Cortical circuit activity underlying sleep slow oscillations and spindles

Oscillatory-Quality of sleep spindles links brain state with sleep regulation and function

Here, we characterized the dynamics of sleep spindles, focusing on their damping, which we estimated using a metric called oscillatory-Quality (o-Quality), derived by fitting an autoregressive model to electrophysiological signals, recorded from the cortex in mice. The o-Quality of sleep spindles correlates weakly with their amplitude, shows marked laminar differences and regional topography across cortical regions, reflects the level of synchrony within and between cortical networks, is strongly modulated by sleep-wake history, reflects the degree of sensory disconnection, and correlates with the strength of coupling between spindles and slow waves. As most spindle events are highly localized and not detectable with conventional low-density recording approaches, o-Quality thus emerges as a valuable metric that allows us to infer the spread and dynamics of spindle activity across the brain and directly links their spatiotemporal dynamics with local and global regulation of brain states, sleep regulation, and function.

Attention-based CNN-BiLSTM for sleep state classification of spatiotemporal wide-field calcium imaging data

BACKGROUND

Wide-field calcium imaging (WFCI) with genetically encoded calcium indicators allows for spatiotemporal recordings of neuronal activity in mice. When applied to the study of sleep, WFCI data are manually scored into the sleep states of wakefulness, non-REM (NREM) and REM by use of adjunct EEG and EMG recordings. However, this process is time-consuming, invasive and often suffers from low inter- and intra-rater reliability. Therefore, an automated sleep state classification method that operates on spatiotemporal WFCI data is desired.

NEW METHOD

A hybrid network architecture consisting of a convolutional neural network (CNN) to extract spatial features of image frames and a bidirectional long short-term memory network (BiLSTM) with attention mechanism to identify temporal dependencies among different time points was proposed to classify WFCI data into states of wakefulness, NREM and REM sleep.

RESULTS

Sleep states were classified with an accuracy of 84 % and Cohen's κ of 0.64. Gradient-weighted class activation maps revealed that the frontal region of the cortex carries more importance when classifying WFCI data into NREM sleep while posterior area contributes most to the identification of wakefulness. The attention scores indicated that the proposed network focuses on short- and long-range temporal dependency in a state-specific manner.

COMPARISON WITH EXISTING METHOD

On a held out, repeated 3-hour WFCI recording, the CNN-BiLSTM achieved a κ of 0.67, comparable to a κ of 0.65 corresponding to the human EEG/EMG-based scoring.

CONCLUSIONS

The CNN-BiLSTM effectively classifies sleep states from spatiotemporal WFCI data and will enable broader application of WFCI in sleep research.

Slow-wave sleep drives sleep-dependent renormalization of synaptic AMPA receptor levels in the hypothalamus

According to the synaptic homeostasis hypothesis (SHY), sleep serves to renormalize synaptic connections that have been potentiated during the prior wake phase due to ongoing encoding of information. SHY focuses on glutamatergic synaptic strength and has been supported by numerous studies examining synaptic structure and function in neocortical and hippocampal networks. However, it is unknown whether synaptic down-regulation during sleep occurs in the hypothalamus, i.e., a pivotal center of homeostatic regulation of bodily functions including sleep itself. We show that sleep, in parallel with the synaptic down-regulation in neocortical networks, down-regulates the levels of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors (AMPARs) in the hypothalamus of rats. Most robust decreases after sleep were observed at both sites for AMPARs containing the GluA1 subunit. Comparing the effects of selective rapid eye movement (REM) sleep and total sleep deprivation, we moreover provide experimental evidence that slow-wave sleep (SWS) is the driving force of the down-regulation of AMPARs in hypothalamus and neocortex, with no additional contributions of REM sleep or the circadian rhythm. SWS-dependent synaptic down-regulation was not linked to EEG slow-wave activity. However, spindle density during SWS predicted relatively increased GluA1 subunit levels in hypothalamic synapses, which is consistent with the role of spindles in the consolidation of memory. Our findings identify SWS as the main driver of the renormalization of synaptic strength during sleep and suggest that SWS-dependent synaptic renormalization is also implicated in homeostatic control processes in the hypothalamus.

Brief sleep disruption alters synaptic structures among hippocampal and neocortical somatostatin-expressing interneurons

Brief sleep loss can disrupt cognition, including information processing in neocortex and hippocampus. Recent studies have identified alterations in synaptic structures of principal neurons within these circuits 1-3 . However, while in vivo recording and bioinformatic data suggest that inhibitory interneurons are more strongly affected by sleep loss 4-9 , it is unclear how sleep and sleep deprivation affect interneurons' synapses. Recent data suggest that activity among hippocampal somatostatin-expressing (SST+) interneurons is selectively increased by experimental sleep disruption 8 . We used Brainbow 3.0 10 to label SST+ interneurons in the dorsal hippocampus, prefrontal cortex, and visual cortex of SST-CRE transgenic mice, then compared synaptic structures in labeled neurons after a 6-h period of ad lib sleep, or gentle handling sleep deprivation (SD) starting at lights on. We find that dendritic spine density among SST+ interneurons in both hippocampus and neocortex was altered in a subregion-specific manner, with increased overall and thin spine density in CA1, decreased mushroom spine density in CA3, and decreased overall and stubby spine density in V1 after SD. Spine size also changed significantly after SD, with dramatic increases in spine volume and surface area in CA3, and small but significant decreases in CA1, PFC and V1. Together, our data suggest that the synaptic connectivity of SST+ interneurons is significantly altered, in a brain region-specific manner, by a few hours of sleep loss. Further, they suggest that sleep loss can disrupt cognition by altering the balance of excitation and inhibition in hippocampal and neocortical networks.

Significance Statement

Changes to the function of somatostatin-expressing (SST+) interneurons have been implicated in the etiology of psychiatric and neurological disorders in which both cognition and sleep behavior are affected. Here, we measure the effects of very brief experimental sleep deprivation on synaptic structures of SST+ interneurons in hippocampus and neocortex, in brain structures critical for sleep-dependent memory processing. We find that only six hours of sleep deprivation restructures SST+ interneurons' dendritic spines, causing widespread and subregion-specific changes to spine density and spine size. These changes have the potential to dramatically alter excitatory-inhibitory balance across these brain networks, leading to cognitive disruptions commonly associated with sleep loss.

Microglial TNFα controls daily changes in synaptic GABAARs and sleep slow waves

Microglia sense the changes in their environment. How microglia actively translate these changes into suitable cues to adapt brain physiology is unknown. We reveal an activity-dependent regulation of cortical inhibitory synapses by microglia, driven by purinergic signaling acting on P2RX7 and mediated by microglia-derived TNFα. We demonstrate that sleep induces microglia-dependent synaptic enrichment of GABAARs in a manner dependent on microglial TNFα and P2RX7. We further show that microglia-specific depletion of TNFα alters slow waves during NREM sleep and blunt memory consolidation in sleep-dependent learning tasks. Together, our results reveal that microglia orchestrate sleep-intrinsic plasticity of synaptic GABAARs, sculpt sleep slow waves, and support memory consolidation.

Possible mechanisms to improve sleep spindles via closed loop stimulation during slow wave sleep: A computational study

Sleep spindles are one of the prominent EEG oscillatory rhythms of non-rapid eye movement sleep. In the memory consolidation, these oscillations have an important role in the processes of long-term potentiation and synaptic plasticity. Moreover, the activity (spindle density and/or sigma power) of spindles has a linear association with learning performance in different paradigms. According to the experimental observations, the sleep spindle activity can be improved by closed loop acoustic stimulations (CLAS) which eventually improve memory performance. To examine the effects of CLAS on spindles, we propose a biophysical thalamocortical model for slow oscillations (SOs) and sleep spindles. In addition, closed loop stimulation protocols are applied on a thalamic network. Our model results show that the power of spindles is increased when stimulation cues are applied at the commencing of an SO Down-to-Up-state transition, but that activity gradually decreases when cues are applied with an increased time delay from this SO phase. Conversely, stimulation is not effective when cues are applied during the transition of an Up-to-Down-state. Furthermore, our model suggests that a strong inhibitory input from the reticular (RE) layer to the thalamocortical (TC) layer in the thalamic network shifts leads to an emergence of spindle activity at the Up-to-Down-state transition (rather than at Down-to-Up-state transition), and the spindle frequency is also reduced (8-11 Hz) by thalamic inhibition.

Sleep-dependent decorrelation of hippocampal spatial representations

Neuronal ensembles are crucial for episodic memory and spatial mapping. Sleep, particularly non-REM (NREM), is vital for memory consolidation, as it triggers plasticity mechanisms through brain oscillations that reactivate neuronal ensembles. Here, we assessed their role in consolidating hippocampal spatial representations during sleep. We recorded hippocampus activity in rats performing a spatial object-place recognition (OPR) memory task, during encoding and retrieval periods, separated by intervening sleep. Successful OPR retrieval correlated with NREM duration, during which cortical oscillations decreased in power and density as well as neuronal spiking, suggesting global downregulation of network excitability. However, neurons encoding specific spatial locations (i.e., place cells) or objects during OPR showed stronger synchrony with brain oscillations compared to non-encoding neurons, and the stability of spatial representations decreased proportionally with NREM duration. Our findings suggest that NREM sleep may promote flexible remapping in hippocampal ensembles, potentially aiding memory consolidation and adaptation to novel spatial contexts.

Spindle-locked ripples mediate memory reactivation during human NREM sleep

Memory consolidation relies in part on the reactivation of previous experiences during sleep. The precise interplay of sleep-related oscillations (slow oscillations, spindles and ripples) is thought to coordinate the information flow between relevant brain areas, with ripples mediating memory reactivation. However, in humans empirical evidence for a role of ripples in memory reactivation is lacking. Here, we investigated the relevance of sleep oscillations and specifically ripples for memory reactivation during human sleep using targeted memory reactivation. Intracranial electrophysiology in epilepsy patients and scalp EEG in healthy participants revealed that elevated levels of slow oscillation - spindle activity coincided with the read-out of experimentally induced memory reactivation. Importantly, spindle-locked ripples recorded intracranially from the medial temporal lobe were found to be correlated with the identification of memory reactivation during non-rapid eye movement sleep. Our findings establish ripples as key-oscillation for sleep-related memory reactivation in humans and emphasize the importance of the coordinated interplay of the cardinal sleep oscillations.

Consciousness and sleep

Sleep is a universal, essential biological process. It is also an invaluable window on consciousness. It tells us that consciousness can be lost but also that it can be regained, in all its richness, when we are disconnected from the environment and unable to reflect. By considering the neurophysiological differences between dreaming and dreamless sleep, we can learn about the substrate of consciousness and understand why it vanishes. We also learn that the ongoing state of the substrate of consciousness determines the way each experience feels regardless of how it is triggered-endogenously or exogenously. Dreaming consciousness is also a window on sleep and its functions. Dreams tell us that the sleeping brain is remarkably lively, recombining intrinsic activation patterns from a vast repertoire, freed from the requirements of ongoing behavior and cognitive control.

Coupled sleep rhythms for memory consolidation

How do passing moments turn into lasting memories? Sheltered from external tasks and distractions, sleep constitutes an optimal state for the brain to reprocess and consolidate previous experiences. Recent work suggests that consolidation is governed by the intricate interaction of slow oscillations (SOs), spindles, and ripples - electrophysiological sleep rhythms that orchestrate neuronal processing and communication within and across memory circuits. This review describes how sequential SO-spindle-ripple coupling provides a temporally and spatially fine-tuned mechanism to selectively strengthen target memories across hippocampal and cortical networks. Coupled sleep rhythms might be harnessed not only to enhance overnight memory retention, but also to combat memory decline associated with healthy ageing and neurodegenerative diseases.

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.

Somatostatin and the pathophysiology of Alzheimer's disease

Among the central features of Alzheimer's disease (AD) progression are altered levels of the neuropeptide somatostatin (SST), and the colocalisation of SST-positive interneurons (SST-INs) with amyloid-β plaques, leading to cell death. In this theoretical review, I propose a molecular model for the pathogenesis of AD based on SST-IN hypofunction and hyperactivity. Namely, hypofunctional and hyperactive SST-INs struggle to control hyperactivity in medial regions in early stages, leading to axonal Aβ production through excessive presynaptic GABAB inhibition, GABAB1a/APP complex downregulation and internalisation. Concomitantly, excessive SST-14 release accumulates near SST-INs in the form of amyloids, which bind to Aβ to form toxic mixed oligomers. This leads to differential SST-IN death through excitotoxicity, further disinhibition, SST deficits, and increased Aβ release, fibrillation and plaque formation. Aβ plaques, hyperactive networks and SST-IN distributions thereby tightly overlap in the brain. Conversely, chronic stimulation of postsynaptic SST2/4 on gulutamatergic neurons by hyperactive SST-INs promotes intense Mitogen-Activated Protein Kinase (MAPK) p38 activity, leading to somatodendritic p-tau staining and apoptosis/neurodegeneration - in agreement with a near complete overlap between p38 and neurofibrillary tangles. This model is suitable to explain some of the principal risk factors and markers of AD progression, including mitochondrial dysfunction, APOE4 genotype, sex-dependent vulnerability, overactive glial cells, dystrophic neurites, synaptic/spine losses, inter alia. Finally, the model can also shed light on qualitative aspects of AD neuropsychology, especially within the domains of spatial and declarative (episodic, semantic) memory, under an overlying pattern of contextual indiscrimination, ensemble instability, interference and generalisation.

A role for δ subunit-containing GABA A receptors on parvalbumin positive neurons in maintaining electrocortical signatures of sleep states

GABA A receptors containing δ subunits have been shown to mediate tonic/slow inhibition in the CNS. These receptors are typically found extrasynaptically and are activated by relatively low levels of ambient GABA in the extracellular space. In the mouse neocortex, δ subunits are expressed on the surface of some pyramidal cells as well as on parvalbumin positive (PV+) interneurons. An important function of PV+ interneurons is the organization of coordinated network activity that can be measured by EEG; however, it remains unclear what role tonic/slow inhibitory control of PV+ neurons may play in shaping oscillatory activity. After confirming a loss of functional δ mediated tonic currents in PV cells in cortical slices from mice lacking Gabrd in PV+ neurons (PV δcKO), we performed EEG recordings to survey network activity across wake and sleep states. PV δcKO mice showed altered spectral content of EEG during NREM and REM sleep that was a result of increased oscillatory activity in NREM and the emergence of transient high amplitude bursts of theta frequency activity during REM. Viral reintroduction of Gabrd to PV+ interneurons in PV δcKO mice rescued REM EEG phenotypes, supporting an important role for δ subunit mediated inhibition of PV+ interneurons for maintaining normal REM cortical oscillations.

Significance statement

The impact on cortical EEG of inhibition on PV+ neurons was studied by deleting a GABA A receptor subunit selectively from these neurons. We discovered unexpected changes at low frequencies during sleep that were rescued by viral reintroduction.

Developmental alcohol exposure is exhausting: Sleep and the enduring consequences of alcohol exposure during development

Prenatal alcohol exposure is the leading nongenetic cause of human intellectual impairment. The long-term impacts of prenatal alcohol exposure on health and well-being are diverse, including neuropathology leading to behavioral, cognitive, and emotional impairments. Additionally negative effects also occur on the physiological level, such as the endocrine, cardiovascular, and immune systems. Among these diverse impacts is sleep disruption. In this review, we describe how prenatal alcohol exposure affects sleep, and potential mechanisms of those effects. Furthermore, we outline the evidence that sleep disruption across the lifespan may be a mediator of some cognitive and behavioral impacts of developmental alcohol exposure, and thus may represent a promising target for treatment.

Hippocampal ripples coincide with "up-state" and spindles in retrosplenial cortex

During NREM sleep, hippocampal sharp-wave ripple (SWR) events are thought to stabilize memory traces for long-term storage in downstream neocortical structures. Within the neocortex, a set of distributed networks organized around retrosplenial cortex (RS-network) interact preferentially with the hippocampus purportedly to consolidate those traces. Transient bouts of slow oscillations and sleep spindles in this RS-network are often observed around SWRs, suggesting that these two activities are related and that their interplay possibly contributes to memory consolidation. To investigate how SWRs interact with the RS-network and spindles, we combined cortical wide-field voltage imaging, Electrocorticography, and hippocampal LFP recordings in anesthetized and sleeping mice. Here, we show that, during SWR, "up-states" and spindles reliably co-occur in a cortical subnetwork centered around the retrosplenial cortex. Furthermore, retrosplenial transient activations and spindles predict slow gamma oscillations in CA1 during SWRs. Together, our results suggest that retrosplenial-hippocampal interaction may be a critical pathway of information exchange between the cortex and hippocampus.

Linking brain structure, cognition, and sleep: insights from clinical data

STUDY OBJECTIVES

To use relatively noisy routinely collected clinical data (brain magnetic resonance imaging (MRI) data, clinical polysomnography (PSG) recordings, and neuropsychological testing), to investigate hypothesis-driven and data-driven relationships between brain physiology, structure, and cognition.

METHODS

We analyzed data from patients with clinical PSG, brain MRI, and neuropsychological evaluations. SynthSeg, a neural network-based tool, provided high-quality segmentations despite noise. A priori hypotheses explored associations between brain function (measured by PSG) and brain structure (measured by MRI). Associations with cognitive scores and dementia status were studied. An exploratory data-driven approach investigated age-structure-physiology-cognition links.

RESULTS

Six hundred and twenty-three patients with sleep PSG and brain MRI data were included in this study; 160 with cognitive evaluations. Three hundred and forty-two participants (55%) were female, and age interquartile range was 52 to 69 years. Thirty-six individuals were diagnosed with dementia, 71 with mild cognitive impairment, and 326 with major depression. One hundred and fifteen individuals were evaluated for insomnia and 138 participants had an apnea-hypopnea index equal to or greater than 15. Total PSG delta power correlated positively with frontal lobe/thalamic volumes, and sleep spindle density with thalamic volume. rapid eye movement (REM) duration and amygdala volume were positively associated with cognition. Patients with dementia showed significant differences in five brain structure volumes. REM duration, spindle, and slow-oscillation features had strong associations with cognition and brain structure volumes. PSG and MRI features in combination predicted chronological age (R2 = 0.67) and cognition (R2 = 0.40).

CONCLUSIONS

Routine clinical data holds extended value in understanding and even clinically using brain-sleep-cognition relationships.

Increase in NREM sleep slow waves following injections of sodium oxybate in the mouse cerebral cortex and the role of somatostatin-positive interneurons

The systemic administration of sodium oxybate (SXB), the sodium salt of gamma-hydroxybutyric acid, promotes slow wave activity (SWA, 0.5-4 Hz EEG power) and increases non-rapid eye movement (NREM) sleep. These effects are mediated by the widely expressed GABAb receptors, and thus, the brain areas targeted by SXB remain unclear. Because slow waves are mainly a cortical phenomenon, we tested here whether systemic SXB promotes SWA by acting directly on the cortex. Moreover, because somatostatin (SOM) + cortical interneurons play a key role in SWA generation, we also assessed their contribution to the effects of SXB. In adult SOM-Cre mice, the injection of SXB in left secondary motor cortex increased SWA during NREM sleep in the first 30 min post-injection (11 mice: either sex). SWA, the amplitude and frequency of the slow waves, and the frequency of the OFF periods increased ipsilaterally and contralaterally to the SXB injection in frontal and parietal cortex. All these changes disappeared when the intracortical injection of SXB was preceded by the chemogenetic inhibition of the SOM+ cells. Thus, SXB may promote the slow waves of NREM sleep, at least in part, by acting directly on the cortex, and this effect involves GABAergic SOM+ interneurons. Our working hypothesis is that SXB potentiates the ability of these cells to inhibit all other cortical cell types via a GABAb mechanism, thus promoting the transition from ON to OFF periods during NREM sleep.

Sleep and wake in a model of the thalamocortical system with Martinotti cells

The mechanisms leading to the alternation between active (UP) and silent (DOWN) states during sleep slow waves (SWs) remain poorly understood. Previous models have explained the transition to the DOWN state by a progressive failure of excitation because of the build-up of adaptation currents or synaptic depression. However, these models are at odds with recent studies suggesting a role for presynaptic inhibition by Martinotti cells (MaCs) in generating SWs. Here, we update a classical large-scale model of sleep SWs to include MaCs and propose a different mechanism for the generation of SWs. In the wake mode, the network exhibits irregular and selective activity with low firing rates (FRs). Following an increase in the strength of background inputs and a modulation of synaptic strength and potassium leak potential mimicking the reduced effect of acetylcholine during sleep, the network enters a sleep-like regime in which local increases of network activity trigger bursts of MaC activity, resulting in strong disfacilitation of the local network via presynaptic GABAB1a -type inhibition. This model replicates findings on slow wave activity (SWA) during sleep that challenge previous models, including low and skewed FRs that are comparable between the wake and sleep modes, higher synchrony of transitions to DOWN states than to UP states, the possibility of triggering SWs by optogenetic stimulation of MaCs, and the local dependence of SWA on synaptic strength. Overall, this work points to a role for presynaptic inhibition by MaCs in the generation of DOWN states during sleep.

Neuromodulation via muscarinic acetylcholine pathway can facilitate distinct, complementary, and sequential roles for NREM and REM states during sleep-dependent memory consolidation

Across vertebrate species, sleep consists of repeating cycles of NREM followed by REM. However, the respective functions of NREM, REM, and their stereotypic cycling pattern are not well understood. Using a simplified biophysical network model, we show that NREM and REM sleep can play differential and critical roles in memory consolidation primarily regulated, based on state-specific changes in cholinergic signaling. Within this network, decreasing and increasing muscarinic acetylcholine (ACh) signaling during bouts of NREM and REM, respectively, differentially alters neuronal excitability and excitatory/inhibitory balance. During NREM, deactivation of inhibitory neurons leads to network-wide disinhibition and bursts of synchronized activity led by firing in engram neurons. These features strengthen connections from the original engram neurons to less-active network neurons. In contrast, during REM, an increase in network inhibition suppresses firing in all but the most-active excitatory neurons, leading to competitive strengthening/pruning of the memory trace. We tested the predictions of the model against in vivo recordings from mouse hippocampus during active sleep-dependent memory storage. Consistent with modeling results, we find that functional connectivity between CA1 neurons changes differentially at transition from NREM to REM sleep during learning. Returning to the model, we find that an iterative sequence of state-specific activations during NREM/REM cycling is essential for memory storage in the network, serving a critical role during simultaneous consolidation of multiple memories. Together these results provide a testable mechanistic hypothesis for the respective roles of NREM and REM sleep, and their universal relative timing, in memory consolidation.

Significance statement

Using a simplified computational model and in vivo recordings from mouse hippocampus, we show that NREM and REM sleep can play differential roles in memory consolidation. The specific neurophysiological features of the two sleep states allow for expansion of memory traces (during NREM) and prevention of overlap between different memory traces (during REM). These features are likely essential in the context of storing more than one new memory simultaneously within a brain network.

Propagating population activity patterns during spontaneous slow waves in the thalamus of rodents

Slow waves (SWs) represent the most prominent electrophysiological events in the thalamocortical system under anesthesia and during deep sleep. Recent studies have revealed that SWs have complex spatiotemporal dynamics and propagate across neocortical regions. However, it is still unclear whether neuronal activity in the thalamus exhibits similar propagation properties during SWs. Here, we report propagating population activity in the thalamus of ketamine/xylazine-anesthetized rats and mice visualized by high-density silicon probe recordings. In both rodent species, propagation of spontaneous thalamic activity during up-states was most frequently observed in dorsal thalamic nuclei such as the higher order posterior (Po), lateral posterior (LP) or laterodorsal (LD) nuclei. The preferred direction of thalamic activity spreading was along the dorsoventral axis, with over half of the up-states exhibiting a gradual propagation in the ventral-to-dorsal direction. Furthermore, simultaneous neocortical and thalamic recordings collected under anesthesia demonstrated that there is a weak but noticeable interrelation between propagation patterns observed during cortical up-states and those displayed by thalamic population activity. In addition, using chronically implanted silicon probes, we detected propagating activity patterns in the thalamus of naturally sleeping rats during slow-wave sleep. However, in comparison to propagating up-states observed under anesthesia, these propagating patterns were characterized by a reduced rate of occurrence and a faster propagation speed. Our findings suggest that the propagation of spontaneous population activity is an intrinsic property of the thalamocortical network during synchronized brain states such as deep sleep or anesthesia. Additionally, our data implies that the neocortex may have partial control over the formation of propagation patterns within the dorsal thalamus under anesthesia.

Reduced overnight memory consolidation and associated alterations in sleep spindles and slow oscillations in early Alzheimer's disease

Spatial navigation critically underlies hippocampal-entorhinal circuit function that is early affected in Alzheimer's disease (AD). There is growing evidence that AD pathophysiology dynamically interacts with the sleep/wake cycle impairing hippocampal memory. To elucidate sleep-dependent consolidation in a cohort of symptomatic AD patients (n = 12, 71.25 ± 2.16 years), we tested hippocampal place learning by means of a virtual reality task and verbal memory by a word-pair association task before and after a night of sleep. Our results show an impaired overnight memory retention in AD compared with controls in the verbal task, together with a significant reduction of sleep spindle activity (i.e., lower amplitude of fast sleep spindles, p = 0.016) and increased duration of the slow oscillation (SO; p = 0.019). Higher spindle density, faster down-to-upstate transitions within SOs, and the time delay between SOs and nested spindles predicted better memory performance in healthy controls but not in AD patients. Our results show that mnemonic processing and memory consolidation in AD is slightly impaired as reflected by dysfunctional oscillatory dynamics and spindle-SO coupling during NonREM sleep. In this translational study based on experimental paradigms in animals and extending previous work in healthy aging and preclinical disease stages, our results in symptomatic AD further deepen the understanding of the memory decline within a bidirectional relationship of sleep and AD pathology.

Respiration modulates sleep oscillations and memory reactivation in humans

The beneficial effect of sleep on memory consolidation relies on the precise interplay of slow oscillations and spindles. However, whether these rhythms are orchestrated by an underlying pacemaker has remained elusive. Here, we tested the relationship between respiration, which has been shown to impact brain rhythms and cognition during wake, sleep-related oscillations and memory reactivation in humans. We re-analysed an existing dataset, where scalp electroencephalography and respiration were recorded throughout an experiment in which participants (N = 20) acquired associative memories before taking a nap. Our results reveal that respiration modulates the emergence of sleep oscillations. Specifically, slow oscillations, spindles as well as their interplay (i.e., slow-oscillation_spindle complexes) systematically increase towards inhalation peaks. Moreover, the strength of respiration - slow-oscillation_spindle coupling is linked to the extent of memory reactivation (i.e., classifier evidence in favour of the previously learned stimulus category) during slow-oscillation_spindles. Our results identify a clear association between respiration and memory consolidation in humans and highlight the role of brain-body interactions during sleep.

Continuity and change in neural plasticity through embryonic morphogenesis, fetal activity-dependent synaptogenesis, and infant memory consolidation

There is an apparent continuity in human neural development that can be traced to venerable themes of vertebrate morphogenesis that have shaped the evolution of the reptilian telencephalon (including both primitive three-layered cortex and basal ganglia) and then the subsequent evolution of the mammalian six-layered neocortex. In this theoretical analysis, we propose that an evolutionary-developmental analysis of these general morphogenetic themes can help to explain the embryonic development of the dual divisions of the limbic system that control the dorsal and ventral networks of the human neocortex. These include the archicortical (dorsal limbic) Papez circuits regulated by the hippocampus that organize spatial, contextual memory, as well as the paleocortical (ventral limbic) circuits that organize object memory. We review evidence that these dorsal and ventral limbic divisions are controlled by the differential actions of brainstem lemnothalamic and midbrain collothalamic arousal control systems, respectively, thereby traversing the vertebrate subcortical neuraxis. These dual control systems are first seen shaping the phyletic morphogenesis of the archicortical and paleocortical foundations of the forebrain in embryogenesis. They then provide dual modes of activity-dependent synaptic organization in the active (lemnothalamic) and quiet (collothalamic) stages of fetal sleep. Finally, these regulatory systems mature to form the major systems of memory consolidation of postnatal development, including the rapid eye movement (lemnothalamic) consolidation of implicit memory and social attachment in the first year, and then-in a subsequent stage-the non-REM (collothalamic) consolidation of explicit memory that is integral to the autonomy and individuation of the second year of life.

Diversity of cortical activity changes beyond depression during Spreading Depolarizations

Spreading depolarizations (SDs) are classically thought to be associated with spreading depression of cortical activity. Here, we found that SDs in patients with subarachnoid hemorrhage produce variable, ranging from depression to booming, changes in electrocorticographic activity, especially in the delta frequency band. In rats, depression of activity was characteristic of high-potassium-induced full SDs, whereas partial superficial SDs caused either little change or a boom of activity at the cortical vertex, supported by volume conduction of signals from spared delta generators in the deep cortical layers. Partial SDs also caused moderate neuronal depolarization and sustained excitation, organized in gamma oscillations in a narrow sub-SD zone. Thus, our study challenges the concept of homology between spreading depolarization and spreading depression by showing that SDs produce variable, from depression to booming, changes in activity at the cortical surface and in different cortical layers depending on the depth of SD penetration.

Sleep spindle maturity promotes slow oscillation-spindle coupling across child and adolescent development

The synchronization of canonical fast sleep spindle activity (12.5-16 Hz, adult-like) precisely during the slow oscillation (0.5-1 Hz) up peak is considered an essential feature of adult non-rapid eye movement sleep. However, there is little knowledge on how this well-known coalescence between slow oscillations and sleep spindles develops. Leveraging individualized detection of single events, we first provide a detailed cross-sectional characterization of age-specific patterns of slow and fast sleep spindles, slow oscillations, and their coupling in children and adolescents aged 5-6, 8-11, and 14-18 years, and an adult sample of 20- to 26-year-olds. Critically, based on this, we then investigated how spindle and slow oscillation maturity substantiate age-related differences in their precise orchestration. While the predominant type of fast spindles was development-specific in that it was still nested in a frequency range below the canonical fast spindle range for the majority of children, the well-known slow oscillation-spindle coupling pattern was evident for sleep spindles in the adult-like canonical fast spindle range in all four age groups-but notably less precise in children. To corroborate these findings, we linked personalized measures of fast spindle maturity, which indicate the similarity between the prevailing development-specific and adult-like canonical fast spindles, and slow oscillation maturity, which reflects the extent to which slow oscillations show frontal dominance, with individual slow oscillation-spindle coupling patterns. Importantly, we found that fast spindle maturity was uniquely associated with enhanced slow oscillation-spindle coupling strength and temporal precision across the four age groups. Taken together, our results suggest that the increasing ability to generate adult-like canonical fast sleep spindles actuates precise slow oscillation-spindle coupling patterns from childhood through adolescence and into young adulthood.

Memory ability and retention performance relate differentially to sleep depth and spindle type

Temporal interactions between non-rapid eye movement (NREM) sleep rhythms especially the coupling between cortical slow oscillations (SO, ∼1 Hz) and thalamic spindles (∼12 Hz) have been proposed to contribute to multi-regional interactions crucial for memory processing and cognitive ability. We investigated relationships between NREM sleep depth, sleep spindles and SO-spindle coupling regarding memory ability and memory consolidation in healthy humans. Findings underscore the functional relevance of spindle dynamics (slow versus fast), SO-phase, and most importantly NREM sleep depth for cognitive processing. Cross-frequency coupling analyses demonstrated stronger precise temporal coordination of slow spindles to SO down-state in N2 for subjects with higher general memory ability. A GLM model underscored this relationship, and furthermore that fast spindle properties were predictive of overnight memory consolidation. Our results suggest cognitive fingerprints dependent on conjoint fine-tuned SO-spindle temporal coupling, spindle properties, and brain sleep state.

CBD lengthens sleep but shortens ripples and leads to intact simple but worse cumulative memory

Cannabidiol (CBD) is on the rise as over-the-counter medication to treat sleep disturbances, anxiety, pain, and epilepsy due to its action on the excitatory/inhibitory balance in the brain. However, it remains unclear if CBD also leads to adverse effects on memory via changes of sleep macro- and microarchitecture. To investigate the effect of CBD on sleep and memory consolidation, we performed two experiments using the object space task testing for both simple and cumulative memory in rats. We show that oral CBD administration extended the sleep period but changed the properties of rest and non-REM sleep oscillations (delta, spindle, ripples). Specifically, CBD also led to less long (>100 ms) ripples and, consequently, worse cumulative memory consolidation. In contrast, simple memories were not affected. In sum, we can confirm the beneficial effect of CBD on sleep; however, this comes with changes in oscillations that negatively impact memory consolidation.

Spindle-dependent memory consolidation in healthy adults: A meta-analysis

Accumulating evidence suggests a central role for sleep spindles in the consolidation of new memories. However, no meta-analysis of the association between sleep spindles and memory performance has been conducted so far. Here, we report meta-analytical evidence for spindle-memory associations and investigate how multiple factors, including memory type, spindle type, spindle characteristics, and EEG topography affect this relationship. The literature search yielded 53 studies reporting 1427 effect sizes, resulting in a small to moderate effect for the average association. We further found that spindle-memory associations were significantly stronger for procedural memory than for declarative memory. Neither spindle types nor EEG scalp topography had an impact on the strength of the spindle-memory relation, but we observed a distinct functional role of global and fast sleep spindles, especially for procedural memory. We also found a moderation effect of spindle characteristics, with power showing the largest effect sizes. Collectively, our findings suggest that sleep spindles are involved in learning, thereby representing a general physiological mechanism for memory consolidation.

Sleep consolidates stimulus-response learning

Performing a motor response to a sensory stimulus creates a memory trace whose behavioral correlates are classically investigated in terms of repetition priming effects. Such stimulus-response learning entails two types of associations that are partly independent: (1) an association between the stimulus and the motor response and (2) an association between the stimulus and the classification task in which it is encountered. Here, we tested whether sleep supports long-lasting stimulus-response learning on a task requiring participants (1) for establishing stimulus-classification associations to classify presented objects along two different dimensions ("size" and "mechanical") and (2) as motor response (action) to respond with either the left or right index finger. Moreover, we examined whether strengthening of stimulus-classification associations is preferentially linked to nonrapid eye movement (non-REM) sleep and strengthening of stimulus-action associations to REM sleep. We tested 48 healthy volunteers in a between-subjects design comparing postlearning retention periods of nighttime sleep versus daytime wakefulness. At postretention testing, we found that sleep supports consolidation of both stimulus-action and stimulus-classification associations, as indicated by increased reaction times in "switch conditions"; that is, when, at test, the acutely instructed classification task and/or correct motor response for a given stimulus differed from that during original learning. Polysomnographic recordings revealed that both kinds of associations were correlated with non-REM spindle activity. Our results do not support the view of differential roles for non-REM and REM sleep in the consolidation of stimulus-classification and stimulus-action associations, respectively.

Beyond rhythm - a framework for understanding the frequency spectrum of neural activity

Cognitive and behavioral processes are often accompanied by changes within well-defined frequency bands of the local field potential (LFP i.e., the voltage induced by neuronal activity). These changes are detectable in the frequency domain using the Fourier transform and are often interpreted as neuronal oscillations. However, aside some well-known exceptions, the processes underlying such changes are difficult to track in time, making their oscillatory nature hard to verify. In addition, many non-periodic neural processes can also have spectra that emphasize specific frequencies. Thus, the notion that spectral changes reflect oscillations is likely too restrictive. In this study, we use a simple yet versatile framework to understand the frequency spectra of neural recordings. Using simulations, we derive the Fourier spectra of periodic, quasi-periodic and non-periodic neural processes having diverse waveforms, illustrating how these attributes shape their spectral signatures. We then show how neural processes sum their energy in the local field potential in simulated and real-world recording scenarios. We find that the spectral power of neural processes is essentially determined by two aspects: (1) the distribution of neural events in time and (2) the waveform of the voltage induced by single neural events. Taken together, this work guides the interpretation of the Fourier spectrum of neural recordings and indicates that power increases in specific frequency bands do not necessarily reflect periodic neural activity.

Human REM sleep recalibrates neural activity in support of memory formation

The proposed mechanisms of sleep-dependent memory consolidation involve the overnight regulation of neural activity at both synaptic and whole-network levels. Now, there is a lack of in vivo data in humans elucidating if, and how, sleep and its varied stages balance neural activity, and if such recalibration benefits memory. We combined electrophysiology with in vivo two-photon calcium imaging in rodents as well as intracranial and scalp electroencephalography (EEG) in humans to reveal a key role for non-oscillatory brain activity during rapid eye movement (REM) sleep to mediate sleep-dependent recalibration of neural population dynamics. The extent of this REM sleep recalibration predicted the success of overnight memory consolidation, expressly the modulation of hippocampal-neocortical activity, favoring remembering rather than forgetting. The findings describe a non-oscillatory mechanism how human REM sleep modulates neural population activity to enhance long-term memory.

How coupled slow oscillations, spindles and ripples coordinate neuronal processing and communication during human sleep

Learning and plasticity rely on fine-tuned regulation of neuronal circuits during offline periods. An unresolved puzzle is how the sleeping brain, in the absence of external stimulation or conscious effort, coordinates neuronal firing rates (FRs) and communication within and across circuits to support synaptic and systems consolidation. Using intracranial electroencephalography combined with multiunit activity recordings from the human hippocampus and surrounding medial temporal lobe (MTL) areas, we show that, governed by slow oscillation (SO) up-states, sleep spindles set a timeframe for ripples to occur. This sequential coupling leads to a stepwise increase in (1) neuronal FRs, (2) short-latency cross-correlations among local neuronal assemblies and (3) cross-regional MTL interactions. Triggered by SOs and spindles, ripples thus establish optimal conditions for spike-timing-dependent plasticity and systems consolidation. These results unveil how the sequential coupling of specific sleep rhythms orchestrates neuronal processing and communication during human sleep.

The Metabotropic Glutamate 5 Receptor in Sleep and Wakefulness: Focus on the Cortico-Thalamo-Cortical Oscillations

Sleep is an essential innate but complex behaviour which is ubiquitous in the animal kingdom. Our knowledge of the distinct neural circuit mechanisms that regulate sleep and wake states in the brain are, however, still limited. It is therefore important to understand how these circuits operate during health and disease. This review will highlight the function of mGlu5 receptors within the thalamocortical circuitry in physiological and pathological sleep states. We will also evaluate the potential of targeting mGlu5 receptors as a therapeutic strategy for sleep disorders that often co-occur with epileptic seizures.

A scoping review for building a criticality-based conceptual framework of altered states of consciousness

The healthy conscious brain is thought to operate near a critical state, reflecting optimal information processing and high susceptibility to external stimuli. Conversely, deviations from the critical state are hypothesized to give rise to altered states of consciousness (ASC). Measures of criticality could therefore be an effective way of establishing the conscious state of an individual. Furthermore, characterizing the direction of a deviation from criticality may enable the development of treatment strategies for pathological ASC. The aim of this scoping review is to assess the current evidence supporting the criticality hypothesis, and the use of criticality as a conceptual framework for ASC. Using the PRISMA guidelines, Web of Science and PubMed were searched from inception to February 7th 2022 to find articles relating to measures of criticality across ASC. N = 427 independent papers were initially found on the subject. N = 378 were excluded because they were either: not related to criticality; not related to consciousness; not presenting results from a primary study; presenting model data. N = 49 independent papers were included in the present research, separated in 7 sub-categories of ASC: disorders of consciousness (DOC) (n = 5); sleep (n = 13); anesthesia (n = 18); epilepsy (n = 12); psychedelics and shamanic state of consciousness (n = 4); delirium (n = 1); meditative state (n = 2). Each category included articles suggesting a deviation of the critical state. While most studies were only able to identify a deviation from criticality without being certain of its direction, the preliminary consensus arising from the literature is that non-rapid eye movement (NREM) sleep reflects a subcritical state, epileptic seizures reflect a supercritical state, and psychedelics are closer to the critical state than normal consciousness. This scoping review suggests that, though the literature is limited and methodologically inhomogeneous, ASC are characterized by a deviation from criticality, though its direction is not clearly reported in a majority of studies. Criticality could become, with more extensive research, an effective and objective way to characterize ASC, and help identify therapeutic avenues to improve criticality in pathological brain states. Furthermore, we suggest how anesthesia and psychedelics could potentially be used as neuromodulation techniques to restore criticality in DOC.

Beyond rhythm - A framework for understanding the frequency spectrum of neural activity

Cognitive and behavioral processes are often accompanied by changes within well-defined frequency bands of the local field potential (LFP i.e., the voltage induced by neuronal activity). These changes are detectable in the frequency domain using the Fourier transform and are often interpreted as neuronal oscillations. However, aside some well-known exceptions, the processes underlying such changes are difficult to track in time, making their oscillatory nature hard to verify. In addition, many non-periodic neural processes can also have spectra that emphasize specific frequencies. Thus, the notion that spectral changes reflect oscillations is likely too restrictive. In this study, we propose a simple yet versatile framework to understand the frequency spectra of neural recordings. Using simulations, we derive the Fourier spectra of periodic, quasi-periodic and non-periodic neural processes having diverse waveforms, illustrating how these attributes shape their spectral signatures. We then show how neural processes sum their energy in the local field potential in simulated and real-world recording scenarios. We find that the spectral power of neural processes is essentially determined by two aspects: 1) the distribution of neural events in time and 2) the waveform of the voltage induced by single neural events. Taken together, this work guides the interpretation of the Fourier spectrum of neural recordings and indicates that power increases in specific frequency bands do not necessarily reflect periodic neural activity.

Alterations to parvalbumin-expressing interneuron function and associated network oscillations in the hippocampal - medial prefrontal cortex circuit during natural sleep in AppNL-G-F/NL-G-F mice

In the early stages of Alzheimer's disease (AD), the accumulation of the peptide amyloid-β (Aβ) damages synapses and disrupts neuronal activity, leading to the disruption of neuronal oscillations associated with cognition. This is thought to be largely due to impairments in CNS synaptic inhibition, particularly via parvalbumin (PV)-expressing interneurons that are essential for generating several key oscillations. Research in this field has largely been conducted in mouse models that over-express humanised, mutated forms of AD-associated genes that produce exaggerated pathology. This has prompted the development and use of knock-in mouse lines that express these genes at an endogenous level, such as the App^{NL-G-F/NL-G-F} mouse model used in the present study. These mice appear to model the early stages of Aβ-induced network impairments, yet an in-depth characterisation of these impairments in currently lacking. Therefore, using 16 month-old App^{NL-G-F/NL-G-F} mice, we analysed neuronal oscillations found in the hippocampus and medial prefrontal cortex (mPFC) during awake behaviour, rapid eye movement (REM) and non-REM (NREM) sleep to assess the extent of network dysfunction. No alterations to gamma oscillations were found to occur in the hippocampus or mPFC during either awake behaviour, REM or NREM sleep. However, during NREM sleep an increase in the power of mPFC spindles and decrease in the power of hippocampal sharp-wave ripples was identified. The latter was accompanied by an increase in the synchronisation of PV-expressing interneuron activity, as measured using two-photon Ca²⁺ imaging, as well as a decrease in PV-expressing interneuron density. Furthermore, although changes were detected in local network function of mPFC and hippocampus, long-range communication between these regions appeared intact. Altogether, our results suggest that these NREM sleep-specific impairments represent the early stages of circuit breakdown in response to amyloidopathy.

Accelerating Maturation of Spatial Memory Systems by Experience: Evidence from Sleep Oscillation Signatures of Memory Processing

During early development, memory systems gradually mature over time, in parallel with the gradual accumulation of knowledge. Yet, it is unknown whether and to what extent maturation is driven by discrete experience. Sleep is thought to contribute to the formation of long-term memory and knowledge through a systems consolidation process that is driven by specific sleep oscillations (i.e., ripples, spindles, and slow oscillations) in cortical and hippocampal networks. Based on these oscillatory signatures, we show here in rats that discrete spatial experience speeds the functional maturation of spatial memory systems during development. Juvenile male rats were exposed for 5 min periods to changes in the spatial configuration of two identical objects on postnatal day (PD)25, PD27, and PD29 (Spatial experience group), while a Control group was exposed on these occasions to the same two objects without changing their positions. On PD31, both groups were tested on a classical Object Place Recognition (OPR) task with a 3 h retention interval during which the sleep-associated EEG and hippocampal local field potentials were recorded. On PD31, consistent with forgoing studies, Control rats still did not express OPR memory. By contrast, rats with Spatial experience formed significant OPR memory and, in parallel, displayed an increased percentage of hippocampal ripples coupled to parietal slow oscillation-spindle complexes, and a stronger ripple-spindle phase-locking during the retention sleep. Our findings support the idea that experience promotes the maturation of memory systems during development by enhancing cortico-hippocampal information exchange and the formation of integrated knowledge representations during sleep.SIGNIFICANCE STATEMENT Cognitive and memory capabilities mature early in life. We show here that and how discrete spatial experience contributes to this process. Using a simple recognition paradigm in developing rats, we found that exposure of the rat pups to three short-lasting experiences enhances spatial memory capabilities to adult-like levels. The adult-like capability of building spatial memory was connected to a more precise coupling of ripples in the hippocampus with slow oscillation-spindle complexes in the thalamo-cortical system when the memory was formed during sleep. Our findings support the view that discrete experience accelerates maturation of cognitive and memory capabilities by enhancing the dialogue between hippocampus and cortex when these experiences are reprocessed during sleep.

Sleep spindles in the healthy brain from birth through 18 years

STUDY OBJECTIVE

Sleep spindles are present from birth and reflect cognitive functions across the lifespan, but normative values for this cognitive biomarker across development are lacking. This study aims to establish normative spindle features over development.

METHODS

All available normal 19-channel electroencephalograms from developmentally normal children between February 2002 and June 2021 in the MGH EEG lab were analyzed. Approximately, 20 000 spindles were hand-marked to train and validate an automated spindle detector across ages. Normative values for spindle rate, duration, frequency, refractory period, and interhemispheric lag are provided for each channel and each age.

RESULTS

Sleep EEGs from 567 developmentally normal children (range 0 days to 18 years) were included. The detector had excellent performance (F1 = 0.47). Maximal spindle activity is seen over central regions during infancy and adolescence and frontopolar regions during childhood. Spindle rate and duration increase nonlinearly, with the most rapid changes during the first 4 months of life and between ages 3 and 14 years. Peak spindle frequency follows a U-shaped curve and discrete frontal slow and central fast spindles are evident by 18 months. Spindle refractory periods decrease between ages 1 and 14 years while interhemispheric asynchrony decreases over the first 3 months of life and between ages 1 and 14 years.

CONCLUSIONS

These data provide age- and region-specific normative values for sleep spindles across development, where measures that deviate from these values can be considered pathological. As spindles provide a noninvasive biomarker for cognitive function across the lifespan, these normative measures can accelerate the discovery and diagnosis in neurodevelopmental disorders.

Sleep-A brain-state serving systems memory consolidation

Although long-term memory consolidation is supported by sleep, it is unclear how it differs from that during wakefulness. Our review, focusing on recent advances in the field, identifies the repeated replay of neuronal firing patterns as a basic mechanism triggering consolidation during sleep and wakefulness. During sleep, memory replay occurs during slow-wave sleep (SWS) in hippocampal assemblies together with ripples, thalamic spindles, neocortical slow oscillations, and noradrenergic activity. Here, hippocampal replay likely favors the transformation of hippocampus-dependent episodic memory into schema-like neocortical memory. REM sleep following SWS might balance local synaptic rescaling accompanying memory transformation with a sleep-dependent homeostatic process of global synaptic renormalization. Sleep-dependent memory transformation is intensified during early development despite the immaturity of the hippocampus. Overall, beyond its greater efficacy, sleep consolidation differs from wake consolidation mainly in that it is supported, rather than impaired, by spontaneous hippocampal replay activity possibly gating memory formation in neocortex.

Assessing brain state and anesthesia level with two-photon calcium signals

Brain states, such as wake, sleep, or different depths of anesthesia are usually assessed using electrophysiological techniques, such as the local field potential (LFP) or the electroencephalogram (EEG), which are ideal signals for detecting activity patterns such as asynchronous or oscillatory activities. However, it is technically challenging to have these types of measures during calcium imaging recordings such as two-photon or wide-field techniques. Here, using simultaneous two-photon and LFP measurements, we demonstrate that despite the slower dynamics of the calcium signal, there is a high correlation between the LFP and two-photon signals taken from the neuropil outside neuronal somata. Moreover, we find the calcium signal to be systematically delayed from the LFP signal, and we use a model to show that the delay between the two signals is due to the physical distance between the recording sites. These results suggest that calcium signals alone can be used to detect activity patterns such as slow oscillations and ultimately assess the brain state and level of anesthesia.

To sleep or not to sleep - Effects on memory in normal aging and disease

Sleep behavior undergoes significant changes across the lifespan, and aging is associated with marked alterations in sleep amounts and quality. The primary sleep changes in healthy older adults include a shift in sleep timing, reduced slow-wave sleep, and impaired sleep maintenance. However, neurodegenerative and psychiatric disorders are more common among the elderly, which further worsen their sleep health. Irrespective of the cause, insufficient sleep adversely affects various bodily functions including energy metabolism, mood, and cognition. In this review, we will focus on the cognitive changes associated with inadequate sleep during normal aging and the underlying neural mechanisms.

Functional differences in cerebral activation between slow wave-coupled and uncoupled sleep spindles

Spindles are often temporally coupled to slow waves (SW). These SW-spindle complexes have been implicated in memory consolidation that involves transfer of information from the hippocampus to the neocortex. However, spindles and SW, which are characteristic of NREM sleep, can occur as part of this complex, or in isolation. It is not clear whether dissociable parts of the brain are recruited when coupled to SW vs. when spindles or SW occur in isolation. Here, we tested differences in cerebral activation time-locked to uncoupled spindles, uncoupled SW and coupled SW-spindle complexes using simultaneous EEG-fMRI. Consistent with the "active system model," we hypothesized that brain activations time-locked to coupled SW-spindles would preferentially occur in brain areas known to be critical for sleep-dependent memory consolidation. Our results show that coupled spindles and uncoupled spindles recruit distinct parts of the brain. Specifically, we found that hippocampal activation during sleep is not uniquely related to spindles. Rather, this process is primarily driven by SWs and SW-spindle coupling. In addition, we show that SW-spindle coupling is critical in the activation of the putamen. Importantly, SW-spindle coupling specifically recruited frontal areas in comparison to uncoupled spindles, which may be critical for the hippocampal-neocortical dialogue that preferentially occurs during sleep.

Role of cerebellum in sleep-dependent memory processes

The activities and role of the cerebellum in sleep have, until recently, been largely ignored by both the sleep and cerebellum fields. Human sleep studies often neglect the cerebellum because it is at a position in the skull that is inaccessible to EEG electrodes. Animal neurophysiology sleep studies have focussed mainly on the neocortex, thalamus and the hippocampus. However, recent neurophysiological studies have shown that not only does the cerebellum participate in the sleep cycle, but it may also be implicated in off-line memory consolidation. Here we review the literature on cerebellar activity during sleep and the role it plays in off-line motor learning, and introduce a hypothesis whereby the cerebellum continues to compute internal models during sleep that train the neocortex.

Somatostatin neuron contributions to cortical slow wave dysfunction in adult mice exposed to developmental ethanol

Introduction

Transitions between sleep and waking and sleep-dependent cortical oscillations are heavily dependent on GABAergic neurons. Importantly, GABAergic neurons are especially sensitive to developmental ethanol exposure, suggesting a potential unique vulnerability of sleep circuits to early ethanol. In fact, developmental ethanol exposure can produce long-lasting impairments in sleep, including increased sleep fragmentation and decreased delta wave amplitude. Here, we assessed the efficacy of optogenetic manipulations of somatostatin (SST) GABAergic neurons in the neocortex of adult mice exposed to saline or ethanol on P7, to modulate cortical slow-wave physiology.

Methods

SST-cre × Ai32 mice, which selectively express channel rhodopsin in SST neurons, were exposed to ethanol or saline on P7. This line expressed similar developmental ethanol induced loss of SST cortical neurons and sleep impairments as C57BL/6By mice. As adults, optical fibers were implanted targeting the prefrontal cortex (PFC) and telemetry electrodes were implanted in the neocortex to monitor slow-wave activity and sleep-wake states.

Results

Optical stimulation of PFC SST neurons evoked slow-wave potentials and long-latency single-unit excitation in saline treated mice but not in ethanol mice. Closed-loop optogenetic stimulation of PFC SST neuron activation on spontaneous slow-waves enhanced cortical delta oscillations, and this manipulation was more effective in saline mice than P7 ethanol mice.

Discussion

Together, these results suggest that SST cortical neurons may contribute to slow-wave impairment after developmental ethanol.

Neural circuit plasticity for complex non-declarative sensorimotor memory consolidation during sleep

Evidence is accumulating that the brain actively consolidates long-term memory during sleep. Motor skill memory is a form of non-declarative procedural memory and can be coordinated with multi-sensory processing such as visual, tactile, and, auditory. Conversely, perception is affected by body movement signal from motor brain regions. Although both cortical and subcortical brain regions are involved in memory consolidation, cerebral cortex activity can be recorded and manipulated noninvasively or minimally invasively in humans and animals. NREM sleep, which is important for non-declarative memory consolidation, is characterized by slow and spindle waves representing thalamo-cortical population activity. In animals, electrophysiological recording, optical imaging, and manipulation approaches have revealed multi-scale cortical dynamics across learning and sleep. In the sleeping cortex, neural activity is affected by prior learning and neural circuits are continually reorganized. Here I outline how sensorimotor coordination is formed through awake learning and subsequent sleep.

Information maximization explains state-dependent synaptic plasticity and memory reorganization during non-rapid eye movement sleep

Slow waves during the non-rapid eye movement (NREM) sleep reflect the alternating up and down states of cortical neurons; global and local slow waves promote memory consolidation and forgetting, respectively. Furthermore, distinct spike-timing-dependent plasticity (STDP) operates in these up and down states. The contribution of different plasticity rules to neural information coding and memory reorganization remains unknown. Here, we show that optimal synaptic plasticity for information maximization in a cortical neuron model provides a unified explanation for these phenomena. The model indicates that the optimal synaptic plasticity is biased toward depression as the baseline firing rate increases. This property explains the distinct STDP observed in the up and down states. Furthermore, it explains how global and local slow waves predominantly potentiate and depress synapses, respectively, if the background firing rate of excitatory neurons declines with the spatial scale of waves as the model predicts. The model provides a unifying account of the role of NREM sleep, bridging neural information coding, synaptic plasticity, and memory reorganization.

A model of autonomous interactions between hippocampus and neocortex driving sleep-dependent memory consolidation

How do we build up our knowledge of the world over time? Many theories of memory formation and consolidation have posited that the hippocampus stores new information, then "teaches" this information to the neocortex over time, especially during sleep. But it is unclear, mechanistically, how this actually works-How are these systems able to interact during periods with virtually no environmental input to accomplish useful learning and shifts in representation? We provide a framework for thinking about this question, with neural network model simulations serving as demonstrations. The model is composed of hippocampus and neocortical areas, which replay memories and interact with one another completely autonomously during simulated sleep. Oscillations are leveraged to support error-driven learning that leads to useful changes in memory representation and behavior. The model has a non-rapid eye movement (NREM) sleep stage, where dynamics between the hippocampus and neocortex are tightly coupled, with the hippocampus helping neocortex to reinstate high-fidelity versions of new attractors, and a REM sleep stage, where neocortex is able to more freely explore existing attractors. We find that alternating between NREM and REM sleep stages, which alternately focuses the model's replay on recent and remote information, facilitates graceful continual learning. We thus provide an account of how the hippocampus and neocortex can interact without any external input during sleep to drive useful new cortical learning and to protect old knowledge as new information is integrated.

Shaping overnight consolidation via slow-oscillation closed-loop targeted memory reactivation

Sleep constitutes a privileged state for new memories to reactivate and consolidate. Previous work has demonstrated that consolidation can be bolstered experimentally either via delivery of reminder cues (targeted memory reactivation [TMR]) or via noninvasive brain stimulation geared toward enhancing endogenous sleep rhythms. Here, we combined both approaches, controlling the timing of TMR cues with respect to ongoing slow-oscillation (SO) phases. Prior to sleep, participants learned associations between unique words and a set of repeating images (e.g., car) while hearing a prototypical image sound (e.g., engine starting). Memory performance on an immediate test vs. a test the next morning quantified overnight memory consolidation. Importantly, two image sounds were designated as TMR cues, with one cue delivered at SO UP states and the other delivered at SO DOWN states. A novel sound was used as a TMR control condition. Behavioral results revealed a significant reduction of overnight forgetting for words associated with UP-state TMR compared with words associated with DOWN-state TMR. Electrophysiological results showed that UP-state cueing led to enhancement of the ongoing UP state and was followed by greater spindle power than DOWN-state cueing. Moreover, UP-state (and not DOWN-state) cueing led to reinstatement of target image representations. Together, these results unveil the behavioral and mechanistic effects of delivering reminder cues at specific phases of endogenous sleep rhythms and mark an important step for the endeavor to experimentally modulate memories during sleep.

Dihydropyridine calcium blockers do not interfere with non-rapid eye movement sleep

Non-rapid eye movement (NREM) sleep is tightly homeostatically regulated and essential for survival. In the electroencephalogram (EEG), oscillations in the delta (0.5-4 Hz) range are prominent during NREM sleep. These delta oscillations are, to date, the best indicator for homeostatic sleep regulation; they are increased after prolonged waking and fade during NREM sleep. The precise mechanisms underlying sleep homeostasis and the generation of EEG delta oscillations are still being investigated. Activity-dependent neuronal calcium influx has been hypothesized to play an important role in generating delta oscillations and might be involved in downstream signaling that mediates sleep function. Dihydropyridine blockers of L-type voltage-gated calcium channels (VGCCs) are in wide clinical use to treat hypertension and other cardiovascular disorders and are readily blood-brain-barrier penetrant. We therefore, wanted to investigate their potential effects on EEG delta oscillation and homeostatic NREM sleep regulation in freely behaving mice. In vivo two-photon imaging of cortical neurons showed larger spontaneous calcium transients in NREM sleep compared to waking. Application of the dihydropyridine calcium blocker nicardipine significantly reduced cortical calcium transients without affecting the generation of delta oscillations. Nicardipine also did not affect EEG delta oscillations over 24 h following application. The time spent in NREM sleep and NREM episode duration was also not affected. Thus, acute block of calcium entry through L-type VGCCs does not interfere with EEG delta oscillations or their homeostatic regulation, despite prior evidence from calcium channel knockout mice.