K-complex, a reactive EEG graphoelement of NREM sleep: an old chap in a new garment

Episodic long-term memory formation during slow-wave sleep

We are unresponsive during slow-wave sleep but continue monitoring external events for survival. Our brain wakens us when danger is imminent. If events are non-threatening, our brain might store them for later consideration to improve decision-making. To test this hypothesis, we examined whether novel vocabulary consisting of simultaneously played pseudowords and translation words are encoded/stored during sleep, and which neural-electrical events facilitate encoding/storage. An algorithm for brain-state-dependent stimulation selectively targeted word pairs to slow-wave peaks or troughs. Retrieval tests were given 12 and 36 hr later. These tests required decisions regarding the semantic category of previously sleep-played pseudowords. The sleep-played vocabulary influenced awake decision-making 36 hr later, if targeted to troughs. The words' linguistic processing raised neural complexity. The words' semantic-associative encoding was supported by increased theta power during the ensuing peak. Fast-spindle power ramped up during a second peak likely aiding consolidation. Hence, new vocabulary played during slow-wave sleep was stored and influenced decision-making days later.

The role of the sleep K-complex on the conversion from mild cognitive impairment to Alzheimer's disease

The present literature points to an alteration of the human K-complex during non-rapid eye movement sleep in Alzheimer's disease. Nevertheless, the few findings on the K-complex changes in mild cognitive impairment and their possible predictive role on the Alzheimer's disease conversion show mixed findings, lack of replication, and a main interest for the frontal region. The aim of the present study was to assess K-complex measures in amnesic mild cognitive impairment subsequently converted in Alzheimer's disease over different cortical regions, comparing them with healthy controls and stable amnesic mild cognitive impairment. We assessed baseline K-complex density, amplitude, area under the curve and overnight changes in frontal, central and parietal midline derivations of 12 amnesic mild cognitive impairment subsequently converted in Alzheimer's disease, 12 stable amnesic mild cognitive impairment and 12 healthy controls. We also assessed delta electroencephalogram power, to determine if K-complex alterations in amnesic mild cognitive impairment occur with modification of the electroencephalogram power in the frequency range of the slow-wave activity. We found a reduced parietal K-complex density in amnesic mild cognitive impairment subsequently converted in Alzheimer's disease compared with stable amnesic mild cognitive impairment and healthy controls, without changes in K-complex morphology and overnight modulation. Both amnesic mild cognitive impairment groups showed decreased slow-wave sleep percentage compared with healthy controls. No differences between groups were observed in slow-wave activity power. Our findings suggest that K-complex alterations in mild cognitive impairment may be observed earlier in parietal regions, likely mirroring the topographical progression of Alzheimer's disease-related brain pathology, and express a frontal predominance only in a full-blown phase of Alzheimer's disease. Consistently with previous results, such K-complex modification occurs in the absence of significant electroencephalogram power changes in the slow oscillations range.

[The role of cerebral activation in the sleep-wake cycle]

The development of views on cerebral activation in the wakefulness-sleep cycle, starting with the work of Constantin von Economo, is considered. The emphasis is on the cyclic activation of high-amplitude discharges in sleep, which, with known assumptions, can include K-complexes, as well as patterns of delta-like waves. Considering the participation of the peripheral nervous system in this, the integrative role of cyclic activation of high-amplitude discharges in the organization of the sleep-wake cycle is discussed.

What is sleep exactly? Global and local modulations of sleep oscillations all around the clock

Wakefulness, non-rapid eye-movement (NREM) and rapid eye-movement (REM) sleep differ from each other along three dimensions: behavioral, phenomenological, physiological. Although these dimensions often fluctuate in step, they can also dissociate. The current paradigm that views sleep as made of global NREM and REM states fail to account for these dissociations. This conundrum can be dissolved by stressing the existence and significance of the local regulation of sleep. We will review the evidence in animals and humans, healthy and pathological brains, showing different forms of local sleep and the consequences on behavior, cognition, and subjective experience. Altogether, we argue that the notion of local sleep provides a unified account for a host of phenomena: dreaming in REM and NREM sleep, NREM and REM parasomnias, intrasleep responsiveness, inattention and mind wandering in wakefulness. Yet, the physiological origins of local sleep or its putative functions remain unclear. Exploring further local sleep could provide a unique and novel perspective on how and why we sleep.

Sleep electroencephalography biomarkers of cognition in obstructive sleep apnea

Obstructive sleep apnea has been associated with cognitive impairment and may be linked to disorders of cognitive function. These associations may be a result of intermittent hypoxaemia, sleep fragmentation and changes in sleep microstructure in obstructive sleep apnea. Current clinical metrics of obstructive sleep apnea, such as the apnea-hypopnea index, are poor predictors of cognitive outcomes in obstructive sleep apnea. Sleep microstructure features, which can be identified on sleep electroencephalography of traditional overnight polysomnography, are increasingly being characterized in obstructive sleep apnea and may better predict cognitive outcomes. Here, we summarize the literature on several major sleep electroencephalography features (slow-wave activity, sleep spindles, K-complexes, cyclic alternating patterns, rapid eye movement sleep quantitative electroencephalography, odds ratio product) identified in obstructive sleep apnea. We will review the associations between these sleep electroencephalography features and cognition in obstructive sleep apnea, and examine how treatment of obstructive sleep apnea affects these associations. Lastly, evolving technologies in sleep electroencephalography analyses will also be discussed (e.g. high-density electroencephalography, machine learning) as potential predictors of cognitive function in obstructive sleep apnea.

Modulation of sleep using noninvasive stimulations during sleep

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

rTMS in mental health disorders

Transcranial magnetic stimulation (TMS) is an innovative and non-invasive technique used in the diagnosis and treatment of psychiatric and neurological disorders. Repetitive TMS (rTMS) can modulate neuronal activity, neuroplasticity and arousal of the waking and sleeping brain, and, more generally, overall mental health. Numerous studies have examined the predictors of the efficacy of rTMS on clinical outcome variables in various psychiatric disorders. These predictors often encompass the stimulated brain region's location, electroencephalogram (EEG) activity patterns, potential morphological and neurophysiological anomalies, and individual patient's response to treatment. Most commonly, rTMS is used in awake patients with depression, catatonia, and tinnitus. Interestingly, rTMS has also shown promise in inducing slow-wave oscillations in insomnia patients, opening avenues for future research into the potential beneficial effects of these oscillations on reports of non-restorative sleep. Furthermore, neurophysiological measures emerge as potential, disease-specific biomarkers, aiding in predicting treatment response and monitoring post-treatment changes. The study posits the convergence of neurophysiological biomarkers and individually tailored rTMS treatments as a gateway to a new era in psychiatric care. The potential of rTMS to induce slow-wave activity also surfaces as a significant contribution to personalized treatment approaches. Further investigations are called for to validate the imaging and electrophysiological biomarkers associated with rTMS. In conclusion, the potential for rTMS to significantly redefine treatment strategies through personalized approaches could enhance the outcomes in neuropsychiatric disorders.

A non-oscillatory, millisecond-scale embedding of brain state provides insight into behavior

Sleep and wake are understood to be slow, long-lasting processes that span the entire brain. Brain states correlate with many neurophysiological changes, yet the most robust and reliable signature of state is enriched in rhythms between 0.1 and 20 Hz. The possibility that the fundamental unit of brain state could be a reliable structure at the scale of milliseconds and microns has not been addressed due to the physical limits associated with oscillation-based definitions. Here, by analyzing high resolution neural activity recorded in 10 anatomically and functionally diverse regions of the murine brain over 24 h, we reveal a mechanistically distinct embedding of state in the brain. Sleep and wake states can be accurately classified from on the order of 100 to 101 ms of neuronal activity sampled from 100 μm of brain tissue. In contrast to canonical rhythms, this embedding persists above 1,000 Hz. This high frequency embedding is robust to substates and rapid events such as sharp wave ripples and cortical ON/OFF states. To ascertain whether such fast and local structure is meaningful, we leveraged our observation that individual circuits intermittently switch states independently of the rest of the brain. Brief state discontinuities in subsets of circuits correspond with brief behavioral discontinuities during both sleep and wake. Our results suggest that the fundamental unit of state in the brain is consistent with the spatial and temporal scale of neuronal computation, and that this resolution can contribute to an understanding of cognition and behavior.

Pre-Sleep Cognitive Arousal Is Unrelated to Sleep Misperception in Healthy Sleepers When Unexpected Sounds Are Played during Non-Rapid Eye Movement Sleep: A Polysomnography Study

Background: It is well-established that environmental noise can disrupt sleep, and cause a mismatch between subjective and objective sleep, which is known as “sleep misperception”. Naturalistic studies indicate that pre-sleep cognitive arousal and sleep misperception are associated in the context of noise. However, it is not known if this is the case when ecologically valid noises are specifically played during non-rapid eye movement (NREM) sleep, which is susceptible to noise-related disruption. The present study evaluated if pre-sleep cognitive arousal was associated with sleep misperception in healthy normal sleepers, when unexpected ecologically valid common nocturnal noises were played during NREM sleep. Methods: Eighteen healthy sleepers (M_age = 23.37 years, SD_age = 3.21 years) participated. Sleep was measured objectively on three consecutive nights using polysomnography, in a sleep laboratory environment, and subjectively, through participant estimates of total sleep time (TST). Night 1 was a baseline night where no noises were played. On Night 2, noises, which were chosen to be representative of habitual nocturnal noises heard in home environments, were played to participants via in-ear headphones after 5 min of objective sleep. Results: Unexpectedly, habitual pre-sleep cognitive arousal was not associated with subjective–objective TST discrepancy on Night 2. Conclusions: These results suggest that in healthy sleepers, when ecologically valid noises are played unexpectedly during NREM sleep in an unfamiliar sleep laboratory environment the subjective experience of sleep is not associated with pre-sleep cognitive arousal, or negatively impacted by noise exposure.

Local sleep: A new concept in brain plasticity

Traditionally, sleep and wakefulness have been considered as two global, mutually exclusive states. However, this view has been challenged by the discovery that sleep and wakefulness are actually locally regulated and that islands of these two states may often coexist in the same individual. Importantly, such a local regulation seems to be the key for many essential functions of sleep, including the maintenance of cognitive efficiency and the consolidation of new skills and memories. Indeed, local changes in sleep-related oscillations occur in brain areas that are used and involved in learning during wakefulness. In turn, these changes directly modulate experience-dependent brain adaptations and the consolidation of newly acquired memories. In line with these observations, alterations in the regional balance between wake- and sleep-like activity have been shown to accompany many pathologic conditions, including psychiatric and neurologic disorders. In the last decade, experimental research has started to shed light on the mechanisms involved in the local regulation of sleep and wakefulness. The results of this research have opened new avenues of investigation regarding the function of sleep and have revealed novel potential targets for the treatment of several pathologic conditions.

Targeting Arousal and Sleep through Noninvasive Brain Stimulation to Improve Mental Health

Arousal and sleep represent fundamental physiological domains, and alterations in the form of insomnia (difficulty falling or staying asleep) or hypersomnia (increased propensity for falling asleep or increased sleep duration) are prevalent clinical problems. Current first-line treatments include psychotherapy and pharmacotherapy. Despite significant success, a number of patients do not benefit sufficiently. Progress is limited by an incomplete understanding of the -neurobiology of insomnia and hypersomnia. This work summarizes current concepts of the regulation of arousal and sleep and its modulation through noninvasive brain stimulation (NIBS), including transcranial magnetic, current, and auditory stimulation. Particularly, we suggest: (1) characterization of patients with sleep problems - across diagnostic entities of mental disorders - based on specific alterations of sleep, including alterations of sleep slow waves, sleep spindles, cross-frequency coupling of brain oscillations, local sleep-wake regulation, and REM sleep and (2) targeting these with specific NIBS techniques. While evidence is accumulating that the modulation of specific alterations of sleep through NIBS is feasible, it remains to be tested whether this translates to clinically relevant effects and new treatment developments.

An energy screening and morphology characterization-based hybrid expert scheme for automatic identification of micro-sleep event K-complex

BACKGROUND AND OBJECTIVE

K-complexes, as a significant indicator in sleep staging and sleep protection, are an important micro-event in sleep analysis. Clinically, K-complexes are recognized through the expert visual inspection of electroencephalogram (EEG) during sleep. Since this process is laborious and has high inter-observer variability, developing automated K-complex detection methods can alleviate the burden on clinicians while providing reliable recognition results. However, existing methods face the following issues. First, most work only identifies the K-complexes in stage 2, which requires distinguishing the sleep stages as the prerequisite for further events' identification. Second, most approaches can only detect the occurrence of events without the ability to predict their location and duration, which are also essential to sleep analysis.

METHODS

In this work, a novel hybrid expert scheme for K-complex detection is proposed by integrating signal morphology with expert knowledge into the decision-making process. To eliminate artifacts, and to minimize the individual variability in raw sleep EEG signals, the potential K-complex candidates are first screened by combining Teager energy operator (TEO) and personalized thresholds. Then, to distinguish signal shapes from background activity, a novel frame of filtering based on morphological filtering (MF) is devised to differentiate morphological components of K-complex waveforms from EEG series. Finally, K-complex waveforms are identified from the extracted morphological information by judgment rules, which are inspired by expert knowledge of micro-sleep events.

RESULTS

Detection performance is evaluated by its application on the public database MASS-C1 (Montreal archives of sleep studies cohort one) which includes the recordings of 19 healthy adults. The detection performance demonstrates an F-measure of 0.63 with a recall of 0.81 and a precision of 0.53 on average. The duration error between events and detections is 0.10 s.

CONCLUSIONS

The presented scheme has detected the occurrence of events. Meanwhile, it has recognized their locations and durations. The favorable results exhibit that the proposed scheme outperforms the state-of-the-art studies and has great potential to help release the burden of experts in sleep EEG analysis.

Shaping the slow waves of sleep: A systematic and integrative review of sleep slow wave modulation in humans using non-invasive brain stimulation

The experimental study of electroencephalographic slow wave sleep (SWS) stretches over more than half a century and has corroborated its importance for basic physiological processes, such as brain plasticity, metabolism and immune system functioning. Alterations of SWS in aging or pathological conditions suggest that modulating SWS might constitute a window for clinically relevant interventions. This work provides a systematic and integrative review of SWS modulation through non-invasive brain stimulation in humans. A literature search using PubMed, conducted in May 2020, identified 3220 studies, of which 82 fulfilled inclusion criteria. Three approaches have been adopted to modulate the macro- and microstructure of SWS, namely auditory, transcranial electrical and transcranial magnetic stimulation. Our current knowledge about the modulatory mechanisms, the space of stimulation parameters and the physiological and behavioral effects are reported and evaluated. The integration of findings suggests that sleep slow wave modulation bears the potential to promote our understanding of the functions of SWS and to develop new treatments for conditions of disrupted SWS.

The Sleep Side of Aging and Alzheimer's Disease

As we age, sleep patterns undergo significant modifications in micro and macrostructure, worsening cognition and quality of life. These are associated with remarkable brain changes, like deterioration in synaptic plasticity, gray and white matter, and significant modifications in hormone levels. Sleep alterations are also a core component of mild cognitive impairment (MCI) and Alzheimer's Disease (AD). AD night time is characterized by a gradual decrease in slow-wave activity and a substantial reduction of REM sleep. Sleep abnormalities can accelerate AD pathophysiology, promoting the accumulation of amyloid-β (Aβ) and phosphorylated tau. Thus, interventions that target sleep disturbances in elderly people and MCI patients have been suggested as a possible strategy to prevent or decelerate conversion to dementia. Although cognitive-behavioral therapy and pharmacological medications are still first-line treatments, despite being scarcely effective, new interventions have been proposed, such as sensory stimulation and Noninvasive Brain Stimulation (NiBS). The present review outlines the current state of the art of the relationship between sleep modifications in healthy aging and the neurobiological mechanisms underlying age-related changes. Furthermore, we provide a critical analysis showing how sleep abnormalities influence the prognosis of AD pathology by intensifying Aβ and tau protein accumulation. We discuss potential therapeutic strategies to target sleep disruptions and conclude that there is an urgent need for testing new therapeutic sleep interventions.

Sleep, Noninvasive Brain Stimulation, and the Aging Brain: Challenges and Opportunities

As we age, sleep patterns undergo severe modifications of their micro and macrostructure, with an overall lighter and more fragmented sleep structure. In general, interventions targeting sleep represent an excellent opportunity not only to maintain life quality in the healthy aging population, but also to enhance cognitive performance and, when pathology arises, to potentially prevent/slow down conversion from e.g. Mild Cognitive Impairment (MCI) to Alzheimer's Disease (AD). Sleep abnormalities are, in fact, one of the earliest recognizable biomarkers of dementia, being also partially responsible for a cascade of cortical events that worsen dementia pathophysiology, including impaired clearance systems leading to build-up of extracellular amyloid-β (Aβ) peptide and intracellular hyperphosphorylated tau proteins. In this context, Noninvasive Brain Stimulation (NiBS) techniques, such as transcranial electrical stimulation (tES) and transcranial magnetic stimulation (TMS), may help investigate the neural substrates of sleep, identify sleep-related pathology biomarkers, and ultimately help patients and healthy elderly individuals to restore sleep quality and cognitive performance. However, brain stimulation applications during sleep have so far not been fully investigated in healthy elderly cohorts, nor tested in AD patients or other related dementias. The manuscript discusses the role of sleep in normal and pathological aging, reviewing available evidence of NiBS applications during both wakefulness and sleep in healthy elderly individuals as well as in MCI/AD patients. Rationale and details for potential future brain stimulation studies targeting sleep alterations in the aging brain are discussed, including enhancement of cognitive performance, overall quality of life as well as protein clearance.

The heritability of the human K-complex: a twin study

Sleep electroencephalogram (EEG) has a trait-like nature. Several findings highlighted the heritability of spectral power in specific frequency ranges and sleep spindles during nonrapid eye movement (NREM) sleep. However, a genetic influence on the K-complex (KC), one of the electrophysiological hallmarks of NREM sleep, has never been assessed. Here, we investigated the heritability of the KC detected during NREM stage 2 comparing 10 monozygotic (MZ) and 10 dizygotic (DZ) twin pairs. Genetic variance analysis (GVA) and intraclass correlation coefficients (ICCs) were performed to assess the genetic effect and within-pair similarity for KC density, amplitude, and for the area under the curve (AUC) of the KC average waveform at Fz, Cz, and Pz scalp locations. Moreover, cluster analysis was performed on the KC average waveform profile. We observed a significant genetic effect on KC AUC at Cz and Pz, and on amplitude at Pz. Within-pair similarity (ICCs) was always significant for MZ twins except for KC density at Fz, whereas DZ twins always exhibited ICCs below the significance threshold, with the exception of density at Pz. The largest differences in within-pair similarity between MZ and DZ groups were observed again for AUC at Cz and Pz. MZ pairs accurately clustered for the KC average waveform with a higher frequency (successful clustering rate for MZ pairs: Fz = 60%; Cz = 80%; Pz = 90%) compared with DZ pairs (successful clustering rate for DZ pairs: Fz = 10%; Cz = 10%; Pz = none). Our results suggest the existence of a genetic influence on the human KC, particularly related to its morphology and maximally observable in central and parietal locations.

Association between Loss of Sleep-specific Waves and Age, Sleep Efficiency, Body Mass Index, and Apnea-Hypopnea Index in Human N3 Sleep

Sleep spindles (SS) and K-complexes (KC) play important roles in human sleep. It has been reported that age, body mass index (BMI), and apnea-hypopnea index (AHI) may influence the number of SS or KC in non-rapid-eye-movement (NREM) 2 (N2) sleep. In this study, we investigated whether the loss of SS or KC is associated with the above factors in NREM 3 (N3) sleep. A total of 152 cases were enrolled from 2013 to 2017. The correlations between the number of SS or KC in N3 sleep and participants’ characteristics were analyzed using Spearman rank correlation. Chi-squared test was used to assess the effects of age, sleep efficiency, and BMI on the loss of N3 sleep, N3 spindle and N3 KC. Our results showed that there were negative correlations between the number of SS in N3 sleep with age, BMI, and AHI (P < 0.001), and similar trends were found for KC as well. The loss of SS and KC in N3 sleep was related with age, BMI, and AHI (P < 0.01), as was the loss of N3 sleep (P < 0.01). However, sleep efficiency was not related with the loss of N3 sleep, SS and KC in N3 sleep (P > 0.05). The present study supports that age, BMI, and AHI are all influencing factors of SS and KC loss in human N3 sleep, but sleep efficiency was not an influencing factor in the loss of N3 sleep and the loss of SS and KC in N3 sleep.

Bidirectional relationship between sleep and Alzheimer's disease: role of amyloid, tau, and other factors

As we age, we experience changes in our nighttime sleep and daytime wakefulness. Individuals afflicted with Alzheimer's disease (AD) can develop sleep problems even before memory and other cognitive deficits are reported. As the disease progresses and cognitive changes ensue, sleep disturbances become even more debilitating. Thus, it is imperative to gain a better understanding of the relationship between sleep and AD pathogenesis. We postulate a bidirectional relationship between sleep and the neuropathological hallmarks of AD; in particular, the accumulation of amyloid-β (Aβ) and tau. Our research group has shown that extracellular levels of both Aβ and tau fluctuate during the normal sleep-wake cycle. Disturbed sleep and increased wakefulness acutely lead to increased Aβ production and decreased Aβ clearance, whereas Aβ aggregation and deposition is enhanced by chronic increased wakefulness in animal models. Once Aβ accumulates, there is evidence in both mice and humans that this results in disturbed sleep. New findings from our group reveal that acute sleep deprivation increases levels of tau in mouse brain interstitial fluid (ISF) and human cerebrospinal fluid (CSF) and chronic sleep deprivation accelerates the spread of tau protein aggregates in neural networks. Finally, recent evidence also suggests that accumulation of tau aggregates in the brain correlates with decreased nonrapid eye movement (NREM) sleep slow wave activity. In this review, we first provide a brief overview of the AD and sleep literature and then highlight recent advances in the understanding of the relationship between sleep and AD pathogenesis. Importantly, the effects of the bidirectional relationship between the sleep-wake cycle and tau have not been previously discussed in other reviews on this topic. Lastly, we provide possible directions for future studies on the role of sleep in AD.

Efficient Implementation of Cerebellar Purkinje Cell With the CORDIC Algorithm on LaCSNN

Purkinje cell is an important neuron for the cerebellar information processing. In this work, we present an efficient implementation of a cerebellar Purkinje model using the Coordinate Rotation Digital Computer (CORDIC) algorithm and implement it on a Large-Scale Conductance-Based Spiking Neural Networks (LaCSNN) system with cost-efficient multiplier-less methods, which are more suitable for large-scale neural networks. The CORDIC-based Purkinje model has been compared with the original model in terms of the voltage activities, dynamic mechanisms, precision, and hardware resource utilization. The results show that the CORDIC-based Purkinje model can reproduce the same biological activities and dynamical mechanisms as the original model with slight deviation. In the aspect of the hardware implementation, it can use only logic resources, so it provides an efficient way for maximizing the FPGA resource utilization, thereby expanding the scale of neural networks that can be implemented on FPGAs.

Local Gamma Activity During Non-REM Sleep in the Context of Sensory Evoked K-Complexes

K-complexes (KCs) and Sleep Slow Oscillations (SSOs) are the EEG expression of neuronal bistability during deeper stages Non-REM sleep. They are characterized by a deep negative deflection lasting about half-a-second, sustained, at the cortical level, by a widespread and synchronized neuronal hyperpolarization (i.e., electrical silence). The phase of hyperpolarization is followed by a period of intense and synchronized neuronal firing (i.e., depolarization phase) resulting at the EEG level, in a large positive deflection (lasting about 0.5 s) and a concurrent high frequency activity (i.e., spindles). Both KCs and SSOs rather than being “local” phenomena, propagate over large sections of the cortex. These features suggest that bistability is a large-scale network phenomenon, possibly driven by a propagating excitatory activity and involving wide populations of synchronized neurons. We have recently shown that KCs and SSOs include a positive bump preceding the negative peak and that for sensory-evoked KCs this bump coincides with the P200 wave. We demonstrated that the P200 has a sensory-modality specific localization, as it is firstly elicited in the primary sensory areas related to the stimulus, which in turn receive projections from the thalamic core. We observed that the P200 acts as a propagating excitatory activity and hypothesized that it could play a key role in inducing the opening of K+ channels, and hence the cortical hyperpolarization. Here we demonstrate that the P200 is sustained by a high-frequency excitation bringing further support to its role in triggering bistability. We show that the P200 has a higher power density in gamma band as compared to the P900 coherently for all sensory modalities, and we confirm that the latter wave is crowned by higher activity in sigma-beta bands. Finally, we characterize the P200 gamma activity at the cortical level in terms of spatial localization and temporal dynamics, demonstrating that it emerges in sensory stimulus-specific primary areas and travels over the cortical mantle spreading toward fronto-central associative areas and fading concurrently with the N550 onset.

The Emergence of Spindles and K-Complexes and the Role of the Dorsal Caudal Part of the Anterior Cingulate as the Generator of K-Complexes

The large multicomponent K-complex (KC) and the rhythmic spindle are the hallmarks of non-rapid eye movement (NREM)-2 sleep stage. We studied with magnetoencephalography (MEG) the progress of light sleep (NREM-1 and NREM-2) and emergence of KCs and spindles. Seven periods of interest (POI) were analyzed: wakefulness, the two quiet "core" periods of light sleep (periods free from any prominent phasic or oscillatory events) and four periods before and during spindles and KCs. For each POI, eight 2-s (1250 time slices) segments were used. We employed magnetic field tomography (MFT) to extract an independent tomographic estimate of brain activity from each MEG data sample. The spectral power was then computed for each voxel in the brain for each segment of each POI. The sets of eight maps from two POIs were contrasted using a voxel-by-voxel t-test. Only increased spectral power was identified in the four key contrasts between POIs before and during spindles and KCs versus the NREM2 core. Common increases were identified for all four subjects, especially within and close to the anterior cingulate cortex (ACC). These common increases were widespread for low frequencies, while for higher frequencies they were focal, confined to specific brain areas. For the pre-KC POI, only one prominent increase was identified, confined to the theta/alpha bands in a small area in the dorsal caudal part of ACC (dcACC). During KCs, the activity in this area grows in intensity and extent (in space and frequency), filling the space between the areas that expanded their low frequency activity (in the delta band) during NREM2 compared to NREM1. Our main finding is that prominent spectral power increases before NREM2 graphoelements are confined to the dcACC, and only for KCs, sharing common features with changes of activity in dcACC of the well-studied error related negativity (ERN). ERN is seen in awake state, in perceptual conflict and situations where there is a difference between expected and actual environmental or internal events. These results suggest that a KC is the sleep side of the awake state ERN, both serving their putative sentinel roles in the frame of the saliency network.

Electroencephalogram abnormalities in patients with NREM parasomnias

OBJECTIVE

Electroencephalographic (EEG) changes in patients with NREM parasomnias (NRP) occur in sleep architecture as changes in slow wave sleep or cyclic pattern, which are not considered abnormal. However, abnormalities in EEG in these patients have recently been reported, indicating that EEG patterns in NRPs are not definitive. Moreover, most of the polysomnography (PSG) findings in NRP patients were reported in the adult population requiring data from pediatric population to avoid bias in conclusion.

METHODS

In sum, 39 patients with a NRP were undergone comprehensive assessments including a PSG with additional EEG montages. EEG recordings were evaluated in patients without a history of epilepsy and further compared between pediatric and adult patients.

RESULTS

Twenty-three (59%) of the patients were pediatric and 77% were male. The mean age was 18.4 (±13.1) years. Of the patients, 19 (49%) had somnambulism, 13 (33%) had confusional arousal and seven (18%) had sleep terrors. Macrostructure of sleep detected by PSG was normal in all patients. After excluding 11 (28%) patients with a positive history of epilepsy, seven (25%) of 28 showed EEG abnormalities within K-complexes in NREM-II stage, six of whom were pediatric patients compared to only one adult (p < 0.05).

CONCLUSION

This study showed that patients with NRP may display EEG abnormalities in NREM-II stage. These abnormalities were more frequent in pediatric patients compared to adults. In NRP patients, utmost care should be taken in EEG evaluations to prevent false diagnosis of epilepsy.

Sleep spindles and K-complex activities are decreased in spinocerebellar ataxia type 2: relationship to memory and motor performances

BACKGROUND

Sleep spindles and K-complexes are electroencephalographic hallmarks of non-rapid eye movement (non-REM) sleep that provide valuable information into brain functioning, plasticity and sleep functions in normal and pathological conditions. However, they have not been systematically investigated in spinocerebellar ataxias (SCA). To close this gap, the current study was carried out to quantify sleep spindles and K-complexes in SCA2 and to assess their relationship with clinical and molecular measures, as well as with memory and attention/executive functioning.

METHODS

In this study, 20 SCA2 patients, 20 preclinical carriers and 20 healthy controls underwent whole-night polysomnographic (PSG) recordings as well as sleep interviews, ataxia scoring and neuropsychological assessments. Sleep spindles and K-complexes were automatically detected during non-REM sleep stage 2 (N2). Their densities were evaluated as events/minute.

RESULTS

Compared to controls, sleep spindle density was significantly reduced in SCA2 patients and preclinical subjects. By contrast, K-complex density was specifically and significantly decreased only in SCA2 patients. Reduced spindle activity correlated with measures of verbal memory, whereas reduced K-complex activity correlated with age, ataxia severity and N3 sleep percentage in SCA2 patients.

CONCLUSIONS

Findings document an impairment of N2 sleep microstructure in SCA2 already in prodromal stages, suggesting an early involvement of thalamo-cortical and/or cortical circuits underlying the generation of sleep spindles and K-complexes. Thus, sleep spindle density may serve as useful biomarker for deficits of neural plasticity mechanisms underlying verbal memory alterations in patients. It may also serve as promising outcome measure in further therapeutical trials targeting memory decline in SCA2. With regard to K-complexes, they have potential usefulness as marker of sleep protection.

Promoting subjective preferences in simple economic choices during nap

Sleep is known to benefit consolidation of memories, especially those of motivational relevance. Yet, it remains largely unknown the extent to which sleep influences reward-associated behavior, in particular, whether and how sleep modulates reward evaluation that critically underlies value-based decisions. Here, we show that neural processing during sleep can selectively bias preferences in simple economic choices when the sleeper is stimulated by covert, reward-associated cues. Specifically, presenting the spoken name of a familiar, valued snack item during midday nap significantly improves the preference for that item relative to items not externally cued. The cueing-specific preference enhancement is sleep-dependent and can be predicted by cue-induced neurophysiological signals at the subject and item level. Computational modeling further suggests that sleep cueing accelerates evidence accumulation for cued options during the post-sleep choice process in a manner consistent with the preference shift. These findings suggest that neurocognitive processing during sleep contributes to the fine-tuning of subjective preferences in a flexible, selective manner.

Physiology-based ERPs in normal and abnormal states

Evoked response potentials (ERPs) and other transients are modeled as impulse responses using physiology-based neural field theory (NFT) of the corticothalamic system of neural activity in the human brain that incorporates synaptic and dendritic dynamics, firing response, axonal propagation, and corticocortical and corticothalamic pathways. The properties of model-predicted ERPs are explored throughout the stability zone of the corticothalamic system, and predicted time series and wavelet spectra are also analyzed. This provides a unified treatment of predicted ERPs for both normal and abnormal states within the brain's stability zone, including likely parameters to represent abnormal states of reduced arousal.

Local and Widespread Slow Waves in Stable NREM Sleep: Evidence for Distinct Regulation Mechanisms

Previous work showed that two types of slow waves are temporally dissociated during the transition to sleep: widespread, large and steep slow waves predominate early in the falling asleep period (type I), while smaller, more circumscribed slow waves become more prevalent later (type II). Here, we studied the possible occurrence of these two types of slow waves in stable non-REM (NREM) sleep and explored potential differences in their regulation. A heuristic approach based on slow wave synchronization efficiency was developed and applied to high-density electroencephalographic (EEG) recordings collected during consolidated NREM sleep to identify the potential type I and type II slow waves. Slow waves with characteristics compatible with those previously described for type I and type II were identified in stable NREM sleep. Importantly, these slow waves underwent opposite changes across the night, with only type II slow waves displaying a clear homeostatic regulation. In addition, we showed that the occurrence of type I slow waves was often followed by larger type II slow waves, whereas the occurrence of type II slow waves was usually followed by smaller type I waves. Finally, type II slow waves were associated with a relative increase in spindle activity, while type I slow waves triggered periods of high-frequency activity. Our results provide evidence for the existence of two distinct slow wave synchronization processes that underlie two different types of slow waves. These slow waves may have different functional roles and mark partially distinct “micro-states” of the sleeping brain.

Using Oscillating Sounds to Manipulate Sleep Spindles

Introduction

EEG oscillations known as sleep spindles have been linked with various aspects of cognition, but the specific functions they signal remain controversial. Two types of EEG sleep spindles have been distinguished: slow spindles at 11-13.5 Hz and fast spindles at 13.5-16 Hz. Slow spindles exhibit a frontal scalp topography, whereas fast spindles exhibit a posterior scalp topography and have been preferentially linked with memory consolidation during sleep. To advance understanding beyond that provided from correlative studies of spindles, we aimed to develop a new method to systematically manipulate spindles.

Aims and Methods

We presented repeating bursts of oscillating white noise to people during a 90-min afternoon nap. During stage 2 and slow-wave sleep, oscillations were embedded within contiguous 10-s stimulation intervals, each comprising 2 s of white noise amplitude modulated at 12 Hz (targeting slow spindles), 15 Hz (targeting fast spindles), or 50 Hz followed by 8 s of constant white noise.

Results

During oscillating stimulation compared to constant stimulation, parietal EEG recordings showed more slow spindles in the 12-Hz condition, more fast spindles in the 15-Hz condition, and no change in the 50-Hz control condition. These effects were topographically selective, and were absent in frontopolar EEG recordings, where slow spindle density was highest. Spindles during stimulation were similar to spontaneous spindles in standard physiological features, including duration and scalp distribution.

Conclusions

These results define a new method to selectively and noninvasively manipulate spindles through acoustic resonance, while also providing new evidence for functional distinctions between the 2 types of EEG spindles.

Neural Markers of Responsiveness to the Environment in Human Sleep

Sleep is characterized by a loss of behavioral responsiveness. However, recent research has shown that the sleeping brain is not completely disconnected from its environment. How neural activity constrains the ability to process sensory information while asleep is yet unclear. Here, we instructed human volunteers to classify words with lateralized hand responses while falling asleep. Using an electroencephalographic (EEG) marker of motor preparation, we show how responsiveness is modulated across sleep. These modulations are tracked using classic event-related potential analyses complemented by Lempel-Ziv complexity (LZc), a measure shown to track arousal in sleep and anesthesia. Neural activity related to the semantic content of stimuli was conserved in light non-rapid eye movement (NREM) sleep. However, these processes were suppressed in deep NREM sleep and, importantly, also in REM sleep, despite the recovery of wake-like neural activity in the latter. In NREM sleep, sensory activations were counterbalanced by evoked down states, which, when present, blocked further processing of external information. In addition, responsiveness markers correlated positively with baseline complexity, which could be related to modulation in sleep depth. In REM sleep, however, this relationship was reversed. We therefore propose that, in REM sleep, endogenously generated processes compete with the processing of external input. Sleep can thus be seen as a self-regulated process in which external information can be processed in lighter stages but suppressed in deeper stages. Last, our results suggest drastically different gating mechanisms in NREM and REM sleep.

SIGNIFICANCE STATEMENT

Previous research has tempered the notion that sleepers are isolated from their environment. Here, we pushed this idea forward and examined, across all sleep stages, the brain's ability to flexibly process sensory information, up to the decision level. We extracted an EEG marker of motor preparation to determine the completion of the sensory processing chain and explored how it is constrained by baseline and evoked neural activity. In NREM sleep, slow waves elicited by stimuli appeared to block response preparation. We also used a novel analytic approach (Lempel-Ziv complexity) and showed that the ability to process external information correlates with neural complexity. A reversal of the correlation between complexity and motor indices in REM sleep suggests drastically different gating mechanisms across sleep stages.

In Search of Sleep Biomarkers of Alzheimer's Disease: K-Complexes Do Not Discriminate between Patients with Mild Cognitive Impairment and Healthy Controls

The K-complex (KC) is one of the hallmarks of Non-Rapid Eye Movement (NREM) sleep. Recent observations point to a drastic decrease of spontaneous KCs in Alzheimer's disease (AD). However, no study has investigated when, in the development of AD, this phenomenon starts. The assessment of KC density in mild cognitive impairment (MCI), a clinical condition considered a possible transitional stage between normal cognitive function and probable AD, is still lacking. The aim of the present study was to compare KC density in AD/MCI patients and healthy controls (HCs), also assessing the relationship between KC density and cognitive decline. Twenty amnesic MCI patients underwent a polysomnographic recording of a nocturnal sleep. Their data were compared to those of previously recorded 20 HCs and 20 AD patients. KCs during stage 2 NREM sleep were visually identified and KC densities of the three groups were compared. AD patients showed a significant KC density decrease compared with MCI patients and HCs, while no differences were observed between MCI patients and HCs. KC density was positively correlated with Mini-Mental State Examination (MMSE) scores. Our results point to the existence of an alteration of KC density only in a full-blown phase of AD, which was not observable in the early stage of the pathology (MCI), but linked with cognitive deterioration.

Preferential processing of emotionally and self-relevant stimuli persists in unconscious N2 sleep

Information processing has been suggested to depend on the current state of the brain as well as stimulus characteristics (e.g. salience). We compared processing of salient stimuli (subject's own names [SONs] and angry voice [AV] stimuli) to processing of unfamiliar names (UNs) and neutral voice (NV) stimuli across different vigilance stages (i.e. wakefulness as well as sleep stages N1 and N2) by means of event-related oscillatory responses during wakefulness and a subsequent afternoon nap. Our findings suggest that emotional prosody and self-relevance drew more attentional resources during wakefulness with specifically AV stimuli being processed more strongly. During N1, SONs were more arousing than UNs irrespective of prosody. Moreover, emotional and self-relevant stimuli evoked stronger responses also during N2 sleep suggesting a 'sentinel processing mode' of the brain during this state of naturally occurring unconsciousness. Finally, this initial preferential processing of salient stimuli during N2 sleep seems to be followed by an inhibitory sleep-protecting process, which is reflected by a K-complex-like response.

K-complexes, spindles, and ERPs as impulse responses: unification via neural field theory

To interrelate K-complexes, spindles, evoked response potentials (ERPs), and spontaneous electroencephalography (EEG) using neural field theory (NFT), physiology-based NFT of the corticothalamic system is used to model cortical excitatory and inhibitory populations and thalamic relay and reticular nuclei. The impulse response function of the model is used to predict the responses to impulses, which are compared with transient waveforms in sleep studies. Fits to empirical data then allow underlying brain physiology to be inferred and compared with other waves. Spontaneous K-complexes, spindles, and other transient waveforms can be reproduced using NFT by treating them as evoked responses to impulsive stimuli with brain parameters appropriate to spontaneous EEG in sleep stage 2. Using this approach, spontaneous K-complexes and sleep spindles can be analyzed using the same single theory as previously been used to account for waking ERPs and other EEG phenomena. As a result, NFT can explain a wide variety of transient waveforms that have only been phenomenologically classified to date. This enables noninvasive fitting to be used to infer underlying physiological parameters. This physiology-based model reproduces the time series of different transient EEG waveforms; it has previously reproduced experimental EEG spectra, and waking ERPs, and many other observations, thereby unifying transient sleep waveforms with these phenomena.

Increased Evoked Potentials to Arousing Auditory Stimuli during Sleep: Implication for the Understanding of Dream Recall

High dream recallers (HR) show a larger brain reactivity to auditory stimuli during wakefulness and sleep as compared to low dream recallers (LR) and also more intra-sleep wakefulness (ISW), but no other modification of the sleep macrostructure. To further understand the possible causal link between brain responses, ISW and dream recall, we investigated the sleep microstructure of HR and LR, and tested whether the amplitude of auditory evoked potentials (AEPs) was predictive of arousing reactions during sleep. Participants (18 HR, 18 LR) were presented with sounds during a whole night of sleep in the lab and polysomnographic data were recorded. Sleep microstructure (arousals, rapid eye movements (REMs), muscle twitches (MTs), spindles, KCs) was assessed using visual, semi-automatic and automatic validated methods. AEPs to arousing (awakenings or arousals) and non-arousing stimuli were subsequently computed. No between-group difference in the microstructure of sleep was found. In N2 sleep, auditory arousing stimuli elicited a larger parieto-occipital positivity and an increased late frontal negativity as compared to non-arousing stimuli. As compared to LR, HR showed more arousing stimuli and more long awakenings, regardless of the sleep stage but did not show more numerous or longer arousals. These results suggest that the amplitude of the brain response to stimuli during sleep determine subsequent awakening and that awakening duration (and not arousal) is the critical parameter for dream recall. Notably, our results led us to propose that the minimum necessary duration of an awakening during sleep for a successful encoding of dreams into long-term memory is approximately 2 min.

Meet Spinky: An Open-Source Spindle and K-Complex Detection Toolbox Validated on the Open-Access Montreal Archive of Sleep Studies (MASS)

Sleep spindles and K-complexes are among the most prominent micro-events observed in electroencephalographic (EEG) recordings during sleep. These EEG microstructures are thought to be hallmarks of sleep-related cognitive processes. Although tedious and time-consuming, their identification and quantification is important for sleep studies in both healthy subjects and patients with sleep disorders. Therefore, procedures for automatic detection of spindles and K-complexes could provide valuable assistance to researchers and clinicians in the field. Recently, we proposed a framework for joint spindle and K-complex detection (Lajnef et al., 2015a) based on a Tunable Q-factor Wavelet Transform (TQWT; Selesnick, 2011a) and morphological component analysis (MCA). Using a wide range of performance metrics, the present article provides critical validation and benchmarking of the proposed approach by applying it to open-access EEG data from the Montreal Archive of Sleep Studies (MASS; O'Reilly et al., 2014). Importantly, the obtained scores were compared to alternative methods that were previously tested on the same database. With respect to spindle detection, our method achieved higher performance than most of the alternative methods. This was corroborated with statistic tests that took into account both sensitivity and precision (i.e., Matthew's coefficient of correlation (MCC), F1, Cohen κ). Our proposed method has been made available to the community via an open-source tool named Spinky (for spindle and K-complex detection). Thanks to a GUI implementation and access to Matlab and Python resources, Spinky is expected to contribute to an open-science approach that will enhance replicability and reliable comparisons of classifier performances for the detection of sleep EEG microstructure in both healthy and patient populations.

Odors enhance slow-wave activity in non-rapid eye movement sleep

Most forms of suprathreshold sensory stimulation perturb sleep. In contrast, presentation of pure olfactory or mild trigeminal odorants does not lead to behavioral or physiological arousal. In fact, some odors promote objective and subjective measures of sleep quality in humans and rodents. The brain mechanisms underlying these sleep-protective properties of olfaction remain unclear. Slow oscillations in the electroencephalogram (EEG) are a marker of deep sleep, and K complexes (KCs) are an EEG marker of cortical response to sensory interference. We therefore hypothesized that odorants presented during sleep will increase power in slow EEG oscillations. Moreover, given that odorants do not drive sleep interruption, we hypothesized that unlike other sensory stimuli odorants would not drive KCs. To test these hypotheses we used polysomnography to measure sleep in 34 healthy subjects (19 women, 15 men; mean age 26.5 ± 2.5 yr) who were repeatedly presented with odor stimuli via a computer-controlled air-dilution olfactometer over the course of a single night. Each participant was exposed to one of four odorants, lavender oil (n = 13), vetiver oil (n = 5), vanillin (n = 12), or ammonium sulfide (n = 4), for durations of 5, 10, and 20 s every 9-15 min. Consistent with our hypotheses, we found that odor presentation during sleep enhanced the power of delta (0.5-4 Hz) and slow spindle (9-12 Hz) frequencies during non-rapid eye movement sleep. The increase was proportionate to odor duration. In addition, odor presentation did not modulate the occurrence of KCs. These findings imply a sleep-promoting olfactory mechanism that may deepen sleep through driving increased slow-frequency oscillations.

Mild Airflow Limitation during N2 Sleep Increases K-complex Frequency and Slows Electroencephalographic Activity

STUDY OBJECTIVES

To determine the effects of mild airflow limitation on K-complex frequency and morphology and electroencephalogram (EEG) spectral power.

METHODS

Transient reductions in continuous positive airway pressure (CPAP) during stable N2 sleep were performed to induce mild airflow limitation in 20 patients with obstructive sleep apnea (OSA) and 10 healthy controls aged 44 ± 13 y. EEG at C3 and airflow were measured in 1-min windows to quantify K-complex properties and EEG spectral power immediately before and during transient reductions in CPAP. The frequency and morphology (amplitude and latency of P200, N550 and N900 components) of K-complexes and EEG spectral power were compared between conditions.

RESULTS

During mild airflow limitation (18% reduction in peak inspiratory airflow from baseline, 0.38 ± 0.11 versus 0.31 ± 0.1 L/sec) insufficient to cause American Academy of Sleep Medicine-defined cortical arousal, K-complex frequency (9.5 ± 4.5 versus 13.7 ± 6.4 per min, P < 0.01), N550 amplitude (25 ± 3 versus 27 ± 3 μV, P < 0.01) and EEG spectral power (delta: 147 ± 48 versus 230 ± 99 μV(2), P < 0.01 and theta bands: 31 ± 14 versus 34 ± 13 μV(2), P < 0.01) significantly increased whereas beta band power decreased (14 ± 5 versus 11 ± 4 μV(2), P < 0.01) compared to the preceding non flow-limited period on CPAP. K-complex frequency, morphology, and timing did not differ between patients and controls.

CONCLUSION

Mild airflow limitation increases K-complex frequency, N550 amplitude, and spectral power of delta and theta bands. In addition to providing mechanistic insight into the role of mild airflow limitation on K-complex characteristics and EEG activity, these findings may have important implications for respiratory conditions in which airflow limitation during sleep is common (e.g., snoring and OSA).

Distribution, Amplitude, Incidence, Co-Occurrence, and Propagation of Human K-Complexes in Focal Transcortical Recordings

K-complexes (KCs) are thought to play a key role in sleep homeostasis and memory consolidation; however, their generation and propagation remain unclear. The commonly held view from scalp EEG findings is that KCs are primarily generated in medial frontal cortex and propagate parietally, whereas an electrocorticography (ECOG) study suggested dorsolateral prefrontal generators and an absence of KCs in many areas. In order to resolve these differing views, we used unambiguously focal bipolar depth electrode recordings in patients with intractable epilepsy to investigate spatiotemporal relationships of human KCs. KCs were marked manually on each channel, and local generation was confirmed with decreased gamma power. In most cases (76%), KCs occurred in a single location, and rarely (1%) in all locations. However, if automatically detected KC-like phenomena were included, only 15% occurred in a single location, and 27% occurred in all recorded locations. Locally generated KCs were found in all sampled areas, including cingulate, ventral temporal, and occipital cortices. Surprisingly, KCs were smallest and occurred least frequently in anterior prefrontal channels. When KCs occur on two channels, their peak order is consistent in only 13% of cases, usually from prefrontal to lateral temporal. Overall, the anterior-posterior separation of electrode pairs explained only 2% of the variance in their latencies. KCs in stages 2 and 3 had similar characteristics. These results open a novel view where KCs overall are universal cortical phenomena, but each KC may variably involve small or large cortical regions and spread in variable directions, allowing flexible and heterogeneous contributions to sleep homeostasis and memory consolidation.