Sleep states are universally described throughout the animal kingdom, yet our understanding of their contribution to brain function and dysfunction remains limited. However, recent advances in neurotechnology and data analysis have extended the repertoire of tools available to tackle the study of sleep, including questions such as ‘Why do we sleep?’, ‘What brain activities are associated with sleep?’ and ‘What are the functions of sleep?’.

Driven by such methodological advances, the field of sleep research has witnessed several paradigm shifts in the last two decades, with new data providing evidence for local, in addition to global, sleep control, multiple rather than single sleep circuits and non-Hebbian in addition to associative information consolidation, among others. These developments have led to the development of new hypotheses on the evolutionary origins of sleep, its neurobiological characteristics and its clinical and societal importance. Yet, many questions remain unanswered, including the causes and consequences of the large diversity of gene expression changes observed during sleep, the relevance of spontaneous neuronal activity and the exact role of the different neuronal circuits and their dynamics during sleep.

In this special issue, 13 new studies in the field of systems-level sleep research are given a stage, together providing an overview of recent technical, methodological and theoretical innovations in the field. First, this special issue includes a series of papers reviewing sleep scoring in animals and offering new avenues to better characterize sleep stages and brain states in multiple animal species. Specifically, Genzel et al. review novel approaches to score sleep in rodents and introduce new recording and signal analysis techniques to clarify NREM sleep stages in rodents (Rayan et al., 2022). This will foster translational research on sleep. Besides the classical EEG and EMG, recent advances in tracking eye and pupil dilation across sleep–wake states can shed light on brain states in multiple animal species, as reviewed by Ungurean and Rattenborg (2023).

At the systems level, multiple cell types and circuits distributed across the whole brain support the ultradian modulation of sleep–wake states in both human and animal models. During sleep, network oscillations reflect the coordinated activity of cellular ensembles at defined frequencies. Specifically, NREM sleep is characterized by prominent slow waves, delta oscillations and spindles, which result from the cellular properties of thalamocortical and intra-cortical networks, while during REM sleep, the septo-hippocampal and intra-cortical circuits generate theta and gamma rhythms, respectively. Cirelli et al. investigated the mechanisms underlying NREM sleep slow waves in normal and pharmacological conditions and the implication of cortical somatostatin interneurons in the generation of these sleep waves (Spano et al., 2022). Visocky et al. (2023) showed that specific modulation of the thalamic reticular nucleus, a structure identified as a generator of sleep spindles, directly influences the architecture of sleep. Consistent with these findings, Cirelli et al. integrated specific cortical interneurons in a thalamocortical in silico model, providing evidence that the diversity of cells types plays a key role in the dynamics of sleep and wake states (Bugnon et al., 2022).

Aiming to further elucidate the mechanisms underlying the spatial and temporal organization of sleep oscillations, Bozic (2023) investigated the role of the thalamic nucleus reuniens in coordinating slow waves, spindles and ripples in mice. In humans, Titone et al. identified a decrease in frequency-dependent resting-state connectivity across multiple networks and frequency bands during NREM sleep and a frequency- and network-specific modulation of connectivity at the onset of REM sleep, suggesting the existence of two connectivity networks during sleep (Titone et al., 2023).

Similarly, Szalárdy et al. (2024) showed that activity of the mediodorsal thalamus contributes to the temporal association of spindles and ripples in human during NREM sleep. Importantly, such coordination predicts overnight declarative memory consolidation in humans as shown by Weiner et al. (2023), but also in associative memory in mice, as described in a study by Zhang and Chen (2024).

Coordination of sleep oscillations can be triggered by sensory stimuli such as sounds, and can promote the consolidation of memories. Although the mechanisms remain unclear, Marshall et al. provide evidence that such stimuli alter hippocampal sharp wave-ripples as well as spindles in mice (Aksamaz et al., 2023). This emphasizes the need to better understand the difference between spontaneously- or sensory-generated oscillations and their contribution to brain plasticity. Along these lines, Jourde et al. (2023) provide a glimpse on the physiology of closed-loop auditory stimulation during sleep in humans using magnetoencephalography.

Awaking from sleep can be triggered by multiple internal and external stimuli including somato-sensory signals. Bastuji et al. (2023) showed that thalamocortical network activity, particularly in the pulvinar, acts as a predictor of arousal upon noxious stimuli during sleep.

Finally, the study of sleep has historically been associated with anaesthesia due to the similarity of some brain oscillations—for example, slow waves—between both states, the reduction of consciousness and the possibility of recording thalamocortical oscillations more easily in anaesthetized head-restrained animal models than in naturally sleeping and unrestrained animals. The study by Mondino et al. (2023) in this special issue provides evidence that evidence that the brain states between anaesthesia and sleep are different both in terms of neurophysiological mechanisms and content. Whether sleep and anaesthesia—and associated unconsciousness—are similar brain states has been long debated over the years, as illustrated by the accompanying commentary (Ward-Flanagan et al., 2023) in this special issue.

In conclusion, the studies included in this special issue collectively illustrate the recent advances in the field of sleep research and its remaining challenges.

A deeper insight into the brain and body processes that govern sleep and wakefulness, as well as the brain activities associated with sleep, will undoubtedly enhance sleep health, lead to effective treatments for sleep disorders and underscore the crucial impact of sleep on mental health and neurodegenerative diseases.

睡眠状态在整个动物界都有普遍的描述，但我们对睡眠状态对大脑功能和功能障碍的影响的了解仍然有限。然而，神经技术和数据分析的最新进展扩展了可用于解决睡眠研究的工具库，包括诸如“我们为什么睡觉？”、“哪些大脑活动与睡眠相关？”等问题。和“睡眠的功能是什么？”。

在这些方法论进步的推动下，睡眠研究领域在过去二十年中见证了几次范式转变，新数据为局部（除了全局）睡眠控制、多重而非单一睡眠回路以及非赫布睡眠控制提供了证据。关联信息整合等。这些进展导致了关于睡眠进化起源、其神经生物学特征及其临床和社会重要性的新假设的发展。然而，许多问题仍未得到解答，包括睡眠期间观察到的大量基因表达变化的原因和后果、自发神经元活动的相关性以及睡眠期间不同神经元回路及其动态的确切作用。

本期特刊收录了系统级睡眠研究领域的 13 项新研究，共同概述了该领域最新的技术、方法和理论创新。首先，本期特刊包括一系列论文，回顾了动物的睡眠评分，并提供了更好地表征多种动物物种的睡眠阶段和大脑状态的新途径。具体来说，Genzel 等人。回顾对啮齿动物睡眠进行评分的新方法，并引入新的记录和信号分析技术来阐明啮齿动物的 NREM 睡眠阶段（Rayan 等人，  2022）。这将促进睡眠的转化研究。正如 Ungurean 和 Rattenborg 所评论的（ 2023 年） ，除了经典的脑电图和肌电图之外，在跟踪睡眠-觉醒状态下的眼睛和瞳孔扩张方面的最新进展可以揭示多种动物物种的大脑状态。

在系统层面，分布在整个大脑中的多种细胞类型和电路支持人类和动物模型中睡眠-觉醒状态的超电调节。在睡眠期间，网络振荡反映了细胞群在定义频率下的协调活动。具体来说，NREM 睡眠的特点是显着的慢波、δ 振荡和纺锤体，这是丘脑皮质和皮质内网络的细胞特性造成的，而在 REM 睡眠期间，隔海马和皮质内回路会产生 θ 和 γ 节律，分别。西雷利等人。研究了正常和药理条件下 NREM 睡眠慢波的机制以及皮质生长抑素中间神经元在这些睡眠波生成中的影响 (Spano 等人，  2022 )。维索基等人。( 2023 )表明，丘脑网状核（一种被确定为睡眠纺锤波发生器的结构）的特定调节直接影响睡眠的结构。与这些发现一致的是，Cirelli 等人。在丘脑皮质计算机模型中集成了特定的皮质中间神经元，提供了证据表明细胞类型的多样性在睡眠和清醒状态的动态中发挥着关键作用（Bugnon 等人，  2022）。

为了进一步阐明睡眠振荡的空间和时间组织的机制，Bozic ( 2023 ) 研究了丘脑团聚核在协调小鼠慢波、纺锤波和波纹中的作用。在人类中，Titone 等人。发现在 NREM 睡眠期间跨多个网络和频带的频率依赖性静息态连接减少，以及在 REM 睡眠开始时频率和网络特定的连接调制，表明睡眠期间存在两个连接网络（Titone 等）等，  2023）。

同样，Szalárdy 等人。( 2024 )表明，内侧丘脑的活动有助于人类在 NREM 睡眠期间纺锤波和波纹的时间关联。重要的是，正如 Weiner 等人所表明的那样，这种协调可以预测人类在一夜之间的陈述性记忆巩固。( 2023 )，而且正如Zhang和Chen ( 2024 )的一项研究中所述，也存在于小鼠的联想记忆中。

睡眠振荡的协调可以由声音等感官刺激触发，并且可以促进记忆的巩固。尽管机制尚不清楚，Marshall 等人。提供的证据表明，此类刺激会改变小鼠海马的尖锐波波纹和纺锤体（Aksamaz 等，  2023）。这强调需要更好地理解自发或感觉产生的振荡之间的差异及其对大脑可塑性的贡献。沿着这些思路，Jourde 等人。( 2023 ) 使用脑磁图来了解人类睡眠期间闭环听觉刺激的生理学。

从睡眠中醒来可以由多种内部和外部刺激（包括体感信号）触发。巴斯图吉等人。( 2023 )表明丘脑皮质网络活动，特别是丘脑皮质网络活动，可以预测睡眠期间有害刺激的觉醒。

最后，睡眠研究历来与麻醉有关，因为两种状态之间的一些大脑振荡（例如慢波）相似，意识减弱，并且在麻醉的头部约束动物中更容易记录丘脑皮层振荡的可能性模型比自然睡眠和不受约束的动物模型更有效。蒙迪诺等人的研究。( 2023 ) 在本期特刊中提供了证据，证明麻醉和睡眠之间的大脑状态在神经生理机制和内容方面都不同。多年来，睡眠和麻醉以及相关的无意识是否是相似的大脑状态一直存在争论，正如 本期特刊中附带的评论（Ward-Flanagan 等人， 2023 ）所示。

总之，本期特刊中包含的研究共同说明了睡眠研究领域的最新进展及其尚存的挑战。

更深入地了解控制睡眠和觉醒的大脑和身体过程，以及与睡眠相关的大脑活动，无疑将增强睡眠健康，导致睡眠障碍的有效治疗，并强调睡眠对心理健康和神经退行性疾病的重要影响疾病。