Does Targeted Memory Reactivation during SWS and REM sleep have differential effects on mnemonic discrimination and generalization?

Targeted memory reactivation (TMR), or the presentation of learning-related cues during sleep, has been shown to benefit memory consolidation for specific memory traces when applied during non-rapid eye movement (NREM) sleep. Prior studies suggest that TMR during REM sleep may play a role in memory generalization processes, but evidence remains scarce. We tested the hypothesis that TMR exerts a differential effect on distinct mnemonic processes as a function of the sleep state (REM vs. NREM) in which TMR is delivered. Mnemonic discrimination and generalization of semantic categories were investigated using an adapted version of the Mnemonic Similarity Task, before and after sleep. Forty-eight participants encoded pictures from eight semantic categories, each associated with a sound. In the pre-sleep immediate test, they had to discriminate "old" (targets) from "similar" (lures) or "new" (foils) pictures. During sleep, half of the sounds were replayed in slow wave sleep (SWS) or REM sleep. Recognition, discrimination, and generalization memory indices were tested in the morning. These indices did not differ between SWS and REM TMR groups or reactivated and non-reactivated item categories. Additional results suggest a positive effect of TMR on performance for highly similar items mostly relying on mnemonic discrimination processes. During sleep, EEG activity after cue presentation increased in the delta-theta and sigma band in the SWS group, and in the beta band in the REM TMR group. These results do not support the hypothesis of a differential processing of novel memory traces when TMR is administered in distinctive physiological sleep states.

Motor learning- and consolidation-related resting state fast and slow brain dynamics across wake and sleep.

Motor skills dynamically evolve during practice and after training. Using magnetoencephalography, we investigated the neural dynamics underpinning motor learning and its consolidation in relation to sleep during resting-state periods after the end of learning (boost window, within 30 min) and at delayed time scales (silent 4 h and next day 24 h windows) with intermediate daytime sleep or wakefulness. Resting-state neural dynamics were investigated at fast (sub-second) and slower (supra-second) timescales using Hidden Markov modelling (HMM) and functional connectivity (FC), respectively, and their relationship to motor performance. HMM results show that fast dynamic activities in a Temporal/Sensorimotor state network predict individual motor performance, suggesting a trait-like association between rapidly recurrent neural patterns and motor behaviour. Short, post-training task re-exposure modulated neural network characteristics during the boost but not the silent window. Re-exposure-related induction effects were observed on the next day, to a lesser extent than during the boost window. Daytime naps did not modulate memory consolidation at the behavioural and neural levels. These results emphasise the critical role of the transient boost window in motor learning and memory consolidation and provide further insights into the relationship between the multiscale neural dynamics of brain networks, motor learning, and consolidation.

Reduced REM and N2 sleep, and lower dream intensity predict increased mind-wandering.

Mind-wandering is a mental state in which attention shifts from the present environment or current task to internally driven, self-referent mental content. Homeostatic sleep pressure seems to facilitate mind-wandering as indicated by studies observing links between increased mind-wandering and impaired sleep. Nevertheless, previous studies mostly relied on cross-sectional measurements and self-reports. We aimed to combine the accuracy of objective sleep measures with the use of self-reports in a naturalistic setting in order to examine if objective sleep parameters predict the tendency for increased mind-wandering on the following day. We used mobile sleep electroencephalographic (EEG) headbands and self-report scales over 7 consecutive nights in a group of 67 healthy participants yielding ~400 analyzable nights. Nights with more wakefulness and shorter REM and slow wave sleep were associated with poorer subjective sleep quality at the intraindividual level. Reduced REM and N2 sleep, as well as less intense dream experiences, predicted more mind-wandering the following day. Our micro-longitudinal study indicates that intraindividual fluctuations in the duration of specific sleep stages predict the perception of sleep quality as assessed in the morning, as well as the intensity of daytime mind-wandering the following hours. The combined application of sleep EEG assessments and self-reports over repeated assessments provides new insights into the subtle intraindividual, night-to-day associations between nighttime sleep and the next day's subjective experiences.

Frequency-dependent connectivity in large-scale resting-state brain networks during sleep.

Functional connectivity (FC) during sleep has been shown to break down as non-rapid eye movement (NREM) sleep deepens before returning to a state closer to wakefulness during rapid eye movement (REM) sleep. However, the specific spatial and temporal signatures of these fluctuations in connectivity patterns remain poorly understood. This study aimed to investigate how frequency-dependent network-level FC fluctuates during nocturnal sleep in healthy young adults using high-density electroencephalography (hdEEG). Specifically, we examined source-localized FC in resting-state networks during NREM2, NREM3 and REM sleep (sleep stages scored using a semi-automatic procedure) in the first three sleep cycles of 29 participants. Our results showed that FC within and between all resting-state networks decreased from NREM2 to NREM3 sleep in multiple frequency bands and all sleep cycles. The data also highlighted a complex modulation of connectivity patterns during the transition to REM sleep whereby delta and sigma bands hosted a persistence of the connectivity breakdown in all networks. In contrast, a reconnection occurred in the default mode and the attentional networks in frequency bands characterizing their organization during wake (i.e., alpha and beta bands, respectively). Finally, all network pairs (except the visual network) showed higher gamma-band FC during REM sleep in cycle three compared to earlier sleep cycles. Altogether, our results unravel the spatial and temporal characteristics of the well-known breakdown in connectivity observed as NREM sleep deepens. They also illustrate a complex pattern of connectivity during REM sleep that is consistent with network- and frequency-specific breakdown and reconnection processes.

Microstructural dynamics of motor learning and sleep-dependent consolidation: A diffusion imaging study.

Memory consolidation can benefit from post-learning sleep, eventually leading to long-term microstructural brain modifications to accommodate new memory representations. Non-invasive diffusion-weighted magnetic resonance imaging (DWI) allows the observation of (micro)structural brain remodeling after time-limited motor learning. Here, we combine conventional diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) that allows modeling dendritic and axonal complexity in gray matter to investigate with improved specificity the microstructural brain mechanisms underlying time- and sleep-dependent motor memory consolidation dynamics. Sixty-one young healthy adults underwent four DWI sessions, two sequential motor trainings, and a night of total sleep deprivation or regular sleep distributed over five days. We observed rapid-motor-learning-related remodeling in occipitoparietal, temporal, and motor-related subcortical regions, reflecting temporary dynamics in learning-related neuronal brain plasticity processes. Sleep-related consolidation seems not to exert a detectable impact on diffusion parameters, at least on the timescale of a few days.

Post-training sleep modulates motor adaptation and task-related beta oscillations.

Motor adaptation reflects the ability of the brain's sensorimotor system to flexibly deal with environmental changes to generate effective motor behaviour. Whether sleep contributes to the consolidation of motor adaptation remains controversial. In this study, we investigated the impact of sleep on motor adaptation and its neurophysiological correlates in a novel motor adaptation task that leverages a highly automatised motor skill, that is, typing. We hypothesised that sleep-associated memory consolidation would benefit motor adaptation and induce modulations in task-related beta band (13-30 Hz) activity during adaptation. Healthy young male experts in typing on the regular computer keyboard were trained to type on a vertically mirrored keyboard while brain activity was recorded using electroencephalography. Typing performance was assessed either after a full night of sleep with polysomnography or a similar period of daytime wakefulness. Results showed improved motor adaptation performance after nocturnal sleep but not after daytime wakefulness, and decreased beta power: (a) during mirrored typing as compared with regular typing; and (b) in the post-sleep versus the pre-sleep mirrored typing sessions. Furthermore, the slope of the electroencephalography signal, a measure of aperiodic brain activity, decreased during mirrored as compared with regular typing. Changes in the electroencephalography spectral slope from pre- to post-sleep mirrored typing sessions were correlated with changes in task performance. Finally, increased fast sleep spindle density (13-15 Hz) during the night following motor adaptation training was predictive of successful motor adaptation. These findings suggest that post-training sleep modulates neural activity supporting adaptive motor functions.

Prevalence of Insomnia and Sleep Habits during the First and Second Wave of COVID-19 in Belgium.

Belgium has one of the highest numbers of COVID-19 cases per 1 million inhabitants. The pandemic has led to significant societal changes with repercussions on sleep and on mental health. We aimed to investigate the effect of the first and the second wave of COVID-19 on the sleep of the Belgian populationWe launched two online questionnaires, one during the first lockdown (7240 respondents) and one during the second (3240 respondents), to test differences in self-reported clinical insomnia (as measured by the Insomnia Severity Index) and sleep habits during the two lockdowns in comparison with the pre-COVID period. The number of persons with clinical insomnia rose during the first lockdown (19.22%) and further during the second (28.91%) in comparison with pre-lockdown (7.04-7.66%). Bed and rise times were delayed and there was an increased time in bed and sleep onset latency. There was further a decrease in total sleep time and in sleep efficiency during both confinements. The prevalence of clinical insomnia quadrupled during the second wave in comparison with the pre-lockdown situation. Sleep habits were most altered in the younger population, indicating a greater risk for this group to develop a sleep-wake rhythm disorder.

Does Motor Memory Reactivation through Practice and Post-Learning Sleep Modulate Consolidation?

Retrieving previously stored information makes memory traces labile again and can trigger restabilization in a strengthened or weakened form depending on the reactivation condition. Available evidence for long-term performance changes upon reactivation of motor memories and the effect of post-learning sleep on their consolidation remains scarce, and so does the data on the ways in which subsequent reactivation of motor memories interacts with sleep-related consolidation. Eighty young volunteers learned (Day 1) a 12-element Serial Reaction Time Task (SRTT) before a post-training Regular Sleep (RS) or Sleep Deprivation (SD) night, either followed (Day 2) by morning motor reactivation through a short SRTT testing or no motor activity. Consolidation was assessed after three recovery nights (Day 5). A 2 × 2 ANOVA carried on proportional offline gains did not evidence significant Reactivation (Morning Reactivation/No Morning Reactivation; p = 0.098), post-training Sleep (RS/SD; p = 0.301) or Sleep*Reactivation interaction (p = 0.257) effect. Our results are in line with prior studies suggesting a lack of supplementary performance gains upon reactivation, and other studies that failed to disclose post-learning sleep-related effects on performance improvement. However, lack of overt behavioural effects does not detract from the possibility of sleep- or reconsolidation-related covert neurophysiological changes underlying similar behavioural performance levels.

Sleep-dependent structural neuroplasticity after a spatial navigation task: A diffusion imaging study.

Evidence for sleep-dependent changes in microstructural neuroplasticity remains scarce, despite the fact that it is a mandatory correlate of the reorganization of learning-related functional networks. We investigated the effects of post-training sleep on structural neuroplasticity markers measuring standard diffusion tensor imaging (DTI), mean diffusivity (MD), and the revised biophysical neurite orientation dispersion and density imaging (NODDI), free water fraction (FWF), and neurite density (NDI) parameters that enable disentangling whether MD changes result from modifications in neurites or in other cellular components (e.g., glial cells). Thirty-four healthy young adults were scanned using diffusion-weighted imaging (DWI) on Day1 before and after 40-min route learning (navigation) in a virtual environment, then were sleep deprived (SD) or slept normally (RS) for the night. After recovery sleep for 2 nights, they were scanned again (Day4) before and after 40-min route learning (navigation) in an extended environment. Sleep-related microstructural changes were computed on DTI (MD) and NODDI (NDI and FWF) parameters in the cortical ribbon and subcortical hippocampal and striatal regions of interest (ROIs). Results disclosed navigation learning-related decreased DWI parameters in the cortical ribbon (MD, FWF) and subcortical (MD, FWF, NDI) areas. Post-learning sleep-related changes were found at Day4 in the extended learning session (pre- to post-relearning percentage changes), suggesting a rapid sleep-related remodeling of neurites and glial cells subtending learning and memory processes in basal ganglia and hippocampal structures.

Sleep and dreaming in the light of reactive and predictive homeostasis.

Dreams are often viewed as fascinating but irrelevant mental epihenomena of the sleeping mind with questionable functional relevance. Despite long hours of oneiric activity, and high individual differences in dream recall, dreams are lost into oblivion. Here, we conceptualize dreaming and dream amnesia as inherent aspects of the reactive and predictive homeostatic functions of sleep. Mental activity during sleep conforms to the interplay of restorative processes and future anticipation, and particularly during the second half of the night, it unfolds as a special form of non-constrained, self-referent, and future-oriented cognitive process. Awakening facilitates constrained, goal-directed prospection that competes for shared neural resources with dream production and dream recall, and contributes to dream amnesia. We present the neurophysiological aspects of reactive and predictive homeostasis during sleep, highlighting the putative role of cortisol in predictive homeostasis and forgetting dreams. The theoretical and methodological aspects of our proposal are discussed in relation to the study of dreaming, dream recall, and sleep-related cognitive processes.

Lateralized tactile stimulation during NREM sleep globally increases both slow and fast frequency activities.

Slow frequency activity during non-rapid eye movement (NREM) sleep emerges from synchronized activity of widely distributed thalamo-cortical and cortico-cortical networks, reflecting homeostatic and restorative properties of sleep. Slow frequency activity exhibits a reactive nature, and can be increased by acoustic stimulation. Although non-invasive brain stimulation is a promising technique in basic and clinical sleep research, sensory stimulation studies focusing on modalities other than the acoustic are scarce. We explored here the potential of lateralized vibro-tactile stimulation (VTS) of the finger to locally modify electroencephalographic activity during nocturnal NREM sleep. Eight seconds-long sequences of vibro-tactile pulses were delivered at a rate of 1 Hz either to the left or to the right index finger, in addition to a sham condition, in fourteen healthy participants. VTS markedly increased slow frequency activity that peaked between 1-4 Hz but extended to higher (~13 Hz) frequencies, with fronto-central dominance. Enhanced slow frequency activity was accompanied by increased (14-22 Hz) fast frequency power peaking over central and posterior locations. VTS increased the amplitude of slow waves, especially during the first 3-4 s of stimulation. Noticeably, we did not observe local-hemispheric effects, that is, VTS resulted in a global cortical response regardless of stimulation laterality. VTS moderately increased slow and fast frequency activities in resting wakefulness, to a much lower extent compared to NREM sleep. The concomitant increase in slow and fast frequency activities in response to VTS indicates an instant homeostatic response coupled with wake-like, high-frequency activity potentially reflecting transient periods of increased environmental processing.

Impact of Sleep Fragmentation on Cognition and Fatigue.

Sleep continuity and efficacy are essential for optimal cognitive functions. How sleep fragmentation (SF) impairs cognitive functioning, and especially cognitive fatigue (CF), remains elusive. We investigated the impact of induced SF on CF through the TloadDback task, measuring interindividual variability in working memory capacity. Sixteen participants underwent an adaptation polysomnography night and three consecutive nights, once in a SF condition induced by non-awakening auditory stimulations, once under restorative sleep (RS) condition, counterbalanced within-subject. In both conditions, participants were administered memory, vigilance, inhibition and verbal fluency testing, and for CF the TloadDback, as well as sleep questionnaires and fatigue and sleepiness visual analog scales were administered. Subjective fatigue increased and sleep architecture was altered after SF (reduced sleep efficiency, percentage of N3 and REM, number of NREM and REM phases) despite similar total sleep time. At the behavioral level, only inhibition deteriorated after SF, and CF similarly evolved in RS and SF conditions. In line with prior research, we show that SF disrupts sleep architecture and exerts a deleterious impact on subjective fatigue and inhibition. However, young healthy participants appear able to compensate for CF induced by three consecutive SF nights. Further studies should investigate SF effects in extended and/or pathological disruption settings.

Predictive coding, multisensory integration, and attentional control: A multicomponent framework for lucid dreaming.

Lucid dreaming (LD) is a mental state in which we realize not being awake but are dreaming while asleep. It often involves vivid, perceptually intense dream images as well as peculiar kinesthetic sensations, such as flying, levitating, or out-of-body experiences. LD is in the cross-spotlight of cognitive neuroscience and sleep research as a particular case to study consciousness, cognition, and the neural background of dream experiences. Here, we present a multicomponent framework for the study and understanding of neurocognitive mechanisms and phenomenological aspects of LD. We propose that LD is associated with prediction error signals arising during sleep and occurring at higher or lower levels of the processing hierarchy. Prediction errors are resolved by generating a superordinate self-model able to integrate ambiguous stimuli arriving from sensory periphery and higher-order cortical regions. While multisensory integration enables lucidity maintenance and contributes to peculiar kinesthetic experiences, attentional control facilitates multisensory integration by dynamically regulating the balance between the influence of top-down mental models and the precision weighting of bottom-up sensory inputs. Our novel framework aims to link neural correlates of LD with current concepts of sleep and arousal regulation and provide testable predictions on interindividual differences in LD as well as neurocognitive mechanisms inducing lucid dreams.

Connectivity in Large-Scale Resting-State Brain Networks Is Related to Motor Learning: A High-Density EEG Study.

Previous research has shown that resting-state functional connectivity (rsFC) between different brain regions (seeds) is related to motor learning and motor memory consolidation. Using high-density electroencephalography (hdEEG), we addressed this question from a brain network perspective. Specifically, we examined frequency-dependent functional connectivity in resting-state networks from twenty-nine young healthy participants before and after they were trained on a motor sequence learning task. Consolidation was assessed with an overnight retest on the motor task. Our results showed training-related decreases in gamma-band connectivity within the motor network, and between the motor and functionally distinct resting-state networks including the attentional network. Brain-behavior correlation analyses revealed that baseline beta, delta, and theta rsFC were related to subsequent motor learning and memory consolidation such that lower connectivity within the motor network and between the motor and several distinct resting-state networks was correlated with better learning and overnight consolidation. Lastly, training-related increases in beta-band connectivity between the motor and the visual networks were related to greater consolidation. Altogether, our results indicate that connectivity in large-scale resting-state brain networks is related to-and modulated by-motor learning and memory consolidation processes. These finding corroborate previous seed-based connectivity research and provide evidence that frequency-dependent functional connectivity in resting-state networks is critically linked to motor learning and memory consolidation.

Recent advances in memory consolidation and information processing during sleep.

Increasingly studied in a systematic manner since the 1970s, the cognitive processes of the brain taking place during sleeping periods remain an important object of scrutiny in the scientific community. In particular, sleep has been demonstrated to play a significant role for learning and memory consolidation processes, and sleep scientists have started unravelling its underlying neurophysiological mechanisms. However, sleep remains a multidimensional phenomenon, and many questions remain left open for future research. In this selective review article, we address recent advances in particular domains in which sleep research has further progressed in the past decade. We highlight the developmental trajectory of sleep-dependent learning and memory consolidation processes, from their development in childhood to their potential impairments in ageing, and the nature and extent of our capabilities for information processing, learning, and memory reinforcement during sleep.

Resting state fast brain dynamics predict interindividual variability in motor performance.

Motor learning features rapid enhancement during practice then offline post-practice gains with the reorganization of related brain networks. We hypothesised that fast transient, sub-second variations in magnetoencephalographic (MEG) network activity during the resting-state (RS) reflect early learning-related plasticity mechanisms and/or interindividual motor variability in performance. MEG RS activity was recorded before and 20 min after motor learning. Hidden Markov modelling (HMM) of MEG power envelope signals highlighted 8 recurrent topographical states. For two states, motor performance levels were associated with HMM temporal parameters both in pre- and post-learning resting-state sessions. However, no association emerged with offline changes in performance. These results suggest a trait-like relationship between spontaneous transient neural dynamics at rest and interindividual variations in motor abilities. On the other hand, transient RS dynamics seem not to be state-dependent, i.e., modulated by learning experience and reflect neural plasticity, at least on the short timescale.

Impaired Sequential but Preserved Motor Memory Consolidation in Multiple Sclerosis Disease.

Studies investigating motor learning in patients with multiple sclerosis (MS) disease highlighted that MS patients exhibit similar learning performance than healthy controls, but that learning can be hampered by the progression of MS eventually leading to impaired efficiency of subcortical-cortical networks. We aimed at investigating whether the long-term, overnight consolidation of sequential motor memories is preserved in MS disease. Thirty-one patients with MS and two healthy control groups (27 young and 14 middle age) were tested over two consecutive days using a serial reaction time task. Performance was tested (a) 20 min after the end of learning at Day 1 to monitor transient offline, short-term increase in motor and sequential performance and (b) after 24 h on Day 2 to quantify overnight delayed changes in performance reflecting memory consolidation. Besides a slower overall RT in patients with MS, motor performance similarly evolved in all groups. Sequence learning as assessed by interference effects was similar in patients with MS and both control groups on Day 1 (Learning and 20-min test). In contrast, while interference effects keep increasing on Day 2 after 24 h (Relearning) in healthy control groups, it reverted to levels reached at the end of learning for patients with MS. Long-term consolidation of sequential knowledge is impaired in patients with MS. At the motor level, learning and overnight consolidation abilities are preserved in MS disease.

Order matters: sleep spindles contribute to memory consolidation only when followed by rapid-eye-movement sleep.

Sleep is known to benefit memory consolidation, but little is known about the contribution of sleep stages within the sleep cycle. The sequential hypothesis proposes that memories are first replayed during nonrapid-eye-movement (NREM or N) sleep and then integrated into existing networks during rapid-eye-movement (REM or R) sleep, two successive critical steps for memory consolidation. However, it lacks experimental evidence as N always precedes R sleep in physiological conditions. We tested this sequential hypothesis in patients with central hypersomnolence disorder, including patients with narcolepsy who present the unique, anti-physiological peculiarity of frequently falling asleep in R sleep before entering N sleep. Patients performed a visual perceptual learning task before and after daytime naps stopped after one sleep cycle, starting in N or R sleep and followed by the other stage (i.e. N-R vs. R-N sleep sequence). We compared over-nap changes in performance, reflecting memory consolidation, depending on the sleep sequence during the nap. Thirty-six patients who slept for a total of 67 naps were included in the analysis. Results show that sleep spindles are associated with memory consolidation only when N is followed by R sleep, that is in physiologically ordered N-R naps, thus providing support to the sequential hypothesis in humans. In addition, we found a negative effect of rapid-eye-movements in R sleep on perceptual consolidation, highlighting the complex role of sleep stages in the balance to remember and to forget.

Partially Preserved Processing of Musical Rhythms in REM but Not in NREM Sleep.

The extent of high-level perceptual processing during sleep remains controversial. In wakefulness, perception of periodicities supports the emergence of high-order representations such as the pulse-like meter perceived while listening to music. Electroencephalography (EEG) frequency-tagged responses elicited at envelope frequencies of musical rhythms have been shown to provide a neural representation of rhythm processing. Specifically, responses at frequencies corresponding to the perceived meter are enhanced over responses at meter-unrelated frequencies. This selective enhancement must rely on higher-level perceptual processes, as it occurs even in irregular (i.e., syncopated) rhythms where meter frequencies are not prominent input features, thus ruling out acoustic confounds. We recorded EEG while presenting a regular (unsyncopated) and an irregular (syncopated) rhythm across sleep stages and wakefulness. Our results show that frequency-tagged responses at meter-related frequencies of the rhythms were selectively enhanced during wakefulness but attenuated across sleep states. Most importantly, this selective attenuation occurred even in response to the irregular rhythm, where meter-related frequencies were not prominent in the stimulus, thus suggesting that neural processes selectively enhancing meter-related frequencies during wakefulness are weakened during rapid eye movement (REM) and further suppressed in non-rapid eye movement (NREM) sleep. These results indicate preserved processing of low-level acoustic properties but limited higher-order processing of auditory rhythms during sleep.

Local use-dependent activity triggers mind wandering: Resource depletion or executive dysfunction?

Mind wandering (MW) is a highly prevalent phenomenon despite its negative consequences on behavior. Current views about its origin share the idea that MW occurs due to changes in the executive functions system. Here, we argue that not all instances of MW are necessarily related to changes in that system. Combining results from MW and sleep research, we propose that MW could also be related to the depletion of resources in primary task-related networks. To test this hypothesis, participants performed four sessions of the texture discrimination task (TDT) on a day. The TDT is a perceptual learning task in which performance is negatively related to the local build-up of sleep pressure. During the TDT, MW was recorded in both a subjective (i.e., with thought probes) and an objective (i.e., phasic pupillary response) manner. Results showed that accuracy on the TDT was mirrored in the objective measure of MW. For the subjective measure, the pattern was similar to that of task performance but could not be interpreted as reliable. These results demonstrate that not all MW is necessarily related to changes in the executive system and support the hypothesis that MW could be related to the depletion of local, task-related resources. (PsycInfo Database Record (c) 2021 APA, all rights reserved).