Spontaneous neural activity during human slow wave sleep

Sleep and emotional functions

In this chapter, we review studies investigating the role of sleep in emotional functions. In particular, evidence has recently accumulated to show that brain regions involved in the processing of emotional and reward-related information are activated during sleep. We suggest that such activation of emotional and reward systems during sleep underlies the reprocessing and consolidation of memories with a high affective and motivational relevance for the organism. We also propose that these mechanisms occurring during sleep promote adapted cognitive and emotional responses in the waking state, including overnight performance improvement, creativity, and sexual functions. Activation across emotional-limbic circuits during sleep also appears to promote emotional maturation and the emergence of consciousness in the developing brain.

The cerebellum and sleep

The importance of the cerebellum in sleep disorders, and vice versa, is only beginning to be understood. Advanced neuroimaging modalities have revealed cerebellar changes in both common and rare sleep disorders. Sleep disorders in those with genetic cerebellar disease, such as spinocerebellar ataxia, Friedreich ataxia, Joubert syndrome, and ataxia-telangiectasia, include excessive daytime sleepiness, restless legs syndrome, periodic limb movements of sleep, obstructive apnea, central apnea, and rapid eye movement behavior disorder. Sleep medicine is an important and under-recognized part of the neurologic evaluation in those with cerebellar disease.

Sleep continuity and total sleep time are associated with task-switching and preparation in young and older adults

Ageing is associated with changes in sleep and decline executive functions, such as task-switching and task preparation. Given that sleep affects executive function, age-related changes in executive function may be attributable to changes in sleep. The present study used a sleep detection device to examine whether or not wake time after sleep onset and total sleep time moderated age differences in task-switching performance and participants' ability to reduce switch costs when given time to prepare. Participants were cognitively healthy [Mini Mental State Examination > 26] younger (n = 54; mean age = 22.9; 67.8% female) and older (n = 45; mean age 62.8; 71.1% female) adults. Using a task-switching paradigm, which manipulated preparation time, we found that smaller global switch costs were associated with lower wake time after sleep onset and longer total sleep time. Greater preparation effects on local switch costs and adoption of a task-set were associated with lower wake time after sleep onset, although this effect was significant only in older adults when stratified by age group. This association was independent of inhibition and working memory abilities. The lack of interactions between sleep and age group indicated that age differences in switch costs were not moderated by better sleep. Our results suggest that young and older adults may benefit similarly from lower wake time after sleep onset and longer total sleep time in overall performance, and individuals with less wake time after sleep onset are more likely to engage preparatory strategies to reduce switch costs and boost task-switching performance.

Two distinct synchronization processes in the transition to sleep: a high-density electroencephalographic study

OBJECTIVES

To assess how the characteristics of slow waves and spindles change in the falling-asleep process.

DESIGN

Participants undergoing overnight high-density electroencephalographic recordings were awakened at 15- to 30-min intervals. One hundred forty-one falling-asleep periods were analyzed at the scalp and source level.

SETTING

Sleep laboratory.

PARTICIPANTS

Six healthy participants.

INTERVENTIONS

Serial awakenings.

RESULTS

The number and amplitude of slow waves followed two dissociated, intersecting courses during the transition to sleep: slow wave number increased slowly at the beginning and rapidly at the end of the falling-asleep period, whereas amplitude at first increased rapidly and then decreased linearly. Most slow waves occurring early in the transition to sleep had a large amplitude, a steep slope, involved broad regions of the cortex, predominated over frontomedial regions, and preferentially originated from the sensorimotor and the posteromedial parietal cortex. Most slow waves occurring later had a smaller amplitude and slope, involved more circumscribed parts of the cortex, and had more evenly distributed origins. Spindles were initially sparse, fast, and involved few cortical regions, then became more numerous and slower, and involved more areas.

CONCLUSIONS

Our results provide evidence for two types of slow waves, which follow dissociated temporal courses in the transition to sleep and have distinct cortical origins and distributions. We hypothesize that these two types of slow waves result from two distinct synchronization processes: (1) a "bottom-up," subcorticocortical, arousal system-dependent process that predominates in the early phase and leads to type I slow waves, and (2) a "horizontal," corticocortical synchronization process that predominates in the late phase and leads to type II slow waves. The dissociation between these two synchronization processes in time and space suggests that they may be differentially affected by experimental manipulations and sleep disorders.

Narcoleptic Patients Show Fragmented EEG-Microstructure During Early NREM Sleep

Narcolepsy is a chronic disorder of the sleep-wake cycle with pathological shifts between sleep stages. These abrupt shifts are induced by a sleep-regulating flip-flop mechanism which is destabilized in narcolepsy without obvious alterations in EEG oscillations. Here, we focus on the question whether the pathology of narcolepsy is reflected in EEG microstate patterns. 30 channel awake and NREM sleep EEGs of 12 narcoleptic patients and 32 healthy subjects were analyzed. Fitting back the dominant amplitude topography maps into the EEG led to a temporal sequence of maps. Mean microstate duration, ratio total time (RTT), global explained variance (GEV) and transition probability of each map were compared between both groups. Nine patients reached N1, 5 N2 and only 4 N3. All healthy subjects reached at least N2, 19 also N3. Four dominant maps could be found during wakefulness and all NREM- sleep stages in healthy subjects. During N3, narcolepsy patients showed an additional fifth map. The mean microstate duration was significantly shorter in narcoleptic patients than controls, most prominent in deep sleep. Single maps' GEV and RTT were also altered in narcolepsy. Being aware of the limitation of our low sample size, narcolepsy patients showed wake-like features during sleep as reflected in shorter microstate durations. These microstructural EEG alterations might reflect the intrusion of brain states characteristic of wakefulness into sleep and an instability of the sleep-regulating flip-flop mechanism resulting not only in pathological switches between REM- and NREM-sleep but also within NREM sleep itself, which may lead to a microstructural fragmentation of the EEG.

The GABAergic parafacial zone is a medullary slow wave sleep-promoting center

Work in animals and humans suggest the existence of a slow–wave sleep (SWS) promoting/EEG synchronizing center in the mammalian lower brainstem. While sleep–active GABAergic neurons in the medullary parafacial zone (PZ) are needed for normal SWS, it remains unclear if these neurons can initiate and maintain SWS or EEG slow wave activity (SWA) in behaving mice. We used genetically targeted activation and optogenetic–based mapping to uncover the downstream circuitry engaged by SWS–promoting PZ neurons, and we show that this circuit uniquely and potently initiates SWS and EEG SWA, regardless of the time of day. PZ neurons monosynaptically innervate and release synaptic GABA onto parabrachial neurons that in turn project to and release synaptic glutamate onto cortically–projecting neurons of the magnocellular basal forebrain; hence a circuit substrate is in place through which GABAergic PZ neurons can potently trigger SWS and modulate the cortical EEG.

Post-error slowing as a consequence of disturbed low-frequency oscillatory phase entrainment

A common finding across many reaction time tasks is that people slow down on trials following errors, a phenomenon known as post-error slowing. In the present study, we tested a novel hypothesis about the neural mechanism underlying post-error slowing. Recent research has shown that when task-relevant stimuli occur in a rhythmic stream, neuronal oscillations entrain to the task structure, thereby enhancing reaction speed. We hypothesized that under such circumstances post-error slowing results from an error-induced disturbance of this endogenous brain rhythm. To test this hypothesis, we measured oscillatory EEG dynamics while human subjects performed a demanding discrimination task under time pressure. We found that low-frequency neuronal oscillations entrained to the stimulus presentation rhythm, and that the low-frequency phase at stimulus onset predicted the speed of responding. Importantly, we found that this entrainment was disrupted following errors, and that the degree of phase disturbance was closely related to the degree of post-error slowing on the subsequent trial. These results describe a new mechanism underlying behavioral changes following errors.

Sleep deprivation leads to a loss of functional connectivity in frontal brain regions

Background

The restorative effect of sleep on waking brain activity remains poorly understood. Previous studies have compared overall neural network characteristics after normal sleep and sleep deprivation. To study whether sleep and sleep deprivation might differentially affect subsequent connectivity characteristics in different brain regions, we performed a within-subject study of resting state brain activity using the graph theory framework adapted for the individual electrode level.

In balanced order, we obtained high-density resting state electroencephalography (EEG) in 8 healthy participants, during a day following normal sleep and during a day following total sleep deprivation. We computed topographical maps of graph theoretical parameters describing local clustering and path length characteristics from functional connectivity matrices, based on synchronization likelihood, in five different frequency bands. A non-parametric permutation analysis with cluster correction for multiple comparisons was applied to assess significance of topographical changes in clustering coefficient and path length.

Results

Significant changes in graph theoretical parameters were only found on the scalp overlying the prefrontal cortex, where the clustering coefficient (local integration) decreased in the alpha frequency band and the path length (global integration) increased in the theta frequency band. These changes occurred regardless, and independent of, changes in power due to the sleep deprivation procedure.

Conclusions

The findings indicate that sleep deprivation most strongly affects the functional connectivity of prefrontal cortical areas. The findings extend those of previous studies, which showed sleep deprivation to predominantly affect functions mediated by the prefrontal cortex, such as working memory. Together, these findings suggest that the restorative effect of sleep is especially relevant for the maintenance of functional connectivity of prefrontal brain regions.

Functional magnetic resonance imaging in narcolepsy and the kleine-levin syndrome

This work aims at reviewing the present state of the art when it comes to understanding the pathophysiology of narcolepsy and the Kleine-Levin syndrome (KLS) from a neuroimaging point of view. This work also aims at discussing future perspectives of functional neuroimaging in these sleep disorders. We focus on functional magnetic resonance imaging (fMRI), which is a technique for in vivo measurements of brain activation in neuronal circuitries under healthy and pathological conditions. fMRI has significantly increased the knowledge on the affected neuronal circuitries in narcolepsy and the Kleine-Levin syndrome. It has been shown that narcolepsy is accompanied with disturbances of the emotional and the closely related reward systems. In the Kleine Levin syndrome, fMRI has identified hyperactivation of the thalamus as a potential biomarker that could be used in the diagnostic procedure. The fMRI findings in both narcolepsy and the Kleine-Levin syndrome are in line with previous structural and functional imaging studies. We conclude that fMRI in combination with multi-modal imaging can reveal important details about the pathophysiology in narcolepsy and the Kleine-Levin syndrome. In the future, fMRI possibly gives opportunities for diagnostic support and prediction of treatment response in individual patients.

Network-dependent modulation of brain activity during sleep

Brain activity dynamically changes even during sleep. A line of neuroimaging studies has reported changes in functional connectivity and regional activity across different sleep stages such as slow-wave sleep (SWS) and rapid-eye-movement (REM) sleep. However, it remains unclear whether and how the large-scale network activity of human brains changes within a given sleep stage. Here, we investigated modulation of network activity within sleep stages by applying the pairwise maximum entropy model to brain activity obtained by functional magnetic resonance imaging from sleeping healthy subjects. We found that the brain activity of individual brain regions and functional interactions between pairs of regions significantly increased in the default-mode network during SWS and decreased during REM sleep. In contrast, the network activity of the fronto-parietal and sensory-motor networks showed the opposite pattern. Furthermore, in the three networks, the amount of the activity changes throughout REM sleep was negatively correlated with that throughout SWS. The present findings suggest that the brain activity is dynamically modulated even in a sleep stage and that the pattern of modulation depends on the type of the large-scale brain networks.

The pharmacology of human sleep, a work in progress?

More is now known about the human pharmacology of sleep than a decade ago, but there are still enormous gaps in our understanding and there is still a lack of effective, specific, goal-directed therapeutic agents. Perhaps this is not surprising considering sleep's plurality its patterns and internal structure varying across animal species and humans (changes through life span, variations across cultures and historical differences), not understanding the function or functions of sleep and the risk-aversive regulatory frameworks currently in place.

Memory consolidation by replay of stimulus-specific neural activity

Memory consolidation transforms initially labile memory traces into more stable representations. One putative mechanism for consolidation is the reactivation of memory traces after their initial encoding during subsequent sleep or waking state. However, it is still unknown whether consolidation of individual memory contents relies on reactivation of stimulus-specific neural representations in humans. Investigating stimulus-specific representations in humans is particularly difficult, but potentially feasible using multivariate pattern classification analysis (MVPA). Here, we show in healthy human participants that stimulus-specific activation patterns can indeed be identified with MVPA, that these patterns reoccur spontaneously during postlearning resting periods and sleep, and that the frequency of reactivation predicts subsequent memory for individual items. We conducted a paired-associate learning task with items and spatial positions and extracted stimulus-specific activity patterns by MVPA in a simultaneous electroencephalography and functional magnetic resonance imaging (fMRI) study. As a first step, we investigated the amount of fMRI volumes during rest that resembled either one of the items shown before or one of the items shown as a control after the resting period. Reactivations during both awake resting state and sleep predicted subsequent memory. These data are first evidence that spontaneous reactivation of stimulus-specific activity patterns during resting state can be investigated using MVPA. They show that reactivation occurs in humans and is behaviorally relevant for stabilizing memory traces against interference. They move beyond previous studies because replay was investigated on the level of individual stimuli and because reactivations were not evoked by sensory cues but occurred spontaneously.

Resting-state functional connectivity MRI reveals active processes central to cognition

Analysis of spontaneously correlated low-frequency activity fluctuations across the brain using functional magnetic resonance imaging (MRI)-commonly referred to as resting-state functional connectivity (RSFC) MRI-was initially seen as a useful tool for mapping functional-anatomic networks in the living human brain, characterizing brain changes and differences in clinical populations, and studying comparative anatomy across species. However, little was known about the potential relevance of RSFC to cognitive processes. Indeed, there has been considerable controversy and debate as to the utility of studying the resting-state in cognitive neuroscience. However, recent work has shown that RSFC, rather than merely reflecting passive or epiphenomenal activity within underlying functional-anatomic networks, reveals important dynamic processes that play an active role in cognition. RSFC has been associated with individual differences in a number of behavioral and cognitive domains, including perception, language, learning and memory, and the organization of conceptual knowledge. In this article, we review and integrate the latest research demonstrating that RSFC is functionally relevant to human behavior and higher-level cognition, and propose a hypothesis regarding its mechanism of action on functional network dynamics and cognition. We conclude that RSFC MRI will be an invaluable tool for future discovery of the fundamental neurocognitive interactions that underlie cognition. WIREs Cogn Sci 2014, 5:233-245. doi: 10.1002/wcs.1275 CONFLICT OF INTEREST: The authors have declared no conflicts of interest for this article. For further resources related to this article, please visit the WIREs website.

Alcohol and the sleeping brain

Alcohol acts as a sedative that interacts with several neurotransmitter systems important in the regulation of sleep. Acute administration of large amounts of alcohol prior to sleep leads to decreased sleep-onset latency and changes in sleep architecture early in the night, when blood alcohol levels are high, with subsequent disrupted, poor-quality sleep later in the night. Alcohol abuse and dependence are associated with chronic sleep disturbance, lower slow-wave sleep, and more rapid-eye-movement sleep than normal, that last long into periods of abstinence and may play a role in relapse. This chapter outlines the evidence for acute and chronic alcohol effects on sleep architecture and sleep electroencephalogram, evidence for tolerance with repeated administration, and possible underlying neurochemical mechanisms for alcohol's effects on sleep. Also discussed are sex differences as well as effects of alcohol on sleep homeostasis and circadian regulation. Evidence for the role of sleep disruption as a risk factor for developing alcohol dependence is discussed in the context of research conducted in adolescents. The utility of sleep-evoked potentials in the assessment of the effects of alcoholism on sleep and the brain and in abstinence-mediated recovery is also outlined. The chapter concludes with a series of questions that need to be answered to determine the role of sleep and sleep disturbance in the development and maintenance of problem drinking and the potential beneficial effects of the treatment of sleep disorders for maintenance of abstinence in alcoholism.

Neuroimaging studies of sleep and memory in humans

Human brain dynamics are nowadays routinely explored at the macroscopic level using a wide variety of non-invasive neuroimaging techniques, including single photon emission computed tomography (SPECT) and positron emission tomography (PET), near infrared spectroscopy (NIRS) and functional magnetic resonance imaging (fMRI). In the past decades, the application of brain imaging methods to the study of sleep raised a renewed interest for the field, especially in the domain of neuroscience. Indeed, these studies enabled researchers to characterize the functional neuroanatomy of sleep stages and identify the neural correlates of phasic and tonic sleep mechanisms. Furthermore, they provided the scientific community with tools to address the crucial question of brain plasticity processes during human sleep, the role of sleep-related plasticity for memory consolidation, and how sleep and the lack of post-training sleep impacts brain functioning in the neural networks underlying memory-related cognitive processes. This chapter reviews the contributions of neuroimaging to our understanding of the functional neuroanatomy of sleep and sleep stages, and discusses how sleep contributes to the long-term consolidation of recently acquired memories in light of contemporary neural models for memory consolidation during sleep.

The functional significance of delta oscillations in cognitive processing

Ample evidence suggests that electroencephalographic (EEG) oscillatory activity is linked to a broad variety of perceptual, sensorimotor, and cognitive operations. However, few studies have investigated the delta band (0.5-3.5 Hz) during different cognitive processes. The aim of this review is to present data and propose the hypothesis that sustained delta oscillations inhibit interferences that may affect the performance of mental tasks, possibly by modulating the activity of those networks that should be inactive to accomplish the task. It is clear that two functionally distinct and potentially competing brain networks can be broadly distinguished by their contrasting roles in attention to the external world vs. the internally directed mentation or concentration. During concentration, EEG delta (1-3.5 Hz) activity increases mainly in frontal leads in different tasks: mental calculation, semantic tasks, and the Sternberg paradigm. This last task is considered a working memory task, but in neural, as well as phenomenological, terms, working memory can be best understood as attention focused on an internal representation. In the Sternberg task, increases in power in the frequencies from 1 to 3.90 Hz in frontal regions are reported. In a Go/No-Go task, power increases at 1 Hz in both conditions were observed during 100-300 ms in central, parietal and temporal regions. However, in the No-Go condition, power increases were also observed in frontal regions, suggesting its participation in the inhibition of the motor response. Increases in delta power were also reported during semantic tasks in children. In conclusion, the results suggest that power increases of delta frequencies during mental tasks are associated with functional cortical deafferentation, or inhibition of the sensory afferences that interfere with internal concentration. These inhibitory oscillations would modulate the activity of those networks that should be inactive to accomplish the task.

Structural brain correlates of human sleep oscillations

Sleep is strongly conserved within species, yet marked and perplexing inter-individual differences in sleep physiology are observed. Combining EEG sleep recordings and high-resolution structural brain imaging, here we demonstrate that the morphology of the human brain offers one explanatory factor of such inter-individual variability. Gray matter volume in interoceptive and exteroceptive cortices correlated with the expression of slower NREM sleep spindle frequencies, supporting their proposed role in sleep protection against conscious perception. Conversely, and consistent with an involvement in declarative memory processing, gray matter volume in bilateral hippocampus was associated with faster NREM sleep spindle frequencies. In contrast to spindles, gray matter volume in the homeostatic sleep-regulating center of the basal forebrain/hypothalamus, together with the medial prefrontal cortex, accounted for individual differences in NREM slow wave oscillations. Together, such findings indicate that the qualitative and quantitative expression of human sleep physiology is significantly related to anatomically specific differences in macroscopic brain structure.

FACET - a "Flexible Artifact Correction and Evaluation Toolbox" for concurrently recorded EEG/fMRI data

Background

In concurrent EEG/fMRI recordings, EEG data are impaired by the fMRI gradient artifacts which exceed the EEG signal by several orders of magnitude. While several algorithms exist to correct the EEG data, these algorithms lack the flexibility to either leave out or add new steps. The here presented open-source MATLAB toolbox FACET is a modular toolbox for the fast and flexible correction and evaluation of imaging artifacts from concurrently recorded EEG datasets. It consists of an Analysis, a Correction and an Evaluation framework allowing the user to choose from different artifact correction methods with various pre- and post-processing steps to form flexible combinations. The quality of the chosen correction approach can then be evaluated and compared to different settings.

Results

FACET was evaluated on a dataset provided with the FMRIB plugin for EEGLAB using two different correction approaches: Averaged Artifact Subtraction (AAS, Allen et al., NeuroImage 12(2):230–239, 2000) and the FMRI Artifact Slice Template Removal (FASTR, Niazy et al., NeuroImage 28(3):720–737, 2005). Evaluation of the obtained results were compared to the FASTR algorithm implemented in the EEGLAB plugin FMRIB. No differences were found between the FACET implementation of FASTR and the original algorithm across all gradient artifact relevant performance indices.

Conclusion

The FACET toolbox not only provides facilities for all three modalities: data analysis, artifact correction as well as evaluation and documentation of the results but it also offers an easily extendable framework for development and evaluation of new approaches.

Neuroimaging studies in insomnia

Chronic insomnia is one of the most prevalent psychiatric disorders and has a significant impact on individual's health. However, the pathophysiology of the disorder is poorly understood. The current review focuses on neuroimaging findings in insomnia. In summary, the current data suggest the following: (1) insomnia is characterized by corticolimbic overactivity during sleep and wakefulness that interferes with sleep initiation and/or maintenance; (2) insomnia patients' daytime performance is associated with a hypoactivation of task-related areas; (3) neurochemically, insomnia patients are probably characterized by reduced cortical GABA levels; (4) insomnia may be associated with abnormal brain morphometry in the frontal cortex, hippocampus and/or anterior cingulate cortex. Future investigations should include larger sample sizes or longitudinal within-subject comparisons. Other possible methodological improvements are discussed.

Developmental changes in sleep and their relationships to psychiatric illnesses

PURPOSE OF REVIEW

Sleep undergoes major changes during development. Its relationship to the complex process of maturation in health and disease has recently received increased attention. This review aims to highlight the recent literature examining the interplay of altered sleep, brain development and emerging psychiatric illnesses in children and adolescents.

RECENT FINDINGS

In addition to a temporal relationship of sleep disturbances preceding the onset of psychiatric illnesses, a bi-directional interaction of altered sleep and symptom severity has increasingly been shown. Sleep architecture shows drastic age-dependent alterations on a structural level during the first 2 decades of life. However, findings regarding disease-specific patterns have remained inconsistent. On a functional level, recent evidence about sleep electroencephalographic characteristics points to a close relationship between slow waves, reflecting the depth of sleep, and cortical plasticity.

SUMMARY

Sleep provides a rich source of information to gain insight into both the healthy and disturbed processes of brain function and maturation. Emerging data suggest that the investigation of slow wave activity is a novel and promising tool for monitoring both of these processes. It is important to understand when and how deviations from typical developmental sleep alterations occur in order to improve prevention and early treatment of disorders affecting a substantial number of children and adolescents.

Consciousness in humans and non-human animals: recent advances and future directions

This joint article reflects the authors' personal views regarding noteworthy advances in the neuroscience of consciousness in the last 10 years, and suggests what we feel may be promising future directions. It is based on a small conference at the Samoset Resort in Rockport, Maine, USA, in July of 2012, organized by the Mind Science Foundation of San Antonio, Texas. Here, we summarize recent advances in our understanding of subjectivity in humans and other animals, including empirical, applied, technical, and conceptual insights. These include the evidence for the importance of fronto-parietal connectivity and of “top-down” processes, both of which enable information to travel across distant cortical areas effectively, as well as numerous dissociations between consciousness and cognitive functions, such as attention, in humans. In addition, we describe the development of mental imagery paradigms, which made it possible to identify covert awareness in non-responsive subjects. Non-human animal consciousness research has also witnessed substantial advances on the specific role of cortical areas and higher order thalamus for consciousness, thanks to important technological enhancements. In addition, much progress has been made in the understanding of non-vertebrate cognition relevant to possible conscious states. Finally, major advances have been made in theories of consciousness, and also in their comparison with the available evidence. Along with reviewing these findings, each author suggests future avenues for research in their field of investigation.

Enhanced spontaneous oscillations in the supplementary motor area are associated with sleep-dependent offline learning of finger-tapping motor-sequence task

Sleep is beneficial for various types of learning and memory, including a finger-tapping motor-sequence task. However, methodological issues hinder clarification of the crucial cortical regions for sleep-dependent consolidation in motor-sequence learning. Here, to investigate the core cortical region for sleep-dependent consolidation of finger-tapping motor-sequence learning, while human subjects were asleep, we measured spontaneous cortical oscillations by magnetoencephalography together with polysomnography, and source-localized the origins of oscillations using individual anatomical brain information from MRI. First, we confirmed that performance of the task at a retest session after sleep significantly increased compared with performance at the training session before sleep. Second, spontaneous δ and fast-σ oscillations significantly increased in the supplementary motor area (SMA) during post-training compared with pretraining sleep, showing significant and high correlation with the performance increase. Third, the increased spontaneous oscillations in the SMA correlated with performance improvement were specific to slow-wave sleep. We also found that correlations of δ oscillation between the SMA and the prefrontal and between the SMA and the parietal regions tended to decrease after training. These results suggest that a core brain region for sleep-dependent consolidation of the finger-tapping motor-sequence learning resides in the SMA contralateral to the trained hand and is mediated by spontaneous δ and fast-σ oscillations, especially during slow-wave sleep. The consolidation may arise along with possible reorganization of a larger-scale cortical network that involves the SMA and cortical regions outside the motor regions, including prefrontal and parietal regions.

Exercise benefits for the aging brain depend on the accompanying cognitive load: insights from sleep electroencephalogram

Although exercise clearly offsets aging effects on the body, its benefits for the aging brain are likely to depend on the extent that physical activity (especially locomotion) facilitates multisensory encounters, curiosity, and interactions with novel environments; this is especially true for exploratory activity, which occupies much of wakefulness for most mammals in the wild. Cognition is inseparable from physical activity, with both interlinked to promote neuroplasticity and more successful brain aging. In these respects and for humans, exercising in a static, featureless, artificially lit indoor setting contrasts with exploratory outdoor walking within a novel environment during daylight. However, little is known about the comparative benefits for the aging brain of longer-term daily regimens of this latter nature including the role of sleep, to the extent that sleep enhances neuroplasticity as shown in short-term laboratory studies. More discerning analyses of sleep electroencephalogram (EEG) slow-wave activity especially 0.5-2-Hz activity would provide greater insights into use-dependent recovery processes during longer-term tracking of these regimens and complement slower changing waking neuropsychologic and resting functional magnetic resonance imaging (fMRI) measures, including those of the brain's default mode network. Although the limited research only points to ephemeral small sleep EEG effects of pure exercise, more enduring effects seem apparent when physical activity incorporates cognitive challenges. In terms of "use it or lose it," curiosity-driven "getting out and about," encountering, interacting with, and enjoying novel situations may well provide the brain with its real exercise, further reflected in changes to the dynamics of sleep.

Concurrent synaptic and systems memory consolidation during sleep

Memories are consolidated during sleep by two apparently antagonistic processes: (1) reinforcement of memory-specific cortical interactions and (2) homeostatic reduction in synaptic efficiency. Using fMRI, we assessed whether episodic memories are processed during sleep by either or both mechanisms, by comparing recollection before and after sleep. We probed whether LTP influences these processes by contrasting two groups of individuals prospectively recruited based on BDNF rs6265 (Val66Met) polymorphism. Between immediate retrieval and delayed testing scheduled after sleep, responses to recollection increased significantly more in Val/Val individuals than in Met carriers in parietal and occipital areas not previously engaged in retrieval, consistent with "systems-level consolidation." Responses also increased differentially between allelic groups in regions already activated before sleep but only in proportion to slow oscillation power, in keeping with "synaptic downscaling." Episodic memories seem processed at both synaptic and systemic levels during sleep by mechanisms involving LTP.

Linking oscillations in cerebellar circuits

In many neuroscience fields, the study of local and global rhythmicity has been receiving increasing attention. These network influences could directly impact on how neuronal groups interact together, organizing for different contexts. The cerebellar cortex harbors a variety of such local circuit rhythms, from the rhythms in the cerebellar cortex per se, or those dictated from important afferents. We present here certain cerebellar oscillatory phenomena that have been recorded in rodents and primates. Those take place in a range of frequencies: from the more known oscillations in the 4-25 Hz band, such as the olivocerebellar oscillatory activity and the granule cell layer oscillations, to the more recently reported slow (<1 Hz oscillations), and the fast (>150 Hz) activity in the Purkinje cell layer. Many of these oscillations appear spontaneously in the circuits, and are modulated by behavioral imperatives. We review here how those oscillations are recorded, some of their modulatory mechanisms, and also identify some of the cerebellar nodes where they could interact. A particular emphasis has been placed on how these oscillations could be modulated by movement and certain neuropathological manifestations. Many of those oscillations could have a definite impact on the way information is processed in the cerebellum and how it interacts with other structures in a variety of contexts.

Sleep and dreaming are for important matters

Recent studies in sleep and dreaming have described an activation of emotional and reward systems, as well as the processing of internal information during these states. Specifically, increased activity in the amygdala and across mesolimbic dopaminergic regions during REM sleep is likely to promote the consolidation of memory traces with high emotional/motivational value. Moreover, coordinated hippocampal-striatal replay during NREM sleep may contribute to the selective strengthening of memories for important events. In this review, we suggest that, via the activation of emotional/motivational circuits, sleep and dreaming may offer a neurobehavioral substrate for the offline reprocessing of emotions, associative learning, and exploratory behaviors, resulting in improved memory organization, waking emotion regulation, social skills, and creativity. Dysregulation of such motivational/emotional processes due to sleep disturbances (e.g., insomnia, sleep deprivation) would predispose to reward-related disorders, such as mood disorders, increased risk-taking and compulsive behaviors, and may have major health implications, especially in vulnerable populations.

Dynamic interaction of spindles and gamma activity during cortical slow oscillations and its modulation by subcortical afferents

Slow oscillations are a hallmark of slow wave sleep. They provide a temporal framework for a variety of phasic events to occur and interact during sleep, including the expression of high-frequency oscillations and the discharge of neurons across the entire brain. Evidence shows that the emergence of distinct high-frequency oscillations during slow oscillations facilitates the communication among brain regions whose activity was correlated during the preceding waking period. While the frequencies of oscillations involved in such interactions have been identified, their dynamics and the correlations between them require further investigation. Here we analyzed the structure and dynamics of these signals in anesthetized rats. We show that spindles and gamma oscillations coexist but have distinct temporal dynamics across the slow oscillation cycle. Furthermore, we observed that spindles and gamma are functionally coupled to the slow oscillations and between each other. Following the activation of ascending pathways from the brainstem by means of a carbachol injection in the pedunculopontine nucleus, we were able to modify the gain in the gamma oscillations that are independent of the spindles while the spindle amplitude was reduced. Furthermore, carbachol produced a decoupling of the gamma oscillations that are dependent on the spindles but with no effect on their amplitude. None of the changes in the high-frequency oscillations affected the onset or shape of the slow oscillations, suggesting that slow oscillations occur independently of the phasic events that coexist with them. Our results provide novel insights into the regulation, dynamics and homeostasis of cortical slow oscillations.

Pharmacologically increasing sleep spindles enhances recognition for negative and high-arousal memories

Sleep affects declarative memory for emotional stimuli differently than it affects declarative memory for nonemotional stimuli. However, the interaction between specific sleep characteristics and emotional memory is not well understood. Recent studies on how sleep affects emotional memory have focused on rapid eye movement sleep (REM) but have not addressed non-REM sleep, particularly sleep spindles. This is despite the fact that sleep spindles are implicated in declarative memory as well as neural models of memory consolidation (e.g., hippocampal neural replay). Additionally, many studies examine a limited range of emotional stimuli and fail to disentangle differences in memory performance because of variance in valence and arousal. Here, we experimentally increase non-REM sleep features, sleep spindle density, and SWS, with pharmacological interventions using zolpidem (Ambien) and sodium oxybate (Xyrem) during daytime naps. We use a full spread of emotional stimuli to test all levels of valence and arousal. We find that increasing sleep spindle density increases memory discrimination (da) for highly arousing and negative stimuli without altering measures of bias (ca). These results indicate a broader role for sleep in the processing of emotional stimuli with differing effects based on arousal and valence, and they raise the possibility that sleep spindles causally facilitate emotional memory consolidation. These findings are discussed in terms of the known use of hypnotics in individuals with emotional mood disorders.

Sleep and the functional connectome

Sleep and the functional connectome are research areas with considerable overlap. Neuroimaging studies of sleep based on EEG-PET and EEG-fMRI are revealing the brain networks that support sleep, as well as networks that may support the roles and processes attributed to sleep. For example, phenomena such as arousal and consciousness are substantially modulated during sleep, and one would expect this modulation to be reflected in altered network activity. In addition, recent work suggests that sleep also has a number of adaptive functions that support waking activity. Thus the study of sleep may elucidate the circuits and processes that support waking function and complement information obtained from fMRI during waking conditions. In this review, we will discuss examples of this for memory, arousal, and consciousness after providing a brief background on sleep and on studying it with fMRI.

About sleep's role in memory

Over more than a century of research has established the fact that sleep benefits the retention of memory. In this review we aim to comprehensively cover the field of "sleep and memory" research by providing a historical perspective on concepts and a discussion of more recent key findings. Whereas initial theories posed a passive role for sleep enhancing memories by protecting them from interfering stimuli, current theories highlight an active role for sleep in which memories undergo a process of system consolidation during sleep. Whereas older research concentrated on the role of rapid-eye-movement (REM) sleep, recent work has revealed the importance of slow-wave sleep (SWS) for memory consolidation and also enlightened some of the underlying electrophysiological, neurochemical, and genetic mechanisms, as well as developmental aspects in these processes. Specifically, newer findings characterize sleep as a brain state optimizing memory consolidation, in opposition to the waking brain being optimized for encoding of memories. Consolidation originates from reactivation of recently encoded neuronal memory representations, which occur during SWS and transform respective representations for integration into long-term memory. Ensuing REM sleep may stabilize transformed memories. While elaborated with respect to hippocampus-dependent memories, the concept of an active redistribution of memory representations from networks serving as temporary store into long-term stores might hold also for non-hippocampus-dependent memory, and even for nonneuronal, i.e., immunological memories, giving rise to the idea that the offline consolidation of memory during sleep represents a principle of long-term memory formation established in quite different physiological systems.

Modulation of γ and spindle-range power by slow oscillations in scalp sleep EEG of children

Deep sleep is characterized by slow waves of electrical activity in the cerebral cortex. They represent alternating down states and up states of, respectively, hyperpolarization with accompanying neuronal silence and depolarization during which neuronal firing resumes. The up states give rise to faster oscillations, notably spindles and gamma activity which appear to be of major importance to the role of sleep in brain function and cognition. Unfortunately, while spindles are easily detectable, gamma oscillations are of very small amplitude. No previous sleep study has succeeded in demonstrating modulations of gamma power along the time course of slow waves in human scalp EEG. As a consequence, progress in our understanding of the functional role of gamma modulation during sleep has been limited to animal studies and exceptional human studies, notably those of intracranial recordings in epileptic patients. Because high synaptic density, which peaks some time before puberty depending on the brain region (Huttenlocher and Dabholkar, 1997), generates oscillations of larger amplitude, we considered that the best chance to demonstrate a modulation of gamma power by slow wave phase in regular scalp sleep EEG would be in school-aged children. Sleep EEG was recorded in 30 healthy children (aged 10.7 ± 0.8 years; mean ± s.d.). Time-frequency analysis was applied to evaluate the time course of spectral power along the development of a slow wave. Moreover, we attempted to modify sleep architecture and sleep characteristics through automated acoustic stimulation coupled to the occurrence of slow waves in one subset of the children. Gamma power increased on the rising slope and positive peak of the slow wave. Gamma and spindle activity is strongly suppressed during the negative peak. There were no differences between the groups who received and did not receive acoustic stimulation in the sleep parameters and slow wave-locked time-frequency analysis. Our findings show, for the first time in scalp EEG in humans, that gamma activity is associated with the up-going slope and peak of the slow wave. We propose that studies in children provide a uniquely feasible opportunity to conduct investigations into the role of gamma during sleep.

Review of somatic symptoms in post-traumatic stress disorder

Post-traumatic stress disorder (PTSD) is associated with both (1) 'ill-defined' or 'medically unexplained' somatic syndromes, e.g. unexplained dizziness, tinnitus and blurry vision, and syndromes that can be classified as somatoform disorders (DSM-IV-TR); and (2) a range of medical conditions, with a preponderance of cardiovascular, respiratory, musculoskeletal, neurological, and gastrointestinal disorders, diabetes, chronic pain, sleep disorders and other immune-mediated disorders in various studies. Frequently reported medical co-morbidities with PTSD across various studies include cardiovascular disease, especially hypertension, and immune-mediated disorders. PTSD is associated with limbic instability and alterations in both the hypothalamic- pituitary-adrenal and sympatho-adrenal medullary axes, which affect neuroendocrine and immune functions, have central nervous system effects resulting in pseudo-neurological symptoms and disorders of sleep-wake regulation, and result in autonomic nervous system dysregulation. Hypervigilance, a central feature of PTSD, can lead to 'local sleep' or regional arousal states, when the patient is partially asleep and partially awake, and manifests as complex motor and/or verbal behaviours in a partially conscious state. The few studies of the effects of standard PTSD treatments (medications, CBT) on PTSD-associated somatic syndromes report a reduction in the severity of ill-defined and autonomically mediated somatic symptoms, self-reported physical health problems, and some chronic pain syndromes.

Increased metabotropic glutamate receptor subtype 5 availability in human brain after one night without sleep

BACKGROUND

Sleep deprivation (wake therapy) provides rapid clinical relief in many patients with major depressive disorder (MDD). Changes in glutamatergic neurotransmission may contribute to the antidepressant response, yet the exact underlying mechanisms are unknown. Metabotropic glutamate receptors of subtype 5 (mGluR5) are importantly involved in modulating glutamatergic neurotransmission and neuronal plasticity. The density of these receptors is reduced in the brain of patients with MDD, particularly in brain structures involved in regulating wakefulness and sleep. We hypothesized that prolonged wakefulness would increase mGluR5 availability in human brain.

METHODS

Metabotropic glutamate receptor subtype 5 binding was quantified with positron emission tomography in 22 young healthy men who completed two experimental blocks separated by 1 week. Two positron emission tomography examinations were conducted in randomized, crossover fashion with the highly selective radioligand, ¹¹C-ABP688, once after 9 hours (sleep control) and once after 33 hours (sleep deprivation) of controlled wakefulness. ¹¹C-ABP688 uptake was quantified in 13 volumes of interest with high mGluR5 expression and presumed involvement in sleep-wake regulation.

RESULTS

Sleep deprivation induced a global increase in mGluR5 binding when compared with sleep control (p<.006). In anterior cingulate cortex, insula, medial temporal lobe, parahippocampal gyrus, striatum, and amygdala, this increase correlated significantly with the sleep deprivation-induced increase in subjective sleepiness.

CONCLUSIONS

This molecular imaging study demonstrates that cerebral functional mGluR5 availability is increased after a single night without sleep. Given that mGluR5 density is reduced in MDD, further research is warranted to examine whether this mechanism is involved in the potent antidepressant effect of wake therapy.

A BOLD statement about the hippocampal-neocortical dialogue

High speed and high spatial resolution are at the top of the wish list of every neuroscientist. An important step of progress in this direction has now been made by sampling throughout the brain fMRI signals that temporally surround important physiological patterns.

Individual differences in white matter diffusion affect sleep oscillations

The characteristic oscillations of the sleeping brain, spindles and slow waves, show trait-like, within-subject stability and a remarkable interindividual variability that correlates with functionally relevant measures such as memory performance and intelligence. Yet, the mechanisms underlying these interindividual differences are largely unknown. Spindles and slow waves are affected by the recent history of learning and neuronal activation, indicating sensitivity to changes in synaptic strength and thus to the connectivity of the neuronal network. Because the structural backbone of this network is formed by white matter tracts, we hypothesized that individual differences in spindles and slow waves depend on the white matter microstructure across a distributed network. We recorded both diffusion-weighted magnetic resonance images and whole-night, high-density electroencephalography and investigated whether individual differences in sleep spindle and slow wave parameters were associated with diffusion tensor imaging metrics; white matter fractional anisotropy and axial diffusivity were quantified using tract-based spatial statistics. Individuals with higher spindle power had higher axial diffusivity in the forceps minor, the anterior corpus callosum, fascicles in the temporal lobe, and the tracts within and surrounding the thalamus. Individuals with a steeper rising slope of the slow wave had higher axial diffusivity in the temporal fascicle and frontally located white matter tracts (forceps minor, anterior corpus callosum). These results indicate that the profiles of sleep oscillations reflect not only the dynamics of the neuronal network at the synaptic level, but also the localized microstructural properties of its structural backbone, the white matter tracts.

Neurophysiological Basis of Sleep's Function on Memory and Cognition

A wealth of recent studies support a function of sleep on memory and cognitive processing. At a physiological level, sleep supports memory in a number of ways including neural replay and enhanced plasticity in the context of reduced ongoing input. This paper presents behavioral evidence for sleep's role in selective remembering and forgetting of declarative memories, in generalization of these memories, and in motor skill consolidation. Recent physiological data reviewed suggests how these behavioral changes might be supported by sleep. Importantly, in reviewing these findings, an integrated view of how distinct sleep stages uniquely contribute to memory processing emerges. This model will be useful in developing future behavioral and physiological studies to test predictions that emerge.

NREM Sleep Oscillations and Brain Plasticity in Aging

The human electroencephalogram (EEG) during non-rapid eye movement sleep (NREM) is characterized mainly by high-amplitude (>75 μV), slow-frequency (<4 Hz) waves (slow waves), and sleep spindles (∼11-15 Hz; >0.25 s). These NREM oscillations play a crucial role in brain plasticity, and importantly, NREM sleep oscillations change considerably with aging. This review discusses the association between NREM sleep oscillations and cerebral plasticity as well as the functional impact of age-related changes on NREM sleep oscillations. We propose that age-related reduction in sleep-dependent memory consolidation may be due in part to changes in NREM sleep oscillations.

Prospective active marker motion correction improves statistical power in BOLD fMRI

Group level statistical maps of blood oxygenation level dependent (BOLD) signals acquired using functional magnetic resonance imaging (fMRI) have become a basic measurement for much of systems, cognitive and social neuroscience. A challenge in making inferences from these statistical maps is the noise and potential confounds that arise from the head motion that occurs within and between acquisition volumes. This motion results in the scan plane being misaligned during acquisition, ultimately leading to reduced statistical power when maps are constructed at the group level. In most cases, an attempt is made to correct for this motion through the use of retrospective analysis methods. In this paper, we use a prospective active marker motion correction (PRAMMO) system that uses radio frequency markers for real-time tracking of motion, enabling on-line slice plane correction. We show that the statistical power of the activation maps is substantially increased using PRAMMO compared to conventional retrospective correction. Analysis of our results indicates that the PRAMMO acquisition reduces the variance without decreasing the signal component of the BOLD (beta). Using PRAMMO could thus improve the overall statistical power of fMRI based BOLD measurements, leading to stronger inferences of the nature of processing in the human brain.

Age-related decline in controlled retrieval: the role of the PFC and sleep

Age-related cognitive impairments often include difficulty retrieving memories, particularly those that rely on executive control. In this paper we discuss the influence of the prefrontal cortex on memory retrieval, and the specific memory processes associated with the prefrontal cortex that decline in late adulthood. We conclude that preretrieval processes associated with preparation to make a memory judgment are impaired, leading to greater reliance on postretrieval processes. This is consistent with the view that impairments in executive control significantly contribute to deficits in controlled retrieval. Finally, we discuss age-related changes in sleep as a potential mechanism that contributes to deficiencies in executive control that are important for efficient retrieval. The sleep literature points to the importance of slow-wave sleep in restoration of prefrontal cortex function. Given that slow-wave sleep significantly declines with age, we hypothesize that age-related changes in slow-wave sleep could mediate age-related decline in executive control, manifesting a robust deficit in controlled memory retrieval processes. Interventions, like physical activity, that improve sleep could be effective methods to enhance controlled memory processes in late life.

Spectral and spatial shifts of post-ictal slow waves in temporal lobe seizures

Temporal lobe seizures have a significant chance to induce impairment of normal brain functions. Even after the termination of ictal discharges, during the post-ictal period, loss of consciousness, decreased responsiveness or other cognitive dysfunctions can persist. Previous studies have found various anatomical and functional abnormalities accompanying temporal lobe seizures, including an abnormal elevation of cortical slow waves. Intracranial electroencephalography studies have shown a prominent increase of lower frequency components during and following seizures that impair (complex partial seizures) but not those that preserve (simple partial seizures) normal consciousness and responsiveness. However, due to the limited spatial coverage of intracranial electroencephalography, the investigation of cortical slow waves cannot be easily extended to the whole brain. In this study, we used scalp electroencephalography to study the spectral features and spatial distribution of post-ictal slow waves with comprehensive spatial coverage. We studied simple partial, complex partial and secondarily generalized seizures in 28 patients with temporal lobe seizures. We used dense-array electroencephalography and source imaging to reconstruct the post-ictal slow-wave distribution. In the studied cohort, we found that a 'global' spectral power shift to lower frequencies accompanied the increased severity of seizures. The delta spectral power relative to higher frequency bands was highest for secondarily generalized seizures, followed by complex partial seizures and lastly simple partial seizures. In addition to this 'global' spectral shift, we found a 'regional' spatial shift in slow-wave activity. Secondarily generalized seizures and complex partial seizures exhibited increased slow waves distributed to frontal areas with spread to contralateral temporal and parietal regions than in simple partial seizures. These results revealed that a widespread cortical network including temporal and fronto-parietal cortex is involved in abnormal slow-wave activity following temporal lobe seizures. The differential spectral and spatial shifts of post-ictal electroencephalography activity in simple partial, complex partial and secondarily generalized seizures suggest a possible connection between cortical slow waves and behavioural and cognitive changes in a human epilepsy model.

Automated detection of sleep EEG slow waves based on matching pursuit using a restricted dictionary

In this paper, an original method to detect sleep slow waves (SSW) in electroencephalogram (EEG) recordings is proposed. This method takes advantage of a Matching Pursuit algorithm using a dictionary reduced to Gabor functions reproducing the main targeted waveform characteristics. By describing the EEG signals in terms of SSW properties, the corresponding algorithm is able to identify waveforms based on the largest matching coefficients. The implemented algorithm was tested on a database of whole night sleep EEG recordings collected in 9 young healthy subjects where SSW have been visually scored by an expert. Besides being fully automated and much faster than visual scoring analysis, the results obtained to the proposed method were in excellent agreement with the expert with 98% of correct detections and a 77% concordance in event time position and duration. These results were superior from those of the classical method both in terms of sensibility and precision.