Sleep Spindle Refractoriness Segregates Periods of Memory Reactivation

Memory Reactivation during Sleep Does Not Act Holistically on Object Memory

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

Delineating memory reactivation in sleep with verbal and non-verbal retrieval cues

Sleep supports memory consolidation via the reactivation of newly formed memory traces. One way to investigate memory reactivation in sleep is by exposing the sleeping brain to auditory retrieval cues; a paradigm known as targeted memory reactivation. To what extent the acoustic properties of memory cues influence the effectiveness of targeted memory reactivation, however, has received limited attention. We addressed this question by exploring how verbal and non-verbal memory cues affect oscillatory activity linked to memory reactivation in sleep. Fifty-one healthy male adults learned to associate visual stimuli with spoken words (verbal cues) and environmental sounds (non-verbal cues). Subsets of the verbal and non-verbal memory cues were then replayed during sleep. The voice of the verbal cues was either matched or mismatched to learning. Memory cues (relative to unheard control cues) prompted an increase in theta/alpha and spindle power, which have been heavily implicated in sleep-associated memory processing. Moreover, verbal memory cues were associated with a stronger increase in spindle power than non-verbal memory cues. There were no significant differences between the matched and mismatched verbal cues. Our findings suggest that verbal memory cues may be most effective for triggering memory reactivation in sleep, as indicated by an amplified spindle response.

Targeted Memory Reactivation during Nonrapid Eye Movement Sleep Enhances Neutral, But Not Negative, Components of Memory

Emotionally salient components of memory are preferentially remembered at the expense of accompanying neutral information. This emotional memory trade-off is enhanced over time, and possibly sleep, through a process of memory consolidation. Sleep is believed to benefit memory through a process of reactivation during nonrapid eye movement sleep (NREM). Here, targeted memory reactivation (TMR) was used to manipulate the reactivation of negative and neutral memories during NREM sleep. Thirty-one male and female participants encoded composite scenes containing either a negative or neutral object superimposed on an always neutral background. During NREM sleep, sounds associated with the scene object were replayed, and memory for object and background components was tested the following morning. We found that TMR during NREM sleep improved memory for neutral, but not negative scene objects. This effect was associated with sleep spindle activity, with a larger spindle response following TMR cues predicting TMR effectiveness for neutral items only. These findings therefore do not suggest a role of NREM memory reactivation in enhancing the emotional memory trade-off across a 12 h period but do align with growing evidence of spindle-mediated memory reactivation in service of neutral declarative memory.

Recurring memory reactivation: The offline component of learning

One can be aware of the effort needed to memorize a new fact or to recall the name of a new acquaintance. Because of experiences like this, learning can seem to have only two components, encoding information and, after some delay, retrieving information. To the contrary, learning entails additional, intervening steps that sometimes are hidden from the learner. For firmly acquiring fact and event knowledge in particular, learners are generally not cognizant of the necessity of offline consolidation. The memories that persist to be available reliably at a later time, according to the present conceptualization, are the ones we repeatedly rehearse and integrate with other knowledge, whether we do this intentionally or unknowingly, awake or asleep. This article examines the notion that learning is not a function of waking brain activity alone. What happens in the brain while we sleep also impacts memory storage, and consequently is a critical component of learning. The idea that memories can change over time and become enduring has long been present in memory research and is foundational for the concept of memory consolidation. Nevertheless, the notion that memory consolidation happens during sleep faced much resistance before eventually being firmly established. Research is still needed to elucidate the operation and repercussions of repeated reactivation during sleep. Comprehensively understanding how offline memory reactivation contributes to learning is vital for both theoretical and practical considerations.

An update on recent advances in targeted memory reactivation during sleep

Targeted Memory Reactivation (TMR) is a noninvasive tool to manipulate memory consolidation during sleep. TMR builds on the brain's natural processes of memory reactivation during sleep and aims to facilitate or bias these processes in a certain direction. The basis of this technique is the association of learning content with sensory cues, such as odors or sounds, that are presented during subsequent sleep to promote memory reactivation. Research on TMR has drastically increased over the last decade with rapid developments. The aim of the present review is to highlight the most recent advances of this research. We focus on effects of TMR on the strengthening of memories in the declarative, procedural and emotional memory domain as well as on ways in which TMR can be used to promote forgetting. We then discuss advanced technical approaches to determine the optimal timing of TMR within the ongoing oscillatory activity of the sleeping brain as well as the specificity of TMR for certain memory contents. We further highlight the specific effects of TMR during REM sleep and in influencing dream content. Finally, we discuss recent evidence for potential applications of TMR for mental health, educational purposes and in the home setting. In conclusion, the last years of research have provided substantial advances in TMR that can guide future endeavors in research and application.

No Benefit in Memory Performance after Nocturnal Memory Reactivation Coupled with Theta-tACS

Targeted memory reactivation (TMR) is an effective technique to enhance sleep-associated memory consolidation. The successful reactivation of memories by external reminder cues is typically accompanied by an event-related increase in theta oscillations, preceding better memory recall after sleep. However, it remains unclear whether the increase in theta oscillations is a causal factor or an epiphenomenon of successful TMR. Here, we used transcranial alternating current stimulation (tACS) to examine the causal role of theta oscillations for TMR during non-rapid eye movement (non-REM) sleep. Thirty-seven healthy participants learned Dutch-German word pairs before sleep. During non-REM sleep, we applied either theta-tACS or control-tACS (23 Hz) in blocks (9 min) in a randomised order, according to a within-subject design. One group of participants received tACS coupled with TMR time-locked two seconds after the reminder cue (time-locked group). Another group received tACS in a continuous manner while TMR cues were presented (continuous group). Contrary to our predictions, we observed no frequency-specific benefit of theta-tACS coupled with TMR during sleep on memory performance, neither for continuous nor time-locked stimulation. In fact, both stimulation protocols blocked the TMR-induced memory benefits during sleep, resulting in no memory enhancement by TMR in both the theta and control conditions. No frequency-specific effect was found on the power analyses of the electroencephalogram. We conclude that tACS might have an unspecific blocking effect on memory benefits typically observed after TMR during non-REM sleep.

Age-associated sleep spindle characteristics in Duchenne muscular dystrophy

Brain oscillations of non-rapid eye movement sleep, including slow oscillations (SO, 0.5-1.5 Hz) and spindles (10-16 Hz), mirror underlying brain maturation across development and are associated with cognition. Hence, age-associated emergence and changes in the electrophysiological properties of these rhythms can lend insight into cortical development, specifically in comparisons between pediatric populations and typically developing peers. We previously evaluated age-associated changes in SOs in male patients with Duchenne muscular dystrophy (DMD), finding a significant age-related decline between 4 and 18 years. While primarily a muscle disorder, male patients with DMD can also have sleep, cognitive, and cortical abnormalities, thought to be driven by altered dystrophin expression in the brain. In this follow-up study, we characterized the age-associated changes in sleep spindles. We found that age-dependent spindle characteristics in patients with DMD, including density, frequency, amplitude, and duration, were consistent with age-associated trends reported in the literature for typically developing controls. Combined with our prior finding of age-associated decline in SOs, our results suggest that SOs, but not spindles, are a candidate intervention target to enhance sleep in patients with DMD.

Individualized temporal patterns dominate cortical upstate and sleep depth in driving human sleep spindle timing

Sleep spindles are critical for memory consolidation and strongly linked to neurological disease and aging. Despite their significance, the relative influences of factors like sleep depth, cortical up/down states, and spindle temporal patterns on individual spindle production remain poorly understood. Moreover, spindle temporal patterns are typically ignored in favor of an average spindle rate. Here, we analyze spindle dynamics in 1008 participants from the Multi-Ethnic Study of Atherosclerosis using a point process framework. Results reveal fingerprint-like temporal patterns, characterized by a refractory period followed by a period of increased spindle activity, which are highly individualized yet consistent night-to-night. We observe increased timing variability with age and distinct gender/age differences. Strikingly, and in contrast to the prevailing notion, individualized spindle patterns are the dominant determinant of spindle timing, accounting for over 70% of the statistical deviance explained by all of the factors we assessed, surpassing the contribution of slow oscillation (SO) phase (~14%) and sleep depth (~16%). Furthermore, we show spindle/SO coupling dynamics with sleep depth are preserved across age, with a global negative shift towards the SO rising slope. These findings offer novel mechanistic insights into spindle dynamics with direct experimental implications and applications to individualized electroencephalography biomarker identification.

Odor cueing of declarative memories during sleep enhances coordinated spindles and slow oscillations

Long-term memories are formed by repeated reactivation of newly encoded information during sleep. This process can be enhanced by using memory-associated reminder cues like sounds and odors. While auditory cueing has been researched extensively, few electrophysiological studies have exploited the various benefits of olfactory cueing. We used high-density electroencephalography in an odor-cueing paradigm that was designed to isolate the neural responses specific to the cueing of declarative memories. We show widespread cueing-induced increases in the duration and rate of sleep spindles. Higher spindle rates were most prominent over centro-parietal areas and largely overlapping with a concurrent increase in the amplitude of slow oscillations (SOs). Interestingly, greater SO amplitudes were linked to a higher likelihood of coupling a spindle and coupled spindles expressed during cueing were more numerous in particular around SO up states. We thus identify temporally and spatially coordinated enhancements of sleep spindles and slow oscillations as a candidate mechanism behind cueing-induced memory processing. Our results further demonstrate the feasibility of studying neural activity patterns linked to such processing using olfactory cueing during sleep.

The neurophysiology of closed-loop auditory stimulation in sleep: A magnetoencephalography study

Closed-loop auditory stimulation (CLAS) is a brain modulation technique in which sounds are timed to enhance or disrupt endogenous neurophysiological events. CLAS of slow oscillation up-states in sleep is becoming a popular tool to study and enhance sleep's functions, as it increases slow oscillations, evokes sleep spindles and enhances memory consolidation of certain tasks. However, few studies have examined the specific neurophysiological mechanisms involved in CLAS, in part because of practical limitations to available tools. To evaluate evidence for possible models of how sound stimulation during brain up-states alters brain activity, we simultaneously recorded electro- and magnetoencephalography in human participants who received auditory stimulation across sleep stages. We conducted a series of analyses that test different models of pathways through which CLAS of slow oscillations may affect widespread neural activity that have been suggested in literature, using spatial information, timing and phase relationships in the source-localized magnetoencephalography data. The results suggest that auditory information reaches ventral frontal lobe areas via non-lemniscal pathways. From there, a slow oscillation is created and propagated. We demonstrate that while the state of excitability of tissue in auditory cortex and frontal ventral regions shows some synchrony with the electroencephalography (EEG)-recorded up-states that are commonly used for CLAS, it is the state of ventral frontal regions that is most critical for slow oscillation generation. Our findings advance models of how CLAS leads to enhancement of slow oscillations, sleep spindles and associated cognitive benefits and offer insight into how the effectiveness of brain stimulation techniques can be improved.

Single closed-loop acoustic stimulation targeting memory consolidation suppressed hippocampal ripple and thalamo-cortical spindle activity in mice

Brain rhythms of sleep reflect neuronal activity underlying sleep-associated memory consolidation. The modulation of brain rhythms, such as the sleep slow oscillation (SO), is used both to investigate neurophysiological mechanisms as well as to measure the impact of sleep on presumed functional correlates. Previously, closed-loop acoustic stimulation in humans targeted to the SO Up-state successfully enhanced the slow oscillation rhythm and phase-dependent spindle activity, although effects on memory retention have varied. Here, we aim to disclose relations between stimulation-induced hippocampo-thalamo-cortical activity and retention performance on a hippocampus-dependent object-place recognition task in mice by applying acoustic stimulation at four estimated SO phases compared to sham condition. Across the 3-h retention interval at the beginning of the light phase closed-loop stimulation failed to improve retention significantly over sham. However, retention during SO Up-state stimulation was significantly higher than for another SO phase. At all SO phases, acoustic stimulation was accompanied by a sharp increase in ripple activity followed by about a second-long suppression of hippocampal sharp wave ripple and longer maintained suppression of thalamo-cortical spindle activity. Importantly, dynamics of SO-coupled hippocampal ripple activity distinguished SOUp-state stimulation. Non-rapid eye movement (NREM) sleep was not impacted by stimulation, yet preREM sleep duration was effected. Results reveal the complex effect of stimulation on the brain dynamics and support the use of closed-loop acoustic stimulation in mice to investigate the inter-regional mechanisms underlying memory consolidation.

Automatic sleep spindles identification and classification with multitapers and convolution

Sleep spindles are isolated transient surges of oscillatory neural activity present during sleep stages 2 and 3 in the nonrapid eye movement (NREM). They can indicate the mechanisms of memory consolidation and plasticity in the brain. Spindles can be identified across cortical areas and classified as either slow or fast. There are spindle transients across different frequencies and power, yet most of their functions remain a mystery. Using several electroencephalogram (EEG) databases, this study presents a new method, called the "spindles across multiple channels" (SAMC) method, for identifying and categorizing sleep spindles in EEGs during the NREM sleep. The SAMC method uses a multitapers and convolution (MT&C) approach to extract the spectral estimation of different frequencies present in sleep EEGs and graphically identify spindles across multiple channels. The characteristics of spindles, such as duration, power, and event areas, are also extracted by the SAMC method. Comparison with other state-of-the-art spindle identification methods demonstrated the superiority of the proposed method with an agreement rate, average positive predictive value, and sensitivity of over 90% for spindle classification across the three databases used in this paper. The computing cost was found to be, on average, 0.004 seconds per epoch. The proposed method can potentially improve the understanding of the behavior of spindles across the scalp and accurately identify and categories sleep spindles.

Temporal cluster-based organization of sleep spindles underlies motor memory consolidation

Sleep benefits motor memory consolidation, which is mediated by sleep spindle activity and associated memory reactivations during non-rapid eye movement (NREM) sleep. However, the particular role of NREM2 and NREM3 sleep spindles and the mechanisms triggering this memory consolidation process remain unclear. Here, simultaneous electroencephalographic and functional magnetic resonance imaging (EEG-fMRI) recordings were collected during night-time sleep following the learning of a motor sequence task. Adopting a time-based clustering approach, we provide evidence that spindles iteratively occur within clustered and temporally organized patterns during both NREM2 and NREM3 sleep. However, the clustering of spindles in trains is related to motor memory consolidation during NREM2 sleep only. Altogether, our findings suggest that spindles' clustering and rhythmic occurrence during NREM2 sleep may serve as an intrinsic rhythmic sleep mechanism for the timed reactivation and subsequent consolidation of motor memories, through synchronized oscillatory activity within a subcortical-cortical network involved during learning.

Neural reactivation during human sleep

Sleep promotes memory consolidation: the process by which newly acquired memories are stabilised, strengthened, and integrated into long-term storage. Pioneering research in rodents has revealed that memory reactivation in sleep is a primary mechanism underpinning sleep's beneficial effect on memory. In this review, we consider evidence for memory reactivation processes occurring in human sleep. Converging lines of research support the view that memory reactivation occurs during human sleep, and is functionally relevant for consolidation. Electrophysiology studies have shown that memory reactivation is tightly coupled to the cardinal neural oscillations of non-rapid eye movement sleep, namely slow oscillation-spindle events. In addition, functional imaging studies have found that brain regions recruited during learning become reactivated during post-learning sleep. In sum, the current evidence paints a strong case for a mechanistic role of neural reactivation in promoting memory consolidation during human sleep.

Disturbed laterality of non-rapid eye movement sleep oscillations in post-stroke human sleep: a pilot study

Sleep is known to promote recovery post-stroke. However, there is a paucity of data profiling sleep oscillations in the post-stroke human brain. Recent rodent work showed that resurgence of physiologic spindles coupled to sleep slow oscillations (SOs) and concomitant decrease in pathological delta (δ) waves is associated with sustained motor performance gains during stroke recovery. The goal of this study was to evaluate bilaterality of non-rapid eye movement (NREM) sleep-oscillations (namely SOs, δ-waves, spindles, and their nesting) in post-stroke patients vs. healthy control subjects. We analyzed NREM-marked electroencephalography (EEG) data in hospitalized stroke-patients (n = 5) and healthy subjects (n = 3). We used a laterality index to evaluate symmetry of NREM oscillations across hemispheres. We found that stroke subjects had pronounced asymmetry in the oscillations, with a predominance of SOs, δ-waves, spindles, and nested spindles in affected hemisphere, when compared to the healthy subjects. Recent preclinical work classified SO-nested spindles as restorative post-stroke and δ-wave-nested spindles as pathological. We found that the ratio of SO-nested spindles laterality index to δ-wave-nested spindles laterality index was lower in stroke subjects. Using linear mixed models (which included random effects of concurrent pharmacologic drugs), we found large and medium effect size for δ-wave nested spindle and SO-nested spindle, respectively. Our results in this pilot study indicate that considering laterality index of NREM oscillations might be a useful metric for assessing recovery post-stroke and that factoring in pharmacologic drugs may be important when targeting sleep modulation for neurorehabilitation post-stroke.

Item-specific neural representations during human sleep support long-term memory

Understanding how individual memories are reactivated during sleep is essential in theorizing memory consolidation. Here, we employed the targeted memory reactivation (TMR) paradigm to unobtrusively replaying auditory memory cues during human participants' slow-wave sleep (SWS). Using representational similarity analysis (RSA) on cue-elicited electroencephalogram (EEG), we found temporally segregated and functionally distinct item-specific neural representations: the early post-cue EEG activity (within 0 to 2,000 ms) contained comparable item-specific representations for memory cues and control cues, signifying effective processing of auditory cues. Critically, the later EEG activity (2,500 to 2,960 ms) showed greater item-specific representations for post-sleep remembered items than for forgotten and control cues, indicating memory reprocessing. Moreover, these later item-specific neural representations were supported by concurrently increased spindles, particularly for items that had not been tested prior to sleep. These findings elucidated how external memory cues triggered item-specific neural representations during SWS and how such representations were linked to successful long-term memory. These results will benefit future research aiming to perturb specific memory episodes during sleep.

The effects of closed-loop auditory stimulation on sleep oscillatory dynamics in relation to motor procedural memory consolidation

STUDY OBJECTIVES

Healthy aging and many disorders show reduced sleep-dependent memory consolidation and corresponding alterations in non-rapid eye movement sleep oscillations. Yet sleep physiology remains a relatively neglected target for improving memory. We evaluated the effects of closed-loop auditory stimulation during sleep (CLASS) on slow oscillations (SOs), sleep spindles, and their coupling, all in relation to motor procedural memory consolidation.

METHODS

Twenty healthy young adults had two afternoon naps: one with auditory stimulation during SO upstates and another with no stimulation. Twelve returned for a third nap with stimulation at variable times in relation to SO upstates. In all sessions, participants trained on the motor sequence task prior to napping and were tested afterward.

RESULTS

Relative to epochs with no stimulation, upstate stimuli disrupted sleep and evoked SOs, spindles, and SO-coupled spindles. Stimuli that successfully evoked oscillations were delivered closer to the peak of the SO upstate and when spindle power was lower than stimuli that failed to evoke oscillations. Across conditions, participants showed similar significant post-nap performance improvement that correlated with the density of SO-coupled spindles.

CONCLUSIONS

Despite its strong effects on sleep physiology, CLASS failed to enhance motor procedural memory. Our findings suggest methods to overcome this failure, including better sound calibration to preserve sleep continuity and the use of real-time predictive algorithms to more precisely target SO upstates and to avoid disrupting endogenous SO-coupled spindles and their mnemonic function. They motivate continued development of CLASS as an intervention to manipulate sleep oscillatory dynamics and improve memory.

Spindle-dependent memory consolidation in healthy adults: A meta-analysis

Accumulating evidence suggests a central role for sleep spindles in the consolidation of new memories. However, no meta-analysis of the association between sleep spindles and memory performance has been conducted so far. Here, we report meta-analytical evidence for spindle-memory associations and investigate how multiple factors, including memory type, spindle type, spindle characteristics, and EEG topography affect this relationship. The literature search yielded 53 studies reporting 1427 effect sizes, resulting in a small to moderate effect for the average association. We further found that spindle-memory associations were significantly stronger for procedural memory than for declarative memory. Neither spindle types nor EEG scalp topography had an impact on the strength of the spindle-memory relation, but we observed a distinct functional role of global and fast sleep spindles, especially for procedural memory. We also found a moderation effect of spindle characteristics, with power showing the largest effect sizes. Collectively, our findings suggest that sleep spindles are involved in learning, thereby representing a general physiological mechanism for memory consolidation.

Closed-loop auditory stimulation of sleep slow oscillations: Basic principles and best practices

Sleep is essential for our physical and mental well-being. During sleep, despite the paucity of overt behavior, our brain remains active and exhibits a wide range of coupled brain oscillations. In particular slow oscillations are characteristic for sleep, however whether they are directly involved in the functions of sleep, or are mere epiphenomena, is not yet fully understood. To disentangle the causality of these relationships, experiments utilizing techniques to detect and manipulate sleep oscillations in real-time are essential. In this review, we first overview the theoretical principles of closed-loop auditory stimulation (CLAS) as a method to study the role of slow oscillations in the functions of sleep. We then describe technical guidelines and best practices to perform CLAS and analyze results from such experiments. We further provide an overview of how CLAS has been used to investigate the causal role of slow oscillations in various sleep functions. We close by discussing important caveats, open questions, and potential topics for future research.

Neural oscillations after acute large artery atherosclerotic cerebral infarction during resting state and sleep spindles

Electroencephalogram-microstate analysis was conducted using low-resolution electromagnetic tomography (LORETA)-KEY to evaluate dynamic brain network changes in patients with acute large artery atherosclerotic cerebral infarction (LAACI) during the rest and sleep stages. This study included 35 age- and sex-matched healthy controls and 34 patients with acute LAACI. Each participant performed a 3-h, 19-channel video electroencephalogram test. Subsequently, 20 epochs of 2-s sleep spindles during stage N2 sleep and five epochs of 10-s electroencephalogram data in the resting state for each participant were obtained. In both the resting state and sleep spindles, patients with LAACI displayed altered neural oscillations. The parameters of microstate A (coverage, occurrence, and duration) increased during the resting state in the patients with LAACI compared with healthy controls. The coverage and occurrence of microstate B and D were reduced in the LAACI group compared with the healthy controls (p < 0.05). Moreover, during sleep spindles, the duration of microstate A and the transition probability from microstate A and B to C decreased, but the coverage of microstate B and the transition rate from microstate B to D increased (p < 0.05) in the LAACI group compared with the healthy controls. These results enable better understanding of how neural oscillations are modified in patients with LAACI during the resting state and sleep spindles. Following LAACI, the dynamic brain network undergoes changes during sleep spindles and the resting state. Continued long-term investigations are required to determine how well these changes in brain dynamics reflect the clinical characteristics of patients with LAACI.

A system based on machine learning for improving sleep

Closed-loop auditory stimulation is one of the well-known and emerging sensory stimulation techniques, which achieves the purpose of sleep regulation by driving the EEG slow oscillation (SO, <1 Hz) through auditory stimulation. The main challenge is to accurately identify the stimulation timing and provide feedback in real-time, which has high requirements on the response time and recognition accuracy of the closed-loop auditory stimulation system. To reduce the impact of systematic errors on the regulation results, most traditional closed-loop auditory stimulation systems try to identify a single feature to determine the timing of stimulus delivery and reduce the system feedback delay by simplifying the calculation. Unlike existing closed-loop regulation systems that identify specific brain features, this paper proposes a closed-loop auditory stimulation sleep regulation system deploying machine learning. The process is: through online sleep real-time automatic staging, tracking the sleep stage to provide feedback quickly, and continuously offering external auditory stimulation at a specific SO phase. This paper uses this system to conduct sleep auditory stimulation regulation experiments on ten subjects. The experimental results show that the sleep closed-loop regulation system proposed in this paper can achieve consistency (effective for almost all subjects in the experiment) and immediate (taking effect immediately after stimulation) modulation effects on SOs. More importantly, the proposed method is superior to existing advanced methods. Therefore, the system designed in this paper has great potential to be more reliable and flexible in sleep regulation.

Clinical value of cortical bursting in preterm infants with intraventricular haemorrhage

BACKGROUND

In healthy preterm infants, cortical burst rate and temporal dynamics predict important measures such as brain growth. We hypothesised that in preterm infants with germinal matrix-intraventricular haemorrhage (GM-IVH), cortical bursting could provide prognostic information.

AIMS

We determined how cortical bursting was influenced by the injury, and whether this was related to developmental outcome.

STUDY DESIGN

Single-centre retrospective cohort study at University College London Hospitals, UK.

SUBJECTS

33 infants with GM-IVH ≥ grade II (median gestational age: 25 weeks).

OUTCOME MEASURES

We identified 47 EEGs acquired between 24 and 40 weeks corrected gestational age as part of routine clinical care. In a subset of 33 EEGs from 25 infants with asymmetric injury, we used the least-affected hemisphere as an internal comparison. We tested whether cortical burst rate predicted survival without severe impairment (median 2 years follow-up).

RESULTS

In asymmetric injury, cortical burst rate was lower over the worst- than least-affected hemisphere, and bursts over the worst-affected hemisphere were less likely to immediately follow bursts over the least-affected hemisphere than vice versa. Overall, burst rate was lower in cases of GM-IVH with parenchymal involvement, relative to milder structural injury grades. Higher burst rate modestly predicted survival without severe language (AUC 0.673) or motor impairment (AUC 0.667), which was partly mediated by structural injury grade.

CONCLUSIONS

Cortical bursting can index the functional injury after GM-IVH: perturbed burst initiation (rate) and propagation (inter-hemispheric dynamics) likely reflect associated grey matter and white matter damage. Higher cortical burst rate is reassuring for a positive outcome.

Targeted memory reactivation during slow-wave sleep vs. sleep stage N2: no significant differences in a vocabulary task

Sleep supports memory consolidation, and slow-wave sleep (SWS) in particular is assumed to benefit the consolidation of verbal learning material. Re-exposure to previously learned words during SWS with a technique known as targeted memory reactivation (TMR) consistently benefits memory. However, TMR has also been successfully applied during sleep stage N2, though a direct comparison between words selectively reactivated during SWS versus N2 is still missing. Here, we directly compared the effects of N2 TMR and SWS TMR on memory performance in a vocabulary learning task in a within-subject design. Thirty-four healthy young participants (21 in the main sample and 13 in an additional sample) learned 120 Dutch-German word pairs before sleep. Participants in the main sample slept for ∼8 h during the night, while participants in the additional sample slept ∼3 h. We reactivated the Dutch words selectively during N2 and SWS in one single night. Forty words were not cued. Participants in the main sample recalled the German translations of the Dutch words after sleep in the morning, while those in the additional sample did so at 2:00 a.m. As expected, we observed no differences in recall performance between words reactivated during N2 and SWS. However, we failed to find an overall memory benefit of reactivated over nonreactivated words. Detailed time-frequency analyses showed that words played during N2 elicited stronger characteristic oscillatory responses in several frequency bands, including spindle and theta frequencies, compared with SWS. These oscillatory responses did not vary with the memory strengths of individual words. Our results question the robustness and replicability of the TMR benefit on memory using our Dutch vocabulary learning task. We discuss potential boundary conditions for vocabulary reactivation paradigms and, most importantly, see the need for further replication studies, ideally including multiple laboratories and larger sample sizes.

The influence of encoding strategy on associative memory consolidation across wake and sleep

Sleep benefits memory consolidation. However, factors present at initial encoding may moderate this effect. Here, we examined the role that encoding strategy plays in subsequent memory consolidation during sleep. Eighty-nine participants encoded pairs of words using two different strategies. Each participant encoded half of the word pairs using an integrative visualization technique, where the two items were imagined in an integrated scene. The other half were encoded nonintegratively, with each word pair item visualized separately. Memory was tested before and after a period of nocturnal sleep (N = 47) or daytime wake (N = 42) via cued recall tests. Immediate memory performance was significantly better for word pairs encoded using the integrative strategy compared with the nonintegrative strategy (P < 0.001). When looking at the change in recall across the delay, there was significantly less forgetting of integrated word pairs across a night of sleep compared with a day spent awake (P < 0.001), with no significant difference in the nonintegrated pairs (P = 0.19). This finding was driven by more forgetting of integrated compared with not-integrated pairs across the wake delay (P < 0.001), whereas forgetting was equivalent across the sleep delay (P = 0.26). Together, these results show that the strategy engaged in during encoding impacts both the immediate retention of memories and their subsequent consolidation across sleep and wake intervals.

Sleep-related motor skill consolidation and generalizability after physical practice, motor imagery, and action observation

Sleep benefits the consolidation of motor skills learned by physical practice, mainly through periodic thalamocortical sleep spindle activity. However, motor skills can be learned without overt movement through motor imagery or action observation. Here, we investigated whether sleep spindle activity also supports the consolidation of non-physically learned movements. Forty-five electroencephalographic sleep recordings were collected during a daytime nap after motor sequence learning by physical practice, motor imagery, or action observation. Our findings reveal that a temporal cluster-based organization of sleep spindles underlies motor memory consolidation in all groups, albeit with distinct behavioral outcomes. A daytime nap offers an early sleep window promoting the retention of motor skills learned by physical practice and motor imagery, and its generalizability toward the inter-manual transfer of skill after action observation. Findings may further have practical impacts with the development of non-physical rehabilitation interventions for patients having to remaster skills following peripherical or brain injury.

Reap while you sleep: Consolidation of memories differs by how they were sown

Newly formed memories are spontaneously reactivated during sleep, leading to their strengthening. This reactivation process can be manipulated by reinstating learning-related stimuli during sleep, a technique termed targeted memory reactivation. Numerous studies have found that delivering cues during sleep improves memory for simple associations, in which one cue reactivates one tested memory. However, real-life memories often live in rich, complex networks of associations. In this review, we will examine recent forays into investigating how targeted sleep reactivation affects memories within complex paradigms, in which one cue can reactivate multiple tested memories. A common theme across studies is that reactivation consequences do not merely depend on whether memories reside in complex arrangements, but on how memories interact with one another during acquisition. We therefore emphasize how intricate study design details that alter the nature of learning and/or participant intentions impact the outcomes of sleep reactivation. In some cases, complex networks of memories interact harmoniously to bring about mutual memory benefits; in other cases, memories interact antagonistically and produce selective impairments in retrieval. Ultimately, although this burgeoning area of research has yet to be systematically explored, results suggest that the fate of reactivated stimuli within complex arrangements depends on how they were learned.

Modulation of sleep using noninvasive stimulations during sleep

Among the various sleep modulation methods for improving sleep, three methods using noninvasive stimulation during sleep have been reviewed and summarized. The first method involves noninvasive direct brain stimulation to induce a current directly in the brain cortex. Electrically or magnetically applied stimulations trigger electrical events such as slow oscillations or sleep spindles, which can also be recorded by an electroencephalogram. The second method involves sensory stimulation during sleep, which provides stimulation through the sensory pathway to invoke equivalent brain activity like direct brain stimulation. Olfactory, vestibular, and auditory stimulation methods have been used, resulting in several sleep-modulating effects, which are characteristic and depend on the experimental paradigm. The third method is to modulate sleep by shifting the autonomic balance affecting sleep homeostasis. To strengthen parasympathetic dominance, stimulation was applied to decrease heart rate by synchronizing the heart rhythm. These noninvasive stimulation methods can strengthen slow-wave sleep, consolidate declarative or procedural memory, and modify sleep macrostructure. These stimulation methods provide evidence and possibility for sleep modulation in our daily life as an alternative method for the treatment of disturbed sleep and enhancing sleep quality and performance beyond the average level.

Targeted memory reactivation during sleep influences social bias as a function of slow-oscillation phase and delta power

To understand how memories are reactivated and consolidated during sleep, experimenters have employed the unobtrusive re-presentation of memory cues from a variety of pre-sleep learning tasks. Using this procedure, known as targeted memory reactivation (TMR), we previously found that reactivation of counter-social-bias training during post-training sleep could selectively enhance training effects in reducing unintentional social biases. Here, we describe re-analyses of electroencephalographic (EEG) data from this previous study to characterize neurophysiological correlates of TMR-induced bias reduction. We found that TMR benefits in bias reduction were associated with (a) the timing of memory-related cue presentation relative to the 0.1-1.5 Hz slow-oscillation phase and (b) cue-elicited EEG power within the 1-4 Hz delta range. Although cue delivery was at a fixed rate in this study and not contingent on the slow-oscillation phase, cues were found to be clustered in slow-oscillation upstates for those participants with stronger TMR benefits. Similarly, higher cue-elicited delta power 250-1000 ms after cue onset was also linked with larger TMR benefits. These electrophysiological results substantiate the claim that memory reactivation altered social bias in the original study, while also informing neural explanations of these benefits. Future research should consider these sleep physiology parameters in relation to TMR applications and to memory reactivation in general.

Memory consolidation during sleep involves context reinstatement in humans

New memories are not quarantined from each other when first encoded; rather, they are interlinked with memories that were encoded in temporal proximity or that share semantic features. By selectively biasing memory processing during sleep, here we test whether context influences sleep consolidation. Participants first formed 18 idiosyncratic narratives, each linking four objects together. Before sleep, they also memorized an on-screen position for each object. During sleep, 12 object-specific sounds were unobtrusively presented, thereby cuing the corresponding spatial memories and impacting spatial recall as a function of initial memory strength. As hypothesized, we find that recall for non-cued objects contextually linked with cued objects also changed. Post-cue electrophysiological responses suggest that activity in the sigma band supports context reinstatement and predicts context-related memory benefits. Concurrently, context-specific electrophysiological activity patterns emerge during sleep. We conclude that reactivation of individual memories during sleep evokes reinstatement of their context, thereby impacting consolidation of associated knowledge.

Functional MRI reveals brain-wide actions of thalamically-initiated oscillatory activities on associative memory consolidation

As a key oscillatory activity in the brain, thalamic spindle activities are long believed to support memory consolidation. However, their propagation characteristics and causal actions at systems level remain unclear. Using functional MRI (fMRI) and electrophysiology recordings in male rats, we found that optogenetically-evoked somatosensory thalamic spindle-like activities targeted numerous sensorimotor (cortex, thalamus, brainstem and basal ganglia) and non-sensorimotor limbic regions (cortex, amygdala, and hippocampus) in a stimulation frequency- and length-dependent manner. Thalamic stimulation at slow spindle frequency (8 Hz) and long spindle length (3 s) evoked the most robust brain-wide cross-modal activities. Behaviorally, evoking these global cross-modal activities during memory consolidation improved visual-somatosensory associative memory performance. More importantly, parallel visual fMRI experiments uncovered response potentiation in brain-wide sensorimotor and limbic integrative regions, especially superior colliculus, periaqueductal gray, and insular, retrosplenial and frontal cortices. Our study directly reveals that thalamic spindle activities propagate in a spatiotemporally specific manner and that they consolidate associative memory by strengthening multi-target memory representation.

Sleep-A brain-state serving systems memory consolidation

Although long-term memory consolidation is supported by sleep, it is unclear how it differs from that during wakefulness. Our review, focusing on recent advances in the field, identifies the repeated replay of neuronal firing patterns as a basic mechanism triggering consolidation during sleep and wakefulness. During sleep, memory replay occurs during slow-wave sleep (SWS) in hippocampal assemblies together with ripples, thalamic spindles, neocortical slow oscillations, and noradrenergic activity. Here, hippocampal replay likely favors the transformation of hippocampus-dependent episodic memory into schema-like neocortical memory. REM sleep following SWS might balance local synaptic rescaling accompanying memory transformation with a sleep-dependent homeostatic process of global synaptic renormalization. Sleep-dependent memory transformation is intensified during early development despite the immaturity of the hippocampus. Overall, beyond its greater efficacy, sleep consolidation differs from wake consolidation mainly in that it is supported, rather than impaired, by spontaneous hippocampal replay activity possibly gating memory formation in neocortex.

Topographic-dynamic reorganisation model of dreams (TRoD) - A spatiotemporal approach

Dreams are one of the most bizarre and least understood states of consciousness. Bridging the gap between brain and phenomenology of (un)conscious experience, we propose the Topographic-dynamic Re-organization model of Dreams (TRoD). Topographically, dreams are characterized by a shift towards increased activity and connectivity in the default-mode network (DMN) while they are reduced in the central executive network, including the dorsolateral prefrontal cortex (except in lucid dreaming). This topographic re-organization is accompanied by dynamic changes; a shift towards slower frequencies and longer timescales. This puts dreams dynamically in an intermediate position between awake state and NREM 2/SWS sleep. TRoD proposes that the shift towards DMN and slower frequencies leads to an abnormal spatiotemporal framing of input processing including both internally- and externally-generated inputs (from body and environment). In dreams, a shift away from temporal segregation to temporal integration of inputs results in the often bizarre and highly self-centric mental contents as well as hallucinatory-like states. We conclude that topography and temporal dynamics are core features of the TroD, which may provide the connection of neural and mental activity, e.g., brain and experience during dreams as their "common currency".

Sleep disruption by memory cues selectively weakens reactivated memories

A widely accepted view in memory research is that recently stored information can be reactivated during sleep, leading to memory strengthening. Two recent studies have shown that this effect can be reversed in participants with highly disrupted sleep. To test whether weakening of reactivated memories can result directly from sleep disruption, in this experiment we varied the intensity of memory reactivation cues such that some produced sleep arousals. Prior to sleep, participants (local community members) learned the locations of 75 objects, each accompanied by a sound naturally associated with that object. Location recall was tested before and after sleep, and a subset of the sounds was presented during sleep to provoke reactivation of the corresponding locations. Reactivation with sleep arousal weakened memories, unlike the improvement typically found after reactivation without sleep arousal. We conclude that reactivated memories can be selectively weakened during sleep, and that memory reactivation may strengthen or weaken memories depending on additional factors such as concurrent sleep disruption.

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.

Updating memories of unwanted emotions during human sleep

Post-learning sleep contributes to memory consolidation. Yet it remains contentious whether sleep affords opportunities to modify or update emotional memories, particularly when people would prefer to forget those memories. Here, we attempted to update memories during sleep, using spoken positive words paired with cues to recent memories of aversive events. Affective updating using positive words during human non-rapid eye movement (NREM) sleep, compared with using neutral words instead, reduced negative affective judgments in post-sleep tests, suggesting that the recalled events were perceived as less aversive. Electroencephalogram (EEG) analyses showed that positive words modulated theta and spindle/sigma activity; specifically, to the extent that theta power was larger for the positive words than for the memory cues that followed, participants judged the memory cues less negatively. Moreover, to the extent that sigma power was larger for the positive words than for the memory cues that followed, participants forgot more episodic details about aversive events. Notably, when the onset of individual positive words coincided with the up-phase of slow oscillations (a state characterized by increased cortical excitability during NREM sleep), affective updating was more successful. In sum, we altered the affective content of memories via the strategic pairing of positive words and memory cues during sleep, linked with EEG theta power increases and the slow oscillation up-phase. These findings suggest novel possibilities for modifying unwanted memories during sleep, which would not require people to consciously confront memories that they prefer to avoid.

L-DOPA increases slow-wave sleep duration and selectively modulates memory persistence in older adults

Introduction

Millions of people worldwide take medications such as L-DOPA that increase dopamine to treat Parkinson's disease. Yet, we do not fully understand how L-DOPA affects sleep and memory. Our earlier research in Parkinson's disease revealed that the timing of L-DOPA relative to sleep affects dopamine's impact on long-term memory. Dopamine projections between the midbrain and hippocampus potentially support memory processes during slow wave sleep. In this study, we aimed to test the hypothesis that L-DOPA enhances memory consolidation by modulating NREM sleep.

Methods

We conducted a double-blind, randomised, placebo-controlled crossover trial with healthy older adults (65-79 years, n = 35). Participants first learned a word list and were then administered long-acting L-DOPA (or placebo) before a full night of sleep. Before sleeping, a proportion of the words were re-exposed using a recognition test to strengthen memory. L-DOPA was active during sleep and the practice-recognition test, but not during initial learning.

Results

The single dose of L-DOPA increased total slow-wave sleep duration by approximately 11% compared to placebo, while also increasing spindle amplitudes around slow oscillation peaks and around 1-4 Hz NREM spectral power. However, behaviourally, L-DOPA worsened memory of words presented only once compared to re-exposed words. The coupling of spindles to slow oscillation peaks correlated with these differential effects on weaker and stronger memories. To gauge whether L-DOPA affects encoding or retrieval of information in addition to consolidation, we conducted a second experiment targeting L-DOPA only to initial encoding or retrieval and found no behavioural effects.

Discussion

Our results demonstrate that L-DOPA augments slow wave sleep in elderly, perhaps tuning coordinated network activity and impacting the selection of information for long-term storage. The pharmaceutical modification of slow-wave sleep and long-term memory may have clinical implications.

Clinical trial registration

Eudract number: 2015-002027-26; https://doi.org/10.1186/ISRCTN90897064, ISRCTN90897064.

Differential thalamocortical interactions in slow and fast spindle generation: A computational model

Cortical slow oscillations (SOs) and thalamocortical sleep spindles are two prominent EEG rhythms of slow wave sleep. These EEG rhythms play an essential role in memory consolidation. In humans, sleep spindles are categorized into slow spindles (8-12 Hz) and fast spindles (12-16 Hz), with different properties. Slow spindles that couple with the up-to-down phase of the SO require more experimental and computational investigation to disclose their origin, functional relevance and most importantly their relation with SOs regarding memory consolidation. To examine slow spindles, we propose a biophysical thalamocortical model with two independent thalamic networks (one for slow and the other for fast spindles). Our modeling results show that fast spindles lead to faster cortical cell firing, and subsequently increase the amplitude of the cortical local field potential (LFP) during the SO down-to-up phase. Slow spindles also facilitate cortical cell firing, but the response is slower, thereby increasing the cortical LFP amplitude later, at the SO up-to-down phase of the SO cycle. Neither the SO rhythm nor the duration of the SO down state is affected by slow spindle activity. Furthermore, at a more hyperpolarized membrane potential level of fast thalamic subnetwork cells, the activity of fast spindles decreases, while the slow spindles activity increases. Together, our model results suggest that slow spindles may facilitate the initiation of the following SO cycle, without however affecting expression of the SO Up and Down states.

Improving memory via automated targeted memory reactivation during sleep

A widely accepted view in memory research is that previously acquired information can be reactivated during sleep, leading to persistent memory storage. Targeted memory reactivation (TMR) was developed as a technique whereby specific memories can be reactivated during sleep using a sensory stimulus linked to prior learning. As a research tool, TMR can improve memory, raising the possibility that it may be useful for cognitive enhancement and clinical therapy. A major challenge for the expanded use of TMR is that a skilled operator must manually control stimulation, which is impractical in many settings. To address this limitation, we developed the SleepStim system for automated TMR in the home. SleepStim includes a smartwatch to collect movement and heart-rate data, plus a smartphone to emit auditory cues. A machine-learning model identifies periods of deep sleep and triggers TMR sounds within these periods. We tested whether this system could replicate the spatial-memory benefit of in-laboratory TMR. Participants learned locations of objects on a grid, and then half of the object locations were reactivated during sleep over 3 nights. Recall was tested each morning. In an experiment with 61 participants, the TMR effect was not significant but varied systematically with stimulus intensity; low-intensity but not high-intensity stimuli produced memory benefits. In a second experiment with 24 participants, we limited stimulus intensity and found that TMR reliably improved spatial memory, consistent with effects observed in laboratory studies. We conclude that SleepStim can effectively accomplish automated TMR, and that avoiding sleep disruption is critical for TMR benefits.

Electrophysiological markers of memory consolidation in the human brain when memories are reactivated during sleep

Sleep contributes to memory consolidation, we presume, because memories are replayed during sleep. Understanding this aspect of consolidation can help with optimizing normal learning in many contexts and with treating memory disorders and other diseases. Here, we systematically manipulated sleep-based processing using targeted memory reactivation; brief sounds coupled with presleep learning were quietly presented again during sleep, producing 1) recall improvements for specific spatial memories associated with those sounds and 2) physiological responses in the sleep electroencephalogram. Neural activity in the hippocampus and adjacent medial temporal cortex was thus found in association with memory consolidation during sleep. These findings advance understanding of consolidation by linking beneficial memory changes during sleep to both memory reactivation and specific patterns of brain activity.

Human accomplishments depend on learning, and effective learning depends on consolidation. Consolidation is the process whereby new memories are gradually stored in an enduring way in the brain so that they can be available when needed. For factual or event knowledge, consolidation is thought to progress during sleep as well as during waking states and to be mediated by interactions between hippocampal and neocortical networks. However, consolidation is difficult to observe directly but rather is inferred through behavioral observations. Here, we investigated overnight memory change by measuring electrical activity in and near the hippocampus. Electroencephalographic (EEG) recordings were made in five patients from electrodes implanted to determine whether a surgical treatment could relieve their seizure disorders. One night, while each patient slept in a hospital monitoring room, we recorded electrophysiological responses to 10 to 20 specific sounds that were presented very quietly, to avoid arousal. Half of the sounds had been associated with objects and their precise spatial locations that patients learned before sleep. After sleep, we found systematic improvements in spatial recall, replicating prior results. We assume that when the sounds were presented during sleep, they reactivated and strengthened corresponding spatial memories. Notably, the sounds also elicited oscillatory intracranial EEG activity, including increases in theta, sigma, and gamma EEG bands. Gamma responses, in particular, were consistently associated with the degree of improvement in spatial memory exhibited after sleep. We thus conclude that this electrophysiological activity in the hippocampus and adjacent medial temporal cortex reflects sleep-based enhancement of memory storage.

Shaping overnight consolidation via slow-oscillation closed-loop targeted memory reactivation

Sleep represents a window of opportunity to modulate the mnemonic fate of recent experiences. Prior work has shown that delivering auditory reminder cues can slow down overnight forgetting, and so does experimental enhancement of natural sleep rhythms. Here, we combined both methods to selectively provide auditory cues during moments of high (UP states) or low (DOWN states) neuronal excitability. We found that UP-state cueing enhanced ongoing UP states and led to significantly lower forgetting rates than DOWN-state cueing. Moreover, electrophysiological markers of memory reprocessing were more pronounced after UP-state cueing. These results illustrate the impact of delivering exogenous stimuli at optimal phases of endogenous brain rhythms and will help improve experimental approaches to strengthening memories during sleep.

Sleep constitutes a privileged state for new memories to reactivate and consolidate. Previous work has demonstrated that consolidation can be bolstered experimentally either via delivery of reminder cues (targeted memory reactivation [TMR]) or via noninvasive brain stimulation geared toward enhancing endogenous sleep rhythms. Here, we combined both approaches, controlling the timing of TMR cues with respect to ongoing slow-oscillation (SO) phases. Prior to sleep, participants learned associations between unique words and a set of repeating images (e.g., car) while hearing a prototypical image sound (e.g., engine starting). Memory performance on an immediate test vs. a test the next morning quantified overnight memory consolidation. Importantly, two image sounds were designated as TMR cues, with one cue delivered at SO UP states and the other delivered at SO DOWN states. A novel sound was used as a TMR control condition. Behavioral results revealed a significant reduction of overnight forgetting for words associated with UP-state TMR compared with words associated with DOWN-state TMR. Electrophysiological results showed that UP-state cueing led to enhancement of the ongoing UP state and was followed by greater spindle power than DOWN-state cueing. Moreover, UP-state (and not DOWN-state) cueing led to reinstatement of target image representations. Together, these results unveil the behavioral and mechanistic effects of delivering reminder cues at specific phases of endogenous sleep rhythms and mark an important step for the endeavor to experimentally modulate memories during sleep.

Real-time stimulation during sleep: prior findings, novel developments, and future perspectives

Real-time brain stimulation is a powerful technique that continues to gain importance in the field of sleep and cognition. In this special issue, we collected 14 articles about real-time stimulation during sleep, including one review, 12 research articles and one letter covering both human and rodent research from various fields. We hope this special issue sparks greater interest and inspires fellow sleep researchers and clinicians to develop new ideas in the exciting topic of real-time stimulation.

Effects of Anti-Seizure Medication on Sleep Spindles and Slow Waves in Drug-Resistant Epilepsy

There is a close bidirectional relationship between sleep and epilepsy. Anti-seizure medications (ASM) act to reduce seizure frequency but can also impact sleep; this remains a relatively unexplored field given the importance of sleep on seizure occurrence, memory consolidation, and quality of life. We compared the effect of poly-ASM treatment on a night of sleep compared to an unmedicated night in patients with drug-resistant epilepsy, where ASMs were withdrawn and later restored as part of their pre-surgical evaluation. Within-subject analysis between medicated and unmedicated nights showed ASMs increased spindle (11-16 Hz) power and decreased slow wave (0.1-2 Hz) amplitude. Spindles became less strongly coupled to slow waves in the ASM night compared to no-ASM night, with effects to both the phase and strength of coupling and correlated with slow wave reduction. These effects were not seen in age-matched controls from the same unit where ASMs were not changed between two nights. Overall, we found that ASM polytherapy not only changed specific sleep waveforms, but also the fine interplay of spindle/slow wave coupling. Since these sleep oscillations impact both seizure occurrence and memory consolidation, our findings provide evidence towards a decoupling impact of ASMs on sleep that should be considered in future studies of sleep and memory disruption in people with epilepsy.

Automated real-time EEG sleep spindle detection for brain-state-dependent brain stimulation

Sleep spindles are a hallmark electroencephalographic feature of non-rapid eye movement sleep, and are believed to be instrumental for sleep-dependent memory reactivation and consolidation. However, direct proof of their causal relevance is hard to obtain, and our understanding of their immediate neurophysiological consequences is limited. To investigate their causal role, spindles need to be targeted in real-time with sensory or non-invasive brain-stimulation techniques. While fully automated offline detection algorithms are well established, spindle detection in real-time is highly challenging due to their spontaneous and transient nature. Here, we present the real-time spindle detector, a robust multi-channel electroencephalographic signal-processing algorithm that enables the automated triggering of stimulation during sleep spindles in a phase-specific manner. We validated the real-time spindle detection method by streaming pre-recorded sleep electroencephalographic datasets to a real-time computer system running a Simulink® Real-Time™ implementation of the algorithm. Sleep spindles were detected with high levels of Sensitivity (~83%), Precision (~78%) and a convincing F1-Score (~81%) in reference to state-of-the-art offline algorithms (which reached similar or lower levels when compared with each other), for both naps and full nights, and largely independent of sleep scoring information. Detected spindles were comparable in frequency, duration, amplitude and symmetry, and showed the typical time-frequency characteristics as well as a centroparietal topography. Spindles were detected close to their centre and reliably at the predefined target phase. The real-time spindle detection algorithm therefore empowers researchers to target spindles during human sleep, and apply the stimulation method and experimental paradigm of their choice.

Mutual interaction between visual homeostatic plasticity and sleep in adult humans

Sleep and plasticity are highly interrelated, as sleep slow oscillations and sleep spindles are associated with consolidation of Hebbian-based processes. However, in adult humans, visual cortical plasticity is mainly sustained by homeostatic mechanisms, for which the role of sleep is still largely unknown. Here, we demonstrate that non-REM sleep stabilizes homeostatic plasticity of ocular dominance induced in adult humans by short-term monocular deprivation: the counterintuitive and otherwise transient boost of the deprived eye was preserved at the morning awakening (>6 hr after deprivation). Subjects exhibiting a stronger boost of the deprived eye after sleep had increased sleep spindle density in frontopolar electrodes, suggesting the involvement of distributed processes. Crucially, the individual susceptibility to visual homeostatic plasticity soon after deprivation correlated with the changes in sleep slow oscillations and spindle power in occipital sites, consistent with a modulation in early occipital visual cortex.

The space-time profiles of sleep spindles and their coordination with slow oscillations on the electrode manifold

Sleep spindles are important for sleep quality and cognitive functions, with their coordination with slow oscillations (SOs) potentially organizing cross-region reactivation of memory traces. Here, we describe the organization of spindles on the electrode manifold and their relation to SOs. We analyzed the sleep night EEG of 34 subjects and detected spindles and SOs separately at each electrode. We compared spindle properties (frequency, duration, and amplitude) in slow wave sleep (SWS) and Stage 2 sleep (S2); and in spindles that coordinate with SOs or are uncoupled. We identified different topographical spindle types using clustering analysis that grouped together spindles co-detected across electrodes within a short delay (±300 ms). We then analyzed the properties of spindles of each type, and coordination to SOs. We found that SWS spindles are shorter than S2 spindles, and spindles at frontal electrodes have higher frequencies in S2 compared to SWS. Furthermore, S2 spindles closely following an SO (about 10% of all spindles) show faster frequency, shorter duration, and larger amplitude than uncoupled ones. Clustering identified Global, Local, Posterior, Frontal-Right and Left spindle types. At centro-parietal locations, Posterior spindles show faster frequencies compared to other types. Furthermore, the infrequent SO-spindle complexes are preferentially recruiting Global SO waves coupled with fast Posterior spindles. Our results suggest a non-uniform participation of spindles to complexes, especially evident in S2. This suggests the possibility that different mechanisms could initiate an SO-spindle complex compared to SOs and spindles separately. This has implications for understanding the role of SOs-spindle complexes in memory reactivation.

Sleep-Specific Processing of Auditory Stimuli Is Reflected by Alpha and Sigma Oscillations

Recent research revealed a surprisingly large range of cognitive operations to be preserved during sleep in humans. The new challenge is therefore to understand functions and mechanisms of processes, which so far have been mainly investigated in awake subjects. The current study focuses on dynamic changes of brain oscillations and connectivity patterns in response to environmental stimulation during non-REM sleep. Our results indicate that aurally presented names were processed and neuronally differentiated across the wake-sleep spectrum. Simultaneously recorded EEG and MEG signals revealed two distinct clusters of oscillatory power increase in response to the stimuli: (1) vigilance state-independent θ synchronization occurring immediately after stimulus onset, followed by (2) sleep-specific α/σ synchronization peaking after stimulus offset. We discuss the possible role of θ, α, and σ oscillations during non-REM sleep, and work toward a unified theory of brain rhythms and their functions during sleep.SIGNIFICANCE STATEMENT Previous research has revealed (residual) capacity of the sleeping human brain to interact with the environment. How sensory processing is realized by the neural assemblies in different stages of sleep is however unclear. To tackle this question, we examined simultaneously recorded MEG and EEG data. We discuss the possible role of θ, α, and σ oscillations during non-REM sleep. In contrast to versatile θ band response that reflected early stimulus processing step, succeeding α and σ band activity was sensitive to the saliency of the incoming information, and contingent on the sleep stage. Our findings suggest that the specific reorganization of mechanisms involved in later stages of sensory processing takes place upon falling asleep.

[Sleep spindles-Function, detection and use as biomarker for diagnostics in psychiatry]

BACKGROUND

The sleep spindle is a graphoelement of an electroencephalogram (EEG), which can be observed in light and deep sleep. Alterations in spindle activity have been described for a range of psychiatric disorders. Due to their relatively constant properties, sleep spindles may therefore be potential biomarkers in psychiatric diagnostics.

METHOD

This article presents an overview of the state of the science on the characteristics and functions of the sleep spindle as well as known alterations of spindle activity in psychiatric disorders. Various methodological approaches and developments of spindle detection are explained with respect to their potential for application in psychiatric diagnostics.

RESULTS AND CONCLUSION

Although alterations in spindle activity in psychiatric disorders are known and have been described in detail, their exact potential for psychiatric diagnostics has yet to be fully determined. In this respect, the acquisition of knowledge in research is currently constrained by manual and automated methods for spindle detection, which require high levels of resources and are error prone. Newer approaches to spindle detection based on deep-learning procedures could overcome the difficulties of previous detection methods, and thus open up new possibilities for the practical application of sleep spindles as biomarkers in the psychiatric practice.

Sleep affects higher-level categorization of speech sounds, but not frequency encoding

Sleep can increase consolidation of new knowledge and skills. It is less clear whether sleep plays a role in other aspects of experience-dependent neuroplasticity, which underlie important human capabilities such as spoken language processing. Theories of sensory learning differ in their predictions; some imply rapid learning at early sensory levels, while other propose a slow, progressive timecourse such that higher-level categorical representations guide immediate, novice learning, while lower-level sensory changes do not emerge until later stages. In this study, we investigated the role of sleep across both behavioural and physiological indices of auditory neuroplasticity. Forty healthy young human adults (23 female) who did not speak a tonal language participated in the study. They learned to categorize non-native Mandarin lexical tones using a sound-to-category training paradigm, and were then randomly assigned to a Nap or Wake condition. Polysomnographic data were recorded to quantify sleep during a 3 h afternoon nap opportunity, or equivalent period of quiet wakeful activity. Measures of behavioural performance accuracy revealed a significant improvement in learning the sound-to-category training paradigm between Nap and Wake groups. Conversely, a neural index of fine sound encoding fidelity of speech sounds known as the frequency-following response (FFR) suggested no change due to sleep, and a null model was supported, using Bayesian statistics. Together, these results support theories that propose a slow, progressive and hierarchical timecourse for sensory learning. Sleep's effect may play the biggest role in the higher-level learning, although contributions to more protracted processes of plasticity that exceed the study duration cannot be ruled out.

A sleep schedule incorporating naps benefits the transformation of hierarchical knowledge

Study Objectives

The learning brain establishes schemas (knowledge structures) that benefit subsequent learning. We investigated how sleep and having a schema might benefit initial learning followed by rearranged and expanded memoranda. We concurrently examined the contributions of sleep spindles and slow-wave sleep to learning outcomes.

Methods

Fifty-three adolescents were randomly assigned to an 8 h Nap schedule (6.5 h nocturnal sleep with a 90-minute daytime nap) or an 8 h No-Nap, nocturnal-only sleep schedule. The study spanned 14 nights, simulating successive school weeks. We utilized a transitive inference task involving hierarchically ordered faces. Initial learning to set up the schema was followed by rearrangement of the hierarchy (accommodation) and hierarchy expansion (assimilation). The expanded sequence was restudied. Recall of hierarchical knowledge was tested after initial learning and at multiple points for all subsequent phases. As a control, both groups underwent a No-schema condition where the hierarchy was introduced and modified without opportunity to set up a schema. Electroencephalography accompanied the multiple sleep opportunities.

Results

There were main effects of Nap schedule and Schema condition evidenced by superior recall of initial learning, reordered and expanded memoranda. Improved recall was consistently associated with higher fast spindle density but not slow-wave measures. This was true for both nocturnal sleep and daytime naps.

Conclusion

A sleep schedule incorporating regular nap opportunities compared to one that only had nocturnal sleep benefited building of robust and flexible schemas, facilitating recall of the subsequently rearranged and expanded structured knowledge. These benefits appear to be strongly associated with fast spindles.

Clinical Trial registration

NCT04044885 (https://clinicaltrials.gov/ct2/show/NCT04044885).