The Assimilation of Novel Information into Schemata and Its Efficient Consolidation.

Schemata enhance memory formation for related novel information. This is true even when this information is neutral with respect to schema-driven expectations. This assimilation of novel information into schemata has been attributed to more effective organizational processing that leads to more referential connections with the activated associative schema network. Animal data suggest that systems consolidation of novel assimilated information is also accelerated. In the current study, we used both multivariate and univariate fMRI analyses to provide further support for these proposals and to elucidate the neural underpinning of these processes. Twenty-eight participants (5 male) overlearned fictitious schemata for 7 weeks and then encoded novel related and control facts in the scanner. These facts were retrieved both immediately and 2 weeks later, also in the scanner. Our results conceptually replicate previous findings with respect to enhanced vmPFC-hippocampus coupling during encoding of novel related information and point to a prior knowledge effect that is distinct from situations where novel information is experienced as congruent or incongruent with a schema. Moreover, the combination of both multivariate and univariate results further specified the proposed contributions of the vmPFC, precuneus and angular gyrus network to the more efficient encoding of schema-related information. In addition, our data provide further evidence for more efficient systems consolidation of such novel schema-related and potentially assimilated information.SIGNIFICANCE STATEMENT Our prior knowledge in a certain domain, often termed schema, heavily influences whether and how we form memories for novel information that can be related to them. The results of the current study show how a ventromedial prefrontal-precuneal-angular network contributes to the more efficient encoding of novel related information. Furthermore, the observed increase in prefrontal-hippocampal coupling during this process points to a critical distinction from the previously described mechanisms supporting the encoding of information that is experienced as congruent with schema-driven expectations. In addition, we find further support for the proposal based on animal data that prior knowledge enhances also the consolidation of schema-related information.

Targeting targeted memory reactivation: Characteristics of cued reactivation in sleep.

Targeted memory reactivation (TMR) is a technique in which sensory cues associated with memories during wake are used to trigger memory reactivation during subsequent sleep. The characteristics of such cued reactivation, and the optimal placement of TMR cues, remain to be determined. We built an EEG classification pipeline that discriminated reactivation of right- and left-handed movements and found that cues which fall on the up-going transition of the slow oscillation (SO) are more likely to elicit a classifiable reactivation. We also used a novel machine learning pipeline to predict the likelihood of eliciting a classifiable reactivation after each TMR cue using the presence of spindles and features of SOs. Finally, we found that reactivations occurred either immediately after the cue or one second later. These findings greatly extend our understanding of memory reactivation and pave the way for development of wearable technologies to efficiently enhance memory through cueing in sleep.

Ongoing neural oscillations predict the post-stimulus outcome of closed loop auditory stimulation during slow-wave sleep.

Large slow oscillations (SO, 0.5-2 Hz) characterise slow-wave sleep and are crucial to memory consolidation and other physiological functions. Manipulating slow oscillations may enhance sleep and memory, as well as benefitting the immune system. Closed-loop auditory stimulation (CLAS) has been demonstrated to increase the SO amplitude and to boost fast sleep spindle activity (11-16 Hz). Nevertheless, not all such stimuli are effective in evoking SOs, even when they are precisely phase locked. Here, we studied what factors of the ongoing activity patterns may help to determine what oscillations to stimulate to effectively enhance SOs or SO-locked spindle activity. Hence, we trained classifiers using the morphological characteristics of the ongoing SO, as measured by electroencephalography (EEG), to predict whether stimulation would lead to a benefit in terms of the resulting SO and spindle amplitude. Separate classifiers were trained using trials from spontaneous control and stimulated datasets, and we evaluated their performance by applying them to held-out data both within and across conditions. We were able to predict both when large SOs occurred spontaneously, and whether a phase-locked auditory click effectively enlarged them with good accuracy for predicting the SO trough (∼70%) and SO peak values (∼80%). Also, we were able to predict when stimulation would elicit spindle activity with an accuracy of ∼60%. Finally, we evaluate the importance of the various SO features used to make these predictions. Our results offer new insight into SO and spindle dynamics and may suggest techniques for developing future methods for online optimization of stimulation.

Cueing emotional memories during slow wave sleep modulates next-day activity in the orbitofrontal cortex and the amygdala.

Emotional memories are preferentially consolidated during sleep, through the process of memory reactivation. Targeted memory reactivation (TMR) has been shown to boost memory consolidation during sleep, but its neural correlates remain unclear, particularly for emotional memories. Here, we aimed to examine how TMR of emotional material during slow wave sleep (SWS) impacts upon neural processing during a subsequent arousal rating task. Participants were trained on a spatial memory task including negative and neutral pictures paired with semantically matching sounds. The picture-sound pairs were rated for emotional arousal before and after the spatial memory task. Then, half of the sounds from each emotional category (negative and neutral) were cued during SWS. The next day, participants were retested on both the arousal rating and the spatial memory task inside an MRI scanner, followed by another retest session a week later. Memory consolidation and arousal processing did not differ between cued and non-cued items of either emotional category. We found increased responses to emotional stimuli in the amygdala and orbitofrontal cortex (OFC), and a cueing versus emotion interaction in the OFC, whereby cueing neutral stimuli led to an increase in OFC activity, while cueing negative stimuli led to decreased OFC activation. Interestingly, the effect of cueing on amygdala activation was modulated by time spent in REM sleep. We conclude that SWS TMR impacts OFC activity, while REM sleep plays a role in mediating the effect of such cueing on amygdala.

Optimising sounds for the driving of sleep oscillations by closed-loop auditory stimulation.

Recent studies have shown that slow oscillations (SOs) can be driven by rhythmic auditory stimulation, which deepens slow-wave sleep (SWS) and improves memory and the immune-supportive hormonal milieu related to this sleep stage. While different attempts have been made to optimise the driving of the SOs by changing the number of click stimulations, no study has yet investigated the impact of applying more than five clicks in a row. Likewise, the importance of the type of sounds in eliciting brain responses is presently unclear. In a study of 12 healthy young participants (10 females; aged 18-26 years), we applied an established closed-loop stimulation method, which delivered sequences of 10 pink noises, 10 pure sounds (B note of 247 Hz), 10 pronounced "a" vowels, 10 sham, 10 variable sounds, and 10 "oddball" sounds on the up phase of the endogenous SOs. By analysing area under the curve, amplitude, and event related potentials, we explored whether the nature of the sound had a differential effect on driving SOs. We showed that every stimulus in a 10-click sequence, induces a SO response. Interestingly, all three types of sounds that we tested triggered SOs. However, pink noise elicited a more pronounced response compared to the other sounds, which was explained by a broader topographical recruitment of brain areas. Our data further suggest that varying the sounds may partially counteract habituation.

Long term effects of cueing procedural memory reactivation during NREM sleep.

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

Cued Reactivation of Motor Learning during Sleep Leads to Overnight Changes in Functional Brain Activity and Connectivity.

Sleep plays a role in memory consolidation. This is demonstrated by improved performance and neural plasticity underlying that improvement after sleep. Targeted memory reactivation (TMR) allows the manipulation of sleep-dependent consolidation through intentionally biasing the replay of specific memories in sleep, but the underlying neural basis of these altered memories remains unclear. We use functional magnetic resonance imaging (fMRI) to show a change in the neural representation of a motor memory after targeted reactivation in slow-wave sleep (SWS). Participants learned two serial reaction time task (SRTT) sequences associated with different auditory tones (high or low pitch). During subsequent SWS, one sequence was reactivated by replaying the associated tones. Participants were retested on both sequences the following day during fMRI. As predicted, they showed faster reaction times for the cued sequence after targeted memory reactivation. Furthermore, increased activity in bilateral caudate nucleus and hippocampus for the cued relative to uncued sequence was associated with time in SWS, while increased cerebellar and cortical motor activity was related to time in rapid eye movement (REM) sleep. Functional connectivity between the caudate nucleus and hippocampus was also increased after targeted memory reactivation. These findings suggest that the offline performance gains associated with memory reactivation are supported by altered functional activity in key cognitive and motor networks, and that this consolidation is differentially mediated by both REM sleep and SWS.

The nature of delayed dream incorporation ('dream-lag effect'): Personally significant events persist, but not major daily activities or concerns.

Incorporation of details from waking life events into rapid eye movement (REM) sleep dreams has been found to be highest on the 2 nights after, and then 5-7 nights after, the event. These are termed, respectively, the day-residue and dream-lag effects. This study is the first to categorize types of waking life experiences and compare their incorporation into dreams across multiple successive nights. Thirty-eight participants completed a daily diary each evening and a dream diary each morning for 14 days. In the daily diary, three categories of experiences were reported: major daily activities (MDAs), personally significant events (PSEs) and major concerns (MCs). After the 14-day period each participant identified the correspondence between items in their daily diaries and subsequent dream reports. The day-residue and dream-lag effects were found for the incorporation of PSEs into dreams (effect sizes of .33 and .27, respectively), but only for participants (n = 19) who had a below-median total number of correspondences between daily diary items and dream reports (termed "low-incorporators" as opposed to "high-incorporators"). Neither the day-residue or dream-lag effects were found for MDAs or MCs. This U-shaped timescale of incorporation of events from daily life into dreams has been proposed to reflect REM sleep-dependent memory consolidation, possibly related to emotional memory processing. This study had a larger sample size of dreams than any dream-lag study hitherto with trained participants. Coupled with previous successful replications, there is thus substantial evidence supporting the dream-lag effect and further explorations of its mechanism, including its neural underpinnings, are warranted.

Sleep Spindle Density Predicts the Effect of Prior Knowledge on Memory Consolidation.

Information that relates to a prior knowledge schema is remembered better and consolidates more rapidly than information that does not. Another factor that influences memory consolidation is sleep and growing evidence suggests that sleep-related processing is important for integration with existing knowledge. Here, we perform an examination of how sleep-related mechanisms interact with schema-dependent memory advantage. Participants first established a schema over 2 weeks. Next, they encoded new facts, which were either related to the schema or completely unrelated. After a 24 h retention interval, including a night of sleep, which we monitored with polysomnography, participants encoded a second set of facts. Finally, memory for all facts was tested in a functional magnetic resonance imaging scanner. Behaviorally, sleep spindle density predicted an increase of the schema benefit to memory across the retention interval. Higher spindle densities were associated with reduced decay of schema-related memories. Functionally, spindle density predicted increased disengagement of the hippocampus across 24 h for schema-related memories only. Together, these results suggest that sleep spindle activity is associated with the effect of prior knowledge on memory consolidation. SIGNIFICANCE STATEMENT: Episodic memories are gradually assimilated into long-term memory and this process is strongly influenced by sleep. The consolidation of new information is also influenced by its relationship to existing knowledge structures, or schemas, but the role of sleep in such schema-related consolidation is unknown. We show that sleep spindle density predicts the extent to which schemas influence the consolidation of related facts. This is the first evidence that sleep is associated with the interaction between prior knowledge and long-term memory formation.

Targeted memory reactivation of newly learned words during sleep triggers REM-mediated integration of new memories and existing knowledge.

Recent memories are spontaneously reactivated during sleep, leading to their gradual strengthening. Whether reactivation also mediates the integration of new memories with existing knowledge is unknown. We used targeted memory reactivation (TMR) during slow-wave sleep (SWS) to selectively cue reactivation of newly learned spoken words. While integration of new words into their phonological neighbourhood was observed in both cued and uncued words after sleep, TMR-triggered integration was predicted by the time spent in rapid eye movement (REM) sleep. These data support complementary roles for SWS and REM in memory consolidation.

Complementary roles of slow-wave sleep and rapid eye movement sleep in emotional memory consolidation.

Although rapid eye movement sleep (REM) is regularly implicated in emotional memory consolidation, the role of slow-wave sleep (SWS) in this process is largely uncharacterized. In the present study, we investigated the relative impacts of nocturnal SWS and REM upon the consolidation of emotional memories using functional magnetic resonance imaging (fMRI) and polysomnography (PSG). Participants encoded emotionally positive, negative, and neutral images (remote memories) before a night of PSG-monitored sleep. Twenty-four hours later, they encoded a second set of images (recent memories) immediately before a recognition test in an MRI scanner. SWS predicted superior memory for remote negative images and a reduction in right hippocampal responses during the recollection of these items. REM, however, predicted an overnight increase in hippocampal-neocortical connectivity associated with negative remote memory. These findings provide physiological support for sequential views of sleep-dependent memory processing, demonstrating that SWS and REM serve distinct but complementary functions in consolidation. Furthermore, these findings extend those ideas to emotional memory by showing that, once selectively reorganized away from the hippocampus during SWS, emotionally aversive representations undergo a comparably targeted process during subsequent REM.

Cued memory reactivation during slow-wave sleep promotes explicit knowledge of a motor sequence.

Memories are gradually consolidated after initial encoding, and this can sometimes lead to a transition from implicit to explicit knowledge. The exact physiological processes underlying this reorganization remain unclear. Here, we used a serial reaction time task to determine whether targeted memory reactivation (TMR) of specific memory traces during slow-wave sleep promotes the emergence of explicit knowledge. Human participants learned two 12-item sequences of button presses (A and B). These differed in both cue order and in the auditory tones associated with each of the four fingers (one sequence had four higher-pitched tones). Subsequent overnight sleep was monitored, and the tones associated with one learned sequence were replayed during slow-wave sleep. After waking, participants demonstrated greater explicit knowledge (p = 0.005) and more improved procedural skill (p = 0.04) for the cued sequence relative to the uncued sequence. Furthermore, fast spindles (13.5-15 Hz) at task-related motor regions predicted overnight enhancement in procedural skill (r = 0.71, p = 0.01). Auditory cues had no effect on post-sleep memory performance in a control group who received TMR before sleep. These findings suggest that TMR during sleep can alter memory representations and promote the emergence of explicit knowledge, supporting the notion that reactivation during sleep is a key mechanism in this process.

Schema-conformant memories are preferentially consolidated during REM sleep.

Memory consolidation is most commonly described by the standard model, which proposes an initial binding role for the hippocampus which diminishes over time as intracortical connections are strengthened. Recent evidence suggests that slow wave sleep (SWS) plays an essential role in this process. Existing animal and human studies have suggested that memories which fit tightly into an existing knowledge framework or schema might use an alternative consolidation route in which the medial prefrontal cortex takes on the binding role. In this study we sought to investigate the role of sleep in this process using a novel melodic memory task. Participants were asked to remember 32 melodies, half of which conformed to a tonal schema present in all enculturated listeners, and half of which did not fit with this schema. After a 24-h consolidation interval, participants were asked to remember a further 32 melodies, before being given a recognition test in which melodies from both sessions were presented alongside some previously unheard foils. Participants remembered schema-conformant melodies better than non-conformant ones. This was much more strongly the case for consolidated melodies, suggesting that consolidation over a 24-h period preferentially consolidated schema-conformant items. Overnight sleep was monitored between the sessions, and the extent of the consolidation benefit for schema-conformant items was associated with both the amount of REM sleep obtained and EEG theta power in frontal and central regions during REM sleep. Overall our data suggest that REM sleep plays a crucial role in the rapid consolidation of schema-conformant items. This finding is consistent with previous results from animal studies and the SLIMM model of Van Kesteren, Ruiter, Fernández, and Henson (2012), and suggest that REM sleep, rather than SWS, may be involved in an alternative pathway of consolidation for schema-conformant memories.

The role of sleep spindles and slow-wave activity in integrating new information in semantic memory.

Assimilating new information into existing knowledge is a fundamental part of consolidating new memories and allowing them to guide behavior optimally and is vital for conceptual knowledge (semantic memory), which is accrued over many years. Sleep is important for memory consolidation, but its impact upon assimilation of new information into existing semantic knowledge has received minimal examination. Here, we examined the integration process by training human participants on novel words with meanings that fell into densely or sparsely populated areas of semantic memory in two separate sessions. Overnight sleep was polysomnographically monitored after each training session and recall was tested immediately after training, after a night of sleep, and 1 week later. Results showed that participants learned equal numbers of both word types, thus equating amount and difficulty of learning across the conditions. Measures of word recognition speed showed a disadvantage for novel words in dense semantic neighborhoods, presumably due to interference from many semantically related concepts, suggesting that the novel words had been successfully integrated into semantic memory. Most critically, semantic neighborhood density influenced sleep architecture, with participants exhibiting more sleep spindles and slow-wave activity after learning the sparse compared with the dense neighborhood words. These findings provide the first evidence that spindles and slow-wave activity mediate integration of new information into existing semantic networks.

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

Sleep is important for abstraction of the underlying principles (or gist) which bind together conceptually related stimuli, but little is known about the neural correlates of this process. Here, we investigate this issue using overnight sleep monitoring and functional magnetic resonance imaging (fMRI). Participants were exposed to a statistically structured sequence of auditory tones then tested immediately for recognition of short sequences which conformed to the learned statistical pattern. Subsequently, after consolidation over either 30 min or 24h, they performed a delayed test session in which brain activity was monitored with fMRI. Behaviorally, there was greater improvement across 24h than across 30 min, and this was predicted by the amount of slow wave sleep (SWS) obtained. Functionally, we observed weaker parahippocampal responses and stronger striatal responses after sleep. Like the behavioral result, these differences in functional response were predicted by the amount of SWS obtained. Furthermore, connectivity between striatum and parahippocampus was weaker after sleep, whereas connectivity between putamen and planum temporale was stronger. Taken together, these findings suggest that abstraction is associated with a gradual shift from the hippocampal to the striatal memory system and that this may be mediated by SWS.

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.

Auditory stimulation during REM sleep modulates REM electrophysiology and cognitive performance.

REM sleep is critical for memory, emotion, and cognition. Manipulating brain activity during REM could improve our understanding of its function and benefits. Earlier studies have suggested that auditory stimulation in REM might modulate REM time and reduce rapid eye movement density. Building on this, we studied the cognitive effects and electroencephalographic responses related to such stimulation. We used acoustic stimulation locked to eye movements during REM and compared two overnight conditions (stimulation and no-stimulation). We evaluated the impact of this stimulation on REM sleep duration and electrophysiology, as well as two REM-sensitive memory tasks: visual discrimination and mirror tracing. Our results show that this auditory stimulation in REM decreases the rapid eye movements that characterize REM sleep and improves performance on the visual task but is detrimental to the mirror tracing task. We also observed increased beta-band activity and decreased theta-band activity following stimulation. Interestingly, these spectral changes were associated with changes in behavioural performance. These results show that acoustic stimulation can modulate REM sleep and suggest that different memory processes underpin its divergent impacts on cognitive performance.

Wearing an eye mask during overnight sleep improves episodic learning and alertness.

Ambient light can influence sleep structure and timing. We explored how wearing an eye mask to block light during overnight sleep impacts memory and alertness, changes that could benefit everyday tasks like studying or driving. In Experiment 1, ninety-four 18-35-year-olds wore an eye mask while they slept every night for a week and underwent a control condition in which light was not blocked for another week. Five habituation nights were followed by a cognitive battery on the sixth and seventh days. This revealed superior episodic encoding and an improvement on alertness when using the mask. In Experiment 2, thirty-five 18-35-year-olds used a wearable device to monitor sleep with and without the mask. This replicated the encoding benefit and showed that it was predicted by time spent in slow-wave sleep. Our findings suggest that wearing an eye mask during overnight sleep can improve episodic encoding and alertness the next day.

Targeted memory reactivation in human REM sleep elicits detectable reactivation.

It is now well established that memories can reactivate during non-rapid eye movement (non-REM) sleep, but the question of whether equivalent reactivation can be detected in rapid eye movement (REM) sleep is hotly debated. To examine this, we used a technique called targeted memory reactivation (TMR) in which sounds are paired with learned material in wake, and then re-presented in subsequent sleep, in this case REM, to trigger reactivation. We then used machine learning classifiers to identify reactivation of task-related motor imagery from wake in REM sleep. Interestingly, the strength of measured reactivation positively predicted overnight performance improvement. These findings provide the first evidence for memory reactivation in human REM sleep after TMR that is directly related to brain activity during wakeful task performance.

Sleep is crucial for rest and recovery, but it also allows the brain to process things it has learned while awake. This is why a person may go to bed frustrated with learning a tune on the piano but wake up the next morning ready to play it without fumbling. For this to happen, it is thought that memories must be reactivated during sleep ­ something which can be studied by monitoring brain activity. While it has been shown that memory reactivation occurs in some stages of human sleep, it was unclear whether it occurred in a specific stage known as REM sleep ­ which is important for learning. To study memory reactivation during REM sleep, Abdellahi et al. recruited volunteers and monitored their brain activity during an 'adaptation night' when certain sounds played as they slept. The following day, memories ­ such as an image or pressing a certain button ­ were paired with the sounds, which were replayed during REM sleep the following night to trigger memory reactivation (experimental night). Abdellahi et al. measured how strongly brain activity during each night related to the waking activity when the sound pairing tasks were imagined and compared the adaptation and experimental nights. The experimental night showed clear signs of memory reactivation after the sounds were played during REM sleep, suggesting that the sounds triggered memories of the associated images or buttons. These findings show that in humans, brain activity patterns that indicate memory reactivation can be identified during REM sleep. The work paves the way for future studies into the characteristics of this memory reactivation and how to trigger it in a way that leads to improvements in memory.

Premotor cortex is sensitive to auditory-visual congruence for biological motion.

The auditory and visual perception systems have developed special processing strategies for ecologically valid motion stimuli, utilizing some of the statistical properties of the real world. A well-known example is the perception of biological motion, for example, the perception of a human walker. The aim of the current study was to identify the cortical network involved in the integration of auditory and visual biological motion signals. We first determined the cortical regions of auditory and visual coactivation (Experiment 1); a conjunction analysis based on unimodal brain activations identified four regions: middle temporal area, inferior parietal lobule, ventral premotor cortex, and cerebellum. The brain activations arising from bimodal motion stimuli (Experiment 2) were then analyzed within these regions of coactivation. Auditory footsteps were presented concurrently with either an intact visual point-light walker (biological motion) or a scrambled point-light walker; auditory and visual motion in depth (walking direction) could either be congruent or incongruent. Our main finding is that motion incongruency (across modalities) increases the activity in the ventral premotor cortex, but only if the visual point-light walker is intact. Our results extend our current knowledge by providing new evidence consistent with the idea that the premotor area assimilates information across the auditory and visual modalities by comparing the incoming sensory input with an internal representation.