Experience-dependent changes in cerebral activation during human REM sleep

Does targeted memory reactivation during slow-wave sleep and rapid eye movement 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 rapid eye movement (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 differential processing of novel memory traces when TMR is administered in distinctive physiological sleep states.

Similarity of brain activity patterns during learning and subsequent resting state predicts memory consolidation

Spontaneous reactivation of brain activity from learning to a subsequent off-line period has been implicated as a neural mechanism underlying memory consolidation. However, similarities in brain activity may also emerge as a result of individual, trait-like characteristics. Here, we introduced a novel approach for analyzing continuous electroencephalography (EEG) data to investigate learning-induced changes as well as trait-like characteristics in brain activity underlying memory consolidation. Thirty-one healthy young adults performed a learning task, and their performance was retested after a short (∼1 h) delay. Consolidation of two distinct types of information (serial-order and probability) embedded in the task were tested to reveal similarities in functional networks that uniquely predict the changes in the respective memory performance. EEG was recorded during learning and pre- and post-learning rest periods. To investigate brain activity associated with consolidation, we quantified similarities in EEG functional connectivity between learning and pre-learning rest (baseline similarity) and learning and post-learning rest (post-learning similarity). While comparable patterns of these two could indicate trait-like similarities, changes from baseline to post-learning similarity could indicate learning-induced changes, possibly spontaneous reactivation. Higher learning-induced changes in alpha frequency connectivity (8.5-9.5 Hz) were associated with better consolidation of serial-order information, particularly for long-range connections across central and parietal sites. The consolidation of probability information was associated with learning-induced changes in delta frequency connectivity (2.5-3 Hz) specifically for more local, short-range connections. Furthermore, there was a substantial overlap between the baseline and post-learning similarities and their associations with consolidation performance, suggesting robust (trait-like) differences in functional connectivity networks underlying memory processes.

Cerebral blood flow in sleep: A systematic review and meta-analysis

Sleep plays an essential role in physiology, allowing the brain and body to restore itself. Despite its critical role, our understanding of the underlying processes in the sleeping human brain is still limited. Sleep comprises several distinct stages with varying depths and temporal compositions. Cerebral blood flow (CBF), which delivers essential nutrients and oxygen to the brain, varies across brain regions throughout these sleep stages, reflecting changes in neuronal function and regulation. This systematic review and meta-analysis assesses global and regional CBF across sleep stages. We included, appraised, and summarized all 38 published sleep studies on CBF in healthy humans that were not or only slightly (<24 h) sleep deprived. Our main findings are that CBF varies with sleep stage and depth, being generally lowest in NREM sleep and highest in REM sleep. These changes appear to stem from sleep stage-specific regional brain activities that serve particular functions, such as alterations in consciousness and emotional processing.

Manipulated overlapping reactivation of multiple memories promotes explicit gist abstraction

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

Enhancing and advancing the understanding and study of dreaming and memory consolidation: Reflections, challenges, theoretical clarity, and methodological considerations

Empirical investigations that search for a link between dreaming and sleep-dependent memory consolidation have focused on testing for an association between dreaming of what was learned, and improved memory performance for learned material. Empirical support for this is mixed, perhaps owing to the inherent challenges presented by the nature of dreams, and methodological inconsistencies. The purpose of this paper is to address critically prevalent assumptions and practices, with the aim of clarifying and enhancing research on this topic, chiefly by providing a theoretical synthesis of existing models and evidence. Also, it recommends the method of Targeted Memory Reactivation (TMR) as a means for investigating if dream content can be linked to specific cued activations. Other recommendations to enhance research practice and enquiry on this subject are also provided, focusing on the HOW and WHY we search for memory sources in dreams, and what purpose (if any) they might serve.

Cerebellum in Alzheimer's disease and other neurodegenerative diseases: an emerging research frontier

The cerebellum is crucial for both motor and nonmotor functions. Alzheimer's disease (AD), alongside other dementias such as vascular dementia (VaD), Lewy body dementia (DLB), and frontotemporal dementia (FTD), as well as other neurodegenerative diseases (NDs) like Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), Huntington's disease (HD), and spinocerebellar ataxias (SCA), are characterized by specific and non-specific neurodegenerations in central nervous system. Previously, the cerebellum's significance in these conditions was underestimated. However, advancing research has elevated its profile as a critical node in disease pathology. We comprehensively review the existing evidence to elucidate the relationship between cerebellum and the aforementioned diseases. Our findings reveal a growing body of research unequivocally establishing a link between the cerebellum and AD, other forms of dementia, and other NDs, supported by clinical evidence, pathological and biochemical profiles, structural and functional neuroimaging data, and electrophysiological findings. By contrasting cerebellar observations with those from the cerebral cortex and hippocampus, we highlight the cerebellum's distinct role in the disease processes. Furthermore, we also explore the emerging therapeutic potential of targeting cerebellum for the treatment of these diseases. This review underscores the importance of the cerebellum in these diseases, offering new insights into the disease mechanisms and novel therapeutic strategies.

The new science of sleep: From cells to large-scale societies

In the past 20 years, more remarkable revelations about sleep and its varied functions have arguably been made than in the previous 200. Building on this swell of recent findings, this essay provides a broad sampling of selected research highlights across genetic, molecular, cellular, and physiological systems within the body, networks within the brain, and large-scale social dynamics. Based on this raft of exciting new discoveries, we have come to realize that sleep, in this moment of its evolution, is very much polyfunctional (rather than monofunctional), yet polyfunctional for reasons we had never previously considered. Moreover, these new polyfunctional insights powerfully reaffirm sleep as a critical biological, and thus health-sustaining, requisite. Indeed, perhaps the only thing more impressive than the unanticipated nature of these newly emerging sleep functions is their striking divergence, from operations of molecular mechanisms inside cells to entire group societal dynamics.

Consciousness and sleep

Sleep is a universal, essential biological process. It is also an invaluable window on consciousness. It tells us that consciousness can be lost but also that it can be regained, in all its richness, when we are disconnected from the environment and unable to reflect. By considering the neurophysiological differences between dreaming and dreamless sleep, we can learn about the substrate of consciousness and understand why it vanishes. We also learn that the ongoing state of the substrate of consciousness determines the way each experience feels regardless of how it is triggered-endogenously or exogenously. Dreaming consciousness is also a window on sleep and its functions. Dreams tell us that the sleeping brain is remarkably lively, recombining intrinsic activation patterns from a vast repertoire, freed from the requirements of ongoing behavior and cognitive control.

The cerebellum and its connections to other brain structures involved in motor and non-motor functions: A comprehensive review

The cerebellum has a large network of neurons that communicate with several brain structures and participate in different functions. Recent studies have demonstrated that the cerebellum is not only associated with motor functions but also participates in several non-motor functions. It is suggested that the cerebellum can modulate behavior through many connections with different nervous system structures in motor, sensory, cognitive, autonomic, and emotional processes. Recently, a growing number of clinical and experimental studies support this theory and provide further evidence. In light of recent findings, a comprehensive review is needed to summarize the knowledge on the influence of the cerebellum on the processing of different functions. Therefore, the aim of this review was to describe the neuroanatomical aspects of the activation of the cerebellum and its connections with other structures of the central nervous system in different behaviors.

Plasticity-stability dynamics during post-training processing of learning

Learning continues beyond the end of training. Post-training learning is supported by changes in plasticity and stability in the brain during both wakefulness and sleep. However, the lack of a unified measure for assessing plasticity and stability dynamics during training and post-training periods has limited our understanding of how these dynamics shape learning. Focusing primarily on procedural learning, we integrate work using behavioral paradigms and a recently developed measure, the excitatory-to-inhibitory (E/I) ratio, to explore the delicate balance between plasticity and stability and its relationship to post-training learning. This reveals plasticity-stability cycles during both wakefulness and sleep that enhance learning and protect it from new learning during post-training processing.

Brain plasticity underlying sleep-dependent motor consolidation after motor imagery

Motor imagery can, similarly to physical practice, improve motor performance through experience-based plasticity. Using magnetoencephalography, we investigated changes in brain activity associated with offline consolidation of motor sequence learning through physical practice or motor imagery. After an initial training session with either physical practice or motor imagery, participants underwent overnight consolidation. As control condition, participants underwent wake-related consolidation after training with motor imagery. Behavioral analyses revealed that overnight consolidation of motor learning through motor imagery outperformed wake-related consolidation (95% CI [0.02, 0.07], P < 0.001, RP2 = 0.05). As regions of interest, we selected the generators of event-related synchronization/desynchronization of alpha (8-12 Hz) and beta (15-30 Hz) oscillations, which predicted the level of performance on the motor sequence. This yielded a primary sensorimotor-premotor network for alpha oscillations and a cortico-cerebellar network for beta oscillations. The alpha network exhibited increased neural desynchronization after overnight consolidation compared to wake-related consolidation. By contrast, the beta network exhibited an increase in neural synchronization after wake-related consolidation compared to overnight consolidation. We provide the first evidence of parallel brain plasticity underlying behavioral changes associated with sleep-dependent consolidation of motor skill learning through motor imagery and physical practice.

Tripping on the edge of consciousness

Herein the major accomplishments, trials and tribulations, and epiphanies experienced by James M. Krueger over the course of his career in sleep research are presented. They include the characterization of a) the supranormal EEG delta waves occurring during NREMS post sleep loss, b) Factor S as a muramyl peptide, c) the physiological roles of cytokines in sleep regulation, d) multiple other sleep regulatory substances, e) the dramatic changes in sleep over the course of infectious diseases, and f) sleep initiation within small neuronal/glial networks. The theory that the preservation of brain plasticity is the primordial sleep function is briefly discussed. These accomplishments resulted from collaborations with many outstanding scientists including James M. Krueger's mentors (John Pappenheimer and Manfred Karnovsky) and collaborators later in life, including Charles Dinarello, Louis Chedid, Mark Opp, Ferenc Obal jr., Dave Rector, Ping Taishi, Linda Toth, Jeannine Majde, Levente Kapas, Eva Szentirmai, Jidong Fang, Chris Davis, Sandip Roy, Tetsuya Kushikata, Fabio Garcia-Garcia, Ilia Karatsoreos, Mark Zielinski, and Alok De, plus many students, e.g. Jeremy Alt, Kathryn Jewett, Erika English, and Victor Leyva-Grado.

To "feel" better, sleep on it!

Emotional memories are consolidated during REM sleep.

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

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

Eye movements during phasic versus tonic rapid eye movement sleep are biomarkers of dissociable electroencephalogram processes for the consolidation of novel problem-solving skills

The hallmark eye movement (EM) bursts that occur during rapid eye movement (REM) sleep are markers of consolidation for procedural memory involving novel cognitive strategies and problem-solving skills. Examination of the brain activity associated with EMs during REM sleep might elucidate the processes involved in memory consolidation, and may uncover the functional significance of REM sleep and EMs themselves. Participants performed a REM-dependent, novel procedural problem-solving task (i.e. the Tower of Hanoi; ToH) before and after intervals of either overnight sleep (n = 20) or a daytime 8-hour wake period (n = 20). In addition, event-related spectral perturbation of the electroencephalogram (EEG) time-locked to EMs occurring either in bursts (i.e. phasic REM), or in isolation (i.e. tonic REM), were compared to sleep on a non-learning control night. ToH improvement was greater following sleep compared to wakefulness. During sleep, prefrontal theta (~2-8 Hz) and central-parietal-occipital sensorimotor rhythm (SMR) activity (~8-16 Hz) time-locked to EMs, were greater on the ToH night versus control night, and during phasic REM sleep, were both positively correlated with overnight memory improvements. Furthermore, SMR power during tonic REM increased significantly from the control night to ToH night, but was relatively stable from night to night during phasic REM. These results suggest that EMs are markers of learning-related increases in theta and SMR during phasic and tonic REM sleep. Phasic and tonic REM sleep may be functionally distinct in terms of their contribution to procedural memory consolidation.

Targeted memory reactivation in human REM sleep elicits detectable reactivation

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

Rule Abstraction Is Facilitated by Auditory Cuing in REM Sleep

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

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.

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.

Memory reactivations during sleep: a neural basis of dream experiences?

Newly encoded memory traces are spontaneously reactivated during sleep. Since their discovery in the 1990s, these memory reactivations have been discussed as a potential neural basis for dream experiences. New results from animal and human research, as well as from the rapidly growing field of sleep and dream engineering, provide essential insights into this question, and reveal both strong parallels and disparities between the two phenomena. We suggest that, although memory reactivations may contribute to subjective experiences across different states of consciousness, they are not likely to be the primary neural basis of dreaming. We identify important limitations in current research paradigms and suggest novel strategies to address this question empirically.

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.

Conscious entry into sleep: Yoga Nidra and accessing subtler states of consciousness

Human sleep is a dynamic and complex process comprising sleep stages with REM and NREM sleep characteristics that come in cycles. During sleep, there is a loss of responsiveness or a perceptual loss of conscious awareness with increasing thresholds for wakefulness as sleep progresses. There are brief bursts of wakefulness or Wake After Sleep Onset (WASO) throughout a nocturnal sleep. Conscious experience during nocturnal sleep is known to occur during lucid dreaming when one is aware during dreams when the dream is occurring. Most cultures have known lucid dreaming since antiquity. However, conscious experience during dreamless sleep is relatively lesser known. Nevertheless, selected Indo-Tibetan meditation literature has documented it since antiquity. Minimal Phenomenal Experience (MPE) research describes lucid dreamless sleep as its target phenomenology. "Conscious entry into sleep" posits tonic alertness is maintained post sleep onset through the sleep stages for sustained durations of time until an eventual loss of conscious awareness. Entering sleep consciously and being aware during dreamless sleep, including Slow Wave Activity, is plausibly to be in the state of "Yoga Nidra" or Yogic sleep. An attentive sleepful state provides access to subtler states of consciousness and significantly deepens the levels of silence. It is phenomenologically distinct from hypnagogic hallucinations and lucid dreaming. Unfortunately, sleep studies validating this phenomenology are yet to be done. Therefore, an experimental methodology akin to those used in lucid dreaming experiments is described.

Functional roles of REM sleep

Rapid eye movement (REM) sleep is an enigmatic and intriguing sleep state. REM sleep differs from non-REM sleep by its characteristic brain activity and from wakefulness by a reduced anti-gravity muscle tone. In addition to these key traits, diverse physiological phenomena appear across the whole body during REM sleep. However, it remains unclear whether these phenomena are the causes or the consequences of REM sleep. Experimental approaches using humans and animal models have gradually revealed the functional roles of REM sleep. Extensive efforts have been made to interpret the characteristic brain activity in the context of memory functions. Numerous physical and psychological functions of REM sleep have also been proposed. Moreover, REM sleep has been implicated in aspects of brain development. Here, we review the variety of functional roles of REM sleep, mainly as revealed by animal models. In addition, we discuss controversies regarding the functional roles of REM sleep.

Imagetic and affective measures of memory reverberation diverge at sleep onset in association with theta rhythm

The 'day residue' - the presence of waking memories into dreams - is a century-old concept that remains controversial in neuroscience. Even at the psychological level, it remains unclear how waking imagery cedes into dreams. Are visual and affective residues enhanced, modified, or erased at sleep onset? Are they linked, or dissociated? What are the neural correlates of these transformations? To address these questions we combined quantitative semantics, sleep EEG markers, visual stimulation, and multiple awakenings to investigate visual and affect residues in hypnagogic imagery at sleep onset. Healthy adults were repeatedly stimulated with an affective image, allowed to sleep and awoken seconds to minutes later, during waking (WK), N1 or N2 sleep stages. 'Image Residue' was objectively defined as the formal semantic similarity between oral reports describing the last image visualized before closing the eyes ('ground image'), and oral reports of subsequent visual imagery ('hypnagogic imagery). Similarly, 'Affect Residue' measured the proximity of affective valences between 'ground image' and 'hypnagogic imagery'. We then compared these grounded measures of two distinct aspects of the 'day residue', calculated within participants, to randomly generated values calculated across participants. The results show that Image Residue persisted throughout the transition to sleep, increasing during N1 in proportion to the time spent in this stage. In contrast, the Affect Residue was gradually neutralized as sleep progressed, decreasing in proportion to the time spent in N1 and reaching a minimum during N2. EEG power in the theta band (4.5-6.5 Hz) was inversely correlated with the Image Residue during N1. The results show that the visual and affective aspects of the 'day residue' in hypnagogic imagery diverge at sleep onset, possibly decoupling visual contents from strong negative emotions, in association with increased theta rhythm.

Advances in the understanding and enhancement of the human cognitive functions of learning and memory

Learning and memory are among the key cognitive functions that drive the human experience. As such, any defective condition associated with these cognitive domains could affect our navigation through everyday life. For years, researchers have been working toward having a clear understanding of how learning and memory work, as well as ways to improve them. Many advances have been made, as well as some challenges that have also been faced in the process. That notwithstanding, there are prospects with regards to the frontier of the enhancement of learning and memory in humans. This review article selectively highlights four broad areas of focus in research into the understanding and enhancement of learning and memory. Brain stimulation, effects of sleep, effects of stress and emotion, and synaptic plasticity are the main focal areas of this review, in terms of some pivotal research works, findings and theories.

Cortico-cortical and thalamo-cortical connectivity during non-REM and REM sleep: Insights from intracranial recordings in humans

OBJECTIVE

To study changes of thalamo-cortical and cortico-cortical connectivity during wakefulness, non-Rapid Eye Movement (non-REM) sleep, including N2 and N3 stages, and REM sleep, using stereoelectroencephalography (SEEG) recording in humans.

METHODS

We studied SEEG recordings of ten patients during wakefulness, non-REM sleep and REM sleep, in seven brain regions of interest including the thalamus. We calculated directed and undirected functional connectivity using a measure of non-linear correlation coefficient h².

RESULTS

The thalamus was more connected to other brain regions during N2 stage and REM sleep than during N3 stage during which cortex was more connected than the thalamus. We found two significant directed links: the first from the prefrontal region to the lateral parietal region in the delta band during N3 sleep and the second from the thalamus to the insula during REM sleep.

CONCLUSIONS

These results showed that cortico-cortical connectivity is more prominent in N3 stage than in N2 and REM sleep. During REM sleep we found significant thalamo-insular connectivity, with a driving role of the thalamus.

SIGNIFICANCE

We found a pattern of cortical connectivity during N3 sleep concordant with antero-posterior traveling slow waves. The thalamus seemed particularly involved as a hub of connectivity during REM sleep.

Neurobiology of dream activity and effects of stimulants on dreams

The sleep-wake cycle is the result of the activity of a multiple neurobiological network interaction. Dreaming feature is one interesting sleep phenomena that represents sensorial components, mostly visual perceptions, accompanied with intense emotions. Further complexity has been added to the topic of the neurobiological mechanism of dreams generation by the current data that suggests the influence of drugs on dream generation. Here, we discuss the review on some of the neurobiological mechanism of the regulation of dream activity, with special emphasis on the effects of stimulants on dreaming.

Discernible effects of tDCS over the primary motor and posterior parietal cortex on different stages of motor learning

Implicit motor learning and memory involve complex cortical and subcortical networks. The induction of plasticity in these network components via non-invasive brain stimulation, including transcranial direct current stimulation (tDCS), has shown to improve motor learning. However, studies showing these effects are mostly restricted to stimulation of the primary motor cortex (M1) during the early stage of learning. Because of this, we aimed to explore the efficacy of anodal tDCS applied over the posterior parietal cortex (PPC), which is involved in memory processes, on serial reaction time task (SRTT) performance. Specifically, to evaluate the involvement of both motor learning network components, we compared the effects of tDCS applied over regions corresponding to M1 and PPC during the early and late stages of learning. The results revealed a selective improvement of reaction time (RT) during anodal stimulation over the PPC in the late stage of learning. These findings support the assumption that the PPC is relevant during specific phases of learning, at least for SRTT performance. The results also indicate that not only the target area (i.e., PPC), but also timing is crucial for achieving the effects of stimulation on motor learning.

Episodic thought distinguishes spontaneous cognition in waking from REM and NREM sleep

Evidence suggests continuity between cognition in waking and sleeping states. However, one type of cognition that may differ is episodic thoughts of the past and future. The current study investigated this across waking, NREM sleep and REM sleep. We analyzed thought reports obtained from a large sample of individuals (N = 138) who underwent experience-sampling during wakefulness as well as serial awakenings in sleep. Our data suggest that while episodic thoughts are common during waking spontaneous thought, episodic thoughts of both the past and the future rarely occur in either N2 or REM sleep. Moreover, replicating previous findings, episodic thoughts during wakefulness exhibit a strong prospective bias and frequently involve autobiographical planning. Together, these results suggest that the occurrence of spontaneous episodic thoughts differs substantially across waking and dreaming sleep states. We suggest that this points to a difference in the way that human consciousness is typically experienced across the sleep-wake cycle.

Prevalence and Risk Factors for Rapid Eye Movement-Related Obstructive Sleep Apnea in Children

OBJECTIVES

Different pathophysiological mechanisms and the distribution of respiratory events among rapid eye movement (REM) and non-rapid eye movement (NREM) sleep modulate the effect of obstructive sleep apnea (OSA). We aimed to study the prevalence and risk factors for REM-related OSA in children.

STUDY DESIGN

Retrospective, cross-sectional study.

METHODS

We recruited 366 children with OSA confirmed by polysomnography (PSG) over a 5-year period. REM-related OSA is defined by an obstructive apnea-hypopnea index (OAHI) in the REM sleep ≥2× than during NREM sleep.

RESULTS

The prevalence of REM-related OSA in children was 50.3%. Children with REM-related OSA were more likely to be female (P = 0.042), and had lower prevalence of adenotonsillar hypertrophy (P = 0.043) compared with children with other OSA subtypes. Children with REM-related OSA slept longer in the supine position (P = 0.003), had shorter duration of NREM1 sleep (P = 0.018), lower nadir SpO₂ (P = 0.005), and a higher oxygen desaturation index 3% (ODI3%) (P = 0.014), and lower arousal index (P = 0.034) compared with other OSA subtypes. Female gender and supine sleep was the independent risk factors for REM-related OSA.

CONCLUSION

The prevalence of REM-related OSA was 50.3%. OAHI_REM should be considered as an important parameter in future clinical research studies done in children with OSA.

A time series analysis of the relation between motor skill acquisition and sleep in infancy

To systematically examine the relation between motor milestone onset and disruption of night sleep in infancy, three families kept microgenetic, prospective, daily checklist diaries of their infants' motor behavior and sleep (197-313 observation days; 19,000 diary entries). Process control and interrupted time series analyses examined whether deviations from the moving average for night wakings and evening sleep duration were temporally linked to motor skill onset and tested for meaningful differences in individual sleep patterns before and after skill onset. Model assumptions defined skill onset as first day of occurrence or as mastery and moving average windows as 3, 7, or 14 days. Changes in infants' sleep patterns were associated with changing expertise for motor milestones. The temporal relation varied depending on infant and sleep parameter. Intensive longitudinal data collection may increase our understanding of micro-events in infant development.

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

STUDY OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Sleep Enhances Consolidation of Memory Traces for Complex Problem-Solving Skills

Sleep consolidates memory for procedural motor skills, reflected by sleep-dependent changes in the hippocampal-striatal-cortical network. Other forms of procedural skills require the acquisition of a novel strategy to solve a problem, which recruit overlapping brain regions and specialized areas including the caudate and prefrontal cortex. Sleep preferentially benefits strategy and problem-solving skills over the accompanying motor execution movements. However, it is unclear how acquiring new strategies benefit from sleep. Here, participants performed a task requiring the execution of a sequence of movements to learn a novel cognitive strategy. Participants performed this task while undergoing fMRI before and after an interval of either a full night sleep, a daytime nap, or wakefulness. Participants also performed a motor control task, which precluded the opportunity to learn the strategy. In this way, we subtracted motor execution-related brain activations from activations specific to the strategy. The sleep and nap groups experienced greater behavioral performance improvements compared to the wake group on the strategy-based task. Following sleep, we observed enhanced activation of the caudate in addition to other regions in the hippocampal-striatal-cortical network, compared to wakefulness. This study demonstrates that sleep is a privileged time to enhance newly acquired cognitive strategies needed to solve problems.

Replay of Learned Neural Firing Sequences during Rest in Human Motor Cortex

The offline “replay” of neural firing patterns underlying waking experience, previously observed in non-human animals, is thought to be a mechanism for memory consolidation. Here, we test for replay in the human brain by recording spiking activity from the motor cortex of two participants who had intracortical microelectrode arrays placed chronically as part of a brain-computer interface pilot clinical trial. Participants took a nap before and after playing a neurally controlled sequence-copying game that consists of many repetitions of one “repeated” sequence sparsely interleaved with varying “control” sequences. Both participants performed repeated sequences more accurately than control sequences, consistent with learning. We compare the firing rate patterns that caused the cursor movements when performing each sequence to firing rate patterns throughout both rest periods. Correlations with repeated sequences increase more from pre- to post-task rest than do correlations with control sequences, providing direct evidence of learning-related replay in the human brain.

Eichenlaub et al. show that in the motor cortex of brain-computer interface trial participants, the firing rate patterns corresponding to a previously learned motor sequence are replayed during rest. These findings provide direct evidence of memory replay in the human brain.

Whole-body procedural learning benefits from targeted memory reactivation in REM sleep and task-related dreaming

Sleep facilitates memory consolidation through offline reactivations of memory traces. Dreaming may play a role in memory improvement and may reflect these memory reactivations. To experimentally address this question, we used targeted memory reactivation (TMR), i.e., application, during sleep, of a stimulus that was previously associated with learning, to assess whether it influences task-related dream imagery (or task-dream reactivations). Specifically, we asked if TMR or task-dream reactivations in either slow-wave (SWS) or rapid eye movement (REM) sleep benefit whole-body procedural learning. Healthy participants completed a virtual reality (VR) flying task prior to and following a morning nap or rest period during which task-associated tones were readministered in either SWS, REM sleep, wake or not at all. Findings indicate that learning benefits most from TMR when applied in REM sleep compared to a Control-sleep group. REM dreams that reactivated kinesthetic elements of the VR task (e.g., flying, accelerating) were also associated with higher improvement on the task than were dreams that reactivated visual elements (e.g., landscapes) or that had no reactivations. TMR did not itself influence dream content but its effects on performance were greater when coexisting with task-dream reactivations in REM sleep. Findings may help explain the mechanistic relationships between dream and memory reactivations and may contribute to the development of sleep-based methods to optimize complex skill learning.

Motor imagery practice benefits during arm immobilization

Motor imagery (MI) is known to engage motor networks and is increasingly used as a relevant strategy in functional rehabilitation following immobilization, whereas its effects when applied during immobilization remain underexplored. Here, we hypothesized that MI practice during 11 h of arm-immobilization prevents immobilization-related changes at the sensorimotor and cortical representations of hand, as well as on sleep features. Fourteen participants were tested after a normal day (without immobilization), followed by two 11-h periods of immobilization, either with concomitant MI treatment or control tasks, one week apart. At the end of each condition, participants were tested on a hand laterality judgment task, then underwent transcranial magnetic stimulation to measure cortical excitability of the primary motor cortices (M1), followed by a night of sleep during which polysomnography data was recorded. We show that MI treatment applied during arm immobilization had beneficial effects on (1) the sensorimotor representation of hands, (2) the cortical excitability over M1 contralateral to arm-immobilization, and (3) sleep spindles over both M1s during the post-immobilization night. Furthermore, (4) the time spent in REM sleep was significantly longer, following the MI treatment. Altogether, these results support that implementing MI during immobilization may limit deleterious effects of limb disuse, at several levels of sensorimotor functioning.

Post-Training Sleep Modulates Topographical Relearning-Dependent Resting State Activity

Continuation of experience-dependent neural activity during offline sleep and wakefulness episodes is a critical component of memory consolidation. Using functional magnetic resonance imaging (fMRI), offline consolidation effects have been evidenced probing behavioural and neurophysiological changes during memory retrieval, i.e., in the context of task practice. Resting state fMRI (rsfMRI) further allows investigating the offline evolution of recently learned information without the confounds of online task-related effects. We used rsfMRI to investigate sleep-related changes in seed-based resting functional connectivity (FC) and amplitude of low frequency fluctuations (ALFF) after spatial navigation learning and relearning. On Day 1, offline resting state activity was measured immediately before and after topographical learning in a virtual town. On Day 4, it was measured again before and after relearning in an extended version of the town. Navigation-related activity was also recorded during target retrieval, i.e., online. Participants spent the first post-training night under regular sleep (RS) or sleep deprivation (SD) conditions. Results evidence FC and ALFF changes in task-related neural networks, indicating the continuation of navigation-related activity in the resting state. Although post-training sleep did not modulate behavioural performance, connectivity analyses evidenced increased FC after post-training SD between navigation-related brain structures during relearning in the extended environment. These results suggest that memory traces were less efficiently consolidated after post-learning SD, eventually resulting in the use of compensatory brain resources to link previously stored spatial elements with the newly presented information.

Brains that Fire Together Wire Together: Interbrain Plasticity Underlies Learning in Social Interactions

Social interactions are powerful determinants of learning. Yet the field of neuroplasticity is deeply rooted in probing changes occurring in synapses, brain structures, and networks within an individual brain. Here I synthesize disparate findings on network neuroplasticity and mechanisms of social interactions to propose a new approach for understanding interaction-based learning that focuses on the dynamics of interbrain coupling. I argue that the facilitation effect of social interactions on learning may be explained by interbrain plasticity, defined here as the short- and long-term experience-dependent changes in interbrain coupling. The interbrain plasticity approach may radically change our understanding of how we learn in social interactions.

Investigation on Neurobiological Mechanisms of Dreaming in the New Decade

Dream research has advanced significantly over the last twenty years, thanks to the new applications of neuroimaging and electrophysiological techniques. Many findings pointed out that mental activity during sleep and wakefulness shared similar neural bases. On the other side, recent studies have highlighted that dream experience is promoted by significant brain activation, characterized by reduced low frequencies and increased rapid frequencies. Additionally, several studies confirmed that the posterior parietal area and prefrontal cortex are responsible for dream experience. Further, early results revealed that dreaming might be manipulated by sensory stimulations that would provoke the incorporation of specific cues into the dream scenario. Recently, transcranial stimulation techniques have been applied to modulate the level of consciousness during sleep, supporting previous findings and adding new information about neural correlates of dream recall. Overall, although multiple studies suggest that both the continuity and activation hypotheses provide a growing understanding of neural processes underlying dreaming, several issues are still unsolved. The impact of state-/trait-like variables, the influence of circadian and homeostatic factors, and the examination of parasomnia-like events to access dream contents are all opened issues deserving further deepening in future research.

Manual dexterity predicts phonological decoding speed in typical reading adults

Manual dexterity and phonological decoding involve the posterior parietal cortex, which controls location coding for visually guided actions, as well as a large fronto-cerebellar network. We studied the relationship between manual dexterity and reading ability in adult typical readers. Two measurements of manual dexterity were collected to index the procedural learning effect. A linear regression model demonstrated that phonological short-term memory, manual dexterity at time 1 and procedural learning of manual dexterity predicted phonological decoding speed. Similar results were found when left-hand dexterity at time 1 and procedural learning dexterity were entered last. The better one's phonological decoding skill was, the less fluent their manual dexterity was, suggesting a recycle from object-location to letter-location coding. However, the greater the procedural learning, the faster phonological decoding was, suggesting that larger plasticity of object-location coding was linked to better letter-location coding. An independent role of the interhemispheric connections or of the right posterior parietal cortex is also suggested.

Post-learning micro- and macro-structural neuroplasticity changes with time and sleep

Neuroplasticity refers to the fact that our brain can partially modify both structure and function to adequately respond to novel environmental stimulations. Neuroplasticity mechanisms are not only operating during the acquisition of novel information (i.e., online) but also during the offline periods that take place after the end of the actual learning episode. Structural brain changes as a consequence of learning have been consistently demonstrated on the long term using non-invasive neuroimaging methods, but short-term changes remained more elusive. Fortunately, the swift development of advanced MR methods over the last decade now allows tracking fine-grained cerebral changes on short timescales beyond gross volumetric modifications stretching over several days or weeks. Besides a mere effect of time, post-learning sleep mechanisms have been shown to play an important role in memory consolidation and promote long-lasting changes in neural networks. Sleep was shown to contribute to structural modifications over weeks of prolonged training, but studies evidencing more rapid post-training sleep structural effects linked to memory consolidation are still scarce in human. On the other hand, animal studies convincingly show how sleep might modulate synaptic microstructure. We aim here at reviewing the literature establishing a link between different types of training/learning and the resulting structural changes, with an emphasis on the role of post-training sleep and time in tuning these modifications. Open questions are raised such as the role of post-learning sleep in macrostructural changes, the links between different MR structural measurement-related modifications and the underlying microstructural brain processes, and bidirectional influences between structural and functional brain changes.

GABA-glutamate supramammillary neurons control theta and gamma oscillations in the dentate gyrus during paradoxical (REM) sleep

Several studies suggest that neurons from the lateral region of the SuM (SuML) innervating the dorsal dentate gyrus (DG) display a dual GABAergic and glutamatergic transmission and are specifically activated during paradoxical (REM) sleep (PS). The objective of the present study is to characterize the anatomical, neurochemical and electrophysiological properties of the SuML-DG projection neurons and to determine how they control DG oscillations and neuronal activation during PS and other vigilance states. For this purpose, we combine structural connectivity techniques using neurotropic viral vectors (rabies virus, AAV), neurochemical anatomy (immunohistochemistry, in situ hybridization) and imaging (light, electron and confocal microscopy) with in vitro (patch clamp) and in vivo (LFP, EEG) optogenetic and electrophysiological recordings performed in transgenic VGLUT2-cre male mice. At the cellular level, we show that the SuML-DG neurons co-release GABA and glutamate on dentate granule cells and increase the activity of a subset of DG granule cells. At the network level, we show that activation of the SuML-DG pathway increases theta power and frequency during PS as well as gamma power during PS and waking in the DG. At the behavioral level, we show that the activation of this pathway does not change animal behavior during PS, induces awakening during slow wave sleep and increases motor activity during waking. These results suggest that the SuML-DG pathway is capable of supporting the increase of theta and gamma power in the DG observed during PS and plays an important modulatory role of DG network activity during this state.

Complementary contributions of non-REM and REM sleep to visual learning

Sleep is beneficial for learning. However, it remains unclear whether learning is facilitated by non-REM (NREM) sleep or by REM sleep, whether it results from plasticity increases or stabilization, and whether facilitation results from learning-specific processing. Here, we trained volunteers on a visual task, and measured the excitatory and inhibitory (E/I) balance in early visual areas during subsequent sleep as an index of plasticity. E/I balance increased during NREM sleep irrespective of whether pre-sleep learning occurred, but it was associated with post-sleep performance gains relative to pre-sleep performance. By contrast, E/I balance decreased during REM sleep but only after pre-sleep training, and the decrease was associated with stabilization of pre-sleep learning. These findings indicate that NREM sleep promotes plasticity, leading to performance gains independent of learning, while REM sleep decreases plasticity to stabilize learning in a learning-specific manner.

Rapid eye movement sleep patterns of brain activation and deactivation occur within unique functional networks

Rapid eye movement (REM) sleep is a paradoxical state where the individual appears asleep while the electroencephalogram pattern resembles that of wakefulness. Regional differences in brain metabolism have been observed during REM sleep compared to wakefulness, but it is not known whether the spatial distribution of metabolic differences corresponds to known functional networks in the brain. Here, we use a combination of techniques to evaluate the networks associated with sites of REM sleep activation and deactivation from previously published positron emission tomography studies. We use seed‐based functional connectivity from healthy adults acquired during quiet rest to show that REM‐activation regions are functionally connected in a network that includes retrosplenial cingulate cortex, parahippocampal gyrus, and extrastriate visual cortices, corresponding to components of the default mode network and visual networks. Regions deactivated during REM sleep localize to right‐lateralized fronto‐parietal and salience networks. A negatively correlated relationship was observed between REM‐activation and deactivation networks. Together, these findings show that regional activation and deactivation patterns of REM sleep tend to occur in distinct functional connectivity networks that are present during wakefulness, providing insights regarding the differential contributions of brain regions to the distinct subjective experiences that occur during REM sleep (dreaming) relative to wakefulness.

Dreaming with hippocampal damage

The hippocampus is linked with both sleep and memory, but there is debate about whether a salient aspect of sleep - dreaming - requires its input. To address this question, we investigated if human patients with focal bilateral hippocampal damage and amnesia engaged in dreaming. We employed a provoked awakening protocol where participants were woken up at various points throughout the night, including during non-rapid eye movement and rapid eye movement sleep, to report their thoughts in that moment. Despite being roused a similar number of times, dream frequency was reduced in the patients compared to control participants, and the few dreams they reported were less episodic-like in nature and lacked content. These results suggest that hippocampal integrity may be necessary for typical dreaming to occur, and aligns dreaming with other hippocampal-dependent processes such as episodic memory that are central to supporting our mental life.

Mechanisms of offline motor learning at a microscale of seconds in large-scale crowdsourced data

Performance improvements during early human motor skill learning are suggested to be driven by short periods of rest during practice, at the scale of seconds. To reveal the unknown mechanisms behind these "micro-offline" gains, we leveraged the sampling power offered by online crowdsourcing (cumulative N over all experiments = 951). First, we replicated the original in-lab findings, demonstrating generalizability to subjects learning the task in their daily living environment (N = 389). Second, we show that offline improvements during rest are equivalent when significantly shortening practice period duration, thus confirming that they are not a result of recovery from performance fatigue (N = 118). Third, retroactive interference immediately after each practice period reduced the learning rate relative to interference after passage of time (N = 373), indicating stabilization of the motor memory at a microscale of several seconds. Finally, we show that random termination of practice periods did not impact offline gains, ruling out a contribution of predictive motor slowing (N = 71). Altogether, these results demonstrate that micro-offline gains indicate rapid, within-seconds consolidation accounting for early skill learning.