EEG sigma and slow‐wave activity during NREM sleep correlate with overnight declarative and procedural memory consolidation

Previous studies suggest that sleep‐specific brain activity patterns such as sleep spindles and electroencephalographic slow‐wave activity contribute to the consolidation of novel memories. The generation of both sleep spindles and slow‐wave activity relies on synchronized oscillations in a thalamo‐cortical network that might be implicated in synaptic strengthening (spindles) and downscaling (slow‐wave activity) during sleep. This study further examined the association between electroencephalographic power during non‐rapid eye movement sleep in the spindle (sigma, 12–16 Hz) and slow‐wave frequency range (0.1–3.5 Hz) and overnight memory consolidation in 20 healthy subjects (10 men, 27.1 ± 4.6 years). We found that both electroencephalographic sigma power and slow‐wave activity were positively correlated with the pre–post‐sleep consolidation of declarative (word list) and procedural (mirror‐tracing) memories. These results, although only correlative in nature, are consistent with the view that processes of synaptic strengthening (sleep spindles) and synaptic downscaling (slow‐wave activity) might act in concert to promote synaptic plasticity and the consolidation of both declarative and procedural memories during sleep.     

Experience-dependent changes in cerebral functional connectivity during human rapid eye movement sleep

One function of sleep is hypothesized to be the reprocessing and consolidation of memory traces (Smith, 1995; Gais et al., 2000; McGaugh, 2000; Stickgold et al., 2000). At the cellular level, neuronal reactivations during post-training sleep in animals have been observed in hippocampal (Wilson and McNaughton, 1994) and cortical (Amzica et al., 1997) neuronal populations. At the systems level, using positron emission tomography, we have recently shown that some brain areas reactivated during rapid-eye-movement sleep in human subjects previously trained on an implicit learning task (a serial reaction time task) (Maquet et al., 2000). These cortical reactivations, located in the left premotor area and bilateral cuneus, were thought to reflect the reprocessing--possibly the consolidation--of memory traces during post-training rapid-eye-movement sleep. Here, the experience-dependent functional connectivity of these brain regions is examined. It is shown that the left premotor cortex is functionally more correlated with the left posterior parietal cortex and bilateral pre-supplementary motor area during rapid-eye-movement sleep of subjects previously trained to the reaction time task compared to rapid-eye-movement sleep of untrained subjects. The increase in functional connectivity during post-training rapid-eye-movement sleep suggests that the brain areas reactivated during post-training rapid-eye-movement sleep participate in the optimization of the network that subtends subject's visuo-motor response. The optimization of this visuo-motor network during sleep could explain the gain in performance observed during the following day.     

The effect of sleep‐specific brain activity versus reduced stimulus interference on declarative memory consolidation

Studies suggest that the consolidation of newly acquired memories and underlying long‐term synaptic plasticity might represent a major function of sleep. In a combined repeated‐measures and parallel‐group sleep laboratory study (active waking versus sleep, passive waking versus sleep), we provide evidence that brief periods of daytime sleep (42.1 ± 8.9 min of non‐rapid eye movement sleep) in healthy adolescents (16 years old, all female), compared with equal periods of waking, promote the consolidation of declarative memory (word‐pairs) in participants with high power in the electroencephalographic sleep spindle (sigma) frequency range. This observation supports the notion that sleep‐specific brain activity when reaching a critical dose, beyond a mere reduction of interference, promotes synaptic plasticity in a hippocampal‐neocortical network that underlies the consolidation of declarative memory.     

Coordinated memory replay in the visual cortex and hippocampus during sleep

Sleep replay of awake experience in the cortex and hippocampus has been proposed to be involved in memory consolidation. However, whether temporally structured replay occurs in the cortex and whether the replay events in the two areas are related are unknown. Here we studied multicell spiking patterns in both the visual cortex and hippocampus during slow-wave sleep in rats. We found that spiking patterns not only in the cortex but also in the hippocampus were organized into frames, defined as periods of stepwise increase in neuronal population activity. The multicell firing sequences evoked by awake experience were replayed during these frames in both regions. Furthermore, replay events in the sensory cortex and hippocampus were coordinated to reflect the same experience. These results imply simultaneous reactivation of coherent memory traces in the cortex and hippocampus during sleep that may contribute to or reflect the result of the memory consolidation process.     

Labile or stable: opposing consequences for memory when reactivated during waking and sleep

Memory consolidation is a dynamic process. Reconsolidation theory assumes that reactivation during wakefulness transiently destabilizes memories, requiring them to reconsolidate in order to persist. Memory reactivation also occurs during slow-wave sleep (SWS) and is assumed to underlie the consolidating effect of sleep. Here, we tested whether the same principle of transient destabilization applies to memory reactivation during SWS. We reactivated memories in humans by presenting associated odor cues either during SWS or wakefulness. Reactivation was followed by an interference task to probe memory stability. As we expected, reactivation during waking destabilized memories. In contrast, reactivation during SWS immediately stabilized memories, thereby directly increasing their resistance to interference. Functional magnetic resonance imaging revealed that reactivation during SWS mainly activated hippocampal and posterior cortical regions, whereas reactivation during wakefulness primarily activated prefrontal cortical areas. Our results show that reactivation of memory serves distinct functions depending on the brain state of wakefulness or sleep.     

Phase‐amplitude coupling of sleep slow oscillatory and spindle activity correlates with overnight memory consolidation

Initially independent lines of research suggest that sleep‐specific brain activity patterns, observed as electroencephalographic slow oscillatory and sleep spindle activity, promote memory consolidation and underlying synaptic refinements. Here, we further tested the emerging concept that specifically the coordinated interplay of slow oscillations and spindle activity (phase‐amplitude coupling) support memory consolidation. Particularly, we associated indices of the interplay between slow oscillatory (0.16–1.25 Hz) and spindle activity (12–16 Hz) during non‐rapid eye movement sleep (strength [modulation index] and phase degree of coupling) in 20 healthy adults with parameters of overnight declarative (word‐list task) and procedural (mirror‐tracing task) memory consolidation. The pattern of results supports the notion that the interplay between oscillations facilitates memory consolidation. The coincidence of the spindle amplitude maximum with the up‐state of the slow oscillation (phase degree) was significantly associated with declarative memory consolidation (r = .65, p = .013), whereas the overall strength of coupling (modulation index) correlated with procedural memory consolidation (r = .45, p = .04). Future studies are needed to test for potential causal effects of the observed association between neural oscillations during sleep and memory consolidation, and to elucidate ways of modulating these processes, for instance through non‐invasive brain‐stimulation techniques.     

Sleep and synaptic renormalization: a computational study

Recent evidence indicates that net synaptic strength in cortical and other networks increases during wakefulness and returns to a baseline level during sleep. These homeostatic changes in synaptic strength are accompanied by corresponding changes in sleep slow wave activity (SWA) and in neuronal firing rates and synchrony. Other evidence indicates that sleep is associated with an initial reactivation of learned firing patterns that decreases over time. Finally, sleep can enhance performance of learned tasks, aid memory consolidation, and desaturate the ability to learn. Using a large-scale model of the corticothalamic system equipped with a spike-timing dependent learning rule, in agreement with experimental results, we demonstrate a net increase in synaptic strength in the waking mode associated with an increase in neuronal firing rates and synchrony. In the sleep mode, net synaptic strength decreases accompanied by a decline in SWA. We show that the interplay of activity and plasticity changes implements a control loop yielding an exponential, self-limiting renormalization of synaptic strength. Moreover, when the model "learns" a sequence of activation during waking, the learned sequence is preferentially reactivated during sleep, and reactivation declines over time. Finally, sleep-dependent synaptic renormalization leads to increased signal-to-noise ratios, increased resistance to interference, and desaturation of learning capabilities. Although the specific mechanisms implemented in the model cannot capture the variety and complexity of biological substrates, and will need modifications in line with future evidence, the present simulations provide a unified, parsimonious account for diverse experimental findings coming from molecular, electrophysiological, and behavioral approaches.     

Cueing vocabulary during sleep increases theta activity during later recognition testing

Neural oscillations in the theta band have repeatedly been implicated in successful memory encoding and retrieval. Several recent studies have shown that memory retrieval can be facilitated by reactivating memories during their consolidation during sleep. However, it is still unknown whether reactivation during sleep also enhances subsequent retrieval‐related neural oscillations. We have recently demonstrated that foreign vocabulary cues presented during sleep improve later recall of the associated translations. Here, we examined the effect of cueing foreign vocabulary during sleep on oscillatory activity during subsequent recognition testing after sleep. We show that those words that were replayed during sleep after learning (cued words) elicited stronger centroparietal theta activity during recognition as compared to noncued words. The reactivation‐induced increase in theta oscillations during later recognition testing might reflect a strengthening of individual memory traces and the integration of the newly learned words into the mental lexicon by cueing during sleep.     

No effect of targeted memory reactivation during slow‐wave sleep on emotional recognition memory

Recent work has suggested that the benefits of sleep for memory consolidation are enhanced for highly salient (versus non‐salient) memories. Using a technique known as targeted memory reactivation, it is possible to selectively strengthen newly learned memories by re‐exposing the sleeping brain to auditory cues. The aim of the current study was to examine whether emotionally salient memories are also more responsive to targeted memory reactivation in slow‐wave sleep than neutral memories. In an initial training phase, participants memorised emotionally negative and neutral pictures, which were each paired with a semantically related sound. Recognition for the pictures was assessed before and after a 90‐min nap opportunity, during which half the sounds were re‐presented during slow‐wave sleep (as assessed via online polysomnographic sleep monitoring). We observed no effect of targeted memory reactivation on the recognition of emotionally negative or neutral memories. Our results highlight the importance of the memory paradigm used to assess targeted memory reactivation, and suggest that the robust and durable nature of recognition memory may make it an insensitive measure of behavioural targeted memory reactivation benefits. To fully assess the impacts of targeted memory reactivation on emotional memory processing in sleep, future studies should adopt experimental paradigms that maximise the salience of emotional stimuli while also providing a sensitive index of memory accuracy.     

Flexible spike timing of layer 5 neurons during dynamic beta oscillation shifts in rat prefrontal cortex

Human brain oscillations occur in different frequency bands that have been linked to different behaviours and cognitive processes. Even within specific frequency bands such as the beta- (14–30 Hz) or gamma-band (30–100 Hz), oscillations fluctuate in frequency and amplitude. Such frequency fluctuations most probably reflect changing states of neuronal network activity, as brain oscillations arise from the correlated synchronized activity of large numbers of neurons. However, the neuronal mechanisms governing the dynamic nature of amplitude and frequency fluctuations within frequency bands remain elusive. Here we show that in acute slices of rat prefrontal cortex (PFC), carbachol-induced oscillations in the beta-band show frequency and amplitude fluctuations. Fast and slow non-harmonic frequencies are distributed differentially over superficial and deep cortical layers, with fast frequencies being present in layer 3, while layer 6 only showed slow oscillation frequencies. Layer 5 pyramidal cells and interneurons experience both fast and slow frequencies and they time their spiking with respect to the dominant frequency. Frequency and phase information is encoded and relayed in the layer 5 network through timed excitatory and inhibitory synaptic transmission. Our data indicate that frequency fluctuations in the beta-band reflect synchronized activity in different cortical subnetworks, that both influence spike timing of output layer 5 neurons. Thus, amplitude and frequency fluctuations within frequency bands may reflect activity in distinct cortical neuronal subnetworks that may process information in a parallel fashion.     

Grouping of brain rhythms in corticothalamic systems

Different brain rhythms, with both low-frequency and fast-frequency, are grouped within complex wave-sequences. Instead of dissecting various frequency bands of the major oscillations that characterize the brain electrical activity during states of vigilance, it is conceptually more rewarding to analyze their coalescence, which is due to neuronal interactions in corticothalamic systems. This concept of unified brain rhythms does not only include low-frequency sleep oscillations but also fast (beta and gamma) activities that are not exclusively confined to brain-activated states, since they also occur during slow-wave sleep. The major factor behind this coalescence is the cortically generated slow oscillation that, through corticocortical and corticothalamic drives, is effective in grouping other brain rhythms. The experimental evidence for unified oscillations derived from simultaneous intracellular recordings of cortical and thalamic neurons in vivo, while recent studies in humans using global methods provided congruent results of grouping different types of slow and fast oscillatory activities. Far from being epiphenomena, spontaneous brain rhythms have an important role in synaptic plasticity. The role of slow-wave sleep oscillation in consolidating memory traces acquired during wakefulness is being explored in both experimental animals and human subjects. Highly synchronized sleep oscillations may develop into seizures that are generated intracortically and lead to inhibition of thalamocortical neurons, via activation of thalamic reticular neurons, which may explain the obliteration of signals from the external world and unconsciousness during some paroxysmal states.     

The relationships between memory systems and sleep stages

Sleep function remains elusive despite our rapidly increasing comprehension of the processes generating and maintaining the different sleep stages. Several lines of evidence support the hypothesis that sleep is involved in the off-line reprocessing of recently-acquired memories. In this review, we summarize the main results obtained in the field of sleep and memory consolidation in both animals and humans, and try to connect sleep stages with the different memory systems. To this end, we have collated data obtained using several methodological approaches, including electrophysiological recordings of neuronal ensembles, post-training modifications of sleep architecture, sleep deprivation and functional neuroimaging studies. Broadly speaking, all the various studies emphasize the fact that the four long-term memory systems (procedural memory, perceptual representation system, semantic and episodic memory, according to Tulving's SPI model; Tulving, 1995) benefit either from non-rapid eye movement (NREM) (not just SWS) or rapid eye movement (REM) sleep, or from both sleep stages. Tulving's classification of memory systems appears more pertinent than the declarative/non-declarative dichotomy when it comes to understanding the role of sleep in memory. Indeed, this model allows us to resolve several contradictions, notably the fact that episodic and semantic memory (the two memory systems encompassed in declarative memory) appear to rely on different sleep stages. Likewise, this model provides an explanation for why the acquisition of various types of skills (perceptual-motor, sensory-perceptual and cognitive skills) and priming effects, subserved by different brain structures but all designated by the generic term of implicit or non-declarative memory, may not benefit from the same sleep stages.     

Sound‐induced perturbations of the brain network in non‐REM sleep,and network oscillations in wake

During sleep, the brain network processes sensory stimuli without awareness. Stimulation must affect differently brain networks in sleep versus wake, but these differences have yet to be quantified. We recorded cortical activity in stage 2 (SII) sleep and wake using EEG while a tone was intermittently played. Zero‐lag correlation measured input to pairs of sensors in the network; cross‐correlation and phase‐lag index measured pairwise corticocortical connectivity. Our analysis revealed that under baseline conditions, the cortical network, in particular the central regions of the frontoparietal cortex, interact at a characteristic latency of 50 ms, but only during wake, not sleep. Nonsalient auditory stimulation causes far greater perturbation of connectivity from baseline in sleep than wake, both in the response to common input and corticocortical connectivity. The findings have key implications for sensory processing.     

Pathophysiology of sleep-dependent memory consolidation processes in children

Cognitive impairments are often associated with abnormal sleep activity in developmental disorders and pathologies of childhood. Besides, accumulated evidence indicates that post-training sleep benefits to the consolidation of recently learned information in healthy adults and children. Although sleep-dependent consolidation effects in children are clearly established for declarative memories, they remain more debated in the procedural memory domain. Nowadays, recent experimental data suggest close interactions between the development of sleep-dependent plasticity markers, cortical maturation and cognition in children. In the present review, we propose that studying sleep and memory consolidation processes in developmental disorders and acquired childhood pathologies can provide novel, enlightening clues to understand the pathophysiological mechanisms subtending the disruption of long-term cerebral plasticity processes eventually leading to cognitive and learning deficits in children.     

Dreaming of a learning task is associated with enhanced memory consolidation: Replication in an overnight sleep study

Sleep following learning benefits memory. One model attributes this effect to the iterative “reactivation” of memory traces in the sleeping brain, demonstrated in animal models. Although technical limitations prohibit using the same methods to observe memory reactivation in the human brain, the study of mental activity during sleep provides an alternative method of observing memory activation during sleep. In fact, the content of dream experience may reflect the process of memory reactivation and consolidation in the sleeping brain. In line with this hypothesis, we previously reported that dreaming about a spatial learning task during a nap strongly predicts subsequent performance improvements. Here, we replicate this observation in an overnight sleep study, for the first time demonstrating that pre‐sleep training on a virtual maze navigation task is reflected in dreams reported from all phases of sleep, with unambiguous representation of the task in dream content associated with improved next‐morning performance. These observations are consistent with reactivation‐based models of memory consolidation in sleep, confirming our earlier finding that the cognitive‐level activation of recent experience during sleep is associated with subsequent performance gains.     

Rapid eye movement sleep deprivation does not affect fear memory reconsolidation in rats

There is increasing evidence that sleep may be involved in memory consolidation. However, there remain comparatively few studies that have explored the relationship between sleep and memory reconsolidation. At present study, we tested the effects of rapid eye movement sleep deprivation (RSD) on the reconsolidation of cued (experiment 1) and contextual (experiment 2) fear memory in rats. Behaviour procedure involved four training phases: habituation, fear conditioning, reactivation and test. Rats were subjected to 6 h RSD starting either immediately after reactivation or 6 h later. The control rats were returned to their home cages immediately after reactivation and left undisturbed. Contrary to those hypotheses speculating a potential role of sleep in reconsolidation, we found that post-reactivation RSD whether from 0 to 6 h or 6 to 12 h had no effect on the reconsolidation of both cued and contextual fear memory. However, our present results did not exclude the potential roles of non-rapid eye movement sleep in the reconsolidation of fear memory or sleep in the reconsolidation of other memory paradigms.     

Impact of network activities on neuronal properties in corticothalamic systems.

Data from in vivo and in vitro experiments are discussed to emphasize that synaptic activities in neocortex and thalamus have a decisive impact on intrinsic neuronal properties in intact-brain preparations under anesthesia and even more so during natural states of vigilance. Thus the firing patterns of cortical neuronal types are not inflexible but may change with the level of membrane potential and during periods rich in synaptic activity. The incidences of some cortical cell classes (defined by their responses to depolarizing current pulses) are different in isolated cortical slabs in vivo or in slices maintained in vitro compared with the intact cortex of naturally awake animals. Network activities, which include the actions of generalized modulatory systems, have a profound influence on the membrane potential, apparent input resistance, and backpropagation of action potentials. The analysis of various oscillatory types leads to the conclusion that in the intact brain, there are no "pure" rhythms, generated in simple circuits, but complex wave sequences (consisting of different, low- and fast-frequency oscillations) that result from synaptic interactions in corticocortical and corticothalamic neuronal loops under the control of activating systems arising in the brain stem core or forebrain structures. As an illustration, it is shown that the neocortex governs the synchronization of network or intrinsically generated oscillations in the thalamus. The rhythmic recurrence of spike bursts and spike trains fired by thalamic and cortical neurons during states of decreased vigilance may lead to plasticity processes in neocortical neurons. If these phenomena, which may contribute to the consolidation of memory traces, are not constrained by inhibitory processes, they induce seizures in which the neocortex initiates the paroxysms and controls their thalamic reflection. The results indicate that intact-brain preparations are necessary to investigate global brain functions such as behavioral states of vigilance and paroxysmal activities.     

No evidence for intra-individual correlations between sleep-mediated declarative memory consolidation and slow-wave sleep

Study ObjectivesMemory consolidation benefits from a retention period filled with sleep. Several theoretical accounts assume that slow-wave sleep (SWS) contributes functionally to processes underlying the stabilization of declarative memories during sleep. However, reports on correlations between memory retention and the amount of SWS are mixed and typically rely on between-subject correlations and small sample sizes. Here we tested for the first time whether the amount of SWS during sleep predicts the effect of sleep on memory consolidation on an intra-individual level in a large sample.MethodsOne hundred and fifty-nine healthy participants came to the lab twice and took a 90 min nap in both sessions. Sleep-mediated memory benefits were tested using the paired associates word-learning task in both sessions.ResultsIn contrast to the theoretical prediction, intra-individual differences in sleep-mediated memory benefits did not significantly correlate with differences in SWS or SWA between the two naps. Also between subjects, the amount of SWS did not correlate with memory retention across the nap. However, subjective ratings of sleep quality were significantly associated with the amount of SWS.ConclusionOur results question the notion that the amount of SWS per se is functionally related to processes of memory consolidation during sleep. While our results do not exclude an important role of SWS for memory, they suggest that “more SWS” does not necessarily imply better memory consolidation.     

Neural basis of alertness and cognitive performance impairments during sleepiness. I. Effects of 24 h of sleep deprivation on waking human regional brain activity

The negative effects of sleep deprivation on alertness and cognitive performance suggest decreases in brain activity and function, primarily in the thalamus, a subcortical structure involved in alertness and attention, and in the prefrontal cortex, a region subserving alertness, attention, and higher-order cognitive processes. To test this hypothesis, 17 normal subjects were scanned for quantifiable brain activity changes during 85 h of sleep deprivation using positron emission tomography (PET) and (18)Fluorine-2-deoxyglucose ((18)FDG), a marker for regional cerebral metabolic rate for glucose (CMRglu) and neuronal synaptic activity. Subjects were scanned prior to and at 24-h intervals during the sleep deprivation period, for a total of four scans per subject. During each 30 min (18)FDG uptake, subjects performed a sleep deprivation-sensitive Serial Addition/Subtraction task. Polysomnographic monitoring confirmed that subjects were awake. Twenty-four hours of sleep deprivation, reported here, resulted in a significant decrease in global CMRglu, and significant decreases in absolute regional CMRglu in several cortical and subcortical structures. No areas of the brain evidenced a significant increase in absolute regional CMRglu. Significant decreases in relative regional CMRglu, reflecting regional brain reductions greater than the global decrease, occurred predominantly in the thalamus and prefrontal and posterior parietal cortices. Alertness and cognitive performance declined in association with these brain deactivations. This study provides evidence that short-term sleep deprivation produces global decreases in brain activity, with larger reductions in activity in the distributed cortico-thalamic network mediating attention and higher-order cognitive processes, and is complementary to studies demonstrating deactivation of these cortical regions during NREM and REM sleep.