Acoustic oddball during NREM sleep: a combined EEG/fMRI study

Sleep neuroimaging: Review and future directions

Sleep research has evolved considerably since the first sleep electroencephalography recordings in the 1930s and the discovery of well-distinguishable sleep stages in the 1950s. While electrophysiological recordings have been used to describe the sleeping brain in much detail, since the 1990s neuroimaging techniques have been applied to uncover the brain organization and functional connectivity of human sleep with greater spatial resolution. The combination of electroencephalography with different neuroimaging modalities such as positron emission tomography, structural magnetic resonance imaging and functional magnetic resonance imaging imposes several challenges for sleep studies, for instance, the need to combine polysomnographic recordings to assess sleep stages accurately, difficulties maintaining and consolidating sleep in an unfamiliar and restricted environment, scanner-induced distortions with physiological artefacts that may contaminate polysomnography recordings, and the necessity to account for all physiological changes throughout the sleep cycles to ensure better data interpretability. Here, we review the field of sleep neuroimaging in healthy non-sleep-deprived populations, from early findings to more recent developments. Additionally, we discuss the challenges of applying concurrent electroencephalography and imaging techniques to sleep, which consequently have impacted the sample size and generalizability of studies, and possible future directions for the field.

A closed-loop auditory stimulation approach selectively modulates alpha oscillations and sleep onset dynamics in humans

Alpha oscillations play a vital role in managing the brain's resources, inhibiting neural activity as a function of their phase and amplitude, and are changed in many brain disorders. Developing minimally invasive tools to modulate alpha activity and identifying the parameters that determine its response to exogenous modulators is essential for the implementation of focussed interventions. We introduce Alpha Closed-Loop Auditory Stimulation (αCLAS) as an EEG-based method to modulate and investigate these brain rhythms in humans with specificity and selectivity, using targeted auditory stimulation. Across a series of independent experiments, we demonstrate that αCLAS alters alpha power, frequency, and connectivity in a phase, amplitude, and topography-dependent manner. Using single-pulse-αCLAS, we show that the effects of auditory stimuli on alpha oscillations can be explained within the theoretical framework of oscillator theory and a phase-reset mechanism. Finally, we demonstrate the functional relevance of our approach by showing that αCLAS can interfere with sleep onset dynamics in a phase-dependent manner.

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

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

Quantifying teenagers' sleep patterns and sex differences in social jetlag using at-home sleep monitoring

Sleep plays an important role in the formative developmental processes occurring during the teenage years. At the same time, teenagers' changing bioregulatory mechanisms and psychosocial factors converge into the so-called social jetlag, a sleep timing misalignment between weekdays and weekends. The aim of this study was to quantify the course of day-to-day changes in sleep/wake patterns and sleep stage distributions, and the sex differences in social jetlag among teenagers. We observed the sleep of 156 teenagers (58.3% girls, 15-16 years) using a novel sleep monitor over the course of up to 10 consecutive days. 1323 nights of data were analyzed using multilevel modeling. On average, participants went to bed at 23:41, woke up at 07:48, slept for 7.7 h and had 85.5% sleep efficiency. Sleep stage distributions were in line with normative data. We found later sleep onset and offset, longer time in bed, sleep duration, and sleep onset latency (p = .001), greater proportion of light sleep and lower proportion of deep sleep, and poorer sleep efficiency (all p < .001) on weekend nights starting on Friday and Saturday. On Friday nights, girls had longer time awake after sleep onset (p = .020) than boys. On Friday and Saturday nights, girls fell asleep earlier (p < .001 and p = .006, respectively). On Saturday nights, girls had shorter sleep latency (p = .024), and better sleep efficiency (p = .019) than boys. In sum, teenagers' sleep patterns reflected healthy, albeit somewhat short sleep. There was convincing evidence of social jetlag, and girls exhibited less severe social jetlag than boys.

Examining First Night Effect on Sleep Parameters with hd-EEG in Healthy Individuals

Difficulty sleeping in a novel environment is a common phenomenon that is often described as the first night effect (FNE). Previous works have found FNE on sleep architecture and sleep power spectra parameters, especially during non-rapid eye movement (NREM) sleep. However, the impact of FNE on sleep parameters, including local differences in electroencephalographic (EEG) activity across nights, has not been systematically assessed. Here, we performed high-density EEG sleep recordings on 27 healthy individuals on two nights and examined differences in sleep architecture, NREM (stages 2 and 3) EEG power spectra, and NREM power topography across nights. We found higher wakefulness after sleep onset (WASO), reduced sleep efficiency, and less deep NREM sleep (stage 3), along with increased high-frequency NREM EEG power during the first night of sleep, corresponding to small to medium effect sizes (Cohen’s d ≤ 0.5). Furthermore, study individuals showed significantly lower slow-wave activity in right frontal/prefrontal regions as well as higher sigma and beta activities in medial and left frontal/prefrontal areas, yielding medium to large effect sizes (Cohen’s d ≥ 0.5). Altogether, these findings suggest the FNE is characterized by less efficient, more fragmented, shallower sleep that tends to affect especially certain brain regions. The magnitude and specificity of these effects should be considered when designing sleep studies aiming to compare across night effects.

Sleep Characteristics in Esport Players and Associations With Game Performance: Residual Dynamic Structural Equation Modeling

The current study aimed to examine sleep characteristics of esport players and the stipulated effects of game performance on consecutive sleep characteristics using residual dynamic structural equation modeling (RDSEM). A sample of 27 Counterstrike players with a mean age of 18½ years participated in the current study. Sleep was detected over a period of 56 days with a Somnofy sleep monitor that utilizes an impulse radio ultra-wideband puls radar and Dopler technology, and weekly game performance was reported by the players. The results showed that esport players' sleep characteristics were in the lower levels of recommended guidelines and that sleep onset started later and sleep offset ended later in the morning compared with athletes from other traditional sports. The esport players displayed stable patterns in sleep onset, sleep offset, time in bed, sleep efficiency and non-REM respiration rates per minute (NREM RPM). On the between-person level, esport players with better game performance spent more time sleeping (r = 0.55) and scored lower on NREM RPM (r = -0.44). Unstandardized within-person cross-lagged paths showed that better game performance predicted subsequent earlier sleep offset. The within-level standardized estimates of the cross-lagged paths revealed that participants with better game performance spent subsequently more time in deep sleep (0.20), less time in light sleep (-0.14), less time in bed (-0.16), and displayed lower NREM RPM (-0.21), earlier sleep offset (-0.21), and onset (-0.09). The findings of better game performance being related to better sleep are discussed in terms of existing knowledge on how stress responses elicitated by poor performance might impact on non-REM respiration rates and sleep.

Automatic Sensory Predictions: A Review of Predictive Mechanisms in the Brain and Their Link to Conscious Processing

The human brain has the astonishing capacity of integrating streams of sensory information from the environment and forming predictions about future events in an automatic way. Despite being initially developed for visual processing, the bulk of predictive coding research has subsequently focused on auditory processing, with the famous mismatch negativity signal as possibly the most studied signature of a surprise or prediction error (PE) signal. Auditory PEs are present during various consciousness states. Intriguingly, their presence and characteristics have been linked with residual levels of consciousness and return of awareness. In this review we first give an overview of the neural substrates of predictive processes in the auditory modality and their relation to consciousness. Then, we focus on different states of consciousness - wakefulness, sleep, anesthesia, coma, meditation, and hypnosis - and on what mysteries predictive processing has been able to disclose about brain functioning in such states. We review studies investigating how the neural signatures of auditory predictions are modulated by states of reduced or lacking consciousness. As a future outlook, we propose the combination of electrophysiological and computational techniques that will allow investigation of which facets of sensory predictive processes are maintained when consciousness fades away.

The effects of sleep on objective measures of gap detection using a time-efficient multi-deviant paradigm

Auditory temporal resolution, measured through gap detection, is critical for the perception of speech. A time-efficient multi-deviant paradigm has previously been developed for gap detection. The purpose of the present study was to determine if this multi-deviant paradigm could be used for gap detection during NREM sleep. ERPs were recorded in 10 young adults while awake and during the first two hours of NREM sleep. A multi-deviant paradigm was employed with six different deviants varying in gap duration, ranging from 2 to 40 ms. During waking, a DRN was observed for the 10, 20, 30 and 40 ms gaps. The DRN was absent during sleep. A P2 was present in NREM for the 20, 30 and 40 ms gaps followed by a P3a to the 30 and 40 ms gaps. An N350 was observed following the 10, 20, 30 and 40 ms gaps. Previous studies have reported significant ERPs to gaps having shorter durations than the present study. The multi-deviant paradigm may not be suitable for the determination of gap threshold during sleep. Nevertheless, it provides an exquisite means to determine perceptibility and the extent of processing of longer duration, supra-threshold gaps during sleep.

Cortical and subcortical hemodynamic changes during sleep slow waves in human light sleep

EEG slow waves, the hallmarks of NREM sleep are thought to be crucial for the regulation of several important processes, including learning, sensory disconnection and the removal of brain metabolic wastes. Animal research indicates that slow waves may involve complex interactions within and between cortical and subcortical structures. Conventional EEG in humans, however, has a low spatial resolution and is unable to accurately describe changes in the activity of subcortical and deep cortical structures. To overcome these limitations, here we took advantage of simultaneous EEG-fMRI recordings to map cortical and subcortical hemodynamic (BOLD) fluctuations time-locked to slow waves of light sleep. Recordings were performed in twenty healthy adults during an afternoon nap. Slow waves were associated with BOLD-signal increases in the posterior brainstem and in portions of thalamus and cerebellum characterized by preferential functional connectivity with limbic and somatomotor areas, respectively. At the cortical level, significant BOLD-signal decreases were instead found in several areas, including insula and somatomotor cortex. Specifically, a slow signal increase preceded slow-wave onset and was followed by a delayed, stronger signal decrease. Similar hemodynamic changes were found to occur at different delays across most cortical brain areas, mirroring the propagation of electrophysiological slow waves, from centro-frontal to inferior temporo-occipital cortices. Finally, we found that the amplitude of electrophysiological slow waves was positively related to the magnitude and inversely related to the delay of cortical and subcortical BOLD-signal changes. These regional patterns of brain activity are consistent with theoretical accounts of the functions of sleep slow waves.

Functional MRI of arousals in nonrapid eye movement sleep

Arousals commonly occur during human sleep and have been associated with several sleep disorders. Arousals are characterized as an abrupt electroencephalography (EEG) frequency change to higher frequencies during sleep. However, the human brain regions involved in arousal are not yet clear. Simultaneous EEG and functional magnetic resonance imaging (fMRI) data were recorded during the early portion of the sleep period in healthy young adults. Arousals were identified based on the EEG data, and fMRI signal changes associated with 83 arousals from 19 subjects were analyzed. Subcortical regions, including the midbrain, thalamus, basal ganglia, and cerebellum, were activated with arousal. Cortices, including the temporal gyrus, occipital gyrus, and frontal gyrus, were deactivated with arousal. The activations associated with arousal in the subcortical regions were consistent with previous findings of subcortical involvement in behavioral arousal and consciousness. Cortical deactivations may serve as a mechanism to direct incoming sensory stimuli to specific brain regions, thereby monitoring environmental perturbations during sleep.

Human blood adenosine biomarkers and non-rapid eye movement sleep stage 3 (NREM3) cortical functional connectivity associations during a 30-day head-down-tilt bed rest analogue: Potential effectiveness of a reactive sledge jump as a countermeasure

We investigated the alterations of sleep regulation and promotion biomarkers as adenosine through its enzymes total adenosine deaminase (tADA)/adenosine deaminase (ADA2) in a microgravity analogue environment of head-down-tilt bed rest and their association with brain connectivity networks during non-rapid eye movement sleep stage 3 (NREM3), as well as the effectiveness of the reactive sledge (RSL) jump countermeasure to promote sleep. A total of 23 healthy male volunteers were maintained in 6° head-down-tilt position for 30 days and assigned either to a control or to a RSL group. Blood collection and polysomnographic recordings were performed on data acquisition day 1, 14, 30 and -14, 21, respectively. Immunochemical techniques and network-based statistics were employed for adenosine enzymes and cortical connectivity estimation. Our findings indicate that human blood adenosine biomarkers as well as NREM3 cortical functional connectivity are impaired in simulated microgravity. RSL physical activity intervened in sleep quality via tADA/ADA2 fluctuations lack, minor cortical connectivity increases, and limited degree of node and resting-state networks. Statistically significant decreases in adenosine biomarkers and NREM3 functional connectivity involving regions (left superior temporal gyrus, right postcentral gyrus, precuneus, left middle frontal gyrus, left postcentral gyrus, left angular gyrus and precuneus) of the auditory, sensorimotor default-mode and executive networks highlight the sleep disturbances due to simulated microgravity and the sleep-promoting role of RSL countermeasure. The head-down-tilt environment led to sleep deterioration projected through NREM3 cortical brain connectivity or/and adenosine biomarkers shift. This decline was more pronounced in the absence of the RSL countermeasure, thereby highlighting its likely exploitation during space missions.

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.

Prediction error signaling explains neuronal mismatch responses in the medial prefrontal cortex

The mismatch negativity (MMN) is a key biomarker of automatic deviance detection thought to emerge from 2 cortical sources. First, the auditory cortex (AC) encodes spectral regularities and reports frequency-specific deviances. Then, more abstract representations in the prefrontal cortex (PFC) allow to detect contextual changes of potential behavioral relevance. However, the precise location and time asynchronies between neuronal correlates underlying this frontotemporal network remain unclear and elusive. Our study presented auditory oddball paradigms along with "no-repetition" controls to record mismatch responses in neuronal spiking activity and local field potentials at the rat medial PFC. Whereas mismatch responses in the auditory system are mainly induced by stimulus-dependent effects, we found that auditory responsiveness in the PFC was driven by unpredictability, yielding context-dependent, comparatively delayed, more robust and longer-lasting mismatch responses mostly comprised of prediction error signaling activity. This characteristically different composition discarded that mismatch responses in the PFC could be simply inherited or amplified downstream from the auditory system. Conversely, it is more plausible for the PFC to exert top-down influences on the AC, since the PFC exhibited flexible and potent predictive processing, capable of suppressing redundant input more efficiently than the AC. Remarkably, the time course of the mismatch responses we observed in the spiking activity and local field potentials of the AC and the PFC combined coincided with the time course of the large-scale MMN-like signals reported in the rat brain, thereby linking the microscopic, mesoscopic, and macroscopic levels of automatic deviance detection.

Microsleep is associated with brain activity patterns unperturbed by auditory inputs

Microsleeps are brief episodes of arousal level decrease manifested through behavioral signs. Brain activity during microsleep in the presence of external stimulus remains poorly understood. In this study, we sought to understand neural responses to auditory stimulation during microsleep. We gave participants the simple task of listening to audios of different pitches and amplitude modulation frequencies during early afternoon functional MRI scans. We found the following: 1) microsleep was associated with cortical activations in broad motor and sensory regions and deactivations in thalamus, irrespective of auditory stimulation; 2) high and low pitch audios elicited different activity patterns in the auditory cortex during awake but not microsleep state; and 3) during microsleep, spatial activity patterns in broad brain regions were similar regardless of the presence or types of auditory stimulus (i.e., stimulus invariant). These findings show that the brain is highly active during microsleep but the activity patterns across broad regions are unperturbed by auditory inputs.NEW & NOTEWORTHY During deep drowsy states, auditory inputs could induce activations in the auditory cortex, but the activation patterns lose differentiation to high/low pitch stimuli. Instead of random activations, activity patterns across the brain during microsleep appear to be structured and may reflect underlying neurophysiological processes that remain unclear.

A Comparison of Auditory Oddball Responses in Dorsolateral Prefrontal Cortex, Basolateral Amygdala, and Auditory Cortex of Macaque

The mismatch negativity (MMN) is an ERP component seen in response to unexpected "novel" stimuli, such as in an auditory oddball task. The MMN is of wide interest and application, but the neural responses that generate it are poorly understood. This is in part due to differences in design and focus between animal and human oddball paradigms. For example, one of the main explanatory models, the "predictive error hypothesis", posits differences in timing and selectivity between signals carried in auditory and prefrontal cortex (PFC). However, these predictions have not been fully tested because (1) noninvasive techniques used in humans lack the combined spatial and temporal precision necessary for these comparisons and (2) single-neuron studies in animal models, which combine necessary spatial and temporal precision, have not focused on higher order contributions to novelty signals. In addition, accounts of the MMN traditionally do not address contributions from subcortical areas known to be involved in novelty detection, such as the amygdala. To better constrain hypotheses and to address methodological gaps between human and animal studies, we recorded single neuron activity from the auditory cortex, dorsolateral PFC, and basolateral amygdala of two macaque monkeys during an auditory oddball paradigm modeled after that used in humans. Consistent with predictions of the predictive error hypothesis, novelty signals in PFC were generally later than in auditory cortex and were abstracted from stimulus-specific effects seen in auditory cortex. However, we found signals in amygdala that were comparable in magnitude and timing to those in PFC, and both prefrontal and amygdala signals were generally much weaker than those in auditory cortex. These observations place useful quantitative constraints on putative generators of the auditory oddball-based MMN and additionally indicate that there are subcortical areas, such as the amygdala, that may be involved in novelty detection in an auditory oddball paradigm.

Evidence of P3a During Sleep, a Process Associated With Intrusions Into Consciousness in the Waking State

The present study examines processes associated with intrusions into consciousness during an unconscious state, natural sleep. The definition of sleep is still much debated. Almost all researchers agree that sleep onset represents a gradual loss of consciousness of the external environment. For sleep to be beneficial, it needs to remain as undisturbed as possible. Nevertheless, unlike other unconsciousness states, sleep is reversible. For purposes of survival, it is critical that the sleeper be able to “detect” and perhaps become conscious of highly relevant biological or personal information. Therefore, even in sleep, the brain must decide whether a new incoming stimulus is relevant and if so, may require an arousal to wakefulness, or whether it is irrelevant and can be gated to prevent disruption of sleep. Event-related potentials (ERPs) were used to measure the extent processing of auditory stimuli some of which elicited an ERP component, the P3a, in the waking state. The P3a is associated with processes resulting in the interruption of frontal central executive, leading to conscious awareness. Very little research has focused on the occurrence of the P3a during sleep. A multi-feature paradigm was used to examine the processing of a frequently occurring “standard” stimulus and six rarely occurring different “deviant” stimuli during wakefulness, NREM, and REM sleep. A P3a was elicited by novel environmental sounds and white noise bursts in the waking state, replicating previous studies. Other deviant stimuli (changes in pitch, intensity, duration) failed to do so. The ERPs indicated that processing of the stimuli that did not elicit a P3a in wakefulness were much inhibited during both NREM and REM sleep. Surprisingly, those deviants that did elicit a P3a in wakefulness continued to do so in stage N2 and REM sleep. The subject did not, however, awaken. These results suggest processes leading to consciousness in wakefulness may still remain active during sleep possibly allowing subjects to act on potentially highly relevant input. This may also explain how sleep can be reversed if the stimulus input is sufficiently critical.

A Modulatory Effect of Brief Passive Exposure to Non-linguistic Sounds on Intrinsic Functional Connectivity: Relevance to Cognitive Performance

A growing literature on resting-state fMRI (R-fMRI) has explored the impact of preceding sensory experience on intrinsic functional connectivity (iFC). However, it remains largely unknown how passive exposure to irrelevant auditory stimuli, which is a constant in everyday life, reconfigures iFC. Here, we directly compared pre- and post-exposure R-fMRI scans to examine: 1) modulatory effects of brief passive exposure to repeating non-linguistic sounds on subsequent iFC, and 2) associations between iFC modulations and cognitive abilities. We used an exploratory regional homogeneity (ReHo) approach that indexes local iFC, and performed a linear mixed-effects modeling analysis. A modulatory effect (increase) in ReHo was observed in the right superior parietal lobule (R.SPL) within the parietal attention network. Post hoc seed-based correlation analyses provided further evidence for increased parietal iFC (e.g., R.SPL with the right inferior parietal lobule). Notably, less iFC modulation was associated with better cognitive performance (e.g., word reading). These results suggest that: 1) the parietal attention network dynamically reconfigures its iFC in response to passive (thus irrelevant) non-linguistic sounds, but also 2) minimization of iFC modulation in the same network characterizes better cognitive performance. Our findings may open up new avenues for investigating cognitive disorders that involve impaired sensory processing.

The beneficial role of memory reactivation for language learning during sleep: A review

Sleep is essential for diverse aspects of language learning. According to a prominent concept these beneficial effects of sleep rely on spontaneous reactivation processes. A series of recent studies demonstrated that inducing such reactivation processes by re-exposure to memory cues during sleep enhances foreign vocabulary learning. Building upon these findings, the present article reviews recent models and empirical findings concerning the beneficial effects of sleep on language learning. Consequently, the memory function of sleep, its neural underpinnings and the role of the sleeping brain in language learning will be summarized. Finally, we will propose a working model concerning the oscillatory requirements for successful reactivation processes and future research questions to advance our understanding of the role of sleep on language learning and memory processes in general.

Diminished Auditory Responses during NREM Sleep Correlate with the Hierarchy of Language Processing

Natural sleep provides a powerful model system for studying the neuronal correlates of awareness and state changes in the human brain. To quantitatively map the nature of sleep-induced modulations in sensory responses we presented participants with auditory stimuli possessing different levels of linguistic complexity. Ten participants were scanned using functional magnetic resonance imaging (fMRI) during the waking state and after falling asleep. Sleep staging was based on heart rate measures validated independently on 20 participants using concurrent EEG and heart rate measurements and the results were confirmed using permutation analysis. Participants were exposed to three types of auditory stimuli: scrambled sounds, meaningless word sentences and comprehensible sentences. During non-rapid eye movement (NREM) sleep, we found diminishing brain activation along the hierarchy of language processing, more pronounced in higher processing regions. Specifically, the auditory thalamus showed similar activation levels during sleep and waking states, primary auditory cortex remained activated but showed a significant reduction in auditory responses during sleep, and the high order language-related representation in inferior frontal gyrus (IFG) cortex showed a complete abolishment of responses during NREM sleep. In addition to an overall activation decrease in language processing regions in superior temporal gyrus and IFG, those areas manifested a loss of semantic selectivity during NREM sleep. Our results suggest that the decreased awareness to linguistic auditory stimuli during NREM sleep is linked to diminished activity in high order processing stations.

Increasing Explicit Sequence Knowledge by Odor Cueing during Sleep in Men but not Women

Sleep consolidates newly acquired memories. Beyond stabilizing memories, sleep is thought to reorganize memory representations such that invariant structures, statistical regularities and even new explicit knowledge are extracted. Whereas increasing evidence suggests that the stabilization of memories during sleep can be facilitated by cueing with learning-associated stimuli, the effect of cueing on memory reorganization is less well understood. Here we asked whether olfactory cueing during sleep enhances the generation of explicit knowledge about an implicitly learned procedural memory task. Subjects were trained on a serial reaction time task (SRTT) containing a hidden 12-element sequence in the presence of an odor. During subsequent sleep, half of the subjects were re-exposed to the odor during periods of slow wave sleep (SWS), while the other half received odorless vehicle. In the next morning, subjects were tested on their explicit knowledge about the underlying sequence in a free recall test and a generation task. Although odor cueing did not significantly affect overall explicit knowledge, differential effects were evident when analyzing male and female subjects separately. Explicit sequence knowledge, both in free recall and the generation task, was enhanced by odor cueing in men, whereas women showed no cueing effect. Procedural skill in the SRTT was not affected by cueing, neither in men nor in women. These findings suggest that olfactory memory reactivation can increase explicit knowledge about implicitly learned information, but only in men. Hormonal differences due to menstrual cycle phase and/or hormonal contraceptives might explain the lacking effect in women.

Implicit memory for words heard during sleep

When we fall asleep, our awareness of the surrounding world fades. Yet, the sleeping brain is far from being dormant and recent research unraveled the preservation of complex sensory processing during sleep. In wakefulness, such processes usually lead to the formation of long-term memory traces, being it implicit or explicit. We examined here the consequences upon awakening of the processing of sensory information at a high level of representation during sleep. Participants were instructed to classify auditory stimuli as words or pseudo-words, through left and right hand responses, while transitioning toward sleep. An analysis of the electroencephalographic (EEG) signal revealed the preservation of lateralized motor activations in response to sounds, suggesting that stimuli were correctly categorized during sleep. Upon awakening, participants did not explicitly remember words processed during sleep and failed to distinguish them from new words (old/new recognition test). However, both behavioral and EEG data indicate the presence of an implicit memory trace for words presented during sleep. In addition, the underlying neural signature of such implicit memories markedly differed from the explicit memories formed during wakefulness, in line with dual-process accounts arguing for two independent systems for explicit and implicit memory. Thus, our results reveal that implicit learning mechanisms can be triggered during sleep and provide a novel approach to explore the neural implementation of memory without awareness.

Connectivity of Superior Temporal Sulcus During Target Detection

Abstract. The aim of the current research was to study functional connectivity (FC) of the right superior temporal sulcus (rSTS) during visual target stimulus processing. This structure is presumed to be crucial in social cognition, but evidently participates in target detection as well. Twenty subjects participated in functional magnetic resonance examination for studying FC. We used psychophysiological interaction (PPI) analysis of data acquired during the visual oddball task. During the visual oddball task rSTS had increased connectivity bilaterally with structures involved in memory operations (mesiotemporal cortices and basal ganglia) and evaluative processing related to decision making (left anterior cingulate cortex). Moreover, we revealed decreased connectivity of rSTS with structures involved in attentional processes (right dorsolateral prefrontal cortex (DLPFC) and the posterior area with bilateral parietal cortex). Based on our results we hypothesize that in the detection of rare events, during visual information processing, rSTS is involved within neuronal networks related to attention, but also at later stages of stimuli processing.

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.

Partial K-Complex Recovery Following Short-Term Abstinence in Individuals with Alcohol Use Disorder

BACKGROUND

The K-complex (KC) is a brain potential characteristic of nonrapid eye movement (NREM) sleep resulting from the synchronous activity of a large population of neurons and hypothesized to reflect brain integrity. KC amplitude is lower in individuals with alcohol use disorder (AUD) compared with age-matched controls, but its recovery with short-term abstinence has not been studied. Therefore, we investigated whether the KC shows significant recovery over the first 4 months of abstinence in individuals with AUD.

METHODS

A total of 16 recently abstinent AUD individuals (46.6 ± 9.3 years) and 13 gender and age-matched healthy controls (41.6 ± 8.3 years) were studied on 3 occasions: the Initial session was within 1 month of the AUD individuals' last drink, then 1 and 3 months later. Overnight electroencephalogram was recorded while participants were presented with tones during stage 2 NREM sleep to elicit KCs.

RESULTS

At the Initial session, AUD participants showed significantly lower KC amplitude and incidence compared with controls. In the AUD individuals, KC amplitude increased significantly from the Initial to the 1-month session. KC incidence showed a marginally significant increase. Neither KC amplitude nor incidence changed from the 1-month to the 3-month session. No changes in KC amplitude or incidence across sessions were observed in the control group.

CONCLUSIONS

Our results demonstrate partial KC recovery during the first 2 months of abstinence. This recovery is consistent with the time course of structural brain recovery in abstinent AUD individuals demonstrated by recent neuroimaging results.

Are Absence Epilepsy and Nocturnal Frontal Lobe Epilepsy System Epilepsies of the Sleep/Wake System?

System epilepsy is an emerging concept interpreting major nonlesional epilepsies as epileptic dysfunctions of physiological systems. I extend here the concept of reflex epilepsy to epilepsies linked to input dependent physiological systems. Experimental and clinical reseach data were collected to create a coherent explanation of underlying pathomechanism in AE and NFLE. We propose that AE should be interpreted as epilepsy linked to the corticothalamic burst-firing mode of NREM sleep, released by evoked vigilance level oscillations characterized by reactive slow wave response. In the genetic variation of NFLE the ascending cholinergic arousal system plays an essential role being in strong relationship with a gain mutation of the nicotinic acethylcholin receptors, rendering the arousal system hyperexcitable. I try to provide a more unitary interpretation for the variable seizure manifestation integrating them as different degree of pathological arosuals and alarm reactions. As a supporting hypothesis the similarity between arousal parasomnias and FNLE is shown, underpinned by overlaping pathomechanism and shared familiarity, but without epileptic features. Lastly we propose that both AE and NFLE are system epilepsies of the sleep-wake system representing epileptic disorders of the antagonistic sleep/arousal network. This interpretation may throw new light on the pathomechanism of AE and NFLE.

Enhancement of sleep slow waves: underlying mechanisms and practical consequences

Even modest sleep restriction, especially the loss of sleep slow wave activity (SWA), is invariably associated with slower electroencephalogram (EEG) activity during wake, the occurrence of local sleep in an otherwise awake brain, and impaired performance due to cognitive and memory deficits. Recent studies not only confirm the beneficial role of sleep in memory consolidation, but also point to a specific role for sleep slow waves. Thus, the implementation of methods to enhance sleep slow waves without unwanted arousals or lightening of sleep could have significant practical implications. Here we first review the evidence that it is possible to enhance sleep slow waves in humans using transcranial direct-current stimulation (tDCS) and transcranial magnetic stimulation. Since these methods are currently impractical and their safety is questionable, especially for chronic long-term exposure, we then discuss novel data suggesting that it is possible to enhance slow waves using sensory stimuli. We consider the physiology of the K-complex (KC), a peripheral evoked slow wave, and show that, among different sensory modalities, acoustic stimulation is the most effective in increasing the magnitude of slow waves, likely through the activation of non-lemniscal ascending pathways to the thalamo-cortical system. In addition, we discuss how intensity and frequency of the acoustic stimuli, as well as exact timing and pattern of stimulation, affect sleep enhancement. Finally, we discuss automated algorithms that read the EEG and, in real-time, adjust the stimulation parameters in a closed-loop manner to obtain an increase in sleep slow waves and avoid undesirable arousals. In conclusion, while discussing the mechanisms that underlie the generation of sleep slow waves, we review the converging evidence showing that acoustic stimulation is safe and represents an ideal tool for slow wave sleep (SWS) enhancement.

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.

Experienced mindfulness meditators exhibit higher parietal-occipital EEG gamma activity during NREM sleep

Over the past several years meditation practice has gained increasing attention as a non-pharmacological intervention to provide health related benefits, from promoting general wellness to alleviating the symptoms of a variety of medical conditions. However, the effects of meditation training on brain activity still need to be fully characterized. Sleep provides a unique approach to explore the meditation-related plastic changes in brain function. In this study we performed sleep high-density electroencephalographic (hdEEG) recordings in long-term meditators (LTM) of Buddhist meditation practices (approximately 8700 mean hours of life practice) and meditation naive individuals. We found that LTM had increased parietal-occipital EEG gamma power during NREM sleep. This increase was specific for the gamma range (25–40 Hz), was not related to the level of spontaneous arousal during NREM and was positively correlated with the length of lifetime daily meditation practice. Altogether, these findings indicate that meditation practice produces measurable changes in spontaneous brain activity, and suggest that EEG gamma activity during sleep represents a sensitive measure of the long-lasting, plastic effects of meditative training on brain function.

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.

EEG-fMRI Methods for the Study of Brain Networks during Sleep

Modern neuroimaging methods may provide unique insights into the mechanism and role of sleep, as well as into particular mechanisms of brain function in general. Many of the recent neuroimaging studies have used concurrent EEG and fMRI, which present unique technical challenges ranging from the difficulty of inducing sleep in the MRI environment to appropriate instrumentation and data processing methods to obtain artifact free data. In addition, the use of EEG-fMRI during sleep leads to unique data interpretation issues, as common approaches developed for the analysis of task-evoked activity do not apply to sleep. Reviewed are a variety of statistical approaches that can be used to characterize brain activity from fMRI data acquired during sleep, with an emphasis on approaches that investigate the presence of correlated activity between brain regions. Each of these approaches has advantages and disadvantages that must be considered in concert with the theoretical questions of interest. Specifically, fundamental theories of sleep control and function should be considered when designing these studies and when choosing the associated statistical approaches. For example, the notion that local brain activity during sleep may be triggered by local, use-dependent activity during wakefulness may be tested by analyzing sleep networks as statistically independent components. Alternatively, the involvement of regions in more global processes such as arousal may be investigated with correlation analysis.

The Fate of Incoming Stimuli during NREM Sleep is Determined by Spindles and the Phase of the Slow Oscillation

The present study aimed at identifying the neurophysiological responses associated with auditory stimulation during non-rapid eye movement (NREM) sleep using simultaneous electroencephalography (EEG)/functional magnetic resonance imaging (fMRI) recordings. It was reported earlier that auditory stimuli produce bilateral activation in auditory cortex, thalamus, and caudate during both wakefulness and NREM sleep. However, due to the spontaneous membrane potential fluctuations cortical responses may be highly variable during NREM. Here we now examine the modulation of cerebral responses to tones depending on the presence or absence of sleep spindles and the phase of the slow oscillation. Thirteen healthy young subjects were scanned successfully during stage 2-4 NREM sleep in the first half of the night in a 3 T scanner. Subjects were not sleep-deprived and sounds were post hoc classified according to (i) the presence of sleep spindles or (ii) the phase of the slow oscillation during (±300 ms) tone delivery. These detected sounds were then entered as regressors of interest in fMRI analyses. Interestingly wake-like responses - although somewhat altered in size and location - persisted during NREM sleep, except during present spindles (as previously published in Dang-Vu et al., 2011) and the negative going phase of the slow oscillation during which responses became less consistent or even absent. While the phase of the slow oscillation did not alter brain responses in primary sensory cortex, it did modulate responses at higher cortical levels. In addition EEG analyses show a distinct N550 response to tones during the presence of light sleep spindles and suggest that in deep NREM sleep the brain is more responsive during the positive going slope of the slow oscillation. The presence of short temporal windows during which the brain is open to external stimuli is consistent with the fact that even during deep sleep meaningful events can be detected. Altogether, our results emphasize the notion that spontaneous fluctuations of brain activity profoundly modify brain responses to external information across all behavioral states, including deep NREM sleep.

Brain activation disturbance for target detection in patients with mild cognitive impairment: an fMRI study

Functional brain imaging in mild cognitive impairment (MCI) reveals differences in activation of task-relevant brain areas between patients and age-matched healthy controls. However, some studies reported hyperactivation and others hypoactivation in MCI compared with controls. The inconsistencies may be explained by compensatory mechanisms due to high complexity of the applied tasks. The oddball task is a simple paradigm that is known to activate a widespread network in the brain, involving attentional and monitoring mechanisms. In the present study, we examined amnestic or amnestic multidomain MCI patients (n = 12) and healthy controls (n = 13) in an auditory oddball task. Participants had to respond to infrequent targets and inhibit response to infrequent novel-nontarget stimuli. Lower stimulus related activation was found in MCI patients compared with healthy controls in parts of the middle temporal gyrus, the temporal pole, regions along the superior temporal sulcus, in the left cuneus, the left supramarginal gyrus, the anterior cingulated cortex and in the left inferior and middle frontal gyrus. Activation for oddball stimuli is assumed to reflect an automatic reflexive engagement of many brain regions in response to potentially important changes in the environment as well as cognitive control to monitor responses. The mechanisms of attention and cognitive control may be severely impaired in MCI and thus, underlie the cognitive deficits of this clinical group.

Independent contributions of cortical gray matter, aging, sex and alcoholism to K-complex amplitude evoked during sleep

STUDY OBJECTIVES

The amplitude of the N550 component derived from the averaged evoked K-complex decreases with normal aging and with alcoholism. The study was designed to determine whether these declines are related to the extent of cortical or subcortical shrinkage.

SETTING

Research sleep laboratory and MR imaging facility

PARTICIPANTS

26 abstinent long-term alcoholic men, 14 abstinent long-term alcoholic women, 18 control men, and 22 control women.

MEASUREMENTS AND RESULTS

MRI data collected at 3T were analyzed from alcoholic and control men and women previously reported to have significantly different evoked delta activity during sleep. Segmented and parcellated MRI data collected at 3T were compared between these groups and evaluated for correlation with evoked K-complex amplitude measured at FP1, Fz, FCz, Cz, CPz, and Pz. Cortical gray matter and regional subcortical tissue volumes entered as predictors into stepwise multiple regression identified cortical gray matter as a unique significant predictor of evoked K-complex at all sites. Age added independent variance at 5 of the 6 sites, while alcoholism and sex added independent variance at frontal sites only.

CONCLUSIONS

These data support recent intracranial studies showing cortical generation of K-complexes by indicating that cortical, but not subcortical volume contributes to K-complex amplitude. Establishing the extent of the relation between cortical volume and K-complex amplitude provides a mechanistic understanding of sleep compromise clinically relevant to normal aging, alcoholism, and likely other conditions affecting cortical volume and integrity.

Temporal dynamics of cortical sources underlying spontaneous and peripherally evoked slow waves

Slow waves are the most prominent electroencephalographic feature of non-rapid eye movement (NREM) sleep. During NREM sleep, cortical neurons oscillate approximately once every second between a depolarized upstate, when cortical neurons are actively firing, and a hyperpolarized downstate, when cortical neurons are virtually silent (Destexhe et al., 1999; Steriade et al., 1993a, 2001). Intracellular recordings indicate that the origins of the slow oscillation are cortical and that corticocortical connections are necessary for their synchronization (Amzica and Steriade, 1995; Steriade et al., 1993b; Timofeev and Steriade, 1996; Timofeev et al., 2000). The currents produced by the near-synchronous slow oscillation of large populations of neurons appear on the scalp as electroencephalogram (EEG) slow waves (Amzica and Steriade, 1997). Despite this cellular understanding, questions remain about the role of specific cortical structures in individual slow waves. Early EEG studies of slow waves in humans were limited by the small number of derivations employed and by the difficulty of relating scalp potentials to underlying brain activity (Brazier, 1949; Roth et al., 1956). Functional neuroimaging methods offer exceptional spatial resolution, but lack the temporal resolution to track individual slow waves (Dang-Vu et al., 2008; Maquet, 2000). Intracranial recordings in patient populations are limited by the availability of medically necessary electrode placements and can be confounded by pathology and medications (Cash et al., 2009; Nir et al., 2011; Wenneberg 2010). Source modeling of high-density EEG recordings offers a unique opportunity for neuroimaging sleep slow waves. So far, the results have challenged several of the influential topographic observations about slow waves that had persisted since the original EEG recordings of sleep. These recent analyses revealed that individual slow waves are idiosyncratic cortical events and that the negative peak of the EEG slow wave often involves cortical structures not necessarily apparent from the scalp, like the inferior frontal gyrus, anterior cingulate, posterior cingulate, and precuneus (Murphy et al., 2009). In addition, not only do slow waves travel (Massimini et al., 2004), but they often do so preferentially through the areas comprising the major connectional backbone of the human cortex (Hagmann et al., 2008). In this chapter, we will review the cellular, intracranial recording, and neuroimaging results concerning EEG slow waves. We will also confront a long held belief about peripherally evoked slow waves, also known as K-complexes, namely that they are modality independent and do not involve cortical sensory pathways. The analysis included here is the first to directly compare K-complexes evoked with three different stimulation modalities within the same subject on the same night using high-density EEG.

Functional neuroimaging insights into the physiology of human sleep

Functional brain imaging has been used in humans to noninvasively investigate the neural mechanisms underlying the generation of sleep stages. On the one hand, REM sleep has been associated with the activation of the pons, thalamus, limbic areas, and temporo-occipital cortices, and the deactivation of prefrontal areas, in line with theories of REM sleep generation and dreaming properties. On the other hand, during non-REM (NREM) sleep, decreases in brain activity have been consistently found in the brainstem, thalamus, and in several cortical areas including the medial prefrontal cortex (MPFC), in agreement with a homeostatic need for brain energy recovery. Benefiting from a better temporal resolution, more recent studies have characterized the brain activations related to phasic events within specific sleep stages. In particular, they have demonstrated that NREM sleep oscillations (spindles and slow waves) are indeed associated with increases in brain activity in specific subcortical and cortical areas involved in the generation or modulation of these waves. These data highlight that, even during NREM sleep, brain activity is increased, yet regionally specific and transient. Besides refining the understanding of sleep mechanisms, functional brain imaging has also advanced the description of the functional properties of sleep. For instance, it has been shown that the sleeping brain is still able to process external information and even detect the pertinence of its content. The relationship between sleep and memory has also been refined using neuroimaging, demonstrating post-learning reactivation during sleep, as well as the reorganization of memory representation on the systems level, sometimes with long-lasting effects on subsequent memory performance. Further imaging studies should focus on clarifying the role of specific sleep patterns for the processing of external stimuli, as well as the consolidation of freshly encoded information during sleep.