The Impact of Sleep on Network Coding and Perceptual Performance

项目摘要/摘要 尽管睡眠通常被认为是生存所必需的，但睡眠所通过的神经机制 对大脑功能的影响在很大程度上是未知的。睡眠是否构成了大脑处于“安静”的被动状态？ 或者，它对后续任务中的网络编码和行为是否起到重要作用？即使是在 睡眠的功能意义还没有被很好地理解，可获得的数据表明 即使在短暂的午睡后，学习和记忆也会有所改善。一个需要理解的关键问题 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。我们将首次解决这些问题，方法是检查是否有简单的 睡眠(休息20分钟)会影响视觉感知能力和视觉信息的编码 神经元群。我们建议在两个视觉皮层同时使用多电极记录 清醒行为猴脑区(V1和V4)研究神经元群体中的动力学和编码 睡眠前、睡中、睡后及其对知觉表现的影响。目标1将研究如何 感觉体验通过决定(I)如何完成任务来改变休息时网络活动的结构 暴露改变了静息期间神经元在网络上的相关性分布，以及(Ii)如果细胞 在刺激暴露期间被共同激活，在随后的休息中更有可能被重新激活。目标2将 检查短暂睡眠是否通过以下方式影响单个神经元和网络的后续刺激编码 确定(I)休息后单个神经元的辨别能力是否得到改善，以及(Ii)是否和 休息后整个网络中的相关活动如何修改。通过对人口反应的解码，我们 将决定(Iii)神经元群体是否在休息后编码更多的信息，以及(Iv)是否以及如何编码 REST改变了单个神经元和局部群体活动之间的同步性。Aim 3将审查 休息是否通过决定(I)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功能是否得到改善 性能是相关的，(Iii)睡眠期间的LFP活动和峰-LFP同步是否 与休息后的行为表现相关，(Iv)是否与 休息以及网络和行为性能的改善。我们的研究有可能 促进我们对休息和睡眠背后的神经机制的理解，从而提供未来 改善睡眠障碍对认知能力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。

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.