Overnight consolidation aids the transfer of statistical knowledge from the medial temporal lobe to the striatum

Consolidation Enhances Sequential Multistep Anticipation but Diminishes Access to Perceptual Features

Many experiences unfold predictably over time. Memory for these temporal regularities enables anticipation of events multiple steps into the future. Because temporally predictable events repeat over days, weeks, and years, we must maintain-and potentially transform-memories of temporal structure to support adaptive behavior. We explored how individuals build durable models of temporal regularities to guide multistep anticipation. Healthy young adults (Experiment 1: N = 99, age range = 18-40 years; Experiment 2: N = 204, age range = 19-40 years) learned sequences of scene images that were predictable at the category level and contained incidental perceptual details. Individuals then anticipated upcoming scene categories multiple steps into the future, immediately and at a delay. Consolidation increased the efficiency of anticipation, particularly for events further in the future, but diminished access to perceptual features. Further, maintaining a link-based model of the sequence after consolidation improved anticipation accuracy. Consolidation may therefore promote efficient and durable models of temporal structure, thus facilitating anticipation of future events.

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.

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.

Failure to consolidate statistical learning in developmental dyslexia

Statistical learning (SL), the ability to pick up patterns in sensory input, serves as one of the building blocks of language acquisition. Although SL has been studied extensively in developmental dyslexia (DD), much less is known about the way SL evolves over time. The handful of studies examining this question were all limited to the acquisition of motor sequential knowledge or highly learned segmented linguistic units. Here we examined memory consolidation of statistical regularities in adults with DD and typically developed (TD) readers by using auditory SL requiring the segmentation of units from continuous input, which represents one of the earliest learning challenges in language acquisition. DD and TD groups were exposed to tones in a probabilistically determined sequential structure varying in difficulty and subsequently tested for recognition of novel short sequences that adhered to this statistical pattern in immediate and delayed-recall sessions separated by a night of sleep. SL performance of the DD group at the easy and hard difficulty levels was poorer than that of the TD group in the immediate-recall session. Importantly, DD participants showed a significant overnight deterioration in SL performance at the medium difficulty level compared to TD, who instead showed overnight stabilization of the learned information. These findings imply that SL difficulties in DD may arise not only from impaired initial learning but also due to a failure to consolidate statistically structured information into long-term memory. We hypothesize that these deficits disrupt the typical course of language acquisition in those with DD.

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.

A failure of sleep-dependent consolidation of visuoperceptual procedural learning in young adults with ADHD

ADHD has been associated with cortico-striatal dysfunction that may lead to procedural memory abnormalities. Sleep plays a critical role in consolidating procedural memories, and sleep problems are an integral part of the psychopathology of ADHD. This raises the possibility that altered sleep processes characterizing those with ADHD could contribute to their skill-learning impairments. On this basis, the present study tested the hypothesis that young adults with ADHD have altered sleep-dependent procedural memory consolidation. Participants with ADHD and neurotypicals were trained on a visual discrimination task that has been shown to benefit from sleep. Half of the participants were tested after a 12-h break that included nocturnal sleep (sleep condition), whereas the other half were tested after a 12-h daytime break that did not include sleep (wakefulness condition) to assess the specific contribution of sleep to improvement in task performance. Despite having a similar degree of initial learning, participants with ADHD did not improve in the visual discrimination task following a sleep interval compared to neurotypicals, while they were on par with neurotypicals during the wakefulness condition. These findings represent the first demonstration of a failure in sleep-dependent consolidation of procedural learning in young adults with ADHD. Such a failure is likely to disrupt automatic control routines that are normally provided by the non-declarative memory system, thereby increasing the load on attentional resources of individuals with ADHD.

What to expect where and when: how statistical learning drives visual selection

While the visual environment contains massive amounts of information, we should not and cannot pay attention to all events. Instead, we need to direct attention to those events that have proven to be important in the past and suppress those that were distracting and irrelevant. Experiences molded through a learning process enable us to extract and adapt to the statistical regularities in the world. While previous studies have shown that visual statistical learning (VSL) is critical for representing higher order units of perception, here we review the role of VSL in attentional selection. Evidence suggests that through VSL, attentional priority settings are optimally adjusted to regularities in the environment, without intention and without conscious awareness.

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.

Musical instrument familiarity affects statistical learning of tone sequences

Most listeners have an implicit understanding of the rules that govern how music unfolds over time. This knowledge is acquired in part through statistical learning, a robust learning mechanism that allows individuals to extract regularities from the environment. However, it is presently unclear how this prior musical knowledge might facilitate or interfere with the learning of novel tone sequences that do not conform to familiar musical rules. In the present experiment, participants listened to novel, statistically structured tone sequences composed of pitch intervals not typically found in Western music. Between participants, the tone sequences either had the timbre of artificial, computerized instruments or familiar instruments (piano or violin). Knowledge of the statistical regularities was measured as by a two-alternative forced choice recognition task, requiring discrimination between novel sequences that followed versus violated the statistical structure, assessed at three time points (immediately post-training, as well as one day and one week post-training). Compared to artificial instruments, training on familiar instruments resulted in reduced accuracy. Moreover, sequences from familiar instruments - but not artificial instruments - were more likely to be judged as grammatical when they contained intervals that approximated those commonly used in Western music, even though this cue was non-informative. Overall, these results demonstrate that instrument familiarity can interfere with the learning of novel statistical regularities, presumably through biasing memory representations to be aligned with Western musical structures. These results demonstrate that real-world experience influences statistical learning in a non-linguistic domain, supporting the view that statistical learning involves the continuous updating of existing representations, rather than the establishment of entirely novel ones.

Neural processes underlying statistical learning for speech segmentation in dogs

To learn words, humans extract statistical regularities from speech. Multiple species use statistical learning also to process speech, but the neural underpinnings of speech segmentation in non-humans remain largely unknown. Here, we investigated computational and neural markers of speech segmentation in dogs, a phylogenetically distant mammal that efficiently navigates humans' social and linguistic environment. Using electroencephalography (EEG), we compared event-related responses (ERPs) for artificial words previously presented in a continuous speech stream with different distributional statistics. Results revealed an early effect (220-470 ms) of transitional probability and a late component (590-790 ms) modulated by both word frequency and transitional probability. Using fMRI, we searched for brain regions sensitive to statistical regularities in speech. Structured speech elicited lower activity in the basal ganglia, a region involved in sequence learning, and repetition enhancement in the auditory cortex. Speech segmentation in dogs, similar to that of humans, involves complex computations, engaging both domain-general and modality-specific brain areas. VIDEO ABSTRACT.

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.

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.

Artificial grammar learning is facilitated by distributed practice: Evidence from a letter reordering task

Previous studies have shown that distributed practice-a training strategy that is known to facilitate memory-is likely to result in greater learning than massed practice. This effect has been demonstrated largely in explicit tasks. The purpose of this study was to test whether statistical learning of artificial grammar is affected by the lag between learning sessions overall, and by high and low complexity stimuli (as measure by chunk strength). Two groups (spaced-short and spaced-long) learned strings of letters created according to a set of rules and were required to produce new strings using given letter sets. For the spaced-short group, the two learning sessions, each including training and a test phase, took place sequentially with a 10-min break, whereas for the spaced-long group, learning sessions were distributed across two days (1-day lag). Overall results showed improved performance following spaced-long practice compared to spaced-short practice. The results also indicated that in the low chunk strength strings (indicating high complexity), both groups demonstrated similar improvement from first to second testing, while in the high chunk strength strings (indicating low complexity), improvement in letter reordering performance was significantly higher when the learning sessions were distributed across two days. This pattern of findings suggests that stimuli complexity affects the extent to which distributed practice enhance artificial grammar learning.

Memory consolidation as an adaptive process

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

Sounding It Out: Auditory Stimulation and Overnight Memory Processing

Purpose of Review

Auditory stimulation is a technique that can enhance neural oscillations linked to overnight memory consolidation. In this review, we evaluate the impacts of auditory stimulation on the neural oscillations of sleep and associated memory processes in a variety of populations.

Recent Findings

Cortical EEG recordings of slow-wave sleep (SWS) are characterised by two cardinal oscillations: slow oscillations (SOs) and sleep spindles. Auditory stimulation delivered in SWS enhances SOs and phase-coupled spindle activity in healthy children and adults, children with ADHD, adults with mild cognitive impairment and patients with major depression. Under certain conditions, auditory stimulation bolsters the benefits of SWS for memory consolidation, although further work is required to fully understand the factors affecting stimulation-related memory gains. Recent work has turned to rapid eye movement (REM) sleep, demonstrating that auditory stimulation can be used to manipulate REM sleep theta oscillations.

Summary

Auditory stimulation enhances oscillations linked to overnight memory processing and shows promise as a technique for enhancing the memory benefits of sleep.

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.

Sleep’s Role in Schema Learning and Creative Insights

Purpose of Review

A recent resurgence of interest in schema theory has influenced research on sleep-dependent memory consolidation and led to a new understanding of how schemata might be activated during sleep and play a role in the reorganisation of memories. This review is aimed at synthesising recent findings into a coherent narrative and draw overall conclusions.

Recent Findings

Rapid consolidation of schematic memories has been shown to benefit from an interval containing sleep. These memories have shown reduced reliance on the hippocampus following consolidation in both humans and rodents. Using a variety of methodologies, notably including the DRM paradigm, it has been shown that activation of a schema can increase the rate of false memory as a result of activation of semantic associates during slow wave sleep (SWS). Memories making use of a schema have shown increased activity in the medial prefrontal cortex, which may reflect both the schematic activation itself and a cognitive control component selecting an appropriate schema to use. SWS seems to be involved in assimilation of new memories within existing semantic frameworks and in making memories more explicit, while REM sleep may be more associated with creating entirely novel associations while keeping memories implicit.

Summary

Sleep plays an important role in schematic memory consolidation, with more rapid consolidation, reduced hippocampal involvement, and increased prefrontal involvement as the key characteristics. Both SWS and REM sleep may have a role to play.

Divided attention does not affect the acquisition and consolidation of transitional probabilities

Statistical learning facilitates the efficient processing and prediction of environmental events and contributes to the acquisition of automatic behaviors. Whereas a minimal level of attention seems to be required for learning to occur, it is still unclear how acquisition and consolidation of statistical knowledge are affected when attention is divided during learning. To test the effect of divided attention on statistical learning and consolidation, ninety-six healthy young adults performed the Alternating Serial Reaction Time task in which they incidentally acquired second-order transitional probabilities. Half of the participants completed the task with a concurrent secondary intentional sequence learning task that was applied to the same stimulus stream. The other half of the participants performed the task without any attention manipulation. Performance was retested after a 12-h post-learning offline period. Half of each group slept during the delay, while the other half had normal daily activity, enabling us to test the effect of delay activity (sleep vs. wake) on the consolidation of statistical knowledge. Divided attention had no effect on statistical learning: The acquisition of second-order transitional probabilities was comparable with and without the secondary task. Consolidation was neither affected by divided attention: Statistical knowledge was similarly retained over the 12-h delay, irrespective of the delay activity. Our findings can contribute to a better understanding of the role of attentional processes in and the robustness of visuomotor statistical learning and consolidation.

The Neurocognition of Developmental Disorders of Language

Developmental disorders of language include developmental language disorder, dyslexia, and motor-speech disorders such as articulation disorder and stuttering. These disorders have generally been explained by accounts that focus on their behavioral rather than neural characteristics; their processing rather than learning impairments; and each disorder separately rather than together, despite their commonalities and comorbidities. Here we update and review a unifying neurocognitive account—the Procedural circuit Deficit Hypothesis (PDH). The PDH posits that abnormalities of brain structures underlying procedural memory (learning and memory that rely on the basal ganglia and associated circuitry) can explain numerous brain and behavioral characteristics across learning and processing, in multiple disorders, including both commonalities and differences. We describe procedural memory, examine its role in various aspects of language, and then present the PDH and relevant evidence across language-related disorders. The PDH has substantial explanatory power, and both basic research and translational implications.

Competitive and cooperative interactions between medial temporal and striatal learning systems

The striatum and medial temporal lobes (MTL) exhibit dissociable roles during learning. Whereas the striatum and its network of thalamic relays and cortical nodes are necessary for nondeclarative learning, the MTL and associated network are required for declarative learning. Several studies have suggested that these networks are functionally competitive during learning. Since these discoveries, however, evidence has accumulated that they can operate in a cooperative fashion. In this review, we discuss evidence for both competition and cooperation between these systems during learning, with the aim of reconciling these seemingly contradictory findings. Examples of cooperation between the striatum and MTL have been provided, especially during consolidation and generalization of knowledge, and do not appear to be precluded by differences in functional specialization. However, whether these systems cooperate or compete does seem to depend on the phase of learning and cognitive or motor aspects of the task. The involvement of other regions, such as midbrain dopaminergic nuclei and the prefrontal cortex, may promote and mediate cooperation between the striatum and the MTL during learning. Building on this body of research, we propose a model for striatum-MTL interactions in learning and memory and attempt to predict, in general terms, when cooperation or competition will occur.

Investigating the formation and consolidation of incidentally learned trust

People make inferences about the trustworthiness of others based on their observed gaze behavior. Faces that consistently look toward a target location are rated as more trustworthy than those that look away from the target. Representations of trust are important for future interactions; yet little is known about how they are consolidated in long-term memory. Sleep facilitates memory consolidation for incidentally learned information and may therefore support the retention of trust representations. We investigated the consolidation of trust inferences across periods of sleep or wakefulness. In addition, we employed a memory cueing procedure (targeted memory reactivation [TMR]) in a bid to strengthen certain trust memories over others. We observed no difference in the retention of trust inferences following delays of sleep or wakefulness, and there was no effect of TMR in either condition. Interestingly, trust inferences remained stable 1 week after learning, irrespective of the initial postlearning delay. A second experiment showed that this implicit learning occurs despite participants’ being unable to explicitly recall the gaze behavior of specific faces immediately after encoding. Together, these results suggest that gist-like, social inferences are formed at the time of learning without retaining the original episodic memory and thus do not benefit from offline consolidation through replay. We discuss our findings in the context of a novel framework whereby trust judgments reflect an efficient, powerful, and adaptable storage device for social information.

What we learned from creating one of the world's most popular MOOCs

Learning How to Learn (LHTL) is currently one of the world's most popular massive open online course (MOOC), with nearly 2.5 million registered learners in its first 4 years. Here, we "reverse engineer" the design of the course's videos to show how creative application of well-known principles of multimedia learning in an MOOC context appear to have fueled the course's popularity. Gaps in knowledge of multimedia learning are also noted. There have been some 50 years of experience researching effective classroom teaching, but less there have been only 5 years since MOOCs became widespread. The success of LHTL may provide further insight into the importance of the principles of multimedia learning, and how those principles might be practically implemented to improve MOOC making and the general design of instructional videos.

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

As part of its role in memory consolidation, sleep has been repeatedly identified as critical for the extraction of regularities from wake experiences. However, many null results have been published as well, with no clear consensus emerging regarding the conditions that yield this sleep effect. Here, we systematically review the role of sleep in the extraction of hidden regularities, specifically those involving associative relations embedded in newly learned information. We found that the specific behavioral task used in a study had far more impact on whether a sleep effect was discovered than either the category of the cognitive processes targeted, or the particular experimental design employed. One emerging pattern, however, was that the explicit detection of hidden rules is more likely to happen when the rules are of a temporal nature (i.e., event A at time t predicts a later event B) than when they are non-temporal. We discuss this temporal rule sensitivity in reference to the compressed memory replay occurring in the hippocampus during slow-wave-sleep, and compare this effect to what happens when the extraction of regularities depends on prior knowledge and relies on structures other than the hippocampus.

How Memory Replay in Sleep Boosts Creative Problem-Solving

Creative thought relies on the reorganisation of existing knowledge. Sleep is known to be important for creative thinking, but there is a debate about which sleep stage is most relevant, and why. We address this issue by proposing that rapid eye movement sleep, or 'REM', and non-REM sleep facilitate creativity in different ways. Memory replay mechanisms in non-REM can abstract rules from corpuses of learned information, while replay in REM may promote novel associations. We propose that the iterative interleaving of REM and non-REM across a night boosts the formation of complex knowledge frameworks, and allows these frameworks to be restructured, thus facilitating creative thought. We outline a hypothetical computational model which will allow explicit testing of these hypotheses.

Transcranial Current Stimulation During Sleep Facilitates Insight into Temporal Rules, but does not Consolidate Memories of Individual Sequential Experiences

Slow-wave sleep (SWS) is known to contribute to memory consolidation, likely through the reactivation of previously encoded waking experiences. Contemporary studies demonstrate that when auditory or olfactory stimulation is administered during memory encoding and then reapplied during SWS, memory consolidation can be enhanced, an effect that is believed to rely on targeted memory reactivation (TMR) induced by the sensory stimulation. Here, we show that transcranial current stimulations (tCS) during sleep can also be used to induce TMR, resulting in the facilitation of high-level cognitive processes. Participants were exposed to repeating sequences in a realistic 3D immersive environment while being stimulated with particular tCS patterns. A subset of these tCS patterns was then reapplied during sleep stages N2 and SWS coupled to slow oscillations in a closed-loop manner. We found that in contrast to our initial hypothesis, performance for the sequences corresponding to the reapplied tCS patterns was no better than for other sequences that received stimulations only during wake or not at all. In contrast, we found that the more stimulations participants received overnight, the more likely they were to detect temporal regularities governing the learned sequences the following morning, with tCS-induced beta power modulations during sleep mediating this effect.

Deconstructing Procedural Memory: Different Learning Trajectories and Consolidation of Sequence and Statistical Learning

Procedural learning is a fundamental cognitive function that facilitates efficient processing of and automatic responses to complex environmental stimuli. Here, we examined training-dependent and off-line changes of two sub-processes of procedural learning: namely, sequence learning and statistical learning. Whereas sequence learning requires the acquisition of order-based relationships between the elements of a sequence, statistical learning is based on the acquisition of probabilistic associations between elements. Seventy-eight healthy young adults (58 females and 20 males) completed the modified version of the Alternating Serial Reaction Time task that was designed to measure Sequence and Statistical Learning simultaneously. After training, participants were randomly assigned to one of three conditions: active wakefulness, quiet rest, or daytime sleep. We examined off-line changes in Sequence and Statistical Learning as well as further improvements after extended practice. Performance in Sequence Learning increased during training, while Statistical Learning plateaued relatively rapidly. After the off-line period, both the acquired sequence and statistical knowledge was preserved, irrespective of the vigilance state (awake, quiet rest or sleep). Sequence Learning further improved during extended practice, while Statistical Learning did not. Moreover, within the sleep group, cortical oscillations and sleep spindle parameters showed differential associations with Sequence and Statistical Learning. Our findings can contribute to a deeper understanding of the dynamic changes of multiple parallel learning and consolidation processes that occur during procedural memory formation.

Visual statistical learning deficits in memory-impaired individuals

Visual statistical learning (VSL) refers to the learning of environmental regularities. Classically considered an implicit process, one patient with isolated hippocampal damage is severely impaired at VSL tasks, suggesting involvement of explicit memory. Here, we asked whether memory impairment (MI) alone, absent of clear hippocampal pathology, predicted deficits across different VSL tasks. A classic VSL task revealed no learning in MI participants (Exp. 1), while imposing attentional demands (Exp. 2: flicker detection, Exp. 3: gender/location categorization) during familiarization revealed modest residual VSL. MI with nonspecific neural correlates predicted impaired VSL overall, but attentional processes may be harnessed for rehabilitation.

Spared and impaired sleep-dependent memory consolidation in schizophrenia

OBJECTIVE

Cognitive deficits in schizophrenia are the strongest predictor of disability and effective treatment is lacking. This reflects our limited mechanistic understanding and consequent lack of treatment targets. In schizophrenia, impaired sleep-dependent memory consolidation correlates with reduced sleep spindle activity, suggesting sleep spindles as a potentially treatable mechanism. In the present study we investigated whether sleep-dependent memory consolidation deficits in schizophrenia are selective.

METHODS

Schizophrenia patients and healthy individuals performed three tasks that have been shown to undergo sleep-dependent consolidation: the Word Pair Task (verbal declarative memory), the Visual Discrimination Task (visuoperceptual procedural memory), and the Tone Task (statistical learning). Memory consolidation was tested 24 h later, after a night of sleep.

RESULTS

Compared with controls, schizophrenia patients showed reduced overnight consolidation of word pair learning. In contrast, both groups showed similar significant overnight consolidation of visuoperceptual procedural memory. Neither group showed overnight consolidation of statistical learning.

CONCLUSION

The present findings extend the known deficits in sleep-dependent memory consolidation in schizophrenia to verbal declarative memory, a core, disabling cognitive deficit. In contrast, visuoperceptual procedural memory was spared. These findings support the hypothesis that sleep-dependent memory consolidation deficits in schizophrenia are selective, possibly limited to tasks that rely on spindles. These findings reinforce the importance of deficient sleep-dependent memory consolidation among the cognitive deficits of schizophrenia and suggest sleep physiology as a potentially treatable mechanism.

Neurophysiological Markers of Statistical Learning in Music and Language: Hierarchy, Entropy, and Uncertainty

Statistical learning (SL) is a method of learning based on the transitional probabilities embedded in sequential phenomena such as music and language. It has been considered an implicit and domain-general mechanism that is innate in the human brain and that functions independently of intention to learn and awareness of what has been learned. SL is an interdisciplinary notion that incorporates information technology, artificial intelligence, musicology, and linguistics, as well as psychology and neuroscience. A body of recent study has suggested that SL can be reflected in neurophysiological responses based on the framework of information theory. This paper reviews a range of work on SL in adults and children that suggests overlapping and independent neural correlations in music and language, and that indicates disability of SL. Furthermore, this article discusses the relationships between the order of transitional probabilities (TPs) (i.e., hierarchy of local statistics) and entropy (i.e., global statistics) regarding SL strategies in human's brains; claims importance of information-theoretical approaches to understand domain-general, higher-order, and global SL covering both real-world music and language; and proposes promising approaches for the application of therapy and pedagogy from various perspectives of psychology, neuroscience, computational studies, musicology, and linguistics.

Mechanisms of Memory Retrieval in Slow-Wave Sleep

Study Objectives

Memories are strengthened during sleep. The benefits of sleep for memory can be enhanced by re-exposing the sleeping brain to auditory cues; a technique known as targeted memory reactivation (TMR). Prior studies have not assessed the nature of the retrieval mechanisms underpinning TMR: the matching process between auditory stimuli encountered during sleep and previously encoded memories. We carried out two experiments to address this issue.

Methods

In Experiment 1, participants associated words with verbal and nonverbal auditory stimuli before an overnight interval in which subsets of these stimuli were replayed in slow-wave sleep. We repeated this paradigm in Experiment 2 with the single difference that the gender of the verbal auditory stimuli was switched between learning and sleep.

Results

In Experiment 1, forgetting of cued (vs. noncued) associations was reduced by TMR with verbal and nonverbal cues to similar extents. In Experiment 2, TMR with identical nonverbal cues reduced forgetting of cued (vs. noncued) associations, replicating Experiment 1. However, TMR with nonidentical verbal cues reduced forgetting of both cued and noncued associations.

Conclusions

These experiments suggest that the memory effects of TMR are influenced by the acoustic overlap between stimuli delivered at training and sleep. Our findings hint at the existence of two processing routes for memory retrieval during sleep. Whereas TMR with acoustically identical cues may reactivate individual associations via simple episodic matching, TMR with nonidentical verbal cues may utilize linguistic decoding mechanisms, resulting in widespread reactivation across a broad category of memories.

Reading and the Neurocognitive Bases of Statistical Learning1

The processes underlying word reading are shaped by statistical properties of the writing system. According to some theoretical perspectives (e.g. Harm & Seidenberg, 2004) reading acquisition should be understood as an exercise in statistical learning. Statistical learning (SL) involves the extraction of organizing principles from a set of inputs. Several lines of research provide convergent evidence supporting the connection between SL and reading acquisition (e.g., Arciuli & Simpson, 2012; Frost et al., 2014; Bogaerts et al., 2015). An obstacle to fully appreciating the theoretical and educational implications of these findings is that SL is itself not well understood. In this paper, we review the current literature on SL with a particular focus on organizing this literature by grounding it in theories of learning and memory more generally. This approach can clarify the nature of SL and provide a framework for understanding its role in reading, reading acquisition, and reading disorders.

Identification of memory reactivation during sleep by EEG classification

Memory reactivation during sleep is critical for consolidation, but also extremely difficult to measure as it is subtle, distributed and temporally unpredictable. This article reports a novel method for detecting such reactivation in standard sleep recordings. During learning, participants produced a complex sequence of finger presses, with each finger cued by a distinct audio-visual stimulus. Auditory cues were then re-played during subsequent sleep to trigger neural reactivation through a method known as targeted memory reactivation (TMR). Next, we used electroencephalography data from the learning session to train a machine learning classifier, and then applied this classifier to sleep data to determine how successfully each tone had elicited memory reactivation. Neural reactivation was classified above chance in all participants when TMR was applied in SWS, and in 5 of the 14 participants to whom TMR was applied in N2. Classification success reduced across numerous repetitions of the tone cue, suggesting either a gradually reducing responsiveness to such cues or a plasticity-related change in the neural signature as a result of cueing. We believe this method will be valuable for future investigations of memory consolidation.

Lack of Cross-Modal Effects in Dual-Modality Implicit Statistical Learning

A current controversy in the area of implicit statistical learning (ISL) is whether this process consists of a single, central mechanism or multiple modality-specific ones. To provide insight into this question, the current study involved three ISL experiments to explore whether multimodal input sources are processed separately in each modality or are integrated together across modalities. In Experiment 1, visual and auditory ISL were measured under unimodal conditions, with the results providing a baseline level of learning for subsequent experiments. Visual and auditory sequences were presented separately, and the underlying grammar used for both modalities was the same. In Experiment 2, visual and auditory sequences were presented simultaneously with each modality using the same artificial grammar to investigate whether redundant multisensory information would result in a facilitative effect (i.e., increased learning) compared to the baseline. In Experiment 3, visual and auditory sequences were again presented simultaneously but this time with each modality employing different artificial grammars to investigate whether an interference effect (i.e., decreased learning) would be observed compared to the baseline. Results showed that there was neither a facilitative learning effect in Experiment 2 nor an interference effect in Experiment 3. These findings suggest that participants were able to track simultaneously and independently two sets of sequential regularities under dual-modality conditions. These findings are consistent with the theories that posit the existence of multiple, modality-specific ISL mechanisms rather than a single central one.

Sleep Does Not Promote Solving Classical Insight Problems and Magic Tricks

During creative problem solving, initial solution attempts often fail because of self-imposed constraints that prevent us from thinking out of the box. In order to solve a problem successfully, the problem representation has to be restructured by combining elements of available knowledge in novel and creative ways. It has been suggested that sleep supports the reorganization of memory representations, ultimately aiding problem solving. In this study, we systematically tested the effect of sleep and time on problem solving, using classical insight tasks and magic tricks. Solving these tasks explicitly requires a restructuring of the problem representation and may be accompanied by a subjective feeling of insight. In two sessions, 77 participants had to solve classical insight problems and magic tricks. The two sessions either occurred consecutively or were spaced 3 h apart, with the time in between spent either sleeping or awake. We found that sleep affected neither general solution rates nor the number of solutions accompanied by sudden subjective insight. Our study thus adds to accumulating evidence that sleep does not provide an environment that facilitates the qualitative restructuring of memory representations and enables problem solving.

Sleep-Dependent Memory Consolidation and Incremental Sentence Comprehension: Computational Dependencies during Language Learning as Revealed by Neuronal Oscillations

We hypothesize a beneficial influence of sleep on the consolidation of the combinatorial mechanisms underlying incremental sentence comprehension. These predictions are grounded in recent work examining the effect of sleep on the consolidation of linguistic information, which demonstrate that sleep-dependent neurophysiological activity consolidates the meaning of novel words and simple grammatical rules. However, the sleep-dependent consolidation of sentence-level combinatorics has not been studied to date. Here, we propose that dissociable aspects of sleep neurophysiology consolidate two different types of combinatory mechanisms in human language: sequence-based (order-sensitive) and dependency-based (order-insensitive) combinatorics. The distinction between the two types of combinatorics is motivated both by cross-linguistic considerations and the neurobiological underpinnings of human language. Unifying this perspective with principles of sleep-dependent memory consolidation, we posit that a function of sleep is to optimize the consolidation of sequence-based knowledge (the when) and the establishment of semantic schemas of unordered items (the what) that underpin cross-linguistic variations in sentence comprehension. This hypothesis builds on the proposal that sleep is involved in the construction of predictive codes, a unified principle of brain function that supports incremental sentence comprehension. Finally, we discuss neurophysiological measures (EEG/MEG) that could be used to test these claims, such as the quantification of neuronal oscillations, which reflect basic mechanisms of information processing in the brain.

Cued Memory Reactivation During SWS Abolishes the Beneficial Effect of Sleep on Abstraction

Study Objectives

Extracting regularities from stimuli in our environment and generalizing these to new situations are fundamental processes in human cognition. Sleep has been shown to enhance these processes, possibly by facilitating reactivation-triggered memory reorganization. Here, we assessed whether cued reactivation during slow wave sleep (SWS) promotes the beneficial effect of sleep on abstraction of statistical regularities.

Methods

We used an auditory statistical learning task, in which the benefit of sleep has been firmly established. Participants were exposed to a probabilistically determined sequence of tones and subsequently tested for recognition of novel short sequences adhering to this same statistical pattern in both immediate and delayed recall sessions. In different groups, the exposure stream was replayed during SWS in the night between the recall sessions (SWS-replay group), in wake just before sleep (presleep replay group), or not at all (control group).

Results

Surprisingly, participants who received replay in sleep performed worse in the delayed recall session than the control and the presleep replay group. They also failed to show the association between SWS and task performance that has been observed in previous studies and was present in the controls. Importantly, sleep structure and sleep quality did not differ between groups, suggesting that replay during SWS did not impair sleep but rather disrupted or interfered with sleep-dependent mechanisms that underlie the extraction of the statistical pattern.

Conclusions

These findings raise important questions about the scope of cued memory reactivation and the mechanisms that underlie sleep-related generalization.

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.

Consolidation Promotes the Emergence of Representational Overlap in the Hippocampus and Medial Prefrontal Cortex

Structured knowledge is thought to form, in part, through the extraction and representation of regularities across overlapping experiences. However, little is known about how consolidation processes may transform novel episodic memories to reflect such regularities. In a multi-day fMRI study, participants encoded trial-unique associations that shared features with other trials. Multi-variate pattern analyses were used to measure neural similarity across overlapping and non-overlapping memories during immediate and 1-week retrieval of these associations. We found that neural patterns in the hippocampus and medial prefrontal cortex represented the featural overlap across memories, but only after a week. Furthermore, after a week, the strength of a memory's unique episodic reinstatement during retrieval was inversely related to its representation of overlap, suggesting a trade-off between the integration of related memories and recovery of episodic details. These findings suggest that consolidation-related changes in neural representations support the gradual organization of discrete episodes into structured knowledge.

Early life stress explains reduced positive memory biases in remitted depression

BACKGROUND

There is contradictory evidence regarding negative memory biases in major depressive disorder (MDD) and whether these persist into remission, which would suggest their role as vulnerability traits rather than correlates of mood state. Early life stress (ELS), common in patients with psychiatric disorders, has independently been associated with memory biases, and confounds MDD versus control group comparisons. Furthermore, in most studies negative biases could have resulted from executive impairments rather than memory difficulties per se.

METHODS

To investigate whether memory biases are relevant to MDD vulnerability and how they are influenced by ELS, we developed an associative recognition memory task for temporo-spatial contexts of social actions with low executive demands, which were matched across conditions (self-blame, other-blame, self-praise, other-praise). We included fifty-three medication-free remitted MDD (25 with ELS, 28 without) and 24 healthy control (HC) participants without ELS.

RESULTS

Only MDD patients with ELS showed a reduced bias (accuracy/speed ratio) towards memory for positive vs. negative materials when compared with MDD without ELS and with HC participants; attenuated positive biases correlated with number of past major depressive episodes, but not current symptoms. There were no biases towards self-blaming or self-praising memories.

CONCLUSIONS

This demonstrates that reduced positive biases in associative memory were specific to MDD patients with ELS rather than a general feature of MDD, and were associated with lifetime recurrence risk which may reflect a scarring effect. If replicated, our results would call for stratifying MDD patients by history of ELS when assessing and treating emotional memories.

Sleep Facilitates Generalisation of Accent Adaptation to a New Talker

Lexically-guided phonetic retuning helps listeners adapt to the phonetic "fingerprint" of a talker. Previous findings show that listeners can generalise from one accented talker to another accented talker, but only for phonetically similar talkers. We tested whether sleep-mediated consolidation promotes generalisation across accented talkers who are not phonetically similar. Native-English participants were trained on a Mandarin-accented talker and tested on this talker and an untrained Mandarin talker. Experiment 1 showed adaptation for the trained talker and a weak transfer to the untrained talker. In Experiment 2, participants were trained and tested either in the morning (Same-Day group) or evening (Overnight group), and again after twelve hours. Both groups retained talker-specific learning over the 12-hour delay. Importantly, the Overnight group showed improvements for the untrained talker, whereas the Same-Day group's performance on the untrained talker deteriorated. We suggest that sleep facilitated talker generalisation by helping listeners abstract away from specific acoustic properties of the trained talker.

Sleep-based memory processing facilitates grammatical generalization: Evidence from targeted memory reactivation

Generalization-the ability to abstract regularities from specific examples and apply them to novel instances-is an essential component of language acquisition. Generalization not only depends on exposure to input during wake, but may also improve offline during sleep. Here we examined whether targeted memory reactivation during sleep can influence grammatical generalization. Participants gradually acquired the grammatical rules of an artificial language through an interactive learning procedure. Then, phrases from the language (experimental group) or stimuli from an unrelated task (control group) were covertly presented during an afternoon nap. Compared to control participants, participants re-exposed to the language during sleep showed larger gains in grammatical generalization. Sleep cues produced a bias, not necessarily a pure gain, suggesting that the capacity for memory replay during sleep is limited. We conclude that grammatical generalization was biased by auditory cueing during sleep, and by extension, that sleep likely influences grammatical generalization in general.

Sleep enhances knowledge of routes and regions in spatial environments

Sleep is thought to preferentially consolidate hippocampus-dependent memory, and as such, spatial navigation. Here, we investigated the effects of sleep on route knowledge and explicit and implicit semantic regions in a virtual environment. Sleep, compared with wakefulness, improved route knowledge and also enhanced awareness of the semantic regionalization within the environment, whereas signs of implicit regionalization remained unchanged. Results support the view that sleep specifically enhances explicit aspects of memory, also in the spatial domain. Enhanced region knowledge after sleep suggests that consolidation during sleep goes along with the formation of more abstract schema-like representations.

Do infants retain the statistics of a statistical learning experience? Insights from a developmental cognitive neuroscience perspective

Statistical structure abounds in language. Human infants show a striking capacity for using statistical learning (SL) to extract regularities in their linguistic environments, a process thought to bootstrap their knowledge of language. Critically, studies of SL test infants in the minutes immediately following familiarization, but long-term retention unfolds over hours and days, with almost no work investigating retention of SL. This creates a critical gap in the literature given that we know little about how single or multiple SL experiences translate into permanent knowledge. Furthermore, different memory systems with vastly different encoding and retention profiles emerge at different points in development, with the underlying memory system dictating the fidelity of the memory trace hours later. I describe the scant literature on retention of SL, the learning and retention properties of memory systems as they apply to SL, and the development of these memory systems. I propose that different memory systems support retention of SL in infant and adult learners, suggesting an explanation for the slow pace of natural language acquisition in infancy. I discuss the implications of developing memory systems for SL and suggest that we exercise caution in extrapolating from adult to infant properties of SL.This article is part of the themed issue 'New frontiers for statistical learning in the cognitive sciences'.

The multi-component nature of statistical learning

The central argument presented in this paper is that statistical learning (SL) is an ability comprised of multiple components that operate largely implicitly. Components relating to the stimulus encoding, retention and abstraction required for SL may include, but are not limited to, certain types of attention, processing speed and memory. It is likely that individuals vary in terms of the efficiency of these underlying components, and in patterns of connectivity among these components, and that SL tasks differ from one another in how they draw on certain underlying components more than others. This theoretical framework is of value because it can assist in gaining a clearer understanding of how SL is linked with individual differences in complex mental activities such as language processing. Variability in language processing across individuals is of central concern to researchers interested in child development, including those interested in neurodevelopmental disorders where language can be affected such as autism spectrum disorders (ASD). This paper discusses the link between SL and individual differences in language processing in the context of age-related changes in SL during infancy and childhood, and whether SL is affected in ASD. Viewing SL as a multi-component ability may help to explain divergent findings from previous empirical research in these areas and guide the design of future studies.This article is part of the themed issue 'New frontiers for statistical learning in the cognitive sciences'.