Sleep spindle-related reactivation of category-specific cortical regions after learning face-scene associations

Forgetting unwanted memories in sleep

Memories are sometimes best forgotten, but how do our brains weaken unwanted details of the past? We propose a theoretical framework in which memory reactivation during sleep supports adaptive forgetting. This mnemonic rebalancing underpins the affective benefits of sleep by ensuring that our memories remain aligned with our emotional goals.

A visual paired associate learning (vPAL) paradigm to study memory consolidation during sleep

Sleep improves the consolidation and long-term stability of newly formed memories and associations. Most research on human declarative memory and its consolidation during sleep uses word-pair associations requiring exhaustive learning. In the present study, we present the visual paired association learning (vPAL) paradigm, in which participants learn new associations between images of celebrities and animals. The vPAL is based on a one-shot exposure that resembles learning in natural conditions. We tested if vPAL can reveal a role for sleep in memory consolidation by assessing the specificity of memory recognition, and the cued recall performance, before and after sleep. We found that a daytime nap improved the stability of recognition memory and discrimination abilities compared to identical intervals of wakefulness. By contrast, cued recall of associations did not exhibit significant sleep-dependent effects. High-density electroencephalography during naps further revealed an association between sleep spindle density and stability of recognition memory. Thus, the vPAL paradigm opens new avenues for future research on sleep and memory consolidation across ages and heterogeneous populations in health and disease.

Coordinated NREM sleep oscillations among hippocampal subfields modulate synaptic plasticity in humans

The integration of hippocampal oscillations during non-rapid eye movement (NREM) sleep is crucial for memory consolidation. However, how cardinal sleep oscillations bind across various subfields of the human hippocampus to promote information transfer and synaptic plasticity remains unclear. Using human intracranial recordings from 25 epilepsy patients, we find that hippocampal subfields, including DG/CA3, CA1, and SUB, all exhibit significant delta and spindle power during NREM sleep. The DG/CA3 displays strong coupling between delta and ripple oscillations with all the other hippocampal subfields. In contrast, the regions of CA1 and SUB exhibit more precise coordination, characterized by event-level triple coupling between delta, spindle, and ripple oscillations. Furthermore, we demonstrate that the synaptic plasticity within the hippocampal circuit, as indexed by delta-wave slope, is linearly modulated by spindle power. In contrast, ripples act as a binary switch that triggers a sudden increase in delta-wave slope. Overall, these results suggest that different subfields of the hippocampus regulate one another through diverse layers of sleep oscillation synchronization, collectively facilitating information processing and synaptic plasticity during NREM sleep.

Sleep spindle density and temporal clustering are associated with sleep-dependent memory consolidation in Parkinson's disease

STUDY OBJECTIVES

Sleep is required for successful memory consolidation. Sleep spindles, bursts of oscillatory activity occurring during non-rapid eye movement sleep, are known to be crucial for this process and, recently, it has been proposed that the temporal organization of spindles into clusters might additionally play a role in memory consolidation. In Parkinson's disease, spindle activity is reduced, and this reduction has been found to be predictive of cognitive decline. However, it remains unknown whether alterations in sleep spindles in Parkinson's disease are predictive of sleep-dependent cognitive processes such as memory consolidation, leaving open questions about the possible mechanisms linking sleep and a more general cognitive state in Parkinson's patients.

METHODS

The current study sought to fill this gap by recording overnight polysomnography and measuring overnight declarative memory consolidation in a sample of 35 patients with Parkinson's. Memory consolidation was measured using a verbal paired-associates task administered before and after the night of recorded sleep.

RESULTS

We found that lower sleep spindle density at frontal leads during non-rapid eye movement stage 3 was associated with worse overnight declarative memory consolidation. We also found that patients who showed less temporal clustering of spindles exhibited worse declarative memory consolidation.

CONCLUSIONS

These results suggest alterations to sleep spindles, which are known to be a consequence of Parkinson's disease, might represent a mechanism by which poor sleep leads to worse cognitive function in Parkinson's patients.

CITATION

Lahlou S, Kaminska M, Doyon J, Carrier J, Sharp M. Sleep spindle density and temporal clustering are associated with sleep-dependent memory consolidation in Parkinson's disease. J Clin Sleep Med. 2024;20(7):1153-1162.

Delineating memory reactivation in sleep with verbal and non-verbal retrieval cues

Sleep supports memory consolidation via the reactivation of newly formed memory traces. One way to investigate memory reactivation in sleep is by exposing the sleeping brain to auditory retrieval cues; a paradigm known as targeted memory reactivation. To what extent the acoustic properties of memory cues influence the effectiveness of targeted memory reactivation, however, has received limited attention. We addressed this question by exploring how verbal and non-verbal memory cues affect oscillatory activity linked to memory reactivation in sleep. Fifty-one healthy male adults learned to associate visual stimuli with spoken words (verbal cues) and environmental sounds (non-verbal cues). Subsets of the verbal and non-verbal memory cues were then replayed during sleep. The voice of the verbal cues was either matched or mismatched to learning. Memory cues (relative to unheard control cues) prompted an increase in theta/alpha and spindle power, which have been heavily implicated in sleep-associated memory processing. Moreover, verbal memory cues were associated with a stronger increase in spindle power than non-verbal memory cues. There were no significant differences between the matched and mismatched verbal cues. Our findings suggest that verbal memory cues may be most effective for triggering memory reactivation in sleep, as indicated by an amplified spindle response.

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.

Are there effects of light exposure on daytime sleep for rotating shift nurses after night shift?: an EEG power analysis

Introduction

Night-shift workers often face various health issues stemming from circadian rhythm shift and the consequent poor sleep quality. We aimed to study nurses working night shifts, evaluate the electroencephalogram (EEG) pattern of daytime sleep, and explore possible pattern changes due to ambient light exposure (30 lux) compared to dim conditions (<5 lux) during daytime sleep.

Moethods

The study involved 31 participants who worked night shifts and 24 healthy adults who had never worked night shifts. The sleep macro and microstructures were analyzed, and electrophysiological activity was compared (1) between nighttime sleep and daytime sleep with dim light and (2) between daytime sleep with dim and 30 lux light conditions.

Results

The daytime sleep group showed lower slow or delta wave power during non-rapid eye movement (NREM) sleep than the nighttime sleep group. During daytime sleep, lower sigma wave power in N2 sleep was observed under light exposure compared to no light exposure. Moreover, during daytime sleep, lower slow wave power in N3 sleep in the last cycle was observed under light exposure compared to no light exposure.

Discussion

Our study demonstrated that night shift work and subsequent circadian misalignment strongly affect sleep quality and decrease slow and delta wave activities in NREM sleep. We also observed that light exposure during daytime sleep could additionally decrease N2 sleep spindle activity and N3 waves in the last sleep cycle.

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.

Sleep spindles consolidate declarative memory with tags: A meta-analysis of adult data

Tags are attached to salient information during the wake period, which can preferentially determine what information can be consolidated during sleep. Previous studies demonstrated that spindles during non-rapid eye movement (NREM) sleep give priority to strengthening memory representations with tags, indicating a privileged reactivation of tagged information. The current meta-analysis investigated whether and how spindles can capture different tags to consolidate declarative memory. This study searched the Web of Science, Google Scholar, PubMed, PsycINFO, and OATD databases for studies that spindles consolidate declarative memory with tags. A meta-analysis using a random-effects model was performed. Based on 19 datasets from 18 studies (N = 388), spindles had a medium effect on the consolidation of declarative memory with tags ( r = 0.519). In addition, spindles derived from whole-night sleep and nap studies were positively related to the consolidation of memory representations with tags. These findings reveal the shared mechanism that spindles are actively involved in the prefrontal-hippocampus circuits to consolidate memory with tags.

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.

Auditory inputs modulate intrinsic neuronal timescales during sleep

Functional magnetic resonance imaging (fMRI) studies have demonstrated that intrinsic neuronal timescales (INT) undergo modulation by external stimulation during consciousness. It remains unclear if INT keep the ability for significant stimulus-induced modulation during primary unconscious states, such as sleep. This fMRI analysis addresses this question via a dataset that comprises an awake resting-state plus rest and stimulus states during sleep. We analyzed INT measured via temporal autocorrelation supported by median frequency (MF) in the frequency-domain. Our results were replicated using a biophysical model. There were two main findings: (1) INT prolonged while MF decreased from the awake resting-state to the N2 resting-state, and (2) INT shortened while MF increased during the auditory stimulus in sleep. The biophysical model supported these results by demonstrating prolonged INT in slowed neuronal populations that simulate the sleep resting-state compared to an awake state. Conversely, under sine wave input simulating the stimulus state during sleep, the model's regions yielded shortened INT that returned to the awake resting-state level. Our results highlight that INT preserve reactivity to stimuli in states of unconsciousness like sleep, enhancing our understanding of unconscious brain dynamics and their reactivity to stimuli.

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.

Functional MRI reveals brain-wide actions of thalamically-initiated oscillatory activities on associative memory consolidation

As a key oscillatory activity in the brain, thalamic spindle activities are long believed to support memory consolidation. However, their propagation characteristics and causal actions at systems level remain unclear. Using functional MRI (fMRI) and electrophysiology recordings in male rats, we found that optogenetically-evoked somatosensory thalamic spindle-like activities targeted numerous sensorimotor (cortex, thalamus, brainstem and basal ganglia) and non-sensorimotor limbic regions (cortex, amygdala, and hippocampus) in a stimulation frequency- and length-dependent manner. Thalamic stimulation at slow spindle frequency (8 Hz) and long spindle length (3 s) evoked the most robust brain-wide cross-modal activities. Behaviorally, evoking these global cross-modal activities during memory consolidation improved visual-somatosensory associative memory performance. More importantly, parallel visual fMRI experiments uncovered response potentiation in brain-wide sensorimotor and limbic integrative regions, especially superior colliculus, periaqueductal gray, and insular, retrosplenial and frontal cortices. Our study directly reveals that thalamic spindle activities propagate in a spatiotemporally specific manner and that they consolidate associative memory by strengthening multi-target memory representation.

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.

Memory reactivations during sleep: a neural basis of dream experiences?

Newly encoded memory traces are spontaneously reactivated during sleep. Since their discovery in the 1990s, these memory reactivations have been discussed as a potential neural basis for dream experiences. New results from animal and human research, as well as from the rapidly growing field of sleep and dream engineering, provide essential insights into this question, and reveal both strong parallels and disparities between the two phenomena. We suggest that, although memory reactivations may contribute to subjective experiences across different states of consciousness, they are not likely to be the primary neural basis of dreaming. We identify important limitations in current research paradigms and suggest novel strategies to address this question empirically.

Topographic-dynamic reorganisation model of dreams (TRoD) - A spatiotemporal approach

Dreams are one of the most bizarre and least understood states of consciousness. Bridging the gap between brain and phenomenology of (un)conscious experience, we propose the Topographic-dynamic Re-organization model of Dreams (TRoD). Topographically, dreams are characterized by a shift towards increased activity and connectivity in the default-mode network (DMN) while they are reduced in the central executive network, including the dorsolateral prefrontal cortex (except in lucid dreaming). This topographic re-organization is accompanied by dynamic changes; a shift towards slower frequencies and longer timescales. This puts dreams dynamically in an intermediate position between awake state and NREM 2/SWS sleep. TRoD proposes that the shift towards DMN and slower frequencies leads to an abnormal spatiotemporal framing of input processing including both internally- and externally-generated inputs (from body and environment). In dreams, a shift away from temporal segregation to temporal integration of inputs results in the often bizarre and highly self-centric mental contents as well as hallucinatory-like states. We conclude that topography and temporal dynamics are core features of the TroD, which may provide the connection of neural and mental activity, e.g., brain and experience during dreams as their "common currency".

Visual Plasticity in Adulthood: Perspectives from Hebbian and Homeostatic Plasticity

The visual system retains profound plastic potential in adulthood. In the current review, we summarize the evidence of preserved plasticity in the adult visual system during visual perceptual learning as well as both monocular and binocular visual deprivation. In each condition, we discuss how such evidence reflects two major cellular mechanisms of plasticity: Hebbian and homeostatic processes. We focus on how these two mechanisms work together to shape plasticity in the visual system. In addition, we discuss how these two mechanisms could be further revealed in future studies investigating cross-modal plasticity in the visual system.

Sleep spindles and slow waves are physiological markers for age-related changes in gray matter in brain regions supporting problem-solving skills

As we age, the added benefit of sleep for memory consolidation is lost. One of the hallmark age-related changes in sleep is the reduction of sleep spindles and slow waves. Gray matter neurodegeneration is related to both age-related changes in sleep and age-related changes in memory, including memory for problem-solving skills. Here, we investigated whether spindles and slow waves might serve as biological markers for neurodegeneration of gray matter and for the related memory consolidation deficits in older adults. Forty healthy young adults (20-35 yr) and 30 healthy older adults (60-85 yr) were assigned to either nap or wake conditions. Participants were trained on the Tower of Hanoi in the morning, followed by either a 90-min nap opportunity or period of wakefulness, and were retested afterward. We found that age-related changes in sleep spindles and slow waves were differentially related to gray matter intensity in young and older adults in brain regions that support sleep-dependent memory consolidation for problem-solving skills. Specifically, we found that spindles were related to gray matter in neocortical areas (e.g., somatosensory and parietal cortex), and slow waves were related to gray matter in the anterior cingulate, hippocampus, and caudate, all areas known to support problem-solving skills. These results suggest that both sleep spindles and slow waves may serve as biological markers of age-related neurodegeneration of gray matter and the associated reduced benefit of sleep for memory consolidation in older adults.

Sleep, learning, and memory in human research using noninvasive neuroimaging techniques

An accumulating body of evidence indicates that sleep is beneficial for learning and memory. Task performance improves significantly after a period that includes sleep, whereas a lack of sleep nullifies or impairs such improvements. Our current knowledge about sleep's role in learning and memory has been obtained based on studies that were conducted in both animal models and human subjects. Nevertheless, how sleep promotes learning and memory in humans is not fully understood. In this review, we overview our current understating of how sleep may contribute to learning and memory, covering different roles of non-rapid eye movement and rapid eye movement sleep. We then discuss cutting-edge advanced techniques that are currently available, including simultaneous functional magnetic resonance imaging (fMRI) and electroencephalogram (EEG) and simultaneous functional magnetic resonance spectroscopy (fMRS) and EEG measurements, and evaluate how these may contribute to advance the understanding of the role of sleep in human cognition. We also highlight the current limitations and challenges using these methods and discuss ways that may allow us to overcome these limitations.

Automated real-time EEG sleep spindle detection for brain-state-dependent brain stimulation

Sleep spindles are a hallmark electroencephalographic feature of non-rapid eye movement sleep, and are believed to be instrumental for sleep-dependent memory reactivation and consolidation. However, direct proof of their causal relevance is hard to obtain, and our understanding of their immediate neurophysiological consequences is limited. To investigate their causal role, spindles need to be targeted in real-time with sensory or non-invasive brain-stimulation techniques. While fully automated offline detection algorithms are well established, spindle detection in real-time is highly challenging due to their spontaneous and transient nature. Here, we present the real-time spindle detector, a robust multi-channel electroencephalographic signal-processing algorithm that enables the automated triggering of stimulation during sleep spindles in a phase-specific manner. We validated the real-time spindle detection method by streaming pre-recorded sleep electroencephalographic datasets to a real-time computer system running a Simulink® Real-Time™ implementation of the algorithm. Sleep spindles were detected with high levels of Sensitivity (~83%), Precision (~78%) and a convincing F1-Score (~81%) in reference to state-of-the-art offline algorithms (which reached similar or lower levels when compared with each other), for both naps and full nights, and largely independent of sleep scoring information. Detected spindles were comparable in frequency, duration, amplitude and symmetry, and showed the typical time-frequency characteristics as well as a centroparietal topography. Spindles were detected close to their centre and reliably at the predefined target phase. The real-time spindle detection algorithm therefore empowers researchers to target spindles during human sleep, and apply the stimulation method and experimental paradigm of their choice.

Neurocognitive Consequences in Children with Sleep Disordered Breathing: Who Is at Risk?

Sleep-disordered breathing (SDB) is a prevalent disease in children characterized by snoring and narrowing of the upper airway leading to gas exchange abnormalities during sleep as well as sleep fragmentation. SDB has been consistently associated with problematic behaviors and adverse neurocognitive consequences in children but causality and determinants of susceptibility remain incompletely defined. Since the 1990s several studies have enlightened these associations and consistently reported poorer academic performance, lower scores on neurocognitive tests, and behavioral abnormalities in children suffering from SDB. However, not all children with SDB develop such consequences, and severity of SDB based on standard diagnostic indices has often failed to discriminate among those children with or without neurocognitive risk. Accordingly, a search for discovery of markers and clinically useful tools that can detect those children at risk for developing cognitive and behavioral deficits has been ongoing. Here, we review the advances in this field and the search for possible detection approaches and unique phenotypes of children with SDB who are at greater risk of developing neurocognitive consequences.

Alterations of sleep oscillations in Alzheimer's disease: A potential role for GABAergic neurons in the cortex, hippocampus, and thalamus

Sleep abnormalities are widely reported in patients with Alzheimer's disease (AD) and are linked to cognitive impairments. Sleep abnormalities could be potential biomarkers to detect AD since they are often observed at the preclinical stage. Moreover, sleep could be a target for early intervention to prevent or slow AD progression. Thus, here we review changes in brain oscillations observed during sleep, their connection to AD pathophysiology and the role of specific brain circuits. Slow oscillations (0.1-1 Hz), sleep spindles (8-15 Hz) and their coupling during non-REM sleep are consistently reduced in studies of patients and in AD mouse models although the timing and magnitude of these alterations depends on the pathophysiological changes and the animal model studied. Changes in delta (1-4 Hz) activity are more variable. Animal studies suggest that hippocampal sharp-wave ripples (100-250 Hz) are also affected. Reductions in REM sleep amount and slower oscillations during REM are seen in patients but less consistently in animal models. Thus, changes in a variety of sleep oscillations could impact sleep-dependent memory consolidation or restorative functions of sleep. Recent mechanistic studies suggest that alterations in the activity of GABAergic neurons in the cortex, hippocampus and thalamic reticular nucleus mediate sleep oscillatory changes in AD and represent a potential target for intervention. Longitudinal studies of the timing of AD-related sleep abnormalities with respect to pathology and dysfunction of specific neural networks are needed to identify translationally relevant biomarkers and guide early intervention strategies to prevent or delay AD progression.

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.

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.

Source EEG reveals that Rolandic epilepsy is a regional epileptic encephalopathy

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Children with RE have fewer spindles but they have typical time–frequency features.

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Spindle deficits extend to multiple cortical regions in Rolandic epilepsy.

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Cognitive deficits are predicted by spindle rate in Rolandic epilepsy.

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Regional spindle rate predicts motor deficits better than Rolandic spindle deficit.

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Spindle features in RE identify a regional thalamocortical epileptic encephalopathy.

Rolandic epilepsy is the most common form of epileptic encephalopathy, characterized by sleep-potentiated inferior Rolandic epileptiform spikes, seizures, and cognitive deficits in school-age children that spontaneously resolve by adolescence. We recently identified a paucity of sleep spindles, physiological thalamocortical rhythms associated with sleep-dependent learning, in the Rolandic cortex during the active phase of this disease. Because spindles are generated in the thalamus and amplified through regional thalamocortical circuits, we hypothesized that: 1) deficits in spindle rate would involve but extend beyond the inferior Rolandic cortex in active epilepsy and 2) regional spindle deficits would better predict cognitive function than inferior Rolandic spindle deficits alone. To test these hypotheses, we obtained high-resolution MRI, high-density EEG recordings, and focused neuropsychological assessments in children with Rolandic epilepsy during active (n = 8, age 9–14.7 years, 3F) and resolved (seizure free for > 1 year, n = 10, age 10.3–16.7 years, 1F) stages of disease and age-matched controls (n = 8, age 8.9–14.5 years, 5F). Using a validated spindle detector applied to estimates of electrical source activity in 31 cortical regions, including the inferior Rolandic cortex, during stages 2 and 3 of non-rapid eye movement sleep, we compared spindle rates in each cortical region across groups. Among detected spindles, we compared spindle features (power, duration, coherence, bilateral synchrony) between groups. We then used regression models to examine the relationship between spindle rate and cognitive function (fine motor dexterity, phonological processing, attention, and intelligence, and a global measure of all functions). We found that spindle rate was reduced in the inferior Rolandic cortices in active but not resolved disease (active P = 0.007; resolved P = 0.2) compared to controls. Spindles in this region were less synchronous between hemispheres in the active group (P = 0.005; resolved P = 0.1) compared to controls; but there were no differences in spindle power, duration, or coherence between groups. Compared to controls, spindle rate in the active group was also reduced in the prefrontal, insular, superior temporal, and posterior parietal regions (i.e., “regional spindle rate”, P < 0.039 for all). Independent of group, regional spindle rate positively correlated with fine motor dexterity (P < 1e-3), attention (P = 0.02), intelligence (P = 0.04), and global cognitive performance (P < 1e-4). Compared to the inferior Rolandic spindle rate alone, models including regional spindle rate trended to improve prediction of global cognitive performance (P = 0.052), and markedly improved prediction of fine motor dexterity (P = 0.006). These results identify a spindle disruption in Rolandic epilepsy that extends beyond the epileptic cortex and a potential mechanistic explanation for the broad cognitive deficits that can be observed in this epileptic encephalopathy.

Learning Monologues at Bedtime Improves Sleep Quality in Actors and Non-Actors

Several studies show that pre-sleep learning determines changes in subsequent sleep, including improvements of sleep quality. Our aims were to confirm this finding using a more ecological task (learning a theatrical monologue) and to investigate whether the effect is modulated by expertise. Using a mixed design, we compared polysomnographic recordings of baseline sleep (BL, 9-h TIB) to those of post-training sleep (TR, with the same TIB but preceded by the training session), in one group of actors (N = 11) and one of non-actors (N = 11). In both groups, TR appears reorganized and re-compacted by the learning session, as shown, among others, by a significant decrease of WASO%, awakenings, arousals, and state transitions and by a trend towards an increased number of complete cycles and total cycle time. Concerning memory performance, the number of synonyms produced was significantly higher in the morning relative to immediate recall. No between-groups differences emerged either for sleep or memory variables. Our data confirm pre-sleep learning's beneficial effect on sleep quality in an ecological context. While expertise appears not to influence memory-related sleep mechanisms, results on morning recall support the recent view that sleep's role in memory processes consists in trace "transformation" for adaptive purposes, rather than rote consolidation.

Long term effects of cueing procedural memory reactivation during NREM sleep

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A single night of TMR benefits procedural memories up to 10 days later.

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Spindle density and SO-spindle coupling strength increase immediately upon cue onset.

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Time spent in N2 but not N3 predicts cueing benefit.

Targeted memory reactivation (TMR) has recently emerged as a promising tool to manipulate and study the sleeping brain. Although the technique is developing rapidly, only a few studies have examined how the effects of TMR develop over time. Here, we use a bimanual serial reaction time task (SRTT) to investigate whether the difference between the cued and un-cued sequence of button presses persists long-term. We further explore the relationship between the TMR benefit and sleep spindles, as well as their coupling with slow oscillations. Our behavioural analysis shows better performance for the dominant hand. Importantly, there was a strong effect of TMR, with improved performance on the cued sequence after sleep. Closer examination revealed a significant benefit of TMR at 10 days post-encoding, but not 24 h or 6 weeks post-encoding. Time spent in stage 2, but not stage 3, of NREM sleep predicted cueing benefit. We also found a significant increase in spindle density and SO-spindle coupling during the cue period, when compared to the no-cue period. Together, our results demonstrate that TMR effects evolve over several weeks post-cueing, as well as emphasising the importance of stage 2, spindles and the SO-spindle coupling in procedural memory consolidation.

Spindle-related brain activation in patients with insomnia disorder: An EEG-fMRI study

Sleep spindles have been implicated in sleep protection, depression and anxiety. However, spindle-related brain imaging mechanism underpinning the deficient sleep protection and emotional regulation in insomnia disorder (ID) remains elusive. The aim of the current study is to investigate the relationship between spindle-related brain activations and sleep quality, symptoms of depression and anxiety in patients with ID. Participants (n = 46, 28 females, 18-60 years) were recruited through advertisements including 16 with ID, according to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, and 30 matched controls. Group differences in spindle-related brain activations were analyzed using multimodality data acquired with simultaneous electroencephalography and functional magnetic resonance imaging during sleep. Compared with controls, patients with ID showed significantly decreased bilateral spindle-related brain activations in the cingulate gyrus (familywise error corrected p ˂ 0.05, cluster size 4401 mm³). Activations in the cingulate gyrus were negatively correlated with Pittsburgh Sleep Quality Index scores (r = -0.404, p = 0.005) and Self-Rating Anxiety Scale scores (r = -0.364, p = 0.013), in the pooled sample. These findings underscore the key role of spindle-related brain activations in the cingulate gyrus in subjective sleep quality and emotional regulation in ID.

Time-dependent transformations of memory representations differ along the long axis of the hippocampus

Research has shown that sleep is beneficial for the long-term retention of memories. According to theories of memory consolidation, memories are gradually reorganized, becoming supported by widespread, distributed cortical networks, particularly during postencoding periods of sleep. However, the effects of sleep on the organization of memories in the hippocampus itself remains less clear. In a 3-d study, participants encoded separate lists of word-image pairs differing in their opportunity for sleep-dependent consolidation. Pairs were initially studied either before or after an overnight sleep period, and were then restudied in a functional magnetic resonance imaging (fMRI) scan session. We used multivariate pattern similarity analyses to examine fine-grained effects of consolidation on memory representations in the hippocampus. We provide evidence for a dissociation along the long axis of the hippocampus that emerges with consolidation, such that representational patterns for object-word memories initially formed prior to sleep become differentiated in anterior hippocampus and more similar, or overlapping, in posterior hippocampus. Differentiation in anterior hippocampal representations correlated with subsequent behavioral performance. Furthermore, representational overlap in posterior hippocampus correlated with the duration of intervening slow wave sleep. Together, these results demonstrate that sleep-dependent consolidation promotes the reorganization of memory traces along the long axis of the hippocampus.

Occipital sleep spindles predict sequence learning in a visuo-motor task

STUDY OBJECTIVES

The brain appears to use internal models to successfully interact with its environment via active predictions of future events. Both internal models and the predictions derived from them are based on previous experience. However, it remains unclear how previously encoded information is maintained to support this function, especially in the visual domain. In the present study, we hypothesized that sleep consolidates newly encoded spatio-temporal regularities to improve predictions afterwards.

METHODS

We tested this hypothesis using a novel sequence-learning paradigm that aimed to dissociate perceptual from motor learning. We recorded behavioral performance and high-density electroencephalography (EEG) in male human participants during initial training and during testing two days later, following an experimental night of sleep (n = 16, including high-density EEG recordings) or wakefulness (n = 17).

RESULTS

Our results show sleep-dependent behavioral improvements correlated with sleep-spindle activity specifically over occipital cortices. Moreover, event-related potential (ERP) responses indicate a shift of attention away from predictable to unpredictable sequences after sleep, consistent with enhanced automaticity in the processing of predictable sequences.

CONCLUSIONS

These findings suggest a sleep-dependent improvement in the prediction of visual sequences, likely related to visual cortex reactivation during sleep spindles. Considering that controls in our experiments did not fully exclude oculomotor contributions, future studies will need to address the extent to which these effects depend on purely perceptual versus oculomotor sequence learning.

Memory consolidation as an adaptive process

We rely on our long-term memories to guide future behaviors, making it adaptive to prioritize the retention of goal-relevant, salient information in memory. In this review, we discuss findings from rodent and human research to demonstrate that active processes during post-encoding consolidation support the selective stabilization of recent experience into adaptive, long-term memories. Building upon literatures focused on dynamics at the cellular level, we highlight that consolidation also transforms memories at the systems level to support future goal-relevant behavior, resulting in more generalized memory traces in the brain and behavior. We synthesize previous literatures spanning animal research, human cognitive neuroscience, and cognitive psychology to propose an integrative framework for adaptive consolidation by which goal-relevant memoranda are "tagged" for subsequent consolidation, resulting in selective transformations to the structure of memories that support flexible, goal-relevant behaviors.

Reward biases spontaneous neural reactivation during sleep

Sleep favors the reactivation and consolidation of newly acquired memories. Yet, how our brain selects the noteworthy information to be reprocessed during sleep remains largely unknown. From an evolutionary perspective, individuals must retain information that promotes survival, such as avoiding dangers, finding food, or obtaining praise or money. Here, we test whether neural representations of rewarded (compared to non-rewarded) events have priority for reactivation during sleep. Using functional MRI and a brain decoding approach, we show that patterns of brain activity observed during waking behavior spontaneously reemerge during slow-wave sleep. Critically, we report a privileged reactivation of neural patterns previously associated with a rewarded task (i.e., winning at a complex game). Moreover, during sleep, activity in task-related brain regions correlates with better subsequent memory performance. Our study uncovers a neural mechanism whereby rewarded life experiences are preferentially replayed and consolidated while we sleep.

Endogenous memory reactivation during sleep in humans is clocked by slow oscillation-spindle complexes

Sleep is thought to support memory consolidation via reactivation of prior experiences, with particular electrophysiological sleep signatures (slow oscillations (SOs) and sleep spindles) gating the information flow between relevant brain areas. However, empirical evidence for a role of endogenous memory reactivation (i.e., without experimentally delivered memory cues) for consolidation in humans is lacking. Here, we devised a paradigm in which participants acquired associative memories before taking a nap. Multivariate decoding was then used to capture endogenous memory reactivation during non-rapid eye movement (NREM) sleep in surface EEG recordings. Our results reveal reactivation of learning material during SO-spindle complexes, with the precision of SO-spindle coupling predicting reactivation strength. Critically, reactivation strength (i.e. classifier evidence in favor of the previously studied stimulus category) in turn predicts the level of consolidation across participants. These results elucidate the memory function of sleep in humans and emphasize the importance of SOs and spindles in clocking endogenous consolidation processes.

Whole-body procedural learning benefits from targeted memory reactivation in REM sleep and task-related dreaming

Sleep facilitates memory consolidation through offline reactivations of memory traces. Dreaming may play a role in memory improvement and may reflect these memory reactivations. To experimentally address this question, we used targeted memory reactivation (TMR), i.e., application, during sleep, of a stimulus that was previously associated with learning, to assess whether it influences task-related dream imagery (or task-dream reactivations). Specifically, we asked if TMR or task-dream reactivations in either slow-wave (SWS) or rapid eye movement (REM) sleep benefit whole-body procedural learning. Healthy participants completed a virtual reality (VR) flying task prior to and following a morning nap or rest period during which task-associated tones were readministered in either SWS, REM sleep, wake or not at all. Findings indicate that learning benefits most from TMR when applied in REM sleep compared to a Control-sleep group. REM dreams that reactivated kinesthetic elements of the VR task (e.g., flying, accelerating) were also associated with higher improvement on the task than were dreams that reactivated visual elements (e.g., landscapes) or that had no reactivations. TMR did not itself influence dream content but its effects on performance were greater when coexisting with task-dream reactivations in REM sleep. Findings may help explain the mechanistic relationships between dream and memory reactivations and may contribute to the development of sleep-based methods to optimize complex skill learning.

The relation between sleep and neurocognitive development in infancy and early childhood: A neuroscience perspective

Sleep is essential for human life. It has different characteristics in the early stages of life compared to later periods: during development, qualitative and quantitative changes in sleep features occur such as the onset of REM/NREM sleep at 3 months, the progressive increase of night sleep duration, and the reduction of total sleep time. Sleep seems to be essential in the cognitive functions' development, especially in the first period of life. Indeed, higher rates of night sleep at the age of 12 and 18 months are associated with higher executive functions' performance. Furthermore, memory consolidation occurs during sleep and sleep contributes to children's learning not only in retaining information but also in organizing memories most efficiently. Therefore, sleep problems could cause negative effects on some features of cognitive development like memory, executive functions, and learning process. There is also an intimate relationship between sleep and regulation of emotional brain functions, with a link between sleep disturbance and behavioral problems.

Coupling of gamma band activity to sleep spindle oscillations - a combined EEG/MEG study

Sleep spindles are crucial to memory consolidation. Cortical gamma oscillations (30-100 Hz) are considered to reflect processing of memory in local cortical networks. The temporal and regulatory relationship between spindles and gamma activity might therefore provide clues into how sleep strengthens cortical memory representations. Here, combining EEG with MEG recordings during sleep in healthy humans (n = 12), we investigated the temporal relationships of cortical gamma band activity, always measured by MEG, during fast (12-16 Hz) and slow (8-12 Hz) sleep spindles detected in the EEG or MEG. Time-frequency distributions did not show a consistent coupling of gamma to the spindle oscillation, although activity in the low gamma (30-40 Hz) and neighboring beta range (<30 Hz) was generally increased during spindles. However, more fine-grained analyses of cross-frequency interactions revealed that both low and high gamma power (30-100 Hz) was coupled to the phase of slow and fast EEG spindles, importantly, with this coupling at a fixed phase only for the oscillations within an individual spindle, but with variable phase across spindles. We did not observe any coupling of gamma activity for spindles detected solely in the MEG and not in parallel EEG recordings, raising the possibility that these are more local spindles of different quality. Similar to fast spindle activity, low gamma band power followed a ~0.025 Hz infraslow rhythm during sleep whose frequency, however, was significantly faster than that of spindle activity. Our findings suggest a general function of fast and slow spindles that by spanning larger cortical networks might serve to synchronize gamma band activity occurring in more local but distributed networks. Thereby, spindles might help linking local memory processing between distributed networks.

Memory and Sleep: How Sleep Cognition Can Change the Waking Mind for the Better

The memories that we retain can serve many functions. They guide our future actions, form a scaffold for constructing the self, and continue to shape both the self and the way we perceive the world. Although most memories we acquire each day are forgotten, those integrated within the structure of multiple prior memories tend to endure. A rapidly growing body of research is steadily elucidating how the consolidation of memories depends on their reactivation during sleep. Processing memories during sleep not only helps counteract their weakening but also supports problem solving, creativity, and emotional regulation. Yet, sleep-based processing might become maladaptive, such as when worries are excessively revisited. Advances in research on memory and sleep can thus shed light on how this processing influences our waking life, which can further inspire the development of novel strategies for decreasing detrimental rumination-like activity during sleep and for promoting beneficial sleep cognition.

Sleep spindle abnormalities related to Alzheimer's disease: a systematic mini-review

Accumulating evidence supports a bidirectional relationship between sleep disruption and Alzheimer's disease (AD) pathology. Among various sleep electroencephalography activities, the sleep spindle is one specific electroencephalographic rhythm that has potential to be a biomarker for AD. This review explores the association between sleep spindles and AD-related dementia from a neuropsychological perspective by a systematic re-examining of recent findings. In general, sleep spindles, characterized by density, amplitude, duration, and frequency, are disrupted in AD. Moreover, its functional coupling with slow oscillation also suffers in AD. While preliminary, our observations and comparisons suggest that spindle density rather than frequency and fast spindles rather than slow spindles could be more sensitive to AD-related dementia, and spindle plasticity provides possibilities for targeted interference. In conclusion, quantitative and qualitative features of sleep spindles represent potential non-invasive and cost-effective biomarkers for AD and provide both therapeutic and public health implications.

Linking the nature and functions of sleep: insights from multimodal imaging of the sleeping brain

Sleep and wakefulness are traditionally considered as two mutually exclusive states with contrasting behavioural manifestations and complementary neurobiological functions. However, the discoveries of local sleep in global wakefulness and local wakefulness in global sleep have challenged this classical view and raised questions about the nature and functions of sleep. Here, we review the contributions from recent multimodal imaging studies of human sleep towards understanding the relationship between the nature and functions of sleep. Through simultaneous tracking of brain state and mapping of brain activity, these studies revealed that the sleeping brain can carry out covert cognitive processing that was thought to be wake-specific (wake-like function in the sleeping brain). Conversely, the awake brain can perform housekeeping functions through local sleep of neural populations (sleep-like function in the awake brain). We discuss how the blurred boundary between sleep and wakefulness highlights the need to radically rethink the definition of brain states, and how the recently discovered fMRI signatures of global and local sleep can help to address these outstanding questions.

A mechanism for learning with sleep spindles

Spindles are ubiquitous oscillations during non-rapid eye movement (NREM) sleep. A growing body of evidence points to a possible link with learning and memory, and the underlying mechanisms are now starting to be unveiled. Specifically, spindles are associated with increased dendritic activity and high intracellular calcium levels, a situation favourable to plasticity, as well as with control of spiking output by feed-forward inhibition. During spindles, thalamocortical networks become unresponsive to inputs, thus potentially preventing interference between memory-related internal information processing and extrinsic signals. At the system level, spindles are co-modulated with other major NREM oscillations, including hippocampal sharp wave-ripples (SWRs) and neocortical slow waves, both previously shown to be associated with learning and memory. The sequential occurrence of reactivation at the time of SWRs followed by neuronal plasticity-promoting spindles is a possible mechanism to explain NREM sleep-dependent consolidation of memories. This article is part of the Theo Murphy meeting issue 'Memory reactivation: replaying events past, present and future'.

Hippocampal and medial prefrontal cortical volume is associated with overnight declarative memory consolidation independent of specific sleep oscillations

The current study was designed to further clarify the influence of brain morphology, sleep oscillatory activity and age on memory consolidation. Specifically, we hypothesized, that a smaller volume of hippocampus, parahippocampal and medial prefrontal cortex negatively impacts declarative, but not procedural, memory consolidation. Explorative analyses were conducted to demonstrate whether a decrease in slow-wave activity negatively impacts declarative memory consolidation, and whether these factors mediate age effects on memory consolidation. Thirty-eight healthy participants underwent an acquisition session in the evening and a retrieval session in the morning after night-time sleep with polysomnographic monitoring. Declarative memory was assessed with the paired-associate word list task, while procedural memory was tested using the mirror-tracing task. All participants underwent high-resolution magnetic resonance imaging. Participants with smaller hippocampal, parahippocampal and medial prefrontal cortex volumes displayed a reduced overnight declarative, but not procedural memory consolidation. Mediation analyses showed significant age effects on overnight declarative memory consolidation, but no significant mediation effects of brain morphology on this association. Further mediation analyses showed that the effects of age and brain morphology on overnight declarative memory consolidation were not mediated by polysomnographic variables or sleep electroencephalogram spectral power variables. Thus, the results suggest that the association between age, specific brain area volume and overnight memory consolidation is highly relevant, but does not necessarily depend on slow-wave sleep as previously conceptualized.

Association of sleep spindle activity and sleepiness in children with sleep-disordered breathing

STUDY OBJECTIVES

The association of snoring and sleep-disordered breathing (SDB) with daytime sleepiness is well documented; however, the exact mechanisms, and especially the role of sleep microstructure that may account for this association remain incompletely understood. In a cohort of children with SDB, we aimed to compare sleep spindle activity between children with daytime sleepiness versus those without daytime sleepiness.

METHODS

Children with SDB who reported daytime sleepiness were recruited and compared with age- and sex-matched SDB controls. Polysomnographic recordings were analyzed evaluating sleep spindle activity. A statistical comparison was carried out in both groups to assess the association between sleepiness and sleep spindle activity.

RESULTS

Thirty-three children with SDB (mean age: 7.5 ± 1.7 years) were included, 10 with and 23 without daytime sleepiness. Spindle activity was lower in children with daytime sleepiness compared with those without; in stage N2, median (interquartile range) sleep spindle indexes were 77.5 (37.3) and 116.9 (71.2) (P = .015), respectively.

CONCLUSIONS

Spindles were significantly reduced in children with SDB and daytime sleepiness. The exact mechanisms of this association remain unknown and future research is needed in order to establish the exact role of sleep spindle activity on daytime symptoms in children with SDB.

Electrophysiological signatures of memory reactivation in humans

The reactivation of neural activity that was present during the encoding of an event is assumed to be essential for human episodic memory retrieval and the consolidation of memories during sleep. Pioneering animal work has already established a crucial role of memory reactivation to prepare and guide behaviour. Research in humans is now delineating the neural processes involved in memory reactivation during both wakefulness and sleep as well as their functional significance. Focusing on the electrophysiological signatures of memory reactivation in humans during both memory retrieval and sleep-related consolidation, this review provides an overview of the state of the art in the field. We outline recent advances, methodological developments and open questions and specifically highlight commonalities and differences in the neuronal signatures of memory reactivation during the states of wakefulness and sleep.

This article is part of the Theo Murphy meeting issue ‘Memory reactivation: replaying events past, present and future’.

Sleep Spindles Promote the Restructuring of Memory Representations in Ventromedial Prefrontal Cortex through Enhanced Hippocampal-Cortical Functional Connectivity

Memory consolidation is hypothesized to involve the distribution and restructuring of memory representations across hippocampal and cortical regions. Theories suggest that, through extended hippocampal-cortical interactions, cortical ensembles come to represent more integrated, or overlapping, memory traces that prioritize commonalities across related memories. Sleep processes, particularly fast sleep spindles, are thought to support consolidation, but evidence for this relationship has been mostly limited to memory retention benefits. Whether fast spindles provide a mechanism for neural changes hypothesized to support consolidation, including the strengthening of hippocampal-cortical networks and integration across memory representations, remains unclear, as does the specificity of regions involved. Using functional connectivity analyses of human fMRI data (both sexes), we show that fast spindle density during overnight sleep is related to enhanced hippocampal-cortical functional connectivity the next day, when restudying information learned before sleep. Spindle density modulated connectivity in distinct hippocampal-cortical networks depending on the category of the consolidated stimuli. Specifically, spindle density correlated with functional connectivity between anterior hippocampus and ventromedial prefrontal cortex (vmPFC) for object-word pairs, and posterior hippocampus and posteromedial cortex for scene-word pairs. Using multivariate pattern analyses, we also show that fast spindle density during postlearning sleep is associated with greater pattern similarity, or representational overlap, across individual object-word memories in vmPFC the next day. Further, the relationship between fast spindle density and representational overlap in vmPFC was mediated by the degree of anterior hippocampal-vmPFC functional connectivity. Together, these results suggest that fast spindles support the network distribution of memory traces, potentially restructuring memory representations in vmPFC.SIGNIFICANCE STATEMENT How new experiences are transformed into long-term memories remains a fundamental question for neuroscience research. Theories suggest that memories are stabilized as they are reorganized in the brain, a process thought to be supported by sleep oscillations, particularly sleep spindles. Although sleep spindles have been associated with benefits in memory retention, it is not well understood how spindles modify neural memory traces. This study found that spindles during overnight sleep correlate with changes in neural memory traces, including enhanced functional connectivity in distinct hippocampal-cortical networks and increased pattern similarity among memories in the cortex. The results provide critical evidence that spindles during overnight sleep may act as a physiological mechanism for the restructuring of neural memory traces.

Brain Rhythms During Sleep and Memory Consolidation: Neurobiological Insights

Sleep can benefit memory consolidation. The characterization of brain regions underlying memory consolidation during sleep, as well as their temporal interplay, reflected by specific patterns of brain electric activity, is surfacing. Here, we provide an overview of recent concepts and results on the mechanisms of sleep-related memory consolidation. The latest studies strongly impacting future directions of research in this field are highlighted.

Gross motor adaptation benefits from sleep after training

Sleep has been shown to facilitate the consolidation of newly acquired motor memories. However, the role of sleep in gross motor learning, especially in motor adaptation, is less clear. Thus, we investigated the effects of nocturnal sleep on the performance of a gross motor adaptation task, i.e. riding an inverse steering bicycle. Twenty‐six male participants (M = 24.19, SD = 3.70 years) were randomly assigned to a PM‐AM‐PM (n = 13) or an AM‐PM‐AM (n = 13) group, i.e. they trained in the evening/morning and were re‐tested the next morning/evening and the following evening/morning (PM‐AM‐PM/AM‐PM‐AM group) so that every participant spent one sleep as well as one wake interval between the three test sessions. Inverse cycling performance was assessed by speed (riding time) and accuracy (standard deviation of steering angle) measures. Behavioural results showed that in the PM‐AM‐PM group a night of sleep right after training stabilized performance (accuracy and speed) and was further improved over the subsequent wake interval. In the AM‐PM‐AM group, a significant performance deterioration after the initial wake interval was followed by the restoration of subjects' performance levels from right after training when a full night of sleep was granted. Regarding sleep, right hemispheric fast N2 sleep spindle activity was related to better stabilization of inverse cycling skills, thus possibly reflecting the ongoing process of updating the participants' mental model from “how to ride a bicycle” to “how to ride an inverse steering bicycle”. Our results demonstrate that sleep facilitates the consolidation of gross motor adaptation, thus adding further insights to the role of sleep for tasks with real‐life relevance.