and visual plasticity

睡眠的初夜效应与视觉可塑性

基本信息

批准号：
9761539
负责人：
YUKA SASAKI
金额：
$ 20.31万
依托单位：
BROWN UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-09-01 至 2021-08-31
项目状态：
已结题

项目摘要

Summary Visual perceptual learning (VPL) is defined as a long-term increase in visual performance as a result of visual experiences. The purpose of the current R21 resubmitted proposal is to advance the understanding of the mechanisms underlying sleep-dependent performance improvement (SDPI) in VPL. This may, in turn, lead to interventions to improve the efficiency of visual skills with healthy individuals and of rehabilitation with people having sleep problems. A prevailing view is that the role of sleep in SDPI is to merely enhance plasticity states triggered by training. However, our preliminary data suggest that even without prior training, plasticity states occur in early visual areas specifically during sleep stage N3. In contrast to the prevailing view, this raises the novel possibility that without training, activity during sleep stage N3 causes plasticity states (sleep-based plasticity). To test this possibility, we will specifically examine how delta activity (1-4 Hz spontaneous oscillations) during sleep stage N3 is involved in SDPI of VPL. However, there are 2 potential difficulties. One is to isolate the effect of activity in a certain sleep stage. Commonly used methods such as sleep-stage deprivation and an intake of a medicine may influence subject’s emotional and intellectual qualities as well as non-targeted sleep stages. To overcome this difficulty, we will use the phenomenon called the first night effect (FNE) in which delta activity in early visual areas during sleep stage N3 selectively reduced during the first sleep session in an unfamiliar environment. By comparing plasticity states during the first and second sleep sessions, we could better isolate the effect of activity in an involved brain region during sleep stage N3 on SDPI. The other difficulty is that there has been no effective method to directly specify plasticity states during sleep in the human brain. To examine plasticity states without training that induce performance changes, using magnetic resonance spectroscopy during sleep, we will measure an excitatory-inhibitory (EI) ratio, which is defined by the ratio of glutamate/gamma-aminobutyric acid concentrations in early visual areas. An EI ratio has been shown to be correlated with the degree of plasticity in VPL. Thus, by measuring EI ratios during sleep, we can examine the degree of plasticity states. We will test the following two specific aims. Aim 1 will address the question as to whether there is sleep-based plasticity that occurs without training- based plasticity by testing the hypothesis. We will first test whether the EI ratio during sleep stage N3 is correlated with delta activity without any preceding visual training. Then, we will examine whether stronger delta activity and a higher EI ratio indeed lead to greater VPL. Aim 2 will address the question as to how much sleep-based plasticity and training-based plasticity contribute to SDPI by testing the hypothesis: Both of the EI ratio changes for sleep-based plasticity and training-based plasticity significantly contribute to SDPI.

摘要视觉知觉学习(VPL)被定义为视觉表现的长期提高经历。目前重新提交的R21提案的目的是促进对 VPL中睡眠依赖绩效改善(SDPI)的潜在机制。这反过来可能会导致提高健康人视觉技能和人的康复效率的干预措施有睡眠问题。一种流行的观点认为，睡眠在SDPI中的作用仅仅是增强可塑性状态由训练引发的。然而，我们的初步数据表明，即使没有事先训练，可塑性状态发生在早期视觉区域，特别是在睡眠阶段N3。与主流观点不同的是，这引发了新的可能性是，在没有训练的情况下，睡眠阶段N3的活动会导致可塑性状态(基于睡眠可塑性)。为了测试这种可能性，我们将专门研究增量活动(1-4赫兹自发)如何在睡眠阶段，N3参与了VPL的SDPI。然而，有两个潜在的困难。一就是分离出某一睡眠阶段活动的影响。常用方法，如睡眠阶段剥夺和服用药物可能会影响受试者的情绪和智力品质以及非定向睡眠阶段。为了克服这一困难，我们将使用称为首夜效应的现象 (FNE)，睡眠阶段N3的早期视觉区域的增量活动在第一阶段选择性地减少在不熟悉的环境中睡觉。通过比较第一次和第二次睡眠中的可塑性状态会话中，我们可以更好地分离睡眠阶段N3中涉及的大脑区域的活动对 SDPI。另一个困难是，还没有有效的方法来直接确定塑性状态在人脑里睡觉。要在不经过培训的情况下检查导致性能更改的可塑性状态，请使用磁共振波谱在睡眠中，我们将测量兴奋抑制(EI)比率，这是定义为谷氨酸/γ-氨基丁酸在早期视觉区域的浓度之比。一个EI比率已证明与VPL的可塑性程度有关。因此，通过测量睡眠期间的EI比率，我们可以检测塑性状态的程度。我们将测试以下两个具体目标。目标1将解决这样一个问题，即是否存在基于睡眠的可塑性，这种可塑性在没有训练的情况下发生。通过检验假设建立在可塑性基础上。我们将首先测试睡眠阶段N3的EI比率是否与未接受过任何视力训练的三角洲活动有关。然后，我们将考察更强的 Delta活动和较高的EI比率确实会导致更大的VPL。目标2将解决基于睡眠的可塑性和基于训练的可塑性对可塑性有多大贡献的问题通过检验假设得出SDPI：睡眠可塑性和训练可塑性的EI比率都发生了变化可塑性对SDPI有显著贡献。