Sleep spindles mediate hippocampal-neocortical coupling during long-duration ripples

Rescuing impaired hippocampal-cortical interactions and spatial reorientation learning and memory during sleep in a mouse model of Alzheimer's disease using hippocampal 40 Hz stimulation

In preclinical Alzheimer's disease (AD), spatial learning and memory is impaired. We reported similar impairments in 3xTg-AD mice on a virtual maze (VM) spatial-reorientation-task that requires using landmarks to navigate. Hippocampal (HPC)-cortical dysfunction during sleep (important for memory consolidation) is a potential mechanism for memory impairments in AD. We previously found deficits in HPC-cortical coordination during sleep coinciding with VM impairments the next day. Some forms of 40 Hz stimulation seem to clear AD pathology in mice, and improve functional connectivity in AD patients. Thus, we implanted a recording array targeting parietal cortex (PC) and HPC to assess HPC-PC coordination, and an optical fiber targeting HPC for 40 Hz or sham optogenetic stimulation in 3xTg/PV cre mice. We assessed PC delta waves (DW) and HPC sharp wave ripples (SWRs). In sham mice, SWR-DW cross-correlations were reduced, similar to 3xTg-AD mice. In 40 Hz mice, this phase-locking was rescued, as was performance on the VM. However, rescued HPC-PC coupling no longer predicted performance as in NonTg animals. Instead, DWs and SWRs independently predicted performance in 40 Hz mice. Thus, 40 Hz stimulation of HPC rescued functional interactions in the HPC-PC network, and rescued impairments in spatial navigation, but did not rescue the correlation between HPC-PC coordination during sleep and learning and memory. Together this pattern of results could inform AD treatment timing by suggesting that despite applying 40 Hz stimulation before significant tau and amyloid aggregation, pathophysiological processes led to brain changes that were not fully reversed even though cognition was recovered.

Significance Statement

One of the earliest symptoms of Alzheimer's disease (AD) is getting lost in space or experiencing deficits in spatial navigation, which involve navigation computations as well as learning and memory. We investigated cross brain region interactions supporting memory formation as a potential causative factor of impaired spatial learning and memory in AD. To assess this relationship between AD pathophysiology, brain changes, and behavioral alterations, we used a targeted approach for clearing amyloid beta and tau to rescue functional interactions in the brain. This research strongly connects brain activity patterns during sleep to tau and amyloid accumulation, and will aid in understanding the mechanisms underlying cognitive dysfunction in AD. Furthermore, the results offer insight for improving early identification and treatment strategies.

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.

Age-Related Changes in Sleep and Its Implications for Cognitive Decline in Aging Persons With Schizophrenia: A Critical Review

BACKGROUND AND HYPOTHESIS

Cognitive impairment is a core feature of schizophrenia that worsens with aging and interferes with quality of life. Recent work identifies sleep as an actionable target to alleviate cognitive deficits. Cardinal non-rapid eye movement (NREM) sleep oscillations such as sleep spindles and slow oscillations are critical for cognition. People living with schizophrenia (PLWS) and their first-degree relatives have a specific reduction in sleep spindles and an abnormality in their temporal coordination with slow oscillations that predict impaired memory consolidation. While NREM oscillatory activity is reduced in typical aging, it is not known how further disruption in these oscillations contributes to cognitive decline in older PLWS. Another understudied risk factor for cognitive deficits among older PLWS is obstructive sleep apnea (OSA) which may contribute to cognitive decline.

STUDY DESIGN

We conducted a narrative review to examine the published literature on aging, OSA, and NREM sleep oscillations in PLWS.

STUDY RESULTS

Spindles are propagated via thalamocortical feedback loops, and this circuitry shows abnormal hyperconnectivity in schizophrenia as revealed by structural and functional MRI studies. While the risk and severity of OSA increase with age, older PLWS are particularly vulnerable to OSA-related cognitive deficits because OSA is often underdiagnosed and undertreated, and OSA adds further damage to the circuitry that generates NREM sleep oscillations.

CONCLUSIONS

We highlight the critical need to study NREM sleep in older PWLS and propose that identifying and treating OSA in older PLWS will provide an avenue to potentially mitigate and prevent cognitive decline.

Comparing targeted memory reactivation during slow wave sleep and sleep stage 2

Sleep facilitates declarative memory consolidation, which is assumed to rely on the reactivation of newly encoded memories orchestrated by the temporal interplay of slow oscillations (SO), fast spindles and ripples. SO as well as the number of spindles coupled to SO are more frequent during slow wave sleep (SWS) compared to lighter sleep stage 2 (S2). But, it is unclear whether memory reactivation is more effective during SWS than during S2. To test this question, we applied Targeted Memory Reactivation (TMR) in a declarative memory design by presenting learning-associated sound cues during SWS vs. S2 in a counterbalanced within-subject design. Contrary to our hypothesis, memory performance was not significantly better when cues were presented during SWS. Event-related potential (ERP) amplitudes were significantly higher for cues presented during SWS than S2, and the density of SO and SO-spindle complexes was generally higher during SWS than during S2. Whereas SO density increased during and after the TMR period, SO-spindle complexes decreased. None of the parameters were associated with memory performance. These findings suggest that the efficacy of TMR does not depend on whether it is administered during SWS or S2, despite differential processing of memory cues in these sleep stages.

Contribution of basal ganglia activity to REM sleep disorder in Parkinson's disease

BACKGROUND

Rapid eye movement (REM) sleep behaviour disorder (RBD) is one of the most common sleep problems and represents a key prodromal marker in Parkinson's disease (PD). It remains unclear whether and how basal ganglia nuclei, structures that are directly involved in the pathology of PD, are implicated in the occurrence of RBD.

METHOD

Here, in parallel with whole-night video polysomnography, we recorded local field potentials from two major basal ganglia structures, the globus pallidus internus and subthalamic nucleus, in two cohorts of patients with PD who had varied severity of RBD. Basal ganglia oscillatory patterns during RBD and REM sleep without atonia were analysed and compared with another age-matched cohort of patients with dystonia that served as controls.

RESULTS

We found that beta power in both basal ganglia nuclei was specifically elevated during REM sleep without atonia in patients with PD, but not in dystonia. Basal ganglia beta power during REM sleep positively correlated with the extent of atonia loss, with beta elevation preceding the activation of chin electromyogram activities by ~200 ms. The connectivity between basal ganglia beta power and chin muscular activities during REM sleep was significantly correlated with the clinical severity of RBD in PD.

CONCLUSIONS

These findings support that basal ganglia activities are associated with if not directly contribute to the occurrence of RBD in PD. Our study expands the understanding of the role basal ganglia played in RBD and may foster improved therapies for RBD by interrupting the basal ganglia-muscular communication during REM sleep in PD.

Recurring memory reactivation: The offline component of learning

One can be aware of the effort needed to memorize a new fact or to recall the name of a new acquaintance. Because of experiences like this, learning can seem to have only two components, encoding information and, after some delay, retrieving information. To the contrary, learning entails additional, intervening steps that sometimes are hidden from the learner. For firmly acquiring fact and event knowledge in particular, learners are generally not cognizant of the necessity of offline consolidation. The memories that persist to be available reliably at a later time, according to the present conceptualization, are the ones we repeatedly rehearse and integrate with other knowledge, whether we do this intentionally or unknowingly, awake or asleep. This article examines the notion that learning is not a function of waking brain activity alone. What happens in the brain while we sleep also impacts memory storage, and consequently is a critical component of learning. The idea that memories can change over time and become enduring has long been present in memory research and is foundational for the concept of memory consolidation. Nevertheless, the notion that memory consolidation happens during sleep faced much resistance before eventually being firmly established. Research is still needed to elucidate the operation and repercussions of repeated reactivation during sleep. Comprehensively understanding how offline memory reactivation contributes to learning is vital for both theoretical and practical considerations.

Differences in sleep spindle wave density between patients with diabetes mellitus and matched controls: implications for sensing and regulation of peripheral blood glucose

Background

Brain waves during sleep are involved in sensing and regulating peripheral glucose level. Whether brain waves in patients with diabetes differ from those of healthy subjects is unknown. We examined the hypothesis that patients with diabetes have reduced sleep spindle waves, a form of brain wave implicated in periphery glucose regulation during sleep.

Methods

From a retrospective analysis of polysomnography (PSG) studies on patients who underwent sleep apnea evaluation, we identified 1,214 studies of patients with diabetes mellitus (>66% type 2) and included a sex- and age-matched control subject for each within the scope of our analysis. We similarly identified 376 patients with prediabetes and their matched controls. We extracted spindle characteristics from artifact-removed PSG electroencephalograms and other patient data from records. We used rank-based statistical methods to test hypotheses. We validated our finding on an external PSG dataset.

Results

Patients with diabetes mellitus exhibited on average about half the spindle density (median=0.38 spindles/min) during sleep as their matched control subjects (median=0.70 spindles/min) (P<2.2e-16). Compared to controls, spindle loss was more pronounced in female patients than in male patients in the frontal regions of the brain (P=0.04). Patients with prediabetes also exhibited signs of lower spindle density compared to matched controls (P=0.01-0.04).

Conclusions

Patients with diabetes have fewer spindle waves that are implicated in glucose regulation than matched controls during sleep. Besides offering a possible explanation for neurological complications from diabetes, our findings open the possibility that reversing/reducing spindle loss could improve the overall health of patients with diabetes mellitus.

Spindle oscillations in communicating axons within a reconstituted hippocampal formation are strongest in CA3 without thalamus

Spindle-shaped waves of oscillations emerge in EEG scalp recordings during human and rodent non-REM sleep. The association of these 10-16 Hz oscillations with events during prior wakefulness suggests a role in memory consolidation. Human and rodent depth electrodes in the brain record strong spindles throughout the cortex and hippocampus, with possible origins in the thalamus. However, the source and targets of the spindle oscillations from the hippocampus are unclear. Here, we employed an in vitro reconstruction of four subregions of the hippocampal formation with separate microfluidic tunnels for single axon communication between subregions assembled on top of a microelectrode array. We recorded spontaneous 400-1000 ms long spindle waves at 10-16 Hz in single axons passing between subregions as well as from individual neurons in those subregions. Spindles were nested within slow waves. The highest amplitudes and most frequent occurrence suggest origins in CA3 neurons that send feed-forward axons into CA1 and feedback axons into DG. Spindles had 50-70% slower conduction velocities than spikes and were not phase-locked to spikes suggesting that spindle mechanisms are independent of action potentials. Therefore, consolidation of declarative-cognitive memories in the hippocampus may be separate from the more easily accessible consolidation of memories related to thalamic motor function.

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.

Impact of single-trial avoidance learning on subsequent sleep

Both non-rapid eye movement (NonREM) sleep and rapid eye movement (REM) sleep, as well as sleep spindle and ripple oscillations, are important for memory formation. Through cortical EEG recordings of prefrontal cortex and hippocampus during and after an inhibitory avoidance task, we analysed the dynamic changes in the amounts of sleep, spindle and ripple oscillations related to memory formation. The total amount of NonREM sleep was reduced during the first hour after learning. Moreover, significant decrease of the total spindle and ripple counts was observed at the first hour after learning as well. In addition, foot shock alone, with no associated learning, produced little effect on the dynamics of sleep oscillations, indicating that the learning experience is necessary for these changes to occur.

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.

Ripple-locked coactivity of stimulus-specific neurons and human associative memory

Associative memory enables the encoding and retrieval of relations between different stimuli. To better understand its neural basis, we investigated whether associative memory involves temporally correlated spiking of medial temporal lobe (MTL) neurons that exhibit stimulus-specific tuning. Using single-neuron recordings from patients with epilepsy performing an associative object-location memory task, we identified the object-specific and place-specific neurons that represented the separate elements of each memory. When patients encoded and retrieved particular memories, the relevant object-specific and place-specific neurons activated together during hippocampal ripples. This ripple-locked coactivity of stimulus-specific neurons emerged over time as the patients' associative learning progressed. Between encoding and retrieval, the ripple-locked timing of coactivity shifted, suggesting flexibility in the interaction between MTL neurons and hippocampal ripples according to behavioral demands. Our results are consistent with a cellular account of associative memory, in which hippocampal ripples coordinate the activity of specialized cellular populations to facilitate links between stimuli.

Scalp and hippocampal sleep correlates of memory function in drug-resistant temporal lobe epilepsy

Seminal animal studies demonstrated the role of sleep oscillations such as cortical slow waves, thalamocortical spindles, and hippocampal ripples in memory consolidation. In humans, whether ripples are involved in sleep-related memory processes is less clear. Here, we explored the interactions between sleep oscillations (measured as traits) and general episodic memory abilities in 26 adults with drug-resistant temporal lobe epilepsy who performed scalp-intracranial electroencephalographic recordings and neuropsychological testing, including two analogous hippocampal-dependent verbal and nonverbal memory tasks. We explored the relationships between hemispheric scalp (spindles, slow waves) and hippocampal physiological and pathological oscillations (spindles, slow waves, ripples, and epileptic spikes) and material-specific memory function. To differentiate physiological from pathological ripples, we used multiple unbiased data-driven clustering approaches. At the individual level, we found material-specific cerebral lateralization effects (left-verbal memory, right-nonverbal memory) for all scalp spindles (rs > 0.51, ps < 0.01) and fast spindles (rs > 0.61, ps < 0.002). Hippocampal epileptic spikes and short pathological ripples, but not physiological oscillations, were negatively (rs > -0.59, ps < 0.01) associated with verbal learning and retention scores, with left lateralizing and antero-posterior effects. However, data-driven clustering failed to separate the ripple events into defined clusters. Correlation analyses with the resulting clusters revealed no meaningful or significant associations with the memory scores. Our results corroborate the role of scalp spindles in memory processes in patients with drug-resistant temporal lobe epilepsy. Yet, physiological and pathological ripples were not separable when using data-driven clustering, and thus our findings do not provide support for a role of sleep ripples as trait-like characteristics of general memory abilities in epilepsy.

Sleep spindle architecture associated with distinct clinical phenotypes in older adults at risk for dementia

Sleep spindles are a hallmark of non-REM sleep and play a fundamental role in memory consolidation. Alterations in these spindles are emerging as sensitive biomarkers for neurodegenerative diseases of ageing. Understanding the clinical presentations associated with spindle alterations may help to elucidate the functional role of these distinct electroencephalographic oscillations and the pathophysiology of sleep and neurodegenerative disorders. Here, we use a data-driven approach to examine the sleep, memory and default mode network connectivity phenotypes associated with sleep spindle architecture in older adults (mean age = 66 years). Participants were recruited from a specialist clinic for early diagnosis and intervention for cognitive decline, with a proportion showing mild cognitive deficits on neuropsychological testing. In a sample of 88 people who underwent memory assessment, overnight polysomnography and resting-state fMRI, a k-means cluster analysis was applied to spindle measures of interest: fast spindle density, spindle duration and spindle amplitude. This resulted in three clusters, characterised by preserved spindle architecture with higher fast spindle density and longer spindle duration (Cluster 1), and alterations in spindle architecture (Clusters 2 and 3). These clusters were further characterised by reduced memory (Clusters 2 and 3) and nocturnal hypoxemia, associated with sleep apnea (Cluster 3). Resting-state fMRI analysis confirmed that default mode connectivity was related to spindle architecture, although directionality of this relationship differed across the cluster groups. Together, these results confirm a diversity in spindle architecture in older adults, associated with clinically meaningful phenotypes, including memory function and sleep apnea. They suggest that resting-state default mode connectivity during the awake state can be associated with sleep spindle architecture; however, this is highly dependent on clinical phenotype. Establishing relationships between clinical and neuroimaging features and sleep spindle alterations will advance our understanding of the bidirectional relationships between sleep changes and neurodegenerative diseases of ageing.

Slow oscillation-spindle cross-frequency coupling predicts overnight declarative memory consolidation in older adults

Cross-frequency coupling (CFC) between brain oscillations during non-rapid-eye-movement (NREM) sleep (e.g. slow oscillations [SO] and spindles) may be a neural mechanism of overnight memory consolidation. Declines in CFC across the lifespan might accompany coinciding memory problems with ageing. However, there are few reports of CFC changes during sleep after learning in older adults, controlling for baseline effects. Our objective was to examine NREM CFC in healthy older adults, with an emphasis on spindle activity and SOs from frontal electroencephalogram (EEG), during a learning night after a declarative learning task, as compared to a baseline night without learning. Twenty-five older adults (M [SD] age = 69.12 [5.53] years; 64% female) completed a two-night study, with a pre- and post-sleep word-pair associates task completed on the second night. SO-spindle coupling strength and a measure of coupling phase distance from the SO up-state were both examined for between-night differences and associations with memory consolidation. Coupling strength and phase distance from the up-state peak were both stable between nights. Change in coupling strength between nights was not associated with memory consolidation, but a shift in coupling phase towards (vs. away from) the up-state peak after learning predicted better memory consolidation. Also, an exploratory interaction model suggested that associations between coupling phase closer to the up-state peak and memory consolidation may be moderated by higher (vs. lower) coupling strength. This study supports a role for NREM CFC in sleep-related memory consolidation in older adults.

Temporal cluster-based organization of sleep spindles underlies motor memory consolidation

Sleep benefits motor memory consolidation, which is mediated by sleep spindle activity and associated memory reactivations during non-rapid eye movement (NREM) sleep. However, the particular role of NREM2 and NREM3 sleep spindles and the mechanisms triggering this memory consolidation process remain unclear. Here, simultaneous electroencephalographic and functional magnetic resonance imaging (EEG-fMRI) recordings were collected during night-time sleep following the learning of a motor sequence task. Adopting a time-based clustering approach, we provide evidence that spindles iteratively occur within clustered and temporally organized patterns during both NREM2 and NREM3 sleep. However, the clustering of spindles in trains is related to motor memory consolidation during NREM2 sleep only. Altogether, our findings suggest that spindles' clustering and rhythmic occurrence during NREM2 sleep may serve as an intrinsic rhythmic sleep mechanism for the timed reactivation and subsequent consolidation of motor memories, through synchronized oscillatory activity within a subcortical-cortical network involved during learning.

Mapping sleep's oscillatory events as a biomarker of Alzheimer's disease

INTRODUCTION

Memory-associated neural circuits produce oscillatory events including theta bursts (TBs), sleep spindles (SPs), and slow waves (SWs) in sleep electroencephalography (EEG). Changes in the "coupling" of these events may indicate early Alzheimer's disease (AD) pathogenesis.

METHODS

We analyzed 205 aging adults using single-channel sleep EEG, cerebrospinal fluid (CSF) AD biomarkers, and Clinical Dementia Rating® (CDR®) scale. We mapped SW-TB and SW-SP neural circuit coupling precision to amyloid positivity, cognitive impairment, and CSF AD biomarkers.

RESULTS

Cognitive impairment correlated with lower TB spectral power in SW-TB coupling. Cognitively unimpaired, amyloid positive individuals demonstrated lower precision in SW-TB and SW-SP coupling compared to amyloid negative individuals. Significant biomarker correlations were found in oscillatory event coupling with CSF Aβ42 /Aβ40 , phosphorylated- tau181 , and total-tau.

DISCUSSION

Sleep-dependent memory processing integrity in neural circuits can be measured for both SW-TB and SW-SP coupling. This breakdown associates with amyloid positivity, increased AD pathology, and cognitive impairment.

HIGHLIGHTS

At-home sleep EEG is a potential biomarker of neural circuits linked to memory. Circuit precision is associated with amyloid positivity in asymptomatic aging adults. Levels of CSF amyloid and tau also correlate with circuit precision in sleep EEG. Theta burst EEG power is decreased in very early mild cognitive impairment. This technique may enable inexpensive wearable EEGs for monitoring brain health.

Neural reactivation during human sleep

Sleep promotes memory consolidation: the process by which newly acquired memories are stabilised, strengthened, and integrated into long-term storage. Pioneering research in rodents has revealed that memory reactivation in sleep is a primary mechanism underpinning sleep's beneficial effect on memory. In this review, we consider evidence for memory reactivation processes occurring in human sleep. Converging lines of research support the view that memory reactivation occurs during human sleep, and is functionally relevant for consolidation. Electrophysiology studies have shown that memory reactivation is tightly coupled to the cardinal neural oscillations of non-rapid eye movement sleep, namely slow oscillation-spindle events. In addition, functional imaging studies have found that brain regions recruited during learning become reactivated during post-learning sleep. In sum, the current evidence paints a strong case for a mechanistic role of neural reactivation in promoting memory consolidation during human sleep.

Towards Optimization of Oscillatory Stimulation During Sleep

BACKGROUND

Oscillatory rhythms during sleep, such as slow oscillations (SOs) and spindles and, most importantly, their coupling, are thought to underlie processes of memory consolidation. External slow oscillatory transcranial direct current stimulation (so-tDCS) with a frequency of 0.75 Hz has been shown to improve this coupling and memory consolidation; however, effects varied quite markedly between individuals, studies, and species. In this study, we aimed to determine how precisely the frequency of stimulation must match the naturally occurring SO frequency in individuals to best improve SO-spindle coupling. Moreover, we systematically tested stimulation durations necessary to induce changes.

MATERIALS AND METHODS

We addressed these questions by comparing so-tDCS with individualized frequency to standardized frequency of 0.75 Hz in a within-subject design with 28 older participants during napping while stimulation train durations were systematically varied between 30 seconds, 2 minutes, and 5 minutes.

RESULTS

Stimulation trains as short as 30 seconds were sufficient to modulate the coupling between SOs and spindle activity. Contrary to our expectations, so-tDCS with standardized frequency indicated stronger aftereffects regarding SO-spindle coupling than individualized frequency. Angle and variance of spindle maxima occurrence during the SO cycle were similarly modulated.

CONCLUSIONS

In sum, short stimulation trains were sufficient to induce significant changes in sleep physiology, allowing for more trains of stimulation, which provides methodological advantages and possibly even larger behavioral effects in future studies. Regarding individualized stimulation frequency, further options of optimization need to be investigated, such as closed-loop stimulation, to calibrate stimulation frequency to the SO frequency at the time of stimulation onset.

CLINICAL TRIAL REGISTRATION

The Clinicaltrials.gov registration number for the study is NCT04714879.

Item-specific neural representations during human sleep support long-term memory

Understanding how individual memories are reactivated during sleep is essential in theorizing memory consolidation. Here, we employed the targeted memory reactivation (TMR) paradigm to unobtrusively replaying auditory memory cues during human participants' slow-wave sleep (SWS). Using representational similarity analysis (RSA) on cue-elicited electroencephalogram (EEG), we found temporally segregated and functionally distinct item-specific neural representations: the early post-cue EEG activity (within 0 to 2,000 ms) contained comparable item-specific representations for memory cues and control cues, signifying effective processing of auditory cues. Critically, the later EEG activity (2,500 to 2,960 ms) showed greater item-specific representations for post-sleep remembered items than for forgotten and control cues, indicating memory reprocessing. Moreover, these later item-specific neural representations were supported by concurrently increased spindles, particularly for items that had not been tested prior to sleep. These findings elucidated how external memory cues triggered item-specific neural representations during SWS and how such representations were linked to successful long-term memory. These results will benefit future research aiming to perturb specific memory episodes during sleep.

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.

Hippocampal memory reactivation during sleep is correlated with specific cortical states of the retrosplenial and prefrontal cortices

Episodic memories are thought to be stabilized through the coordination of cortico-hippocampal activity during sleep. However, the timing and mechanism of this coordination remain unknown. To investigate this, we studied the relationship between hippocampal reactivation and slow-wave sleep up and down states of the retrosplenial cortex (RTC) and prefrontal cortex (PFC). We found that hippocampal reactivations are strongly correlated with specific cortical states. Reactivation occurred during sustained cortical Up states or during the transition from up to down state. Interestingly, the most prevalent interaction with memory reactivation in the hippocampus occurred during sustained up states of the PFC and RTC, while hippocampal reactivation and cortical up-to-down state transition in the RTC showed the strongest coordination. Reactivation usually occurred within 150-200 msec of a cortical Up state onset, indicating that a buildup of excitation during cortical Up state activity influences the probability of memory reactivation in CA1. Conversely, CA1 reactivation occurred 30-50 msec before the onset of a cortical down state, suggesting that memory reactivation affects down state initiation in the RTC and PFC, but the effect in the RTC was more robust. Our findings provide evidence that supports and highlights the complexity of bidirectional communication between cortical regions and the hippocampus during sleep.

Dual memory model for experience-once task-incremental lifelong learning

Experience replay (ER) is a widely-adopted neuroscience-inspired method to perform lifelong learning. Nonetheless, existing ER-based approaches consider very coarse memory modules with simple memory and rehearsal mechanisms that cannot fully exploit the potential of memory replay. Evidence from neuroscience has provided fine-grained memory and rehearsal mechanisms, such as the dual-store memory system consisting of PFC-HC circuits. However, the computational abstraction of these processes is still very challenging. To address these problems, we introduce the Dual-Memory (Dual-MEM) model emulating the memorization, consolidation, and rehearsal process in the PFC-HC dual-store memory circuit. Dual-MEM maintains an incrementally updated short-term memory to benefit current-task learning. At the end of the current task, short-term memories will be consolidated into long-term ones for future rehearsal to alleviate forgetting. For the Dual-MEM optimization, we propose two learning policies that emulate different memory retrieval strategies: Direct Retrieval Learning and Mixup Retrieval Learning. Extensive evaluations on eight benchmarks demonstrate that Dual-MEM delivers compelling performance while maintaining high learning and memory utilization efficiencies under the challenging experience-once setting.

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.

Cognitive neuroscience perspective on memory: overview and summary

This paper explores memory from a cognitive neuroscience perspective and examines associated neural mechanisms. It examines the different types of memory: working, declarative, and non-declarative, and the brain regions involved in each type. The paper highlights the role of different brain regions, such as the prefrontal cortex in working memory and the hippocampus in declarative memory. The paper also examines the mechanisms that underlie the formation and consolidation of memory, including the importance of sleep in the consolidation of memory and the role of the hippocampus in linking new memories to existing cognitive schemata. The paper highlights two types of memory consolidation processes: cellular consolidation and system consolidation. Cellular consolidation is the process of stabilizing information by strengthening synaptic connections. System consolidation models suggest that memories are initially stored in the hippocampus and are gradually consolidated into the neocortex over time. The consolidation process involves a hippocampal-neocortical binding process incorporating newly acquired information into existing cognitive schemata. The paper highlights the role of the medial temporal lobe and its involvement in autobiographical memory. Further, the paper discusses the relationship between episodic and semantic memory and the role of the hippocampus. Finally, the paper underscores the need for further research into the neurobiological mechanisms underlying non-declarative memory, particularly conditioning. Overall, the paper provides a comprehensive overview from a cognitive neuroscience perspective of the different processes involved in memory consolidation of different types of memory.

An evolutionary conserved division-of-labor between archicortical and neocortical ripples organizes information transfer during sleep

Systems-level memory consolidation during sleep depends on the temporally precise interplay between cardinal sleep oscillations. Specifically, hippocampal ripples constitute a key substrate of the hippocampal-neocortical dialogue underlying memory formation. Recently, it became evident that ripples are not unique to archicortex, but constitute a wide-spread neocortical phenomenon. To date, little is known about the morphological similarities between archi- and neocortical ripples. Moreover, it remains undetermined if neocortical ripples fulfill distinct functional roles. Leveraging intracranial recordings from the human medial temporal lobe (MTL) and neocortex during sleep, our results reveal region-specific functional specializations, albeit a near-uniform morphology. While MTL ripples synchronize the memory network to trigger directional MTL-to-neocortical information flow, neocortical ripples reduce information flow to minimize interference. At the population level, MTL ripples confined population dynamics to a low-dimensional subspace, while neocortical ripples diversified the population response; thus, constituting an effective mechanism to functionally uncouple the MTL-neocortical network. Critically, we replicated the key findings in rodents, where the same division-of-labor between archi- and neocortical ripples was evident. In sum, these results uncover an evolutionary preserved mechanism where the precisely coordinated interplay between MTL and neocortical ripples temporally segregates MTL information transfer from subsequent neocortical processing during sleep.

Interneuronal GluK1 kainate receptors control maturation of GABAergic transmission and network synchrony in the hippocampus

Kainate type glutamate receptors (KARs) are strongly expressed in GABAergic interneurons and have the capability of modulating their functions via ionotropic and G-protein coupled mechanisms. GABAergic interneurons are critical for generation of coordinated network activity in both neonatal and adult brain, yet the role of interneuronal KARs in network synchronization remains unclear. Here, we show that GABAergic neurotransmission and spontaneous network activity is perturbed in the hippocampus of neonatal mice lacking GluK1 KARs selectively in GABAergic neurons. Endogenous activity of interneuronal GluK1 KARs maintains the frequency and duration of spontaneous neonatal network bursts and restrains their propagation through the hippocampal network. In adult male mice, the absence of GluK1 in GABAergic neurons led to stronger hippocampal gamma oscillations and enhanced theta-gamma cross frequency coupling, coinciding with faster spatial relearning in the Barnes maze. In females, loss of interneuronal GluK1 resulted in shorter sharp wave ripple oscillations and slightly impaired abilities in flexible sequencing task. In addition, ablation of interneuronal GluK1 resulted in lower general activity and novel object avoidance, while causing only minor anxiety phenotype. These data indicate a critical role for GluK1 containing KARs in GABAergic interneurons in regulation of physiological network dynamics in the hippocampus at different stages of development.

Sleep fMRI with simultaneous electrophysiology at 9.4 T in male mice

Sleep is ubiquitous and essential, but its mechanisms remain unclear. Studies in animals and humans have provided insights of sleep at vastly different spatiotemporal scales. However, challenges remain to integrate local and global information of sleep. Therefore, we developed sleep fMRI based on simultaneous electrophysiology at 9.4 T in male mice. Optimized un-anesthetized mouse fMRI setup allowed manifestation of NREM and REM sleep, and a large sleep fMRI dataset was collected and openly accessible. State dependent global patterns were revealed, and state transitions were found to be global, asymmetrical and sequential, which can be predicted up to 17.8 s using LSTM models. Importantly, sleep fMRI with hippocampal recording revealed potentiated sharp-wave ripple triggered global patterns during NREM than awake state, potentially attributable to co-occurrence of spindle events. To conclude, we established mouse sleep fMRI with simultaneous electrophysiology, and demonstrated its capability by revealing global dynamics of state transitions and neural events.

Mapping Sleep's Oscillatory Events as a Biomarker of Alzheimer's Disease

Objective

Memory-associated neural circuits produce oscillatory events within single-channel sleep electroencephalography (EEG), including theta bursts (TBs), sleep spindles (SPs) and multiple subtypes of slow waves (SWs). Changes in the temporal "coupling" of these events are proposed to serve as a biomarker for early stages of Alzheimer's disease (AD) pathogenesis.

Methods

We analyzed data from 205 aging adults, including single-channel sleep EEG, cerebrospinal fluid (CSF) AD-associated biomarkers, and Clinical Dementia Rating® (CDR®) scale. Individual SW events were sorted into high and low transition frequencies (TF) subtypes. We utilized time-frequency spectrogram locations within sleep EEG to "map" the precision of SW-TB and SW-SP neural circuit coupling in relation to amyloid positivity (by CSF Aβ 42 /Aβ 40 threshold), cognitive impairment (by CDR), and CSF levels of AD-associated biomarkers.

Results

Cognitive impairment was associated with lower TB spectral power in both high and low TF SW-TB coupling (p<0.001, p=0.001). Cognitively unimpaired, amyloid positive aging adults demonstrated lower precision of the neural circuits propagating high TF SW-TB (p<0.05) and low TF SW-SP (p<0.005) event coupling, compared to cognitively unimpaired amyloid negative individuals. Biomarker correlations were significant for high TF SW-TB coupling with CSF Aβ 42 /Aβ 40 (p=0.005), phosphorylated-tau 181 (p<0.005), and total-tau (p<0.05). Low TF SW-SP coupling was also correlated with CSF Aβ 42 /Aβ 40 (p<0.01).

Interpretation

Loss of integrity in neural circuits underlying sleep-dependent memory processing can be measured for both SW-TB and SW-SP coupling in spectral time-frequency space. Breakdown of sleep's memory circuit integrity is associated with amyloid positivity, higher levels of AD-associated pathology, and cognitive impairment.

Ripples in macaque V1 and V4 are modulated by top-down visual attention

Sharp-wave ripples (SWRs) are highly synchronous neuronal activity events. They have been predominantly observed in the hippocampus during offline states such as pause in exploration, slow-wave sleep, and quiescent wakefulness. SWRs have been linked to memory consolidation, spatial navigation, and spatial decision-making. Recently, SWRs have been reported during visual search, a form of remote spatial exploration, in macaque hippocampus. However, the association between SWRs and multiple forms of awake conscious and goal-directed behavior is unknown. We report that ripple activity occurs in macaque visual areas V1 and V4 during focused spatial attention. The occurrence of ripples is modulated by stimulus characteristics, increased by attention toward the receptive field, and by the size of the attentional focus. During attention cued to the receptive field, the monkey's reaction time in detecting behaviorally relevant events was reduced by ripples. These results show that ripple activity is not limited to hippocampal activity during offline states, rather they occur in the neocortex during active attentive states and vigilance behaviors.

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.

Fast network oscillations during non-REM sleep support memory consolidation

The neocortex is disconnected from the outside world during sleep, which has been hypothesized to be relevant for synaptic reorganization involved in memory consolidation. Fast network oscillations, such as hippocampal sharp-wave ripples, cortical ripples, and amygdalar high-frequency oscillations, are prominent during non-REM sleep. Although these oscillations are thought to be generated by local circuit mechanisms, their occurrence rates and amplitudes are modulated by thalamocortical spindles and neocortical slow oscillations during non-REM sleep, suggesting that fast network oscillations and slower oscillations cooperatively work to facilitate memory consolidation. This review discusses the recent progress in understanding the generation, coordination, and functional roles of fast network oscillations. Further, it outlines how fast network oscillations in distinct brain regions synergistically support memory consolidation and retrieval by hosting cross-regional coactivation of memory-related neuronal ensembles.

Conserved Population Dynamics in the Cerebro-Cerebellar System between Waking and Sleep

Despite the importance of the cerebellum for motor learning, and the recognized role of sleep in motor memory consolidation, surprisingly little is known about neural activity in the sleeping cerebro-cerebellar system. Here, we used wireless recording from primary motor cortex (M1) and the cerebellum in three female monkeys to examine the relationship between patterns of single-unit spiking activity observed during waking behavior and in natural sleep. Across the population of recorded units, we observed similarities in the timing of firing relative to local field potential features associated with both movements during waking and up state during sleep. We also observed a consistent pattern of asymmetry in pairwise cross-correlograms, indicative of preserved sequential firing in both wake and sleep at low frequencies. Despite the overall similarity in population dynamics between wake and sleep, there was a global change in the timing of cerebellar activity relative to motor cortex, from contemporaneous in the awake state to motor cortex preceding the cerebellum in sleep. We speculate that similar population dynamics in waking and sleep may imply that cerebellar internal models are activated in both states, despite the absence of movement when asleep. Moreover, spindle frequency coherence between the cerebellum and motor cortex may provide a mechanism for cerebellar computations to influence sleep-dependent learning processes in the motor cortex.SIGNIFICANCE STATEMENT It is well known that sleep can lead to improved motor performance. One possibility is that off-line learning results from neural activity during sleep in brain areas responsible for the control of movement. In this study we show for the first time that neuronal patterns in the cerebro-cerebellar system are conserved during both movements and sleep up-states, albeit with a shift in the relative timing between areas. Additionally, we show the presence of simultaneous M1-cerebellar spike coherence at spindle frequencies associated with up-state replay and postulate that this is a mechanism whereby a cerebellar internal model can shape plasticity in neocortical circuits during sleep.

Sleep spindles in people with schizophrenia, schizoaffective disorders or bipolar disorders: a pilot study in a general population-based cohort

BACKGROUND

Sleep spindles have been involved in sleep stabilization and sleep-related memory mechanisms and their deficit emerged as possible biomarker in schizophrenia. However, whether this sleep phenotype is also present in other disorders that share psychotic symptoms remains unclear. To address this gap, we assessed sleep spindles in participants of a prospective population-based cohort who underwent psychiatric assessment (CoLaus|PsyCoLaus) and polysomnographic recording (HypnoLaus).

METHODS

Sleep was recorded using ambulatory polysomnography in participants (N = 1037) to the PsyCoLaus study. Sleep spindle parameters were measured in people with a lifelong diagnosis of schizophrenia (SZ), schizoaffective depressive (SAD), schizoaffective manic (SAM), bipolar disorder type I (BP-I) and type II (BP-II). The associations between lifetime diagnostic status (independent variables, SZ, SAD, SAM, BPD-I, BPD-II, controls) and spindle parameters (dependent variables) including density, duration, frequency and maximum amplitude, for all (slow and fast), slow- and fast-spindle were assessed using linear mixed models. Pairwise comparisons of the different spindle parameters between the SZ group and each of the other psychiatric groups was performed using a contrast testing framework from our multiple linear mixed models.

RESULTS

Our results showed a deficit in the density and duration of sleep spindles in people with SZ. They also indicated that participants with a diagnosis of SAD, SAM, BP-I and BP-II exhibited different sleep spindle phenotypes. Interestingly, spindle densities and frequencies were different in people with a history of manic symptoms (SAM, BP-I, and BP-II) from those without (SZ, SAD).

CONCLUSIONS

Although carried out on a very small number of participants due to the low prevalence of these disorders in general population, this pilot study brought new elements that argued in favor of a deficit of sleep spindles density and duration in people with schizophrenia. In addition, while we could expect a gradual change in intensity of the same sleep spindle parameters through psychotic diagnoses, our results seem to indicate a more complex situation in which the frequency of sleep spindles might be more impacted by diagnoses including a history of mania or hypomania. Further studies with a larger number of participants are required to confirm these effects.

Brain activations time locked to slow wave-coupled sleep spindles correlates with intellectual abilities

Sleep spindles (SP) are one of the few known electrophysiological neuronal biomarkers of interindividual differences in cognitive abilities and aptitudes. Recent simultaneous electroencephalography with functional magnetic resonance imaging (EEG-fMRI) studies suggest that the magnitude of the activation of brain regions recruited during spontaneous spindle events is specifically related to Reasoning abilities. However, it is not known if the relationship with cognitive abilities differs between uncoupled spindles, uncoupled slow waves (SW), and coupled SW–SP complexes, nor have the functional-neuroanatomical substrates that support this relationship been identified. Here, we investigated the functional significance of activation of brain areas recruited during SW-coupled spindles, uncoupled spindles, and uncoupled slow waves. We hypothesize that brain activations time locked to SW-coupled spindle complexes will be primarily associated to Reasoning abilities, especially in subcortical areas. Our results provide direct evidence that the relationship between Reasoning abilities and sleep spindles depends on spindle coupling status. Specifically, we found that the putamen and thalamus, recruited during coupled SW–SP events were positively correlated with Reasoning abilities. In addition, we found a negative association between Reasoning abilities and hippocampal activation time-locked to uncoupled SWs that might reflect a refractory mechanism in the absence of new, intensive hippocampal-dependent memory processing.

Recurrent Hippocampo-neocortical sleep-state divergence in humans

Sleep is assumed to be a unitary, global state in humans and most other animals that is coordinated by executive centers in the brain stem, hypothalamus, and basal forebrain. However, the common observation of unihemispheric sleep in birds and marine mammals, as well as the recently discovered nonpathological regional sleep in rodents, calls into question whether the whole human brain might also typically exhibit different states between brain areas at the same time. We analyzed sleep states independently from simultaneously recorded hippocampal depth electrodes and cortical scalp electrodes in eight human subjects who were implanted with depth electrodes for pharmacologically intractable epilepsy evaluation. We found that the neocortex and hippocampus could be in nonsimultaneous states, on average, one-third of the night and that the hippocampus often led in asynchronous state transitions. Nonsimultaneous bout lengths varied from 30 s to over 30 min. These results call into question the conclusions of studies, across phylogeny, that measure only surface cortical state but seek to assess the functions and drivers of sleep states throughout the brain.

Are there roles for heterogeneous ribosomes during sleep in the rodent brain?

The regulation of mRNA translation plays an essential role in neurons, contributing to important brain functions, such as brain plasticity and memory formation. Translation is conducted by ribosomes, which at their core consist of ribosomal proteins (RPs) and ribosomal RNAs. While translation can be regulated at diverse levels through global or mRNA-specific means, recent evidence suggests that ribosomes with distinct configurations are involved in the translation of different subsets of mRNAs. However, whether and how such proclaimed ribosome heterogeneity could be connected to neuronal functions remains largely unresolved. Here, we postulate that the existence of heterologous ribosomes within neurons, especially at discrete synapses, subserve brain plasticity. This hypothesis is supported by recent studies in rodents showing that heterogeneous RP expression occurs in dendrites, the compartment of neurons where synapses are made. We further propose that sleep, which is fundamental for brain plasticity and memory formation, has a particular role in the formation of heterologous ribosomes, specialised in the translation of mRNAs specific for synaptic plasticity. This aspect of our hypothesis is supported by recent studies showing increased translation and changes in RP expression during sleep after learning. Thus, certain RPs are regulated by sleep, and could support different sleep functions, in particular brain plasticity. Future experiments investigating cell-specific heterogeneity in RPs across the sleep-wake cycle and in response to different behaviour would help address this question.

Real-time stimulation during sleep: prior findings, novel developments, and future perspectives

Real-time brain stimulation is a powerful technique that continues to gain importance in the field of sleep and cognition. In this special issue, we collected 14 articles about real-time stimulation during sleep, including one review, 12 research articles and one letter covering both human and rodent research from various fields. We hope this special issue sparks greater interest and inspires fellow sleep researchers and clinicians to develop new ideas in the exciting topic of real-time stimulation.

Effects of Anti-Seizure Medication on Sleep Spindles and Slow Waves in Drug-Resistant Epilepsy

There is a close bidirectional relationship between sleep and epilepsy. Anti-seizure medications (ASM) act to reduce seizure frequency but can also impact sleep; this remains a relatively unexplored field given the importance of sleep on seizure occurrence, memory consolidation, and quality of life. We compared the effect of poly-ASM treatment on a night of sleep compared to an unmedicated night in patients with drug-resistant epilepsy, where ASMs were withdrawn and later restored as part of their pre-surgical evaluation. Within-subject analysis between medicated and unmedicated nights showed ASMs increased spindle (11-16 Hz) power and decreased slow wave (0.1-2 Hz) amplitude. Spindles became less strongly coupled to slow waves in the ASM night compared to no-ASM night, with effects to both the phase and strength of coupling and correlated with slow wave reduction. These effects were not seen in age-matched controls from the same unit where ASMs were not changed between two nights. Overall, we found that ASM polytherapy not only changed specific sleep waveforms, but also the fine interplay of spindle/slow wave coupling. Since these sleep oscillations impact both seizure occurrence and memory consolidation, our findings provide evidence towards a decoupling impact of ASMs on sleep that should be considered in future studies of sleep and memory disruption in people with epilepsy.

Enhancement of Hippocampal-Thalamocortical Temporal Coordination during Slow-Frequency Long-Duration Anterior Thalamic Spindles

Temporal nesting of cortical slow oscillations, thalamic spindles, and hippocampal ripples indicates multiregional neuronal interactions required for memory consolidation. However, how the thalamic activity during spindles organizes hippocampal dynamics remains largely undetermined. We analyzed simultaneous recordings of anterodorsal thalamus and CA1 in male mice to determine the contribution of thalamic spindles in cross-regional synchronization. Our results indicated that temporal hippocampo-thalamocortical coupling was more enhanced during slower and longer thalamic spindles. Additionally, spindles occurring closer to slow oscillation trough were more strongly coupled to ripples. We found that the temporal association between CA1 spiking/ripples and thalamic spindles was stronger following spatial exploration compared with baseline sleep. We further developed a hippocampal-thalamocortical model to explain the mechanism underlying the duration and frequency-dependent coupling of thalamic spindles to hippocampal activity. Our findings shed light on our understanding of the functional role of thalamic activity during spindles on multiregional information transfer.SIGNIFICANCE STATEMENT The contribution of thalamic spindles with differential properties to cross-regional synchronization and information transfer still remains poorly understood. Using simultaneous anterodorsal thalamic and hippocampal recordings from naturally sleeping mice before and after exploration, we found strong coupling of CA1 units to anterodorsal thalamic spindles and increase of this coupling following spatial experience. We further showed that the temporal coupling of CA1 units and hippocampal ripples with thalamic spindles and the spindle-associated modulation of CA1 units with ripples were stronger for spindles with slower frequency of oscillations. Our experimental as well as computational findings using a hippocampal-thalamocortical model provide the first demonstration that spindle frequency and duration can provide valuable information about the underlying multiregional interactions essential for memory consolidation computations.

Slow oscillations promote long-range effective communication: The key for memory consolidation in a broken-down network

This work introduces a noninvasive approach to understanding information processing during sleep. Our results demonstrate that slow oscillations (SOs) provide the temporal-topographical event framework whereby long-range information flow increases dramatically compared to the relatively local activity patterns of the rest of sleep. The findings represent a conceptual leap in understanding how SOs unlock memory consolidation in a broken-down network, which is by promoting long-range, effective communication. This research will promote further investigations of understanding how brain oscillations alone and in nested rhythms promote network communication, as well as investigate how these properties vary and predict patterns of deficits in clinical populations and aging humans.

A prominent and robust finding in cognitive neuroscience is the strengthening of memories during nonrapid eye movement (NREM) sleep, with slow oscillations (SOs;<1Hz) playing a critical role in systems-level consolidation. However, NREM generally shows a breakdown in connectivity and reduction of synaptic plasticity with increasing depth: a brain state seemingly unfavorable to memory consolidation. Here, we present an approach to address this apparent paradox that leverages an event-related causality measure to estimate directional information flow during NREM in epochs with and without SOs. Our results confirm that NREM is generally a state of dampened neural communication but reveals that SOs provide two windows of enhanced large-scale communication before and after the SO trough. These peaks in communication are significantly higher when SOs are coupled with sleep spindles compared with uncoupled SOs. To probe the functional relevance of these SO-selective peaks of information flow, we tested the temporal and topographic conditions that predict overnight episodic memory improvement. Our results show that global, long-range communication during SOs promotes sleep-dependent systems consolidation of episodic memories. A significant correlation between peaks of information flow and memory improvement lends predictive validity to our measurements of effective connectivity. In other words, we were able to predict memory improvement based on independent electrophysiological observations during sleep. This work introduces a noninvasive approach to understanding information processing during sleep and provides a mechanism for how systems-level brain communication can occur during an otherwise low connectivity sleep state. In short, SOs are a gating mechanism for large-scale neural communication, a necessary substrate for systems consolidation and long-term memory formation.

Mesial-Temporal Epileptic Ripples Correlate With Verbal Memory Impairment

Rationale

High frequency oscillations (HFO; ripples = 80–200, fast ripples 200–500 Hz) are promising epileptic biomarkers in patients with epilepsy. However, especially in temporal epilepsies differentiation of epileptic and physiological HFO activity still remains a challenge. Physiological sleep-spindle-ripple formations are known to play a role in slow-wave-sleep memory consolidation. This study aimed to find out if higher rates of mesial-temporal spindle-ripples correlate with good memory performance in epilepsy patients and if surgical removal of spindle-ripple-generating brain tissue correlates with a decline in memory performance. In contrast, we hypothesized that higher rates of overall ripples or ripples associated with interictal epileptic spikes correlate with poor memory performance.

Methods

Patients with epilepsy implanted with electrodes in mesial-temporal structures, neuropsychological memory testing and subsequent epilepsy surgery were included. Ripples and epileptic spikes were automatically detected in intracranial EEG and sleep-spindles in scalp EEG. The coupling of ripples to spindles was automatically analyzed. Mesial-temporal spindle-ripple rates in the speech-dominant-hemisphere (left in all patients) were correlated with verbal memory test results, whereas ripple rates in the non-speech-dominant hemisphere were correlated with non-verbal memory test performance, using Spearman correlation).

Results

Intracranial EEG and memory test results from 25 patients could be included. All ripple rates were significantly higher in seizure onset zone channels (p < 0.001). Patients with pre-surgical verbal memory impairment had significantly higher overall ripple rates in left mesial-temporal channels than patients with intact verbal memory (Mann–Whitney-U-Test: p = 0.039). Spearman correlations showed highly significant negative correlations of the pre-surgical verbal memory performance with left mesial-temporal spike associated ripples (r_s = −0.458; p = 0.007) and overall ripples (r_s = −0.475; p = 0.006). All three ripple types in right-sided mesial-temporal channels did not correlate with pre-surgical nonverbal memory. No correlation for the difference between post- and pre-surgical memory and pre-surgical spindle-ripple rates was seen in patients with left-sided temporal or mesial-temporal surgery.

Discussion

This study fails to establish a clear link between memory performance and spindle ripples. This highly suggests that spindle-ripples are only a small portion of physiological ripples contributing to memory performance. More importantly, this study indicates that spindle-ripples do not necessarily compromise the predictive value of ripples in patients with temporal epilepsy. The majority of ripples were clearly linked to areas with poor memory function.

Coupling of in vitro Neocortical-Hippocampal Coculture Bursts Induces Different Spike Rhythms in Individual Networks

Brain-state alternation is important for long-term memory formation. Each brain state can be identified with a specific process in memory formation, e.g., encoding during wakefulness or consolidation during sleeping. The hippocampal-neocortical dialogue was proposed as a hypothetical framework for systems consolidation, which features different cross-frequency couplings between the hippocampus and distributed neocortical regions in different brain states. Despite evidence supporting this hypothesis, little has been reported about how information is processed with shifts in brain states. To address this gap, we developed an in vitro neocortical-hippocampal coculture model to study how activity coupling can affect connections between coupled networks. Neocortical and hippocampal neurons were cultured in two different compartments connected by a micro-tunnel structure. The network activity of the coculture model was recorded by microelectrode arrays underlying the substrate. Rhythmic bursting was observed in the spontaneous activity and electrical evoked responses. Rhythmic bursting activity in one compartment could couple to that in the other via axons passing through the micro-tunnels. Two types of coupling patterns were observed: slow-burst coupling (neocortex at 0.1–0.5 Hz and hippocampus at 1 Hz) and fast burst coupling (neocortex at 20–40 Hz and hippocampus at 4–10 Hz). The network activity showed greater synchronicity in the slow-burst coupling, as indicated by changes in the burstiness index. Network synchronicity analysis suggests the presence of different information processing states under different burst activity coupling patterns. Our results suggest that the hippocampal-neocortical coculture model possesses multiple modes of burst activity coupling between the cortical and hippocampal parts. With the addition of external stimulation, the neocortical-hippocampal network model we developed can elucidate the influence of state shifts on information processing.

Sleep spindles track cortical learning patterns for memory consolidation

Memory consolidation-the transformation of labile memory traces into stable long-term representations-is facilitated by post-learning sleep. Computational and biophysical models suggest that sleep spindles may play a key mechanistic role for consolidation, igniting structural changes at cortical sites involved in prior learning. Here, we tested the resulting prediction that spindles are most pronounced over learning-related cortical areas and that the extent of this learning-spindle overlap predicts behavioral measures of memory consolidation. Using high-density scalp electroencephalography (EEG) and polysomnography (PSG) in healthy volunteers, we first identified cortical areas engaged during a temporospatial associative memory task (power decreases in the alpha/beta frequency range, 6-20 Hz). Critically, we found that participant-specific topographies (i.e., spatial distributions) of post-learning sleep spindle amplitude correlated with participant-specific learning topographies. Importantly, the extent to which spindles tracked learning patterns further predicted memory consolidation across participants. Our results provide empirical evidence for a role of post-learning sleep spindles in tracking learning networks, thereby facilitating memory consolidation.

Rhythmic Memory Consolidation in the Hippocampus

Functions of the brain and body are oscillatory in nature and organized according to a logarithmic scale. Brain oscillations and bodily functions such as respiration and heartbeat appear nested within each other and coupled together either based on phase or based on phase and amplitude. This facilitates communication in wide-spread neuronal networks and probably also between the body and the brain. It is a widely accepted view, that nested electrophysiological brain oscillations involving the neocortex, thalamus, and the hippocampus form the basis of memory consolidation. This applies especially to declarative memories, that is, memories of life events, for example. Here, we present our view of hippocampal contribution to the process of memory consolidation based on the general ideas stated above and on some recent findings on the topic by us and by other research groups. We propose that in addition to the interplay between neocortical slow oscillations, spindles, and hippocampal sharp-wave ripples during sleep, there are also additional mechanisms available in the hippocampus to control memory consolidation: a rather non-oscillatory hippocampal electrophysiological phenomenon called the dentate spike might provide a means to not only consolidate but to also modify the neural representation of declarative memories. Further, we suggest that memory consolidation in the hippocampus might be in part paced by breathing. These considerations might open new possibilities for regulating memory consolidation in rest and sleep.

Visuomotor Adaptation Modulates the Clustering of Sleep Spindles Into Trains

Sleep spindles are thought to promote memory consolidation. Recently, we have shown that visuomotor adaptation (VMA) learning increases the density of spindles and promotes the coupling between spindles and slow oscillations, locally, with the level of spindle-SO synchrony predicting overnight memory retention. Yet, growing evidence suggests that the rhythmicity in spindle occurrence may also influence the stabilization of declarative and procedural memories. Here, we examined if VMA learning promotes the temporal organization of sleep spindles into trains. We found that VMA increased the proportion of spindles and spindle-SO couplings in trains. In agreement with our previous work, this modulation was observed over the contralateral hemisphere to the trained hand, and predicted overnight memory retention. Interestingly, spindles grouped in a cluster showed greater amplitude and duration than isolated spindles. The fact that these features increased as a function of train length, provides evidence supporting a biological advantage of this temporal arrangement. Our work opens the possibility that the periodicity of NREM oscillations may be relevant in the stabilization of procedural memories.

Slow oscillation–spindle coupling strength predicts real-life gross-motor learning in adolescents and adults

Previously, we demonstrated that precise temporal coordination between slow oscillations (SOs) and sleep spindles indexes declarative memory network development (Hahn et al., 2020). However, it is unclear whether these findings in the declarative memory domain also apply in the motor memory domain. Here, we compared adolescents and adults learning juggling, a real-life gross-motor task. Juggling performance was impacted by sleep and time of day effects. Critically, we found that improved task proficiency after sleep lead to an attenuation of the learning curve, suggesting a dynamic juggling learning process. We employed individualized cross-frequency coupling analyses to reduce inter- and intragroup variability of oscillatory features. Advancing our previous findings, we identified a more precise SO–spindle coupling in adults compared to adolescents. Importantly, coupling precision over motor areas predicted overnight changes in task proficiency and learning curve, indicating that SO–spindle coupling relates to the dynamic motor learning process. Our results provide first evidence that regionally specific, precisely coupled sleep oscillations support gross-motor learning.

Eszopiclone and Zolpidem Produce Opposite Effects on Hippocampal Ripple Density

Clinical populations have memory deficits linked to sleep oscillations that can potentially be treated with sleep medications. Eszopiclone and zolpidem (two non-benzodiazepine hypnotics) both enhance sleep spindles. Zolpidem improved sleep-dependent memory consolidation in humans, but eszopiclone did not. These divergent results may reflect that the two drugs have different effects on hippocampal ripple oscillations, which correspond to the reactivation of neuronal ensembles that represent previous waking activity and contribute to memory consolidation. We used extracellular recordings in the CA1 region of rats and systemic dosing of eszopiclone and zolpidem to test the hypothesis that these two drugs differentially affect hippocampal ripples and spike activity. We report evidence that eszopiclone makes ripples sparser, while zolpidem increases ripple density. In addition, eszopiclone led to a drastic decrease in spike firing, both in putative pyramidal cells and interneurons, while zolpidem did not substantially alter spiking. These results provide an explanation of the different effects of eszopiclone and zolpidem on memory in human studies and suggest that sleep medications can be used to regulate hippocampal ripple oscillations, which are causally linked to sleep-dependent memory consolidation.

Looking for the neural basis of memory

Memory neuroscientists often measure neural activity during task trials designed to recruit specific memory processes. Behavior is championed as crucial for deciphering brain-memory linkages but is impoverished in typical experiments that rely on summary judgments. We criticize this approach as being blind to the multiple cognitive, neural, and behavioral processes that occur rapidly within a trial to support memory. Instead, time-resolved behaviors such as eye movements occur at the speed of cognition and neural activity. We highlight successes using eye-movement tracking with in vivo electrophysiology to link rapid hippocampal oscillations to encoding and retrieval processes that interact over hundreds of milliseconds. This approach will improve research on the neural basis of memory because it pinpoints discrete moments of brain-behavior-cognition correspondence.