State-dependent brainstem ensemble dynamics and their interactions with hippocampus across sleep states

Overnight neuronal plasticity and adaptation to emotional distress

Expressions such as 'sleep on it' refer to the resolution of distressing experiences across a night of sound sleep. Sleep is an active state during which the brain reorganizes the synaptic connections that form memories. This Perspective proposes a model of how sleep modifies emotional memory traces. Sleep-dependent reorganization occurs through neurophysiological events in neurochemical contexts that determine the fates of synapses to grow, to survive or to be pruned. We discuss how low levels of acetylcholine during non-rapid eye movement sleep and low levels of noradrenaline during rapid eye movement sleep provide a unique window of opportunity for plasticity in neuronal representations of emotional memories that resolves the associated distress. We integrate sleep-facilitated adaptation over three levels: experience and behaviour, neuronal circuits, and synaptic events. The model generates testable hypotheses for how failed sleep-dependent adaptation to emotional distress is key to mental disorders, notably disorders of anxiety, depression and post-traumatic stress with the common aetiology of insomnia.

The Ponto-Geniculo-Occipital (PGO) Waves in Dreaming: An Overview

Rapid eye movement (REM) sleep is the main sleep correlate of dreaming. Ponto-geniculo-occipital (PGO) waves are a signature of REM sleep. They represent the physiological mechanism of REM sleep that specifically limits the processing of external information. PGO waves look just like a message sent from the pons to the lateral geniculate nucleus of the visual thalamus, the occipital cortex, and other areas of the brain. The dedicated visual pathway of PGO waves can be interpreted by the brain as visual information, leading to the visual hallucinosis of dreams. PGO waves are considered to be both a reflection of REM sleep brain activity and causal to dreams due to their stimulation of the cortex. In this review, we summarize the role of PGO waves in potential neural circuits of two major theories, i.e., (1) dreams are generated by the activation of neural activity in the brainstem; (2) PGO waves signaling to the cortex. In addition, the potential physiological functions during REM sleep dreams, such as memory consolidation, unlearning, and brain development and plasticity and mood regulation, are discussed. It is hoped that our review will support and encourage research into the phenomenon of human PGO waves and their possible functions in dreaming.

Pontine Waves Accompanied by Short Hippocampal Sharp Wave-Ripples During Non-rapid Eye Movement Sleep

Ponto-geniculo-occipital or pontine (P) waves have long been recognized as an electrophysiological signature of rapid eye movement (REM) sleep. However, P-waves can be observed not just during REM sleep, but also during non-REM (NREM) sleep. Recent studies have uncovered that P-waves are functionally coupled with hippocampal sharp wave ripples (SWRs) during NREM sleep. However, it remains unclear to what extent P-waves during NREM sleep share their characteristics with P-waves during REM sleep and how the functional coupling to P-waves modulates SWRs. Here, we address these issues by performing multiple types of electrophysiological recordings and fiber photometry in both sexes of mice. P-waves during NREM sleep share their waveform shapes and local neural ensemble dynamics at a short (~100 milliseconds) timescale with their REM sleep counterparts. However, the dynamics of mesopontine cholinergic neurons are distinct at a longer (~10 seconds) timescale: although P-waves are accompanied by cholinergic transients, the cholinergic tone gradually reduces before P-wave genesis during NREM sleep. While P-waves are coupled to hippocampal theta rhythms during REM sleep, P-waves during NREM sleep are accompanied by a rapid reduction in hippocampal ripple power. SWRs coupled with P-waves are short-lived and hippocampal neural firing is also reduced after P-waves. These results demonstrate that P-waves are part of coordinated sleep-related activity by functionally coupling with hippocampal ensembles in a state-dependent manner.

The neurophysiologic landscape of the sleep onset: a systematic review

Background

The sleep onset process is an ill-defined complex process of transition from wakefulness to sleep, characterized by progressive modifications at the subjective, behavioural, cognitive, and physiological levels. To this date, there is no international consensus which could aid a principled characterisation of this process for clinical research purposes. The current review aims to systemise the current knowledge about the underlying mechanisms of the natural heterogeneity of this process.

Methods

In this systematic review, studies investigating the process of the sleep onset from 1970 to 2022 were identified using electronic database searches of PsychINFO, MEDLINE, and Embase.

Results

A total of 139 studies were included; 110 studies in healthy participants and 29 studies in participants with sleep disorders. Overall, there is a limited consensus across a body of research about what distinct biomarkers of the sleep onset constitute. Only sparse data exists on the physiology, neurophysiology and behavioural mechanisms of the sleep onset, with majority of studies concentrating on the non-rapid eye movement stage 2 (NREM 2) as a potentially better defined and a more reliable time point that separates sleep from the wake, on the sleep wake continuum.

Conclusions

The neurophysiologic landscape of sleep onset bears a complex pattern associated with a multitude of behavioural and physiological markers and remains poorly understood. The methodological variation and a heterogenous definition of the wake-sleep transition in various studies to date is understandable, given that sleep onset is a process that has fluctuating and ill-defined boundaries. Nonetheless, the principled characterisation of the sleep onset process is needed which will allow for a greater conceptualisation of the mechanisms underlying this process, further influencing the efficacy of current treatments for sleep disorders.

A medullary hub for controlling REM sleep and pontine waves

Rapid-eye-movement (REM) sleep is a distinct behavioral state associated with vivid dreaming and memory processing. Phasic bursts of electrical activity, measurable as spike-like pontine (P)-waves, are a hallmark of REM sleep implicated in memory consolidation. However, the brainstem circuits regulating P-waves, and their interactions with circuits generating REM sleep, remain largely unknown. Here, we show that an excitatory population of dorsomedial medulla (dmM) neurons expressing corticotropin-releasing-hormone (CRH) regulates both REM sleep and P-waves in mice. Calcium imaging showed that dmM CRH neurons are selectively activated during REM sleep and recruited during P-waves, and opto- and chemogenetic experiments revealed that this population promotes REM sleep. Chemogenetic manipulation also induced prolonged changes in P-wave frequency, while brief optogenetic activation reliably triggered P-waves along with transiently accelerated theta oscillations in the electroencephalogram (EEG). Together, these findings anatomically and functionally delineate a common medullary hub for the regulation of both REM sleep and P-waves.

Sleep sharp wave ripple and its functions in memory and synaptic plasticity

Memory is one of the fundamental cognitive functions of brain. The formation and consolidation of memory depend on the hippocampus and sleep. Sharp wave ripple (SWR) is an electrophysiological event which is most frequently observed in the hippocampus during sleep. It represents a highly synchronized neuronal activity pattern which modulates numerous brain regions including the neocortex, subcortical areas, and the hippocampus itself. In this review, we discuss how SWRs link experiences to memories and what happens in the hippocampus and other brain regions during sleep by focusing on synaptic plasticity.

Pupil Dynamics-derived Sleep Stage Classification of a Head-fixed Mouse Using a Recurrent Neural Network

The standard method for sleep state classification is thresholding the amplitudes of electroencephalography (EEG) and electromyography (EMG) data, followed by manual correction by an expert. Although popular, this method has some shortcomings: (1) the time-consuming manual correction by human experts is sometimes a bottleneck hindering sleep studies, (2) EEG electrodes on the skull interfere with wide-field imaging of the cortical activity of a head-fixed mouse under a microscope, (3) invasive surgery to fix the electrodes on the thin mouse skull risks brain tissue injury, and (4) metal electrodes for EEG and EMG recording are difficult to apply to some experimental apparatus such as that for functional magnetic resonance imaging. To overcome these shortcomings, we propose a pupil dynamics-based vigilance state classification method for a head-fixed mouse using a long short-term memory (LSTM) model, a variant of a recurrent neural network, for multi-class labeling of NREM, REM, and WAKE states. For supervisory hypnography, EEG and EMG recording were performed on head-fixed mice. This setup was combined with left eye pupillometry using a USB camera and a markerless tracking toolbox, DeepLabCut. Our open-source LSTM model with feature inputs of pupil diameter, pupil location, pupil velocity, and eyelid opening for 10 s at a 10 Hz sampling rate achieved vigilance state estimation with a higher classification performance (macro F1 score, 0.77; accuracy, 86%) than a feed-forward neural network. Findings from a diverse range of pupillary dynamics implied possible subdivision of the vigilance states defined by EEG and EMG. Pupil dynamics-based hypnography can expand the scope of alternatives for sleep stage scoring of head-fixed mice.

What are the neural mechanisms and physiological functions of dreams?

Dreams are mental experiences, including perceptions, thoughts, and emotions, that occur during sleep. In dreams, hallucinatory perceptions, particularly visual and motoric, are often accompanied by negative emotions. When people dream, they perceive them as real even though they are bizarre and distorted in time and space. People often cannot recall their dreams, even though people dream every night. Dreaming is a strange physiological phenomenon. Research has demonstrated that dreaming is closely associated with rapid eye movement (REM) sleep. It is known that dreaming also occurs during non-REM (NREM) sleep, but the content appears to be different. Dreams during REM sleep tend to be longer, more vivid, more story-like, and more bizarre than those during NREM sleep. In this review, the neural circuits underlying dreaming and the physiological functions associated with it are summarized. Two major theories have been proposed regarding the neural circuits involved in dreaming. One is that dreams are generated by the activation of neural activity in the brainstem and its signal transmission to the cortex. The other is that dreams are caused by forebrain activation by dopamine. Whereas the physiological function of dreams remains unclear, several hypotheses have been proposed that are associated with memory and emotions.

Functional roles of REM sleep

Rapid eye movement (REM) sleep is an enigmatic and intriguing sleep state. REM sleep differs from non-REM sleep by its characteristic brain activity and from wakefulness by a reduced anti-gravity muscle tone. In addition to these key traits, diverse physiological phenomena appear across the whole body during REM sleep. However, it remains unclear whether these phenomena are the causes or the consequences of REM sleep. Experimental approaches using humans and animal models have gradually revealed the functional roles of REM sleep. Extensive efforts have been made to interpret the characteristic brain activity in the context of memory functions. Numerous physical and psychological functions of REM sleep have also been proposed. Moreover, REM sleep has been implicated in aspects of brain development. Here, we review the variety of functional roles of REM sleep, mainly as revealed by animal models. In addition, we discuss controversies regarding the functional roles of REM sleep.

REM sleep is associated with distinct global cortical dynamics and controlled by occipital cortex

The cerebral cortex is spontaneously active during sleep, yet it is unclear how this global cortical activity is spatiotemporally organized, and whether such activity not only reflects sleep states but also contributes to sleep state switching. Here we report that cortex-wide calcium imaging in mice revealed distinct sleep stage-dependent spatiotemporal patterns of global cortical activity, and modulation of such patterns could regulate sleep state switching. In particular, elevated activation in the occipital cortical regions (including the retrosplenial cortex and visual areas) became dominant during rapid-eye-movement (REM) sleep. Furthermore, such pontogeniculooccipital (PGO) wave-like activity was associated with transitions to REM sleep, and optogenetic inhibition of occipital activity strongly promoted deep sleep by suppressing the NREM-to-REM transition. Thus, whereas subcortical networks are critical for initiating and maintaining sleep and wakefulness states, distinct global cortical activity also plays an active role in controlling sleep states.

Pupillary behavior during wakefulness, non-REM sleep, and REM sleep in birds is opposite that of mammals

Mammalian pupils respond to light^1,2 and dilate with arousal, attention, cognitive workload, and emotions,³ thus reflecting the state of the brain. Pupil size also varies during sleep, constricting during deep non-REM sleep^4-7 and dilating slightly during REM sleep.^4-6 Anecdotal reports suggest that, unlike mammals, birds constrict their pupils during aroused states, such as courtship and aggression,^8-10 raising the possibility that pupillary behavior also differs between mammals and birds during sleep. Here, we measured pupil size in awake pigeons and used their translucent eyelid to investigate sleep-state-dependent changes in pupil size. Male pigeons constricted their pupils during courtship and other male-female interactions but not while engaging in other waking behaviors. Unlike mouse pupils, the pigeons' pupils were dilated during non-REM sleep, while over 1,000 bursts of constriction and relaxation, which we call rapid iris movements (RIMs), occurred primarily during REM sleep. Consistent with the avian iris being composed largely of striated muscles,^11-15 rather than smooth muscles, as in mammals, pharmacological experiments revealed that RIMs are mediated by nicotinic cholinergic receptors in the iris muscles. Despite receiving input from a parasympathetic nucleus, but consistent with its striated nature, the avian iris sphincter muscle behaves like skeletal muscles controlled by the somatic nervous system, constricting during courtship displays, relaxing during non-REM sleep, and twitching during REM sleep. We speculate that during wakefulness, pupillary constrictions are involved in social communication, whereas RIMs occurring during REM sleep might maintain the efficacy of this motor system and/or reflect the processing of associated memories.

State-Dependent Changes in Perception and Coding in the Mouse Somatosensory Cortex

An animal's behavioral state is reflected in the dynamics of cortical population activity and its capacity to process sensory information. To better understand the relationship between behavioral states and information processing, mice are trained to detect varying amplitudes of whisker-deflection under two-photon calcium imaging. Layer 2/3 neurons in the vibrissal primary somatosensory cortex are imaged across different behavioral states, defined based on detection performance (low to high-state) and pupil diameter. The neurometric curve in each behavioral state mirrors the corresponding psychometric performance, with calcium signals predictive of the animal's choice. High behavioral states are associated with lower network synchrony, extending over shorter cortical distances. The decrease in correlation across neurons in high state results in enhanced information transmission capacity at the population level. The observed state-dependent changes suggest that the coding regime within the first stage of cortical processing may underlie adaptive routing of relevant information through the sensorimotor system.

Mutual Interactions between Brain States and Alzheimer's Disease Pathology: A Focus on Gamma and Slow Oscillations

Brain state varies from moment to moment. While brain state can be defined by ongoing neuronal population activity, such as neuronal oscillations, this is tightly coupled with certain behavioural or vigilant states. In recent decades, abnormalities in brain state have been recognised as biomarkers of various brain diseases and disorders. Intriguingly, accumulating evidence also demonstrates mutual interactions between brain states and disease pathologies: while abnormalities in brain state arise during disease progression, manipulations of brain state can modify disease pathology, suggesting a therapeutic potential. In this review, by focusing on Alzheimer's disease (AD), the most common form of dementia, we provide an overview of how brain states change in AD patients and mouse models, and how controlling brain states can modify AD pathology. Specifically, we summarise the relationship between AD and changes in gamma and slow oscillations. As pathological changes in these oscillations correlate with AD pathology, manipulations of either gamma or slow oscillations can modify AD pathology in mouse models. We argue that neuromodulation approaches to target brain states are a promising non-pharmacological intervention for neurodegenerative diseases.

Region-Specific and State-Dependent Astrocyte Ca2+ Dynamics during the Sleep-Wake Cycle in Mice

Neural activity is diverse, and varies depending on brain regions and sleep/wakefulness states. However, whether astrocyte activity differs between sleep/wakefulness states, and whether there are differences in astrocyte activity among brain regions remain poorly understood. Therefore, in this study, we recorded astrocyte intracellular calcium (Ca2+) concentrations of mice during sleep/wakefulness states in the cortex, hippocampus, hypothalamus, cerebellum, and pons using fiber photometry. For this purpose, male transgenic mice expressing the genetically encoded ratiometric Ca2+ sensor YCnano50 specifically in their astrocytes were used. We demonstrated that Ca2+ levels in astrocytes substantially decrease during rapid eye movement (REM) sleep, and increase after the onset of wakefulness. In contrast, differences in Ca2+ levels during non-REM (NREM) sleep were observed among the different brain regions, and no significant decrease was observed in the hypothalamus and pons. Further analyses focusing on the transition between sleep/wakefulness states and correlation analysis with the duration of REM sleep showed that Ca2+ dynamics differs among brain regions, suggesting the existence of several clusters, i.e., the first comprising the cortex and hippocampus, the second comprising the hypothalamus and pons, and the third comprising the cerebellum. Our study thus demonstrated that astrocyte Ca2+ levels change substantially according to sleep/wakefulness states. These changes were consistent in general unlike neural activity. However, we also clarified that Ca2+ dynamics varies depending on the brain region, implying that astrocytes may play various physiological roles in sleep.SIGNIFICANCE STATEMENT Sleep is an instinctive behavior of many organisms. In the previous five decades, the mechanism of the neural circuits controlling sleep/wakefulness states and the neural activities associated with sleep/wakefulness states in various brain regions have been elucidated. However, whether astrocytes, which are a type of glial cell, change their activity during different sleep/wakefulness states was poorly understood. Here, we demonstrated that dynamic changes in astrocyte Ca2+ concentrations occur in the cortex, hippocampus, hypothalamus, cerebellum, and pons of mice during natural sleep. Further analyses demonstrated that Ca2+ dynamics slightly differ among different brain regions, implying that the physiological roles of astrocytes in sleep/wakefulness might vary depending on the brain region.

Effects of optogenetic stimulation of basal forebrain parvalbumin neurons on Alzheimer's disease pathology

Neuronal activity can modify Alzheimer's disease pathology. Overexcitation of neurons can facilitate disease progression whereas the induction of cortical gamma oscillations can reduce amyloid load and improve cognitive functions in mouse models. Although previous studies have induced cortical gamma oscillations by either optogenetic activation of cortical parvalbumin-positive (PV+) neurons or sensory stimuli, it is still unclear whether other approaches to induce gamma oscillations can also be beneficial. Here we show that optogenetic activation of PV+ neurons in the basal forebrain (BF) increases amyloid burden, rather than reducing it. We applied 40 Hz optical stimulation in the BF by expressing channelrhodopsin-2 (ChR2) in PV+ neurons of 5xFAD mice. After 1-h induction of cortical gamma oscillations over three days, we observed the increase in the concentration of amyloid-β42 in the frontal cortical region, but not amyloid-β40. Amyloid plaques were accumulated more in the medial prefrontal cortex and the septal nuclei, both of which are targets of BF PV+ neurons. These results suggest that beneficial effects of cortical gamma oscillations on Alzheimer's disease pathology can depend on the induction mechanisms of cortical gamma oscillations.

Neural and Homeostatic Regulation of REM Sleep

Rapid eye movement (REM) sleep is a distinct, homeostatically controlled brain state characterized by an activated electroencephalogram (EEG) in combination with paralysis of skeletal muscles and is associated with vivid dreaming. Understanding how REM sleep is controlled requires identification of the neural circuits underlying its initiation and maintenance, and delineation of the homeostatic processes regulating its expression on multiple timescales. Soon after its discovery in humans in 1953, the pons was demonstrated to be necessary and sufficient for the generation of REM sleep. But, especially within the last decade, researchers have identified further neural populations in the hypothalamus, midbrain, and medulla that regulate REM sleep by either promoting or suppressing this brain state. The discovery of these populations was greatly facilitated by the availability of novel technologies for the dissection of neural circuits. Recent quantitative models integrate findings about the activity and connectivity of key neurons and knowledge about homeostatic mechanisms to explain the dynamics underlying the recurrence of REM sleep. For the future, combining quantitative with experimental approaches to directly test model predictions and to refine existing models will greatly advance our understanding of the neural and homeostatic processes governing the regulation of REM sleep.

Simultaneous Electrophysiology and Fiber Photometry in Freely Behaving Mice

In vivo electrophysiology is the gold standard technique used to investigate sub-second neural dynamics in freely behaving animals. However, monitoring cell-type-specific population activity is not a trivial task. Over the last decade, fiber photometry based on genetically encoded calcium indicators (GECIs) has been widely adopted as a versatile tool to monitor cell-type-specific population activity in vivo. However, this approach suffers from low temporal resolution. Here, we combine these two approaches to monitor both sub-second field potentials and cell-type-specific population activity in freely behaving mice. By developing an economical custom-made system and constructing a hybrid implant of an electrode and a fiber optic cannula, we simultaneously monitor artifact-free mesopontine field potentials and calcium transients in cholinergic neurons across the sleep-wake cycle. We find that mesopontine cholinergic activity co-occurs with sub-second pontine waves, called P-waves, during rapid eye movement sleep. Given the simplicity of our approach, simultaneous electrophysiological recording and cell-type-specific imaging provides a novel and valuable tool for interrogating state-dependent neural circuit dynamics in vivo.

State-dependent brainstem ensemble dynamics and their interactions with hippocampus across sleep states

The brainstem plays a crucial role in sleep-wake regulation. However, the ensemble dynamics underlying sleep regulation remain poorly understood. Here, we show slow, state-predictive brainstem ensemble dynamics and state-dependent interactions between the brainstem and the hippocampus in mice. On a timescale of seconds to minutes, brainstem populations can predict pupil dilation and vigilance states and exhibit longer prediction power than hippocampal CA1 neurons. On a timescale of sub-seconds, pontine waves (P-waves) are accompanied by synchronous firing of brainstem neurons during both rapid eye movement (REM) and non-REM (NREM) sleep. Crucially, P-waves functionally interact with CA1 activity in a state-dependent manner: during NREM sleep, hippocampal sharp wave-ripples (SWRs) precede P-waves. On the other hand, P-waves during REM sleep are phase-locked with ongoing theta oscillations and are followed by burst firing of CA1 neurons. This state-dependent global coordination between the brainstem and hippocampus implicates distinct functional roles of sleep.

Though almost all animals sleep, its exact purpose remains an enigma. This is particularly true for the period of sleep where people dream most vividly, which is known as rapid eye movement sleep or REM sleep for short. In addition to the eye movements that give it its name, during this phase of sleep, the pupils of the eyes become smaller, muscles relax and neurons in part of the brain activate in a regular, repeating way known as pontine waves or P-waves.

The brainstem is a key brain region that helps the body determine when it is time to sleep and when it is time to be awake. It is found at the back of the brain, and connects the brain to the spinal cord, serving as a conduit for nerve signals to and from the rest of the body. However, it was not clear how the brainstem’s activity during sleep interacts with other brain regions that are important in the sleep process, such as the hippocampus.

REM sleep is not unique to humans; in fact, it occurs in all mammals. Tsunematsu et al. studied mice to better understand the role of the brainstem during sleep. In the experiments, the brain waves, muscle tone and pupil sizes of the mice were monitored, while a probe inserted into the brainstem of the mice measured the activity of the neurons. Analysis of the probe data could predict changes in pupil size ten seconds beforehand and transitions between wakefulness, REM sleep and non-REM sleep up to sixty seconds in advance. This long timescale suggests that there are a number of complex interactions following brainstem activity that lead to the changes in sleep state.

Tsunematsu et al. were also able to detect P-waves for the first time in mice and found that they are timed with activity from the hippocampus depending on the sleep state. During REM sleep, the P-waves precede the hippocampal activity, while during non-REM sleep, they follow it. These results further imply that the two sleep states serve different purposes. The detection of P-waves in mice shows that they are similar to other mammals that have previously been studied. Further studies in mice could help to provide more insight into the mechanisms of sleep and the purpose of the different stages.