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

Sleep Spindles: Mechanisms and Functions

Sleep spindles are burstlike signals in the electroencephalogram (EEG) of the sleeping mammalian brain and electrical surface correlates of neuronal oscillations in thalamus. As one of the most inheritable sleep EEG signatures, sleep spindles probably reflect the strength and malleability of thalamocortical circuits that underlie individual cognitive profiles. We review the characteristics, organization, regulation, and origins of sleep spindles and their implication in non-rapid-eye-movement sleep (NREMS) and its functions, focusing on human and rodent. Spatially, sleep spindle-related neuronal activity appears on scales ranging from small thalamic circuits to functional cortical areas, and generates a cortical state favoring intracortical plasticity while limiting cortical output. Temporally, sleep spindles are discrete events, part of a continuous power band, and elements grouped on an infraslow time scale over which NREMS alternates between continuity and fragility. We synthesize diverse and seemingly unlinked functions of sleep spindles for sleep architecture, sensory processing, synaptic plasticity, memory formation, and cognitive abilities into a unifying sleep spindle concept, according to which sleep spindles 1) generate neural conditions of large-scale functional connectivity and plasticity that outlast their appearance as discrete EEG events, 2) appear preferentially in thalamic circuits engaged in learning and attention-based experience during wakefulness, and 3) enable a selective reactivation and routing of wake-instated neuronal traces between brain areas such as hippocampus and cortex. Their fine spatiotemporal organization reflects NREMS as a physiological state coordinated over brain and body and may indicate, if not anticipate and ultimately differentiate, pathologies in sleep and neurodevelopmental, -degenerative, and -psychiatric conditions.

Primate somatosensory cortical neurons are entrained to both spontaneous and peripherally evoked spindle oscillations

Recurrent thalamocortical circuits produce a number of rhythms critical to brain function. In slow-wave sleep, spindles (7-16 Hz) are a prominent spontaneous oscillation generated by thalamic circuits and triggered by cortical slow waves. In wakefulness and under anesthesia, brief peripheral sensory stimuli can evoke 10-Hz reverberations due potentially to similar thalamic mechanisms. Functionally, sleep spindles and peripherally evoked spindles may play a role in memory consolidation and perception, respectively. Yet, rarely have the circuits involved in these two rhythms been compared in the same animals and never in primates. Here, we investigated the entrainment of primary somatosensory cortex (S1) neurons to both rhythms in ketamine-sedated macaques. First, we compared spontaneous spindles in sedation and natural sleep to validate the model. Then, we quantified entrainment with spike-field coherence and phase-locking statistics. We found that S1 neurons entrained to spontaneous sleep spindles were also entrained to the evoked spindles, although entrainment strength and phase systematically differed. Our results indicate that the spindle oscillations triggered by top-down spontaneous cortical activity and bottom-up peripheral input share a common cortical substrate.NEW & NOTEWORTHY Brief sensory stimuli evoke 10-Hz oscillations in thalamocortical neuronal activity and in perceptual thresholds. The mechanisms underlying this evoked rhythm are not well understood but are thought to be similar to those generating sleep spindles. We directly compared the entrainment of cortical neurons to both spontaneous spindles and peripherally evoked oscillations in sedated monkeys. We found that the entrainment strengths to each rhythm were positively correlated, although with differing entrainment phases, implying involvement of similar networks.

Closed-Loop Acoustic Stimulation Enhances Sleep Oscillations But Not Memory Performance

Slow oscillations and spindle activity during non-rapid eye movement sleep have been implicated in memory consolidation. Closed-loop acoustic stimulation has previously been shown to enhance slow oscillations and spindle activity during sleep and improve verbal associative memory. We assessed the effect of closed-loop acoustic stimulation during a daytime nap on a virtual reality spatial navigation task in 12 healthy human subjects in a randomized within-subject crossover design. We show robust enhancement of slow oscillation and spindle activity during sleep. However, no effects on behavioral performance were observed when comparing real versus sham stimulation. To explore whether memory enhancement effects were task specific and dependent on nocturnal sleep, in a second experiment with 19 healthy subjects, we aimed to replicate a previous study that used closed-loop acoustic stimulation to enhance memory for word pairs. The methods used were as close as possible to those used in the original study, except that we used a double-blind protocol, in which both subject and experimenter were unaware of the test condition. Again, we successfully enhanced slow oscillation and spindle power, but again did not strengthen associative memory performance with stimulation. We conclude that enhancement of sleep oscillations may be insufficient to enhance memory performance in spatial navigation or verbal association tasks, and provide possible explanations for lack of behavioral replication.

Sleep Spindle-dependent Functional Connectivity Correlates with Cognitive Abilities

EEG studies have shown that interindividual differences in the electrophysiological properties of sleep spindles (e.g., density, amplitude, duration) are highly correlated with trait-like "reasoning" abilities (i.e., "fluid intelligence"; problem-solving skills; the ability to employ logic or identify complex patterns), but not interindividual differences in STM or "verbal" intellectual abilities. Previous simultaneous EEG-fMRI studies revealed brain activations time-locked to spindles. Our group has recently demonstrated that the extent of activation in a subset of these regions was related to interindividual differences in reasoning intellectual abilities, specifically. However, spindles reflect communication between spatially distant and functionally distinct brain areas. The functional communication among brain regions related to spindles and their relationship to reasoning abilities have yet to be investigated. Using simultaneous EEG-fMRI sleep recordings and psychophysiological interaction analysis, we identified spindle-related functional communication among brain regions in the thalamo-cortical-BG system, the salience network, and the default mode network. Furthermore, the extent of the functional connectivity of the cortical-striatal circuitry and the thalamo-cortical circuitry was specifically related to reasoning abilities but was unrelated to STM or verbal abilities, thus suggesting that individuals with higher fluid intelligence have stronger functional coupling among these brain areas during spontaneous spindle events. This may serve as a first step in further understanding the function of sleep spindles and the brain network functional communication, which support the capacity for fluid intelligence.

Reduced sleep spindle activity in children with primary snoring

BACKGROUND

Habitually snoring children are at risk of manifesting disease-related problems even if their sleep studies are overall within normal limits.

STUDY OBJECTIVES

To compare sleep spindle activity in children with primary snoring and healthy controls.

METHODS

Sleep spindle activity including analysis of fast and slow spindles (ie, >13 Hz and <13 Hz, respectively) was evaluated in polysomnographic (PSG) recordings of 20 randomly selected children with primary snoring (PS; normal PSG recordings except for objective presence of snoring; 12 boys, mean age 6.5 ± 2.1 years), and 20 age- and gender-matched PSG-confirmed non-snoring controls.

RESULTS

PS children showed significantly lower spindle indices in all non-rapid eye movement (NREM) sleep stages (p < 0.05). In contrast, fast spindles were found in 40% (n = 8) children with PS and in 25% (n = 5) controls. Sleep spindle activity was particularly higher in NREM sleep stage 2 in controls compared PS (76% versus 43% of all marked sleep spindles events in NREM sleep stage 2, p < 0.001).

CONCLUSIONS

Children with PS exhibit significantly reduced spindle activity when compared to matched controls. Reduced sleep spindle activity may be an indicator of sleep disruption and, therefore, could be involved in the development of disease-related consequences in snoring children.

The Neurophysiological Effect of Acoustic Stimulation with Real-time Sleep Spindle Detection

Sleep spindle is a salient brain activity found in the sigma frequency range (11-16 Hz) during sleep stage 2. It has been demonstrated that sleep spindle is related to memory consolidation, neurodegenerative disease, and mental disorders. Slow wave activity (0.5-4 Hz) is the most prominent EEG activity during sleep and appears as a large, spontaneous synchronization of cortical neurons. The role of slow wave activity has been proposed to regulate synaptic strength and memory consolidation. Many studies have investigated the effect of acoustic stimuli during the sleep slow wave. However, there have been few studies which investigated an effect of acoustic stimulation during sleep spindle activity. In this study, we examined the neurophysiological effect of acoustic stimulation during sleep spindle activity. We delivered pink noise after the detection of sleep spindle, and surmised that acoustic stimulation after sleep spindle detection may preserve delta activity during ongoing sleep. Further, we observed suppression of the sleep spindle activity around the times of acoustic stimulation and evoked slow wave activity and theta band activity immediately after tone onset.

Sleep Spindles: Timed for Memory Consolidation

It has long been known that sleep supports memory consolidation. Two recent studies now shed light on how sleep spindles, characteristic 11-16 Hz activity bursts, contribute critically to memory processing during the night.

Sleep changes following intensive cognitive activity

Studies over the last 40 years have mainly investigated sleep structure changes as a result of wake duration, in the frame of the classical sleep regulation theories. However, wake intervals of the same duration can profoundly differ in their intensity, which actually reflects the degree of cognitive and physical activity. Data on how sleep can be modified by wake intensity changes (initially sparse and of little consistence) have become much more substantial, especially in the frame of the intense research debate on sleep-memory relationships. Our aim is to examine the vast repertoire of sleep modifications that depend on waking cognitive manipulations, highlighting the sleep features that appear most affected. By systematically addressing this issue, we want to set the basis for future research exploring both the specific nature of the mechanisms involved and the applicative psychosocial and clinical fall-outs, in terms of possible behavioural interventions for sleep quality improvement.

Mechanisms of systems memory consolidation during sleep

Long-term memory formation is a major function of sleep. Based on evidence from neurophysiological and behavioral studies mainly in humans and rodents, we consider the formation of long-term memory during sleep as an active systems consolidation process that is embedded in a process of global synaptic downscaling. Repeated neuronal replay of representations originating from the hippocampus during slow-wave sleep leads to a gradual transformation and integration of representations in neocortical networks. We highlight three features of this process: (i) hippocampal replay that, by capturing episodic memory aspects, drives consolidation of both hippocampus-dependent and non-hippocampus-dependent memory; (ii) brain oscillations hallmarking slow-wave and rapid-eye movement sleep that provide mechanisms for regulating both information flow across distant brain networks and local synaptic plasticity; and (iii) qualitative transformations of memories during systems consolidation resulting in abstracted, gist-like representations.

Awake Reactivation of Prior Experiences Consolidates Memories and Biases Cognition

After experiences are encoded into memory, post-encoding reactivation mechanisms have been proposed to mediate long-term memory stabilization and transformation. Spontaneous reactivation of hippocampal representations, together with hippocampal-cortical interactions, are leading candidate mechanisms for promoting systems-level memory strengthening and reorganization. While the replay of spatial representations has been extensively studied in rodents, here we review recent fMRI work that provides evidence for spontaneous reactivation of nonspatial, episodic event representations in the human hippocampus and cortex, as well as for experience-dependent alterations in systems-level hippocampal connectivity. We focus on reactivation during awake post-encoding periods, relationships between reactivation and subsequent behavior, how reactivation is modulated by factors that influence consolidation, and the implications of persistent reactivation for biasing ongoing perception and cognition.

Sequential replay of nonspatial task states in the human hippocampus

Sequential neural activity patterns related to spatial experiences are "replayed" in the hippocampus of rodents during rest. We investigated whether replay of nonspatial sequences can be detected noninvasively in the human hippocampus. Participants underwent functional magnetic resonance imaging (fMRI) while resting after performing a decision-making task with sequential structure. Hippocampal fMRI patterns recorded at rest reflected sequentiality of previously experienced task states, with consecutive patterns corresponding to nearby states. Hippocampal sequentiality correlated with the fidelity of task representations recorded in the orbitofrontal cortex during decision-making, which were themselves related to better task performance. Our findings suggest that hippocampal replay may be important for building representations of complex, abstract tasks elsewhere in the brain and establish feasibility of investigating fast replay signals with fMRI.

Targeted Memory Reactivation during Sleep Elicits Neural Signals Related to Learning Content

Retrieval of learning-related neural activity patterns is thought to drive memory stabilization. However, finding reliable, noninvasive, content-specific indicators of memory retrieval remains a central challenge. Here, we attempted to decode the content of retrieved memories in the EEG during sleep. During encoding, male and female human subjects learned to associate spatial locations of visual objects with left- or right-hand movements, and each object was accompanied by an inherently related sound. During subsequent slow-wave sleep within an afternoon nap, we presented half of the sound cues that were associated (during wake) with left- and right-hand movements before bringing subjects back for a final postnap test. We trained a classifier on sleep EEG data (focusing on lateralized EEG features that discriminated left- vs right-sided trials during wake) to predict learning content when we cued the memories during sleep. Discrimination performance was significantly above chance and predicted subsequent memory, supporting the idea that retrieval leads to memory stabilization. Moreover, these lateralized signals increased with postcue sleep spindle power, demonstrating that retrieval has a strong relationship with spindles. These results show that lateralized activity related to individual memories can be decoded from sleep EEG, providing an effective indicator of offline retrieval.SIGNIFICANCE STATEMENT Memories are thought to be retrieved during sleep, leading to their long-term stabilization. However, there has been relatively little work in humans linking neural measures of retrieval of individual memories during sleep to subsequent memory performance. This work leverages the prominent electrophysiological signal triggered by lateralized movements to robustly demonstrate the retrieval of specific cued memories during sleep. Moreover, these signals predict subsequent memory and are correlated with sleep spindles, neural oscillations that have previously been implicated in memory stabilization. Together, these findings link memory retrieval to stabilization and provide a powerful tool for investigating memory in a wide range of learning contexts and human populations.

Regulation of Local Sleep by the Thalamic Reticular Nucleus

In spite of the uniform appearance of sleep as a behavior, the sleeping brain does not produce electrical activities in unison. Different types of brain rhythms arise during sleep and vary between layers, areas, or from one functional system to another. Local heterogeneity of such activities, here referred to as local sleep, overturns fundamental tenets of sleep as a globally regulated state. However, little is still known about the neuronal circuits involved and how they can generate their own specifically-tuned sleep patterns. NREM sleep patterns emerge in the brain from interplay of activity between thalamic and cortical networks. Within this fundamental circuitry, it now turns out that the thalamic reticular nucleus (TRN) acts as a key player in local sleep control. This is based on a marked heterogeneity of the TRN in terms of its cellular and synaptic architecture, which leads to a regional diversity of NREM sleep hallmarks, such as sleep spindles, delta waves and slow oscillations. This provides first evidence for a subcortical circuit as a determinant of cortical local sleep features. Here, we review novel cellular and functional insights supporting TRN heterogeneity and how these elements come together to account for local NREM sleep. We also discuss open questions arising from these studies, focusing on mechanisms of sleep regulation and the role of local sleep in brain plasticity and cognitive functions.

A contextual binding theory of episodic memory: systems consolidation reconsidered

Episodic memory reflects the ability to recollect the temporal and spatial context of past experiences. Episodic memories depend on the hippocampus but have been proposed to undergo rapid forgetting unless consolidated during offline periods such as sleep to neocortical areas for long-term storage. Here, we propose an alternative to this standard systems consolidation theory (SSCT) - a contextual binding account - in which the hippocampus binds item-related and context-related information. We compare these accounts in light of behavioural, lesion, neuroimaging and sleep studies of episodic memory and contend that forgetting is largely due to contextual interference, episodic memory remains dependent on the hippocampus across time, contextual drift produces post-encoding activity and sleep benefits memory by reducing contextual interference.

All-night functional magnetic resonance imaging sleep studies

BACKGROUND

Previous functional magnetic resonance imaging (fMRI) sleep studies have been hampered by the difficulty of obtaining extended amounts of sleep in the sleep-adverse environment of the scanner and often have resorted to manipulations such as sleep depriving subjects before scanning. These manipulations limit the generalizability of the results.

NEW METHOD

The current study is a methodological validation of procedures aimed at obtaining all-night fMRI data in sleeping subjects with minimal exposure to experimentally induced sleep deprivation. Specifically, subjects slept in the scanner on two consecutive nights, allowing the first night to serve as an adaptation night.

RESULTS/COMPARISON WITH EXISTING METHOD(S)

Sleep scoring results from simultaneously acquired electroencephalography data on Night 2 indicate that subjects (n = 12) reached the full spectrum of sleep stages including slow-wave (M = 52.1 min, SD = 26.5 min) and rapid eye movement (REM, M = 45.2 min, SD = 27.9 min) sleep and exhibited a mean of 2.1 (SD = 1.1) nonREM-REM sleep cycles.

CONCLUSIONS

It was found that by diligently applying fundamental principles and methodologies of sleep and neuroimaging science, performing all-night fMRI sleep studies is feasible. However, because the two nights of the study were performed consecutively, some sleep deprivation from Night 1 as a cause of the Night 2 results is likely, so consideration should be given to replicating the current study with a washout period. It is envisioned that other laboratories can adopt the core features of this protocol to obtain similar results.

Non-REM Sleep Characteristics Predict Early Cognitive Impairment in an Aging Population

Objective: Recent research suggests that sleep disorders or changes in sleep stages or EEG waveform precede over time the onset of the clinical signs of pathological cognitive impairment (e.g., Alzheimer's disease). The aim of this study was to identify biomarkers based on EEG power values and spindle characteristics during sleep that occur in the early stages of mild cognitive impairment (MCI) in older adults. Methods: This study was a case-control cross-sectional study with 1-year follow-up of cases. Patients with isolated subjective cognitive complaints (SCC) or MCI were recruited in the Bordeaux Memory Clinic (MEMENTO cohort). Cognitively normal controls were recruited. All participants were recorded with two successive polysomnography 1 year apart. Delta, theta, and sigma absolute spectral power and spindle characteristics (frequency, density, and amplitude) were analyzed from purified EEG during NREM and REM sleep periods during the entire second night. Results: Twenty-nine patients (8 males, age = 71 ± 7 years) and 29 controls were recruited at T0. Logistic regression analyses demonstrated that age-related cognitive impairment were associated with a reduced delta power (odds ratio (OR) 0.072, P < 0.05), theta power (OR 0.018, P < 0.01), sigma power (OR 0.033, P < 0.05), and spindle maximal amplitude (OR 0.002, P < 0.05) during NREM sleep. Variables were adjusted on age, gender, body mass index, educational level, and medication use. Seventeen patients were evaluated at 1-year follow-up. Correlations showed that changes in self-reported sleep complaints, sleep consolidation, and spindle characteristics (spectral power, maximal amplitude, duration, and frequency) were associated with cognitive impairment (P < 0.05). Conclusion: A reduction in slow-wave, theta and sigma activities, and a modification in spindle characteristics during NREM sleep are associated very early with a greater risk of the occurrence of cognitive impairment. Poor sleep consolidation, lower amplitude, and faster frequency of spindles may be early sleep biomarkers of worsening cognitive decline in older adults.

Remembering to Forget: A Dual Role for Sleep Oscillations in Memory Consolidation and Forgetting

It has been known since the time of patient H. M. and Karl Lashley's equipotentiality studies that the hippocampus and cortex serve mnestic functions. Current memory models maintain that these two brain structures accomplish unique, but interactive, memory functions. Specifically, most modeling suggests that memories are rapidly acquired during waking experience by the hippocampus, before being later consolidated into the cortex for long-term storage. Sleep has been shown to be critical for the transfer and consolidation of memories in the cortex. Like memory consolidation, a role for sleep in adaptive forgetting has both historical precedent, as Francis Crick suggested in 1983 that sleep was for "reverse-learning," and recent empirical support. In this article I review the evidence indicating that the same brain activity involved in sleep replay associated memory consolidation is responsible for sleep-dependent forgetting. In reviewing the literature, it became clear that both a cellular mechanism for systems consolidation and an agreed upon general, as well as cellular, mechanism for sleep-dependent forgetting is seldom discussed or is lacking. I advocate here for a candidate cellular systems consolidation mechanism wherein changes in calcium kinetics and the activation of consolidative signaling cascades arise from the triple phase locking of non-rapid eye movement sleep (NREMS) slow oscillation, sleep spindle and sharp-wave ripple rhythms. I go on to speculatively consider several sleep stage specific forgetting mechanisms and conclude by discussing a notional function of NREM-rapid eye movement sleep (REMS) cycling. The discussed model argues that the cyclical organization of sleep functions to first lay down and edit and then stabilize and integrate engrams. All things considered, it is increasingly clear that hallmark sleep stage rhythms, including several NREMS oscillations and the REMS hippocampal theta rhythm, serve the dual function of enabling simultaneous memory consolidation and adaptive forgetting. Specifically, the same sleep rhythms that consolidate new memories, in the cortex and hippocampus, simultaneously organize the adaptive forgetting of older memories in these brain regions.

The reciprocal relation between sleep and memory in infancy: Memory-dependent adjustment of sleep spindles and spindle-dependent improvement of memories

Sleep spindle activity in infants supports their formation of generalized memories during sleep, indicating that specific sleep processes affect the consolidation of memories early in life. Characteristics of sleep spindles depend on the infant's developmental state and are known to be associated with trait-like factors such as intelligence. It is, however, largely unknown which state-like factors affect sleep spindles in infancy. By varying infants' wake experience in a within-subject design, here we provide evidence for a learning- and memory-dependent modulation of infant spindle activity. In a lexical-semantic learning session before a nap, 14- to 16-month-old infants were exposed to unknown words as labels for exemplars of unknown object categories. In a memory test on the next day, generalization to novel category exemplars was tested. In a nonlearning control session preceding a nap on another day, the same infants heard known words as labels for exemplars of already known categories. Central-parietal fast sleep spindles increased after the encoding of unknown object-word pairings compared to known pairings, evidencing that an infant's spindle activity varies depending on its prior knowledge for newly encoded information. Correlations suggest that enhanced spindle activity was particularly triggered, when similar unknown pairings were not generalized immediately during encoding. The spindle increase triggered by previously not generalized object-word pairings, moreover, boosted the formation of generalized memories for these pairings. Overall, the results provide first evidence for a fine-tuned regulation of infant sleep quality according to current consolidation requirements, which improves the infant long-term memory for new experiences.

Brain Activation Time-Locked to Sleep Spindles Associated With Human Cognitive Abilities

Simultaneous electroencephalography and functional magnetic resonance imaging (EEG–fMRI) studies have revealed brain activations time-locked to spindles. Yet, the functional significance of these spindle-related brain activations is not understood. EEG studies have shown that inter-individual differences in the electrophysiological characteristics of spindles (e.g., density, amplitude, duration) are highly correlated with “Reasoning” abilities (i.e., “fluid intelligence”; problem solving skills, the ability to employ logic, identify complex patterns), but not short-term memory (STM) or verbal abilities. Spindle-dependent reactivation of brain areas recruited during new learning suggests night-to-night variations reflect offline memory processing. However, the functional significance of stable, trait-like inter-individual differences in brain activations recruited during spindle events is unknown. Using EEG–fMRI sleep recordings, we found that a subset of brain activations time-locked to spindles were specifically related to Reasoning abilities but were unrelated to STM or verbal abilities. Thus, suggesting that individuals with higher fluid intelligence have greater activation of brain regions recruited during spontaneous spindle events. This may serve as a first step to further understand the function of sleep spindles and the brain activity which supports the capacity for Reasoning.

Primed to Sleep: The Dynamics of Synaptic Plasticity Across Brain States

It is commonly accepted that brain plasticity occurs in wakefulness and sleep. However, how these different brain states work in concert to create long-lasting changes in brain circuitry is unclear. Considering that wakefulness and sleep are profoundly different brain states on multiple levels (e.g., cellular, molecular and network activation), it is unlikely that they operate exactly the same way. Rather it is probable that they engage different, but coordinated, mechanisms. In this article we discuss how plasticity may be divided across the sleep-wake cycle, and how synaptic changes in each brain state are linked. Our working model proposes that waking experience triggers short-lived synaptic events that are necessary for transient plastic changes and mark (i.e., 'prime') circuits and synapses for further processing in sleep. During sleep, synaptic protein synthesis at primed synapses leads to structural changes necessary for long-term information storage.

The impact of sleep on complex gross-motor adaptation in adolescents

Sleep has been shown to facilitate the consolidation of newly acquired motor memories in adults. However, the role of sleep in motor memory consolidation is less clear in children and adolescents, especially concerning real‐life gross‐motor skills. Therefore, we investigated the effects of sleep and wakefulness on a complex gross‐motor adaptation task by using a bicycle with an inverse steering device. A total of 29 healthy adolescents aged between 11 and 14 years (five female) were either trained to ride an inverse steering bicycle (learning condition) or a stationary bicycle (control condition). Training took place in the morning (wake, n = 14) or in the evening (sleep, n = 15) followed by a 9‐hr retention interval and a subsequent re‐test session. Slalom cycling performance was assessed by speed (riding time) and accuracy (standard deviation of steering angle) measures. Behavioural results showed no evidence for sleep‐dependent memory consolidation. However, overnight gains in accuracy were associated with an increase in left hemispheric N2 slow sleep spindle activity from control to learning night. Furthermore, decreases in REM and tonic REM duration were related to higher overnight improvements in accuracy. Regarding speed, an increase in REM and tonic REM duration was favourable for higher overnight gains in riding time. Thus, although not yet detectable on a behavioural level, sleep seemed to play a role in the acquisition of gross‐motor skills. A promising direction for future research is to focus on the possibility of delayed performance gains in adolescent populations.

Odor-evoked category reactivation in human ventromedial prefrontal cortex during sleep promotes memory consolidation

Slow-wave sleep is an optimal opportunity for memory consolidation: when encoding occurs in the presence of a sensory cue, delivery of that cue during sleep enhances retrieval of associated memories. Recent studies suggest that cues might promote consolidation by inducing neural reinstatement of cue-associated content during sleep, but direct evidence for such mechanisms is scant, and the relevant brain areas supporting these processes are poorly understood. Here, we address these gaps by combining a novel olfactory cueing paradigm with an object-location memory task and simultaneous EEG-fMRI recording in human subjects. Using pattern analysis of fMRI ensemble activity, we find that presentation of odor cues during sleep promotes reactivation of category-level information in ventromedial prefrontal cortex that significantly correlates with post-sleep memory performance. In identifying the potential mechanisms by which odor cues selectively modulate memory in the sleeping brain, these findings bring unique insights into elucidating how and what we remember.

Cued reactivation during slow-wave sleep induces brain connectivity changes related to memory stabilization

Memory reprocessing following acquisition enhances memory consolidation. Specifically, neural activity during encoding is thought to be 'replayed' during subsequent slow-wave sleep. Such memory replay is thought to contribute to the functional reorganization of neural memory traces. In particular, memory replay may facilitate the exchange of information across brain regions by inducing a reconfiguration of connectivity across the brain. Memory reactivation can be induced by external cues through a procedure known as "targeted memory reactivation". Here, we analysed data from a published study with auditory cues used to reactivate visual object-location memories during slow-wave sleep. We characterized effects of memory reactivation on brain network connectivity using graph-theory. We found that cue presentation during slow-wave sleep increased global network integration of occipital cortex, a visual region that was also active during retrieval of object locations. Although cueing did not have an overall beneficial effect on the retention of cued versus uncued associations, individual differences in overnight memory stabilization were related to enhanced network integration of occipital cortex. Furthermore, occipital cortex displayed enhanced connectivity with mnemonic regions, namely the hippocampus, parahippocampal gyrus, thalamus and medial prefrontal cortex during cue sound presentation. Together, these results suggest a neural mechanism where cue-induced replay during sleep increases integration of task-relevant perceptual regions with mnemonic regions. This cross-regional integration may be instrumental for the consolidation and long-term storage of enduring memories.

The hippocampus is crucial for forming non-hippocampal long-term memory during sleep

There is a long-standing division in memory research between hippocampus-dependent memory and non-hippocampus-dependent memory, as only the latter can be acquired and retrieved in the absence of normal hippocampal function^1,2. Consolidation of hippocampus-dependent memory, in particular, is strongly supported by sleep^3-5. Here we show that the formation of long-term representations in a rat model of non-hippocampus-dependent memory depends not only on sleep but also on activation of a hippocampus-dependent mechanism during sleep. Rats encoded non-hippocampus-dependent (novel-object recognition^6-8) and hippocampus-dependent (object-place recognition) memories before a two-hour period of sleep or wakefulness. Memory was tested either immediately thereafter or remotely (after one or three weeks). Whereas object-place recognition memory was stronger for rats that had slept after encoding (rather than being awake) at both immediate and remote testing, novel-object recognition memory profited from sleep only three weeks after encoding, at which point it was preserved in rats that had slept after encoding but not in those that had been awake. Notably, inactivation of the hippocampus during post-encoding sleep by intrahippocampal injection of muscimol abolished the sleep-induced enhancement of remote novel-object recognition memory. By contrast, muscimol injection before remote retrieval or memory encoding had no effect on test performance, confirming that the encoding and retrieval of novel-object recognition memory are hippocampus-independent. Remote novel-object recognition memory was associated with spindle activity during post-encoding slow-wave sleep, consistent with the view that neuronal memory replay during slow-wave sleep contributes to long-term memory formation. Our results indicate that the hippocampus has an important role in long-term consolidation during sleep even for memories that have previously been considered hippocampus-independent.

Sleep Spindles and Memory Reprocessing

We propose a framework for the memory function of spindle oscillations during sleep. In this framework, memories are reinstated by spindle events and further reprocessed during subsequent spindle refractory periods. We posit that spindle refractoriness is crucial for protecting memory reprocessing from interference. We further argue that temporally-coordinated spindle refractory periods across local networks facilitate the consolidation of rich, multimodal representations, and that localized spindle refractoriness optimizes oscillatory interactions that support systems consolidation in the sleeping brain.

Cortical circuit activity underlying sleep slow oscillations and spindles

Slow oscillations and sleep spindles are hallmarks of the EEG during slow-wave sleep (SWS). Both oscillatory events, especially when co-occurring in the constellation of spindles nesting in the slow oscillation upstate, are considered to support memory formation and underlying synaptic plasticity. The regulatory mechanisms of this function at the circuit level are poorly understood. Here, using two-photon imaging in mice, we relate EEG-recorded slow oscillations and spindles to calcium signals recorded from the soma of cortical putative pyramidal-like (Pyr) cells and neighboring parvalbumin-positive interneurons (PV-Ins) or somatostatin-positive interneurons (SOM-Ins). Pyr calcium activity was increased more than threefold when spindles co-occurred with slow oscillation upstates compared with slow oscillations or spindles occurring in isolation. Independent of whether or not a spindle was nested in the slow oscillation upstate, the slow oscillation downstate was preceded by enhanced calcium signal in SOM-Ins that vanished during the upstate, whereas spindles were associated with strongly increased PV-In calcium activity. Additional wide-field calcium imaging of Pyr cells confirmed the enhanced calcium activity and its widespread topography associated with spindles nested in slow oscillation upstates. In conclusion, when spindles are nested in slow oscillation upstates, maximum Pyr activity appears to concur with strong perisomatic inhibition of Pyr cells via PV-Ins and low dendritic inhibition via SOM-Ins (i.e., conditions that might optimize synaptic plasticity within local cortical circuits).

Competitive learning modulates memory consolidation during sleep

Competition between memories can cause weakening of those memories. Here we investigated memory competition during sleep in human participants by presenting auditory cues that had been linked to two distinct picture-location pairs during wake. We manipulated competition during learning by requiring participants to rehearse picture-location pairs associated with the same sound either competitively (choosing to rehearse one over the other, leading to greater competition) or separately; we hypothesized that greater competition during learning would lead to greater competition when memories were cued during sleep. With separate-pair learning, we found that cueing benefited spatial retention. With competitive-pair learning, no benefit of cueing was observed on retention, but cueing impaired retention of well-learned pairs (where we expected strong competition). During sleep, post-cue beta power (16-30 Hz) indexed competition and predicted forgetting, whereas sigma power (11-16 Hz) predicted subsequent retention. Taken together, these findings show that competition between memories during learning can modulate how they are consolidated during sleep.

A Novel Approach to Dream Content Analysis Reveals Links Between Learning-Related Dream Incorporation and Cognitive Abilities

Can dreams reveal insight into our cognitive abilities and aptitudes (i.e., "human intelligence")? The relationship between dream production and trait-like cognitive abilities is the foundation of several long-standing theories on the neurocognitive and cognitive-psychological basis of dreaming. However, direct experimental evidence is sparse and remains contentious. On the other hand, recent research has provided compelling evidence demonstrating a link between dream content and new learning, suggesting that dreams reflect memory processing during sleep. It remains to be investigated whether the extent of learning-related dream incorporation (i.e., the semantic similarity between waking experiences and dream content) is related to inter-individual differences in cognitive abilities. The relationship between pre-post sleep memory performance improvements and learning-related dream incorporation was investigated (N = 24) to determine if this relationship could be explained by inter-individual differences in intellectual abilities (e.g., reasoning, short term memory (STM), and verbal abilities). The extent of dream incorporation using a novel and objective method of dream content analysis, employed a computational linguistic approach to measure the semantic relatedness between verbal reports describing the experience on a spatial (e.g., maze navigation) or a motor memory task (e.g., tennis simulator) with subsequent hypnagogic reverie dream reports and waking "daydream" reports, obtained during a daytime nap opportunity. Consistent with previous studies, the extent to which something new was learned was related (r = 0.47) to how richly these novel experiences were incorporated into the content of dreams. This was significant for early (the first 4 dream reports) but not late dreams (the last 4 dream reports). Notably, here, we show for the first time that the extent of this incorporation for early dreams was related (r = 0.41) to inter-individual differences in reasoning abilities. On the other hand, late dream incorporation was related (r = 0.46) to inter-individual differences in verbal abilities. There was no relationship between performance improvements and intellectual abilities, and thus, inter-individual differences in cognitive abilities did not mediate the relationship between performance improvements and dream incorporation; suggesting a direct relationship between reasoning abilities and dream incorporation. This study provides the first evidence that learning-related dream production is related to inter-individual differences in cognitive abilities.

Sleep spindle activity in children with obstructive sleep apnea as a marker of neurocognitive performance: A pilot study

STUDY OBJECTIVES

To assess spindle activity as possible markers for neurocognitive consequences in children with mild obstructive sleep apnea.

METHODS

Children aged 6-11 years diagnosed with mild OSA (i.e., an apnea hypopnea index <5.0) were recruited and compared with age and gender-matched healthy controls. Polysomnographic recordings were analyzed for sleep microstructure and spindle activity. All children completed also an intelligence test battery (i.e., the Wechsler intelligence test for children, 4th version).

RESULTS

Nineteen children with OSA (13 boys, mean age 7.1 ± 1.4 y), and 14 controls (7 boys, mean age 8.1 ± 1.9 y) were included. Mean IQ was 110 ± 12 for the complete sample, in children with OSA 111 ± 13, and in controls 108 ± 12 (p = 0.602). Controls showed a higher spindle index in N2 stage than children with OSA: 143.0 ± 42.5 vs 89.5 ± 56.9, respectively (p = 0.003). Spindle index in NREM was strongly and significantly correlated with Verbal Comprehension Index (VCI), Working Memory Index (WMI), Processing Speed Index (PSI), and total IQ in children with OSA.

CONCLUSIONS

Children with mild OSA demonstrate a different pattern of sleep spindle activity that seems to be linked with neurocognitive performance, especially concerning memory. Sleep spindle activity seems to be involved with mechanisms related with neurocognitive consequences in children with OSA.

Impact of sex steroids and reproductive stage on sleep-dependent memory consolidation in women

Age and sex are two of the three major risk factors for Alzheimer's disease (ApoE-e4 allele is the third), with women having a twofold greater risk for Alzheimer's disease after the age of 75 years. Sex differences have been shown across a wide range of cognitive skills in young and older adults, and evidence supports a role for sex steroids, especially estradiol, in protecting against the development of cognitive decline in women. Sleep may also be a protective factor against age-related cognitive decline, since specific electrophysiological sleep events (e.g. sleep spindle/slow oscillation coupling) are critical for offline memory consolidation. Furthermore, studies in young women have shown fluctuations in sleep events and sleep-dependent memory consolidation during different phases of the menstrual cycle that are associated with the levels of sex steroids. An under-appreciated possibility is that there may be an important interaction between these two protective factors (sex steroids and sleep) that may play a role in daily fluctuations in cognitive processing, in particular memory, across a woman's lifespan. Here, we summarize the current knowledge of sex steroid-dependent influences on sleep and cognition across the lifespan in women, with special emphasis on sleep-dependent memory processing. We further indicate gaps in knowledge that require further experimental examination in order to fully appreciate the complex and changing landscape of sex steroids and cognition. Lastly, we propose a series of testable predictions for how sex steroids impact sleep events and sleep-dependent cognition across the three major reproductive stages in women (reproductive years, menopause transition, and post-menopause).

Memory Consolidation Is Linked to Spindle-Mediated Information Processing during Sleep

How are brief encounters transformed into lasting memories? Previous research has established the role of non-rapid eye movement (NREM) sleep, along with its electrophysiological signatures of slow oscillations (SOs) and spindles, for memory consolidation [1, 2, 3, 4]. In related work, experimental manipulations have demonstrated that NREM sleep provides a window of opportunity to selectively strengthen particular memory traces via the delivery of auditory cues [5, 6, 7, 8, 9, 10], a procedure known as targeted memory reactivation (TMR). It has remained unclear, however, whether TMR triggers the brain’s endogenous consolidation mechanisms (linked to SOs and/or spindles) and whether those mechanisms in turn mediate effective processing of mnemonic information. We devised a novel paradigm in which associative memories (adjective-object and adjective-scene pairs) were selectively cued during a post-learning nap, successfully stabilizing next-day retention relative to non-cued memories. First, we found that, compared to novel control adjectives, memory cues evoked an increase in fast spindles. Critically, during the time window of cue-induced spindle activity, the memory category linked to the verbal cue (object or scene) could be reliably decoded, with the fidelity of this decoding predicting the behavioral consolidation benefits of TMR. These results provide correlative evidence for an information processing role of sleep spindles in service of memory consolidation.

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We cued memory reactivation in sleep to investigate the functional role of spindles

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Memory cueing bolstered retrieval performance the following day

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Relative to control stimuli, memory cues evoked a surge in fast spindle activity

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Memory content could be reliably decoded during this spindle increase

Neural mechanisms of mental schema: a triplet of delta, low beta/spindle and ripple oscillations

Schemas are higher-level knowledge structures that integrate and organise lower-level representations. As internal templates, schemas are formed according to how events are perceived, interpreted and remembered. Although these higher-level units are assumed to play a fundamental role in our daily life from an early age, the neuronal basis and mechanisms of schema formation and use remain largely unknown. It is important to elucidate how the brain constructs and maintains these higher-level units. In order to examine the possible neural underpinnings of schema, we recapitulate previous work and discuss their findings related to schemas as the brain template. We specifically focused on low beta/spindle oscillations, which are assumed to be the key components of schemas, and propose that the brain template is implemented with a triplet of neural oscillations, that is delta, low beta/spindle and ripple oscillations.

Transient synchronization of hippocampo-striato-thalamo-cortical networks during sleep spindle oscillations induces motor memory consolidation

Sleep benefits motor memory consolidation. This mnemonic process is thought to be mediated by thalamo-cortical spindle activity during NREM-stage2 sleep episodes as well as changes in striatal and hippocampal activity. However, direct experimental evidence supporting the contribution of such sleep-dependent physiological mechanisms to motor memory consolidation in humans is lacking. In the present study, we combined EEG and fMRI sleep recordings following practice of a motor sequence learning (MSL) task to determine whether spindle oscillations support sleep-dependent motor memory consolidation by transiently synchronizing and coordinating specialized cortical and subcortical networks. To that end, we conducted EEG source reconstruction on spindle epochs in both cortical and subcortical regions using novel deep-source localization techniques. Coherence-based metrics were adopted to estimate functional connectivity between cortical and subcortical structures over specific frequency bands. Our findings not only confirm the critical and functional role of NREM-stage2 sleep spindles in motor skill consolidation, but provide first-time evidence that spindle oscillations [11-17 Hz] may be involved in sleep-dependent motor memory consolidation by locally reactivating and functionally binding specific task-relevant cortical and subcortical regions within networks including the hippocampus, putamen, thalamus and motor-related cortical regions.

Replay of large-scale spatio-temporal patterns from waking during subsequent NREM sleep in human cortex

Animal studies support the hypothesis that in slow-wave sleep, replay of waking neocortical activity under hippocampal guidance leads to memory consolidation. However, no intracranial electrophysiological evidence for replay exists in humans. We identified consistent sequences of population firing peaks across widespread cortical regions during complete waking periods. The occurrence of these “Motifs” were compared between sleeps preceding the waking period (“Sleep-Pre”) when the Motifs were identified, and those following (“Sleep-Post”). In all subjects, the majority of waking Motifs (most of which were novel) had more matches in Sleep-Post than in Sleep-Pre. In rodents, hippocampal replay occurs during local sharp-wave ripples, and the associated neocortical replay tends to occur during local sleep spindles and down-to-up transitions. These waves may facilitate consolidation by sequencing cell-firing and encouraging plasticity. Similarly, we found that Motifs were coupled to neocortical spindles, down-to-up transitions, theta bursts, and hippocampal sharp-wave ripples. While Motifs occurring during cognitive task performance were more likely to have more matches in subsequent sleep, our studies provide no direct demonstration that the replay of Motifs contributes to consolidation. Nonetheless, these results confirm a core prediction of the dominant neurobiological theory of human memory consolidation.

Sleep in Humans Stabilizes Pattern Separation Performance

Replay of hippocampal neural representations during sleep is thought to promote systems consolidation of declarative memory. How this reprocessing of memory during sleep affects the hippocampal representation itself, is unclear. Here we tested hippocampal stimulus processing (i.e., pattern separation) before and after periods of sleep and wakefulness in humans (female and male participants). Pattern separation deteriorated across the wake period but remained stable across sleep (p = 0.013) with this sleep-wake difference being most pronounced for stimuli with low similarity to targets (p = 0.006). Stimuli with the highest similarity showed a reversed pattern with reduced pattern separation performance after sleep (p = 0.038). Pattern separation performance was positively correlated with sleep spindle density, slow oscillation density, and theta power phase-locked to slow oscillations. Sleep, presumably by neural memory replay, shapes hippocampal representations and enhances computations of pattern separation to subsequent presentation of similar stimuli.SIGNIFICANCE STATEMENT The consolidation of hippocampus-dependent memories is causally related to reactivation during sleep of previously encoded representations. Here, we show that reactivation-based consolidation processes during sleep shape the hippocampal representation itself. We studied the effect of sleep and wakefulness on pattern separation (i.e., orthogonalization of similar representations) and completion performance (i.e., recall of a memory in light of noisy input) that are essential cognitive elements of encoding and retrieval of information by the hippocampus. Our results demonstrate that pattern separation was stabilized after sleep but diminished after wakefulness. We further showed that pattern separation was related to EEG oscillatory parameters of non-REM sleep serving as markers of sleep-dependent memory consolidation and hippocampal reactivation.

Enhanced Memory Consolidation Via Automatic Sound Stimulation During Non-REM Sleep

Introduction:

Slow-wave sleep (SWS) slow waves and sleep spindle activity have been shown to be crucial for memory consolidation. Recently, memory consolidation has been causally facilitated in human participants via auditory stimuli phase-locked to SWS slow waves.

Aims:

Here, we aimed to develop a new acoustic stimulus protocol to facilitate learning and to validate it using different memory tasks. Most importantly, the stimulation setup was automated to be applicable for ambulatory home use.

Methods:

Fifteen healthy participants slept 3 nights in the laboratory. Learning was tested with 4 memory tasks (word pairs, serial finger tapping, picture recognition, and face-name association). Additional questionnaires addressed subjective sleep quality and overnight changes in mood. During the stimulus night, auditory stimuli were adjusted and targeted by an unsupervised algorithm to be phase-locked to the negative peak of slow waves in SWS. During the control night no sounds were presented.

Results:

Results showed that the sound stimulation increased both slow wave (p = .002) and sleep spindle activity (p < .001). When overnight improvement of memory performance was compared between stimulus and control nights, we found a significant effect in word pair task but not in other memory tasks. The stimulation did not affect sleep structure or subjective sleep quality.

Conclusions:

We showed that the memory effect of the SWS-targeted individually triggered single-sound stimulation is specific to verbal associative memory. Moreover, the ambulatory and automated sound stimulus setup was promising and allows for a broad range of potential follow-up studies in the future.

Using Oscillating Sounds to Manipulate Sleep Spindles

Introduction

EEG oscillations known as sleep spindles have been linked with various aspects of cognition, but the specific functions they signal remain controversial. Two types of EEG sleep spindles have been distinguished: slow spindles at 11-13.5 Hz and fast spindles at 13.5-16 Hz. Slow spindles exhibit a frontal scalp topography, whereas fast spindles exhibit a posterior scalp topography and have been preferentially linked with memory consolidation during sleep. To advance understanding beyond that provided from correlative studies of spindles, we aimed to develop a new method to systematically manipulate spindles.

Aims and Methods

We presented repeating bursts of oscillating white noise to people during a 90-min afternoon nap. During stage 2 and slow-wave sleep, oscillations were embedded within contiguous 10-s stimulation intervals, each comprising 2 s of white noise amplitude modulated at 12 Hz (targeting slow spindles), 15 Hz (targeting fast spindles), or 50 Hz followed by 8 s of constant white noise.

Results

During oscillating stimulation compared to constant stimulation, parietal EEG recordings showed more slow spindles in the 12-Hz condition, more fast spindles in the 15-Hz condition, and no change in the 50-Hz control condition. These effects were topographically selective, and were absent in frontopolar EEG recordings, where slow spindle density was highest. Spindles during stimulation were similar to spontaneous spindles in standard physiological features, including duration and scalp distribution.

Conclusions

These results define a new method to selectively and noninvasively manipulate spindles through acoustic resonance, while also providing new evidence for functional distinctions between the 2 types of EEG spindles.

Identifying sleep spindles with multichannel EEG and classification optimization

Researchers classify critical neural events during sleep called spindles that are related to memory consolidation using the method of scalp electroencephalography (EEG). Manual classification is time consuming and is susceptible to low inter-rater agreement. This could be improved using an automated approach. This study presents an optimized filter based and thresholding (FBT) model to set up a baseline for comparison to evaluate machine learning models using naïve features, such as raw signals, peak frequency, and dominant power. The FBT model allows us to formally define sleep spindles using signal processing but may miss examples most human scorers would agree are spindles. Machine learning methods in theory should be able to approach performance of human raters but they require a large quantity of scored data, proper feature representation, intensive feature engineering, and model selection. We evaluate both the FBT model and machine learning models with naïve features. We show that the machine learning models derived from the FBT model improve classification performance. An automated approach designed for the current data was applied to the DREAMS dataset [1]. With one of the expert's annotation as a gold standard, our pipeline yields an excellent sensitivity that is close to a second expert's scores and with the advantage that it can classify spindles based on multiple channels if more channels are available. More importantly, our pipeline could be modified as a guide to aid manual annotation of sleep spindles based on multiple channels quickly (6-10 s for processing a 40-min EEG recording), making spindle detection faster and more objective.

Targeted Memory Reactivation during Sleep Adaptively Promotes the Strengthening or Weakening of Overlapping Memories

System memory consolidation is conceptualized as an active process whereby newly encoded memory representations are strengthened through selective memory reactivation during sleep. However, our learning experience is highly overlapping in content (i.e., shares common elements), and memories of these events are organized in an intricate network of overlapping associated events. It remains to be explored whether and how selective memory reactivation during sleep has an impact on these overlapping memories acquired during awake time. Here, we test in a group of adult women and men the prediction that selective memory reactivation during sleep entails the reactivation of associated events and that this may lead the brain to adaptively regulate whether these associated memories are strengthened or pruned from memory networks on the basis of their relative associative strength with the shared element. Our findings demonstrate the existence of efficient regulatory neural mechanisms governing how complex memory networks are shaped during sleep as a function of their associative memory strength.SIGNIFICANCE STATEMENT Numerous studies have demonstrated that system memory consolidation is an active, selective, and sleep-dependent process in which only subsets of new memories become stabilized through their reactivation. However, the learning experience is highly overlapping in content and thus events are encoded in an intricate network of related memories. It remains to be explored whether and how memory reactivation has an impact on overlapping memories acquired during awake time. Here, we show that sleep memory reactivation promotes strengthening and weakening of overlapping memories based on their associative memory strength. These results suggest the existence of an efficient regulatory neural mechanism that avoids the formation of cluttered memory representation of multiple events and promotes stabilization of complex memory networks.

More Effective Consolidation of Episodic Long-Term Memory in Children Than Adults-Unrelated to Sleep

Abilities to encode and remember events in their spatiotemporal context (episodic memory) rely on brain regions that mature late during childhood and are supported by sleep. We compared the temporal dynamics of episodic memory formation and the role of sleep in this process between 62 children (8-12 years) and 57 adults (18-37 years). Subjects recalled "what-where-when" memories after a short 1-hr retention interval or after a long 10.5-hr interval containing either nocturnal sleep or daytime wakefulness. Although children showed diminished recall of episodes after 1 hr, possibly resulting from inferior encoding, unlike adults, they showed no further decrease in recall after 10.5 hr. In both age groups, episodic memory benefitted from sleep. However, children's more effective offline retention was unrelated to sleep.

Evaluating and Improving Automatic Sleep Spindle Detection by Using Multi-Objective Evolutionary Algorithms

Sleep spindles are brief bursts of brain activity in the sigma frequency range (11–16 Hz) measured by electroencephalography (EEG) mostly during non-rapid eye movement (NREM) stage 2 sleep. These oscillations are of great biological and clinical interests because they potentially play an important role in identifying and characterizing the processes of various neurological disorders. Conventionally, sleep spindles are identified by expert sleep clinicians via visual inspection of EEG signals. The process is laborious and the results are inconsistent among different experts. To resolve the problem, numerous computerized methods have been developed to automate the process of sleep spindle identification. Still, the performance of these automated sleep spindle detection methods varies inconsistently from study to study. There are two reasons: (1) the lack of common benchmark databases, and (2) the lack of commonly accepted evaluation metrics. In this study, we focus on tackling the second problem by proposing to evaluate the performance of a spindle detector in a multi-objective optimization context and hypothesize that using the resultant Pareto fronts for deriving evaluation metrics will improve automatic sleep spindle detection. We use a popular multi-objective evolutionary algorithm (MOEA), the Strength Pareto Evolutionary Algorithm (SPEA2), to optimize six existing frequency-based sleep spindle detection algorithms. They include three Fourier, one continuous wavelet transform (CWT), and two Hilbert-Huang transform (HHT) based algorithms. We also explore three hybrid approaches. Trained and tested on open-access DREAMS and MASS databases, two new hybrid methods of combining Fourier with HHT algorithms show significant performance improvement with F₁-scores of 0.726–0.737.

Decoding material-specific memory reprocessing during sleep in humans

Neuronal learning activity is reactivated during sleep but the dynamics of this reactivation in humans are still poorly understood. Here we use multivariate pattern classification to decode electrical brain activity during sleep and determine what type of images participants had viewed in a preceding learning session. We find significant patterns of learning-related processing during rapid eye movement (REM) and non-REM (NREM) sleep, which are generalizable across subjects. This processing occurs in a cyclic fashion during time windows congruous to critical periods of synaptic plasticity. Its spatial distribution over the scalp and relevant frequencies differ between NREM and REM sleep. Moreover, only the strength of reprocessing in slow-wave sleep influenced later memory performance, speaking for at least two distinct underlying mechanisms between these states. We thus show that memory reprocessing occurs in both NREM and REM sleep in humans and that it pertains to different aspects of the consolidation process.

Reactivation or transformation? Motor memory consolidation associated with cerebral activation time-locked to sleep spindles

Motor memory consolidation is thought to depend on sleep-dependent reactivation of brain areas recruited during learning. However, up to this point, there has been no direct evidence to support this assertion in humans, and the physiological processes supporting such reactivation are unknown. Here, simultaneous electroencephalographic and functional magnetic resonance imaging (EEG-fMRI) recordings were conducted during post-learning sleep to directly investigate the spindle-related reactivation of a memory trace formed during motor sequence learning (MSL), and its relationship to overnight enhancement in performance (reflecting consolidation). We show that brain regions within the striato-cerebello-cortical network recruited during training on the MSL task, and in particular the striatum, were also activated during sleep, time-locked to spindles. Interestingly, the consolidated trace in the striatum was not simply strengthened, but was transformed/reorganized from rostrodorsal (associative) to caudoventral (sensorimotor) subregions. Moreover, the degree of the reactivation was correlated with overnight improvements in performance. Altogether, the present findings demonstrate that striatal reactivation linked to sleep spindles in the post-learning night, is related to motor memory consolidation.