Sleep and the extraction of hidden regularities: A systematic review and the importance of temporal rules

Integration of overlapping sequences emerges with consolidation through medial prefrontal cortex neural ensembles and hippocampal-cortical connectivity

Systems consolidation theories propose two mechanisms that enable the behavioral integration of related memories: coordinated reactivation between hippocampus and cortex, and the emergence of cortical traces that reflect overlap across memories. However, there is limited empirical evidence that links these mechanisms to the emergence of behavioral integration over time. In two experiments, participants implicitly encoded sequences of objects with overlapping structure. Assessment of behavioral integration showed that response times during a recognition task reflected behavioral priming between objects that never occurred together in time but belonged to overlapping sequences. This priming was consolidation-dependent and only emerged for sequences learned 24 hr prior to the test. Critically, behavioral integration was related to changes in neural pattern similarity in the medial prefrontal cortex and increases in post-learning rest connectivity between the posterior hippocampus and lateral occipital cortex. These findings suggest that memories with a shared predictive structure become behaviorally integrated through a consolidation-related restructuring of the learned sequences, providing insight into the relationship between different consolidation mechanisms that support behavioral integration.

Manipulated overlapping reactivation of multiple memories promotes explicit gist abstraction

Sleep is considered to promote gist abstraction on the basis of spontaneous memory reactivation. As speculated in the theory of 'information overlap to abstract (iOtA)', 'overlap' between reactivated memories, beyond reactivation, is crucial to gist abstraction. Yet so far, empirical research has not tested this theory by manipulating the factor of 'overlap'. In the current study, 'overlap' itself was manipulated by targeted memory reactivation (TMR), through simultaneously reactivating multiple memories that either contain or do not contain spatially overlapped gist information, to investigate the effect of overlapping reactivation on gist abstraction. This study had a factorial design of 2 factors with 2 levels respectively (spatial overlap/no spatial overlap, TMR/no-TMR). Accordingly, 82 healthy college students (aged 19 ∼ 25, 57 females) were randomized into four groups. After learning 16 pictures, paired with 4 auditory cues (4 pictures - 1 cue) according to the grouping, participants were given a 90-minute nap opportunity. Then TMR cueing was conducted during N2 and slow wave sleep of the nap. Performance in memory task was used to measure gist abstraction. The results showed a significant main effect of TMR on both implicit and explicit gist abstraction, and a marginally significant interaction effect on explicit gist abstraction. Further analyses showed that explicit gist abstraction in the spatial overlap & TMR group was significantly better than in the control group. Moreover, explicit gist abstraction was positively correlated with spindle density. The current study thus indicates that TMR facilitates gist abstraction, and explicit gist abstraction may benefit more from overlapping reactivation.

Memory Reactivation during Sleep Does Not Act Holistically on Object Memory

Memory reactivation during sleep is thought to facilitate memory consolidation. Most sleep reactivation research has examined how reactivation of specific facts, objects, and associations benefits their overall retention. However, our memories are not unitary, and not all features of a memory persist in tandem over time. Instead, our memories are transformed, with some features strengthened and others weakened. Does sleep reactivation drive memory transformation? We leveraged the Targeted Memory Reactivation technique in an object category learning paradigm to examine this question. Participants (20 female, 14 male) learned three categories of novel objects, where each object had unique, distinguishing features as well as features shared with other members of its category. We used a real-time EEG protocol to cue the reactivation of these objects during sleep at moments optimized to generate reactivation events. We found that reactivation improved memory for distinguishing features while worsening memory for shared features, suggesting a differentiation process. The results indicate that sleep reactivation does not act holistically on object memories, instead supporting a transformation where some features are enhanced over others.

Visual artificial grammar learning across 1 year in 7-year-olds and adults

Acquiring sequential information is of utmost importance, for example, for language acquisition in children. Yet, the long-term storage of statistical learning in children is poorly understood. To address this question, 27 7-year-olds and 28 young adults completed four sessions of visual sequence learning (Year 1). From this sample, 16 7-year-olds and 20 young adults participated in another four equivalent sessions after a 12-month-delay (Year 2). The first three sessions of each year used Stimulus Set 1, and the last session used Stimulus Set 2 to investigate transfer effects. Each session consisted of alternating learning and test phases in a modified artificial grammar learning task. In Year 1, 7-year-olds and adults learned the regularities and showed transfer to Stimulus Set 2. Both groups retained their final performance level over the 1-year period. In Year 2, children and adults continued to improve with Stimulus Set 1 but did not show additional transfer gains. Adults overall outperformed children, but transfer effects were indistinguishable between both groups. The current results suggest that long-term memory traces are formed from repeated sequence learning that can be used to generalize sequence rules to new visual input. However, the current study did not provide evidence for a childhood advantage in learning and remembering sequence rules.

J, Tandoc M, Antony J, Schapiro A. Memory reactivation during sleep does not act holistically on object memory

Memory reactivation during sleep is thought to facilitate memory consolidation. Most sleep reactivation research has examined how reactivation of specific facts, objects, and associations benefits their overall retention. However, our memories are not unitary, and not all features of a memory persist in tandem over time. Instead, our memories are transformed, with some features strengthened and others weakened. Does sleep reactivation drive memory transformation? We leveraged the Targeted Memory Reactivation technique in an object category learning paradigm to examine this question. Participants (20 female, 14 male) learned three categories of novel objects, where each object had unique, distinguishing features as well as features shared with other members of its category. We used a real-time EEG protocol to cue the reactivation of these objects during sleep at moments optimized to generate reactivation events. We found that reactivation improved memory for distinguishing features while worsening memory for shared features, suggesting a differentiation process. The results indicate that sleep reactivation does not act holistically on object memories, instead supporting a transformation process where some features are enhanced over others.

Memory reactivation in slow wave sleep enhances relational learning in humans

Sleep boosts the integration of memories, and can thus facilitate relational learning. This benefit may be due to memory reactivation during non-REM sleep. We set out to test this by explicitly cueing reactivation using a technique called targeted memory reactivation (TMR), in which sounds are paired with learned material in wake and then softly played during subsequent sleep, triggering reactivation of the associated memories. We specifically tested whether TMR in slow wave sleep leads to enhancements in inferential thinking in a transitive inference task. Because the Up-phase of the slow oscillation is more responsive to cues than the Down-phase, we also asked whether Up-phase stimulation is more beneficial for such integration. Our data show that TMR during the Up-Phase boosts the ability to make inferences, but only for the most distant inferential leaps. Up-phase stimulation was also associated with detectable memory reinstatement, whereas Down-phase stimulation led to below-chance performance the next morning. Detection of memory reinstatement after Up-state stimulation was negatively correlated with performance on the most difficult inferences the next morning. These findings demonstrate that cueing memory reactivation at specific time points in sleep can benefit difficult relational learning problems.

Overnight exposure to pink noise could jeopardize sleep-dependent insight and pattern detection

Accumulated evidence from the past decades suggests that sleep plays a crucial role in memory consolidation and the facilitation of higher-level cognitive processes such as abstraction and gist extraction. In addition, recent studies show that applying pink noise during sleep can further enhance sleep-dependent memory consolidation, potentially by modulating sleep physiology through stochastic resonance. However, whether this enhancement extends to higher cognitive processes remains untested. In this study, we investigated how the application of open-loop pink noise during sleep influences the gain of insight into hidden patterns. Seventy-two participants were assigned to three groups: daytime-wake, silent sleep, and sleep with pink noise. Each group completed the number reduction task, an established insight paradigm known to be influenced by sleep, over two sessions with a 12-h interval. Sleep groups were monitored by the DREEM 3 headband in home settings. Contrary to our prediction, pink noise did not induce an increase in insight compared to silent sleep and was statistically more similar to the wake condition despite evidence for its typical influence on sleep physiology. Particularly, we found that pink noise limited the time spent in the initial cycle of N1 just after sleep onset, while time spent in N1 positively predicted insight. These results echo recent suggestions that the time in the initial cycle of N1 plays a critical role in insight formation. Overall, our results suggest that open-loop pink noise during sleep may be detrimental to insight formation and creativity due to the alterations it causes to normal sleep architecture.

Individual differences in information processing during sleep and wake predict sleep-based memory consolidation of complex rules

Memory is critical for many cognitive functions, from remembering facts, to learning complex environmental rules. While memory encoding occurs during wake, memory consolidation is associated with sleep-related neural activity. Further, research suggests that individual differences in alpha frequency during wake (∼7 - 13 Hz) modulate memory processes, with higher individual alpha frequency (IAF) associated with greater memory performance. However, the relationship between wake-related EEG individual differences, such as IAF, and sleep-related neural correlates of memory consolidation has been largely unexplored, particularly in a complex rule-based memory context. Here, we aimed to investigate whether wake-derived IAF and sleep neurophysiology interact to influence rule learning in a sample of 35 healthy adults (16 males; mean age = 25.4, range: 18 - 40). Participants learned rules of a modified miniature language prior to either 8hrs of sleep or wake, after which they were tested on their knowledge of the rules in a grammaticality judgement task. Results indicate that sleep neurophysiology and wake-derived IAF do not interact but modulate memory for complex linguistic rules separately. Phase-amplitude coupling between slow oscillations and spindles during non-rapid eye-movement (NREM) sleep also promoted memory for rules that were analogous to the canonical English word order. As an exploratory analysis, we found that rapid eye-movement (REM) sleep theta power at posterior regions interacts with IAF to predict rule learning and proportion of time in REM sleep predicts rule learning differentially depending on grammatical rule type. Taken together, the current study provides behavioural and electrophysiological evidence for a complex role of NREM and REM sleep neurophysiology and wake-derived IAF in the consolidation of rule-based information.

Sleep-related benefits to transitive inference are modulated by encoding strength and joint rank

Transitive inference is a measure of relational learning that has been shown to improve across sleep. Here, we examine this phenomenon further by studying the impact of encoding strength and joint rank. In experiment 1, participants learned adjacent premise pairs and were then tested on inferential problems derived from those pairs. In line with prior work, we found improved transitive inference performance after retention across a night of sleep compared with wake alone. Experiment 2 extended these findings using a within-subject design and found superior transitive inference performance on a hierarchy, consolidated across 27 h including sleep compared with just 3 h of wake. In both experiments, consolidation-related improvement was enhanced when presleep learning (i.e., encoding strength) was stronger. We also explored the interaction of these effects with the joint rank effect, in which items were scored according to their rank in the hierarchy, with more dominant item pairs having the lowest scores. Interestingly, the consolidation-related benefit was greatest for more dominant inference pairs (i.e., those with low joint rank scores). Overall, our findings provide further support for the improvement of transitive inference across a consolidation period that includes sleep. We additionally show that encoding strength and joint rank strongly modulate this effect.

Rule Abstraction Is Facilitated by Auditory Cuing in REM Sleep

Sleep facilitates abstraction, but the exact mechanisms underpinning this are unknown. Here, we aimed to determine whether triggering reactivation in sleep could facilitate this process. We paired abstraction problems with sounds, then replayed these during either slow-wave sleep (SWS) or rapid eye movement (REM) sleep to trigger memory reactivation in 27 human participants (19 female). This revealed performance improvements on abstraction problems that were cued in REM, but not problems cued in SWS. Interestingly, the cue-related improvement was not significant until a follow-up retest 1 week after the manipulation, suggesting that REM may initiate a sequence of plasticity events that requires more time to be implemented. Furthermore, memory-linked trigger sounds evoked distinct neural responses in REM, but not SWS. Overall, our findings suggest that targeted memory reactivation in REM can facilitate visual rule abstraction, although this effect takes time to unfold.SIGNIFICANCE STATEMENT The ability to abstract rules from a corpus of experiences is a building block of human reasoning. Sleep is known to facilitate rule abstraction, but it remains unclear whether we can manipulate this process actively and which stage of sleep is most important. Targeted memory reactivation (TMR) is a technique that uses re-exposure to learning-related sensory cues during sleep to enhance memory consolidation. Here, we show that TMR, when applied during REM sleep, can facilitate the complex recombining of information needed for rule abstraction. Furthermore, we show that this qualitative REM-related benefit emerges over the course of a week after learning, suggesting that memory integration may require a slower form of plasticity.

Advantage conferred by overnight sleep on schema-related memory may last only a day

Study Objectives

Sleep contributes to declarative memory consolidation. Independently, schemas benefit memory. Here we investigated how sleep compared with active wake benefits schema consolidation 12 and 24 hours after initial learning.

Methods

Fifty-three adolescents (age: 15-19 years) randomly assigned into sleep and active wake groups participated in a schema-learning protocol based on transitive inference (i.e. If B > C and C > D then B > D). Participants were tested immediately after learning and following 12-, and 24-hour intervals of wake or sleep for both the adjacent (e.g. B-C, C-D; relational memory) and inference pairs: (e.g.: B-D, B-E, and C-E). Memory performance following the respective 12- and 24-hour intervals were analyzed using a mixed ANOVA with schema (schema, no-schema) as the within-participant factor, and condition (sleep, wake) as the between-participant factor.

Results

Twelve hours after learning, there were significant main effects of condition (sleep, wake) and schema, as well as a significant interaction, whereby schema-related memory was significantly better in the sleep condition compared to wake. Higher sleep spindle density was most consistently associated with greater overnight schema-related memory benefit. After 24 hours, the memory advantage of initial sleep was diminished.

Conclusions

Overnight sleep preferentially benefits schema-related memory consolidation following initial learning compared with active wake, but this advantage may be eroded after a subsequent night of sleep. This is possibly due to delayed consolidation that might occur during subsequent sleep opportunities in the wake group.

Clinical Trial Information

Name: Investigating Preferred Nap Schedules for Adolescents (NFS5) URL: https://clinicaltrials.gov/ct2/show/NCT04044885. Registration: NCT04044885.

No evidence for a preferential role of sleep in episodic memory abstraction

Substantial evidence suggests that sleep has a role in declarative memory consolidation. An influential notion holds that such sleep-related memory consolidation is associated with a process of abstraction. The neural underpinnings of this putative process are thought to involve a hippocampo-neocortical dialogue. Specifically, the idea is that, during sleep, the statistical contingencies across episodes are re-coded to a less hippocampus-dependent format, while at the same time losing configural information. Two previous studies from our lab, however, failed to show a preferential role of sleep in either episodic memory decontextualisation or the formation of abstract knowledge across episodic exemplars. Rather these processes occurred over sleep and wake time alike. Here, we present two experiments that replicate and extend these previous studies and exclude some alternative interpretations. The combined data show that sleep has no preferential function in this respect. Rather, hippocampus-dependent memories are generalised to an equal extent across both wake and sleep time. The one point on which sleep outperforms wake is actually the preservation of episodic detail of memories stored prior to sleep.

Contributions of memory and brain development to the bioregulation of naps and nap transitions in early childhood

The transition from multiple sleep bouts each day to a single overnight sleep bout (i.e., nap transition) is a universal process in human development. Naps are important during infancy and early childhood as they enhance learning through memory consolidation. However, a normal part of development is the transition out of naps. Understanding nap transitions is essential in order to maximize early learning and promote positive long-term cognitive outcomes. Here, we propose a novel hypothesis regarding the cognitive, physiological, and neural changes that accompany nap transitions. Specifically, we posit that maturation of the hippocampal-dependent memory network results in more efficient memory storage, which reduces the buildup of homeostatic sleep pressure across the cortex (as reflected by slow-wave activity), and eventually, contributes to nap transitions. This hypothesis synthesizes evidence of bioregulatory mechanisms underlying nap transitions and sheds new light on an important window of change in development. This framework can be used to evaluate multiple untested predictions from the field of sleep science and ultimately, yield science-based guidelines and policies regarding napping in childcare and early education settings.

A model of bi-directional interactions between complementary learning systems for memory consolidation of sequential experiences

The standard theory of memory consolidation posits a dual-store memory system: a fast-learning fast-decaying hippocampus that transfers memories to slow-learning long-term cortical storage. Hippocampal lesions interrupt this transfer, so recent memories are more likely to be lost than more remote memories. Existing models of memory consolidation that simulate this temporally graded retrograde amnesia operate only on static patterns or unitary variables as memories and study only one-way interaction from the hippocampus to the cortex. However, the mechanisms underlying the consolidation of episodes, which are sequential in nature and comprise multiple events, are not well-understood. The representation of learning for sequential experiences in the cortical-hippocampal network as a self-consistent dynamical system is not sufficiently addressed in prior models. Further, there is evidence for a bi-directional interaction between the two memory systems during offline periods, whereby the reactivation of waking neural patterns originating in the cortex triggers time-compressed sequential replays in the hippocampus, which in turn drive the consolidation of the pertinent sequence in the cortex. We have developed a computational model of memory encoding, consolidation, and recall for storing temporal sequences that explores the dynamics of this bi-directional interaction and time-compressed replays in four simulation experiments, providing novel insights into whether hippocampal learning needs to be suppressed for stable memory consolidation and into how new and old memories compete for limited replay opportunities during offline periods. The salience of experienced events, based on factors such as recency and frequency of use, is shown to have considerable impact on memory consolidation because it biases the relative probability that a particular event will be cued in the cortex during offline periods. In the presence of hippocampal learning during sleep, our model predicts that the fast-forgetting hippocampus can continually refresh the memory traces of a given episodic sequence if there are no competing experiences to be replayed.

Sleep Facilitates Extraction of Temporal Regularities With Varying Timescales

Evidence suggests that memory consolidation is facilitated by sleep, both through the strengthening of existing memories and by extracting regularities embedded in those memories. We previously observed that one sleep stage, Slow-Wave sleep (SWS), is particularly involved in the extraction of temporal regularities. We suggested that this attribute can naturally stem from the time-compressed memory replay known to occur in the hippocampus during SWS. A prediction coming out of this “temporal scaffolding” hypothesis is that sleep would be especially influential on extraction of temporal regularities when the time gap between the events constituting the regularities is shortish. In this study, we tested this prediction. Eighty-three participants performed a cognitive task in which hidden temporal regularities of varying time gaps were embedded. Detecting these regularities could significantly improve performance. Participants performed the task in two sessions with an interval filled with either wake or sleep in between. We found that sleep improved performance across all time gaps and that the longer the gap had been, the smaller was the improvement across both sleep and wake. No interaction between sleep and gap size was observed; however, unlike sleeping participants, awake participants did not exhibit any further performance improvement for the long gaps following the interval. In addition, across all participants, performance for the long gaps was associated with the development of conscious awareness to the regularities. We discuss these results in light of the temporal scaffolding hypothesis and suggest future directions to further elucidate the mechanisms involved.

Effects of Sleep on Language and Motor Consolidation: Evidence of Domain General and Specific Mechanisms

The current study explores the effects of time and sleep on the consolidation of a novel language learning task containing both item-specific knowledge and the extraction of grammatical regularities. We also compare consolidation effects in language and motor sequence learning tasks, to ask whether consolidation mechanisms are domain general. Young adults learned to apply plural inflections to novel words based on morphophonological rules embedded in the input, and learned to type a motor sequence using a keyboard. Participants were randomly assigned into one of two groups, practicing each task during either the morning or evening hours. Both groups were retested 12 and 24 hours post-training. Performance on frequent trained items in the language task stabilized only following sleep, consistent with a hippocampal mechanism for item-specific learning. However, regularity extraction, indicated by generalization to untrained items in the linguistic task, as well as performance on motor sequence learning, improved 24 hours post-training, irrespective of the timing of sleep. This consolidation process is consistent with a frontostriatal skill-learning mechanism, common across the language and motor domains. This conclusion is further reinforced by cross-domain correlations at the individual level between improvement across 24 hours in the motor task and in the low-frequency trained items in the linguistic task, which involve regularity extraction. Taken together, our results at the group and individual levels suggest that some aspects of consolidation are shared across the motor and language domains, and more specifically, between motor sequence learning and grammar learning.

Attitudinal Effects of Stimulus Co-occurrence and Stimulus Relations: Sleep Supports Propositional Learning Via Memory Consolidation

Adaptive behavior requires that organisms learn not only which stimuli tend to co-occur (e.g., whether stimulus A co-occurs with unpleasant stimulus B) but also how co-occurring stimuli are related (e.g., whether A starts or stops B). In a preregistered study ( N = 200 adults), we investigated whether sleep would promote adaptive evaluative choices requiring joint memories for stimulus co-occurrences and stimulus relations. Participants learned about hypothetical pharmaceutical products that either cause or prevent positive or negative health conditions, followed by measures of evaluative choices and explicit memory. After a 12-hr retention interval including either nocturnal sleep or daytime wake, participants completed the same measures a second time. Results showed that sleep strengthened the impact of causal product–condition relations on choices (revealed by multinomial modeling analyses) and enhanced memories for specific stimulus co-occurrences (revealed by memory preservation analyses). The findings suggest that sleep promotes adaptive evaluative choices via offline memory consolidation.

Memory decay distinguishes subtypes of gist

Memories are thought to become more gist-like over time. Multiple related memories might form generalized memory representations, losing specific details but enhancing or retaining gist. The time course within which gist memory emerges, however, is the subject of less consensus. To address this question, we focused our design on four kinds of gist: inferential gist (relations extracted across non-contiguous events), statistical learning (regularities extracted from a series), summary gist (a theme abstracted from a temporally contiguous series of items), and category gist (characterization of a stimulus at a higher level in the semantic hierarchy). Seventy participants completed memory encoding tasks addressing these types of gist and corresponding retrieval tasks the same evening, the morning after, and one week later, as well as an MRI at a later time point. We found little evidence that gist slowly emerges over time or that gist traces are more resistant to forgetting than detail traces. Instead, we found that initial gist memory shortly after encoding was either retained over time or decayed. Inferential gist and statistical learning were retained over a week, whereas memory for category and summary gist decayed. We discuss several interpretations for differences between these two subtypes of gist. Individual differences in REM or slow-wave sleep and hippocampal volumes did not predict changes in memory for these four kinds of gist in a healthy young adult population.

How do we generalize?

Humans and animals are able to generalize or transfer information from previous experience so that they can behave appropriately in novel situations. What mechanisms-computations, representations, and neural systems-give rise to this remarkable ability? The members of this Generative Adversarial Collaboration (GAC) come from a range of academic backgrounds but are all interested in uncovering the mechanisms of generalization. We started out this GAC with the aim of arbitrating between two alternative conceptual accounts: (1) generalization stems from integration of multiple experiences into summary representations that reflect generalized knowledge, and (2) generalization is computed on-the-fly using separately stored individual memories. Across the course of this collaboration, we found that-despite using different terminology and techniques, and although some of our specific papers may provide evidence one way or the other-we in fact largely agree that both of these broad accounts (as well as several others) are likely valid. We believe that future research and theoretical synthesis across multiple lines of research is necessary to help determine the degree to which different candidate generalization mechanisms may operate simultaneously, operate on different scales, or be employed under distinct conditions. Here, as the first step, we introduce some of these candidate mechanisms and we discuss the issues currently hindering better synthesis of generalization research. Finally, we introduce some of our own research questions that have arisen over the course of this GAC, that we believe would benefit from future collaborative efforts.

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

STUDY OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

A Daytime Nap Does Not Enhance the Retention of a First-Order or Second-Order Motor Sequence

This study examined the effects of a daytime nap on the retention of implicitly learnt “first-order conditional” (FOC) and “second-order conditional” (SOC) motor sequences. The implicit learning and retention of a motor sequence has been linked to the neural processes undertaken by the basal ganglia and primary motor cortex (i.e., procedural memory system). There is evidence, however, suggesting that SOC learning may further rely on the hippocampus-supported declarative memory system. Sleep appears to benefit the retention of information processed by the declarative memory system, but not the procedural memory system. Thus, it was hypothesized that sleep would benefit the retention of a SOC motor sequence but not a FOC sequence. The implicit learning and retention of these sequences was examined using the Serial Reaction Time Task. In this study, healthy adults implicitly learnt either a FOC (n = 20) or a SOC sequence (n = 20). Retention of both sequences was assessed following a daytime nap and period of wakefulness. Sleep was not found to improve the retention of the SOC sequence. There were no significant differences in the retention of a FOC or a SOC sequence following a nap or period of wakefulness. The study questions whether the declarative memory system is involved in the retention of implicitly learnt SOC sequences.

Does memory reactivation during sleep support generalization at the cost of memory specifics?

Sleep is important for memory, but does it favor consolidation of specific details or extraction of generalized information? Both may occur together when memories are reactivated during sleep, or a loss of certain memory details may facilitate generalization. To examine these issues, we tested memory in participants who viewed landscape paintings by six artists. Paintings were cropped to show only a section of the scene. During a learning phase, each painting section was presented with the artist's name and with a nonverbal sound that had been uniquely associated with that artist. In a test of memory for specifics, participants were shown arrays of six painting sections, all by the same artist. Participants attempted to select the one that was seen in the learning phase. Generalization was tested by asking participants to view new paintings and, for each one, decide which of the six artists created it. After this testing, participants had a 90-minute sleep opportunity with polysomnographic monitoring. When slow-wave sleep was detected, three of the sound cues associated with the artists were repeatedly presented without waking the participants. After sleep, participants were again tested for memory specifics and generalization. Memory reactivation during sleep due to the sound cues led to a relative decline in accuracy on the specifics test, which could indicate the transition to a loss of detail that facilitates generalization, particularly details such as the borders. Generalization performance showed very little change after sleep and was unaffected by the sound cues. Although results tentatively implicate sleep in memory transformation, further research is needed to examine memory change across longer time periods.

How do children with autism spectrum disorder form gist memory during sleep? A study of slow oscillation-spindle coupling

Sleep is assumed to support memory through an active systems consolidation process that does not only strengthen newly encoded representations but also facilitates the formation of more abstract gist memories. Studies in humans and rodents indicate a key role of the precise temporal coupling of sleep slow oscillations (SO) and spindles in this process. The present study aimed at bolstering these findings in typically developing (TD) children, and at dissecting particularities in SO-spindle coupling underlying signs of enhanced gist memory formation during sleep found in a foregoing study in children with autism spectrum disorder (ASD) without intellectual impairment. Sleep data from 19 boys with ASD and 20 TD boys (9-12 years) were analyzed. Children performed a picture-recognition task and the Deese-Roediger-McDermott (DRM) task before nocturnal sleep (encoding) and in the next morning (retrieval). Sleep-dependent benefits for visual-recognition memory were comparable between groups but were greater for gist abstraction (recall of DRM critical lure words) in ASD than TD children. Both groups showed a closely comparable SO-spindle coupling, with fast spindle activity nesting in SO-upstates, suggesting that a key mechanism of memory processing during sleep is fully functioning already at childhood. Picture-recognition at retrieval after sleep was positively correlated to frontocortical SO-fast-spindle coupling in TD children, and less in ASD children. Critical lure recall did not correlate with SO-spindle coupling in TD children but showed a negative correlation (r = -.64, p = .003) with parietal SO-fast-spindle coupling in ASD children, suggesting other mechanisms specifically conveying gist abstraction, that may even compete with SO-spindle coupling.

From incidental learning to explicit memory: The role of sleep after exposure to a serial reaction time task

This laboratory study explores whether sleep has different effects on explicit (recognition-based) and implicit (priming-based) memory. Eighty-nine healthy participants were randomly assigned to one of two experimental conditions: sleep or wake. All participants were previously exposed to an incidental learning session involving a 12-element deterministic second-order conditional sequence embedded in a serial reaction time task. The participants' explicit and implicit knowledge was assessed both immediately after the learning session (pretest) and after 12 h (posttest). For the sleep group, participants had a night of normal sleep between pretest and posttest, whereas the wake group spent 12 h awake during the day. The measures involved an explicit recognition test and an implicit priming reaction-time test with old fragments from a previously learned sequence and new fragments of a different control sequence. The sleep group showed statistically significant improvement between the pretest and the posttest in the explicit memory measure, whereas the wake group did not. In the implicit task, both groups improved similarly after a 12-h retention interval. These results suggest that throughout sleep, implicitly acquired information is processed offline to yield an explicit representation of knowledge incidentally acquired the night before.

Sleep Facilitates Problem Solving With No Additional Gain Through Targeted Memory Reactivation

According to the active systems consolidation theory, memories undergo reactivation during sleep that can give rise to qualitative changes of the representations. These changes may generate new knowledge such as gaining insight into solutions for problem solving. targeted memory reactivation (TMR) uses learning-associated cues, such as sounds or odors, which have been shown to improve memory consolidation when re-applied during sleep. Here we tested whether TMR during slow wave sleep (SWS) and/or rapid eye movement (REM) sleep increases problem solving. Young healthy volunteers participated in one of two experiments. Experiment 1 tested the effect of natural sleep on problem solving. Subjects were trained in a video game-based problem solving task until being presented with a non-solved challenge. Followed by a ~10-h incubation interval filled with nocturnal sleep or daytime wakefulness, subjects were tested on the problem solving challenge again. Experiment 2 tested the effect of TMR on problem solving, with subjects receiving auditory TMR either during SWS (SWSstim), REM sleep (REMstim), or wakefulness (Wakestim). In Experiment 1, sleep improved problem solving, with 62% of subjects from the Sleep group solving the problem compared to 24% of the Wake group. Subjects with higher amounts of SWS in the Sleep group had a higher chance to solve the problem. In Experiment 2, TMR did not change the sleep effect on problem solving: 56 and 58% of subjects from the SWSstim and REMstim groups solved the problem compared to 57% from the Wakestim group. These findings indicate that sleep, and particularly SWS, facilitates problem solving, whereas this effect is not further increased by TMR.

Sleep spindle activity correlates with implicit statistical learning consolidation in untreated obstructive sleep apnea patients

OBJECTIVE/BACKGROUND

The aim of this study was to examine the relationship between overnight consolidation of implicit statistical learning with spindle frequency EEG activity and slow frequency delta power during non-rapid eye movement (NREM) sleep in obstructive sleep apnea (OSA).

PATIENTS/METHODS

Forty-seven OSA participants completed the experiment. Prior to sleep, participants performed a reaction time cover task containing hidden patterns of pictures, about which participants were not informed. After the familiarisation phase, participants underwent overnight polysomnography. 24 h after the familiarisation phase, participants performed a test phase to assess their learning of the hidden patterns, expressed as a percentage of the number of correctly identified patterns. Spindle frequency activity (SFA) and delta power (0.5-4.5 Hz), were quantified from NREM electroencephalography. Associations between statistical learning and sleep EEG, and OSA severity measures were examined.

RESULTS

SFA in NREM sleep in frontal and central brain regions was positively correlated with statistical learning scores (r = 0.41 to 0.31, p = 0.006 to 0.044). In multiple regression, greater SFA and longer sleep onset latency were significant predictors of better statistical learning performance. Delta power and OSA severity were not significantly correlated with statistical learning.

CONCLUSIONS

These findings suggest spindle activity may serve as a marker of statistical learning capability in OSA. This work provides novel insight into how altered sleep physiology relates to consolidation of implicitly learnt information in patients with moderate to severe OSA.

The "implicit" serial reaction time task induces rapid and temporary adaptation rather than implicit motor learning

The serial reaction time task (SRTT) has been widely used to induce learning of a repeated motor sequence without the participants' awareness. The task has also been of major influence for defining current concepts of offline consolidation after motor learning. The present study intended to replicate previous findings in a larger population of 53 healthy individuals. We were unable to reproduce previous results of online and offline implicit motor learning with the SRTT. Trials with a repeated sequence rapidly induced shorter reaction times compared to random trials, but this improvement was lost in a post-test obtained a few minutes after the training block. Furthermore, no offline consolidation was observed as there was no change in sequence specific reaction time gain between the post-test immediately after training and a re-test obtained 8 h after training. Online or offline learning remained absent when we modulated the number of sequence repetitions, the error levels, and the structure of random sequences. We conclude that the SRTT induces a rapid and temporary adaptation to the sequence rather than learning, since the repeated motor sequence does not seem to be encoded in memory.

How robust are sleep-mediated memory benefits?

Memories benefit from a retention interval filled with sleep. Current theories assume that this beneficial effect relies on consolidation processes occurring during slow-wave sleep (SWS). However, in the last years, several key findings supporting these theories could not be replicated or occurred only under certain conditions, suggesting that effects of sleep on memory are smaller, more task-dependent, less SWS-related, less robust and less long-lasting than previously assumed. In this review, we summarize recent replication failures, null-findings, meta-analyses and studies reporting important boundary conditions for the effect of sleep on declarative memory. We argue that more attempts to replicate and meta-analytic approaches together with higher standards for reproducible science are critical to advance the field of sleep and memory.

How to optimize knowledge construction in the brain

Well-structured knowledge allows us to quickly understand the world around us and make informed decisions to adequately control behavior. Knowledge structures, or schemas, are presumed to aid memory encoding and consolidation of new experiences so we cannot only remember the past, but also guide behavior in the present and predict the future. However, very strong schemas can also lead to unwanted side effects such as false memories and misconceptions. To overcome this overreliance on a schema, we should aim to create robust schemas that are on the one hand strong enough to help to remember and predict, but also malleable enough to avoid such undesirable side effects. This raises the question as to whether there are ways to deliberately influence knowledge construction processes, with the goal to reach such optimally balanced schemas. Here, we will discuss how the mnemonic processes in our brains build long-term knowledge and, more specifically, how different phases of memory formation (encoding, consolidation, retrieval, and reconsolidation) contribute to this schema build-up. We finally provide ways how to best keep a balance between generalized semantic and detailed episodic memories, which can prove very useful in, e.g., educational settings.

Ill-Defined Problem Solving Does Not Benefit From Daytime Napping

The main goal of the present study was to explore the role of sleep in the process of ill-defined problem solving. The results of previous studies indicate that various cognitive processes are largely dependent on the quality and quantity of sleep. However, while sleep-related memory consolidation seems to be well-grounded, with regard to the impact of sleep on problem solving, existing research yields mixed and rather inconclusive results. Moreover, this effect has been mainly tested using simple and well-defined, common laboratory problems, such as the remote associate test (RAT), crossword and anagram puzzles, numeric and logic problems, etc. What is lacking is research on the effect of sleep on solving more complex and more real-life oriented ill-defined problems. In the present study, we hypothesized that sleep can improve performance in solving this kind of problems. The study involved 40 participants, randomly assigned to two experimental conditions: sleep group and waking group. The experimental protocol comprised three stages: problem presentation, retention interval, and testing stage. The problem was presented to the participants in the form of an interactive computer game concerning a complex, elaborate crime story. During the retention interval, the participants—depending on the condition—took a nap or stayed awake; sleeping participants underwent polysomnography recording, while waking participants performed activities not related to the experimental problem. In the testing stage, participants tried to solve the presented problem. The solutions generated were assessed both for quality (reasonableness, consistency, and story recall) and creativity (fluency, flexibility, originality, and elaboration). Contrary to expectations, we found no effect of sleep on ill-defined problem solving. Neither quality nor creativity of the solutions generated by the participants was higher in the nap group than in the waking group. There were also no performance improvements with regard to any sleep stage or incidence of dreams. Our study adds to a growing body of evidence that sleep probably might provide an incubation gap, but not a facilitating environment serving the purpose of problem solving, at least with regard to ill-defined problems.

Prior Knowledge Predicts Early Consolidation in Second Language Learning

Language learning occurs in distinct phases. Whereas some improvement is evident during training, offline memory consolidation processes that take place after the end of training play an important role in learning of linguistic information. The timing of offline consolidation is thought to depend on the type of task, with generalization of implicit knowledge suggested to take more time and sleep to consolidate. The current study aims to investigate individual differences in the timing of consolidation following learning of morphological inflections in a novel language in typical adults. Participants learned to make plural inflections in an artificial language, where inflection was based on morpho-phonological regularities. Participants were trained in the evening, and consolidation was measured after two intervals: 12 h (one night) and 36 h (two nights) post training. We measured both inflection of trained items, which may rely on item-specific learning, and generalization to new untrained items, which requires extraction of morpho-phonological regularities. The results for both trained and un-trained items showed two patterns of consolidation: early versus late, that is while some participants improved during the first night, others, who deteriorated in performance during the first night, improved in the later consolidation interval. Importantly, phonological awareness in L1 predicted early consolidation for trained items. Furthermore, there was no association between participants' consolidation trajectory in trained and untrained items. Our results suggest that consolidation timing depends on the interaction between task characteristics and individual abilities. Moreover, the results show that prior meta-linguistic knowledge predicts the quality of early consolidation processes. These results are consistent with studies in rodents and humans, showing that prior knowledge accelerates consolidation of newly learnt episodic memory. Finally, the rate of consolidation across exposures to the language might explain some of the variability found in the attained level of second language proficiency.