The Impact of Sleep on Network Coding and Perceptual Performance

睡眠对网络编码和感知性能的影响

• 批准号: 9565710
• 负责人: VALENTIN DRAGOI
• 金额: $ 13.3万
• 依托单位: UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-08-01 至 2018-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9565710
• 关键词: Address; Affect; Animals; Area; Behavior; Behavioral; Biological Neural Networks; Brain; Cells; Code; Complex; Data; Discrimination; Electrodes; Exhibits; Eye; Future; Goals; Human; Image; Income; Individual; Jaw; Learning; Macaca; Measures; Memory; Monkeys; Napping; Neurons; Performance; Play; Population; Prevalence; Property; Prosthesis; Research; Rest; Role; Sensory; Sleep; Sleep Disorders; Stimulus; Stream; Structure; Testing; Time; Visual; Visual Cortex; Work; area V1; awake; behavior influence; cognitive performance; experience; experimental study; improved; neuromechanism; neuronal circuitry; nonhuman primate; practical application; receptive field; response; visual coding; visual information

PROJECT SUMMARY/ABSTRACT Although sleep is generally believed to be essential for survival, the neuronal mechanisms by which it affects brain function are largely unknown. Does sleep constitute a passive state in which the brain is `quiet' or does it play an important role for network coding and behavior in subsequent tasks? Even though the functional significance of sleep is not well understood, the available data suggest that significant improvements in learning and memory are found even after brief naps. A critical issue for understanding sleep function is whether and how it impacts the accuracy of neuronal network computations to improve behavioral performance. We will address these issues for the first time by examining whether brief sleep (20 min of rest) influences visual perceptual performance and the coding of visual information across neuronal populations. We propose to use multiple-electrode recording simultaneously in two visual cortical areas (V1 and V4) of awake behaving monkey to examine the dynamics and coding in neuronal populations before, during, and after sleep, and their impact on perceptual performance. Aim 1 will examine how sensory experience changes the structure of network activity during rest by determining (i) how task exposure modifies the distribution of neuronal correlations across networks during rest, and (ii) if cells that are coactivated during stimulus exposure are more likely to be reactivated during subsequent rest. Aim 2 will examine whether brief sleep influences subsequent stimulus coding by individual neurons and networks by determining (i) whether single neuron discrimination performance is improved after rest, and (ii) whether and how correlated activity across the network is modified after rest. By decoding the population response we will determine (iii) whether neuronal populations encode more information after rest, and (iv) whether and how rest changes the synchrony between individual neurons and local population activity. Aim 3 will examine whether rest influences the relationship between neuronal and behavioral performance by determining (i) whether behavioral performance is improved after rest, (ii) whether the post-sleep neuronal and behavioral performance are correlated, (iii) whether LFP activity and spike-LFP synchronization during sleep are correlated with post-rest behavioral performance, (iv) whether there is a relationship between the amount of rest and the improvement in network and behavioral performance. Our research has the potential to advance our understanding of the neural mechanisms underlying rest and sleep and thus provide future solutions to ameliorate the detrimental effects of sleep disorder on cognitive performance, including practical applications for non-invasive neuronal prosthetic devices.

项目概要/摘要 尽管人们普遍认为睡眠对于生存至关重要，但睡眠的神经机制 影响大脑功能的情况在很大程度上尚不清楚。睡眠是否构成大脑“安静”的被动状态 或者对后续任务中的网络编码和行为起到重要作用？尽管 睡眠的功能意义尚不十分清楚，现有数据表明， 即使在短暂的小睡之后，学习和记忆力也会得到改善。理解的一个关键问题 睡眠功能是指它是否以及如何影响神经网络计算的准确性 提高行为表现。我们将通过检查是否简短来首次解决这些问题 睡眠（休息 20 分钟）影响视觉感知表现和视觉信息编码 神经元群。我们建议在两个视觉皮层同时使用多电极记录 清醒行为猴子的区域（V1 和 V4），用于检查神经元群体的动态和编码 睡眠前、睡眠中和睡眠后，以及它们对知觉表现的影响。目标 1 将研究如何 感官体验通过确定（i）任务如何改变休息期间的网络活动结构 暴露会改变休息期间神经元相关性在网络中的分布，并且（ii）如果细胞 在刺激暴露期间被共同激活的细胞更有可能在随后的休息期间被重新激活。目标2将 通过以下方式检查短暂的睡眠是否会影响单个神经元和网络的后续刺激编码 确定（i）休息后单神经元辨别能力是否有所改善，以及（ii）是否和 休息后如何修改网络上的相关活动。通过解码人群反应，我们 将确定（iii）神经元群体在休息后是否编码更多信息，以及（iv）是否以及如何编码 休息改变了个体神经元和局部群体活动之间的同步性。目标 3 将检查 通过确定 (i) 休息是否影响神经元和行为表现之间的关系 休息后行为表现是否得到改善，（ii）睡眠后神经元和行为是否 (iii) 睡眠期间的 LFP 活动和峰值 LFP 同步是否相关 与休息后行为表现相关，(iv) 运动量与休息后行为表现之间是否存在关系 休息以及网络和行为表现的改善。我们的研究有潜力 增进我们对休息和睡眠背后的神经机制的理解，从而为未来提供帮助 改善睡眠障碍对认知表现的不利影响的解决方案，包括 非侵入性神经假体装置的实际应用。