Human gamma oscillations during slow wave sleep

Neocortical local field potentials have shown that gamma oscillations occur spontaneously during slow-wave sleep (SWS). At the macroscopic EEG level in the human brain, no evidences were reported so far. In this study, by using simultaneous scalp and intracranial EEG recordings in 20 epileptic subjects, we examined gamma oscillations in cerebral cortex during SWS. We report that gamma oscillations in low (30-50 Hz) and high (60-120 Hz) frequency bands recurrently emerged in all investigated regions and their amplitudes coincided with specific phases of the cortical slow wave. In most of the cases, multiple oscillatory bursts in different frequency bands from 30 to 120 Hz were correlated with positive peaks of scalp slow waves ("IN-phase" pattern), confirming previous animal findings. In addition, we report another gamma pattern that appears preferentially during the negative phase of the slow wave ("ANTI-phase" pattern). This new pattern presented dominant peaks in the high gamma range and was preferentially expressed in the temporal cortex. Finally, we found that the spatial coherence between cortical sites exhibiting gamma activities was local and fell off quickly when computed between distant sites. Overall, these results provide the first human evidences that gamma oscillations can be observed in macroscopic EEG recordings during sleep. They support the concept that these high-frequency activities might be associated with phasic increases of neural activity during slow oscillations. Such patterned activity in the sleeping brain could play a role in off-line processing of cortical networks.     

Sleep-Stage Correlates of Hippocampal Electroencephalogram in Primates

It has been demonstrated in the rodent hippocampus that rhythmic slow activity (theta) predominantly occurs during rapid eye movement (REM) sleep, while sharp waves and associated ripples occur mainly during non-REM sleep. However, evidence is lacking for correlates of sleep stages with electroencephalogram (EEG) in the hippocampus of monkeys. In the present study, we recorded hippocampal EEG from the dentate gyrus in monkeys overnight under conditions of polysomnographical monitoring. As result, the hippocampal EEG changed in a manner similar to that of the surface EEG: during wakefulness, the hippocampal EEG showed fast, desynchronized waves, which were partly replaced with slower waves of intermediate amplitudes during the shallow stages of non-REM sleep. During the deep stages of non-REM sleep, continuous, slower oscillations (0.5–8 Hz) with high amplitudes were predominant. During REM sleep, the hippocampal EEG again showed fast, desynchronized waves similar to those found during wakefulness. These results indicate that in the monkey, hippocampal rhythmic slow activity rarely occurs during REM sleep, which is in clear contrast to that of rodents. In addition, the increase in the slower oscillations of hippocampal EEG during non-REM sleep, which resembled that of the surface EEG, may at least partly reflect cortical inputs to the dentate gyrus during this behavioral state.     

Electrophysiological correlates of rest and activity in Drosophila melanogaster

Extended periods of rest in Drosophila melanogaster resemble mammalian sleep states in that they are characterized by heightened arousal thresholds and specific alterations in gene expression. Defined as inactivity periods spanning 5 or more min, amounts of this sleep-like state are, as in mammals, sensitive to prior amounts of waking activity, time of day, and pharmacological intervention. Clearly recognizable changes in the pattern and amount of brain electrical activity accompany changes in motor activity and arousal thresholds originally used to identify mammalian sleeping behavior. Electroencephalograms (EEGs) and/or local field potentials (LFPs) are now widely used to quantify sleep state amounts and define types of sleep. Thus, slow-wave sleep (SWS) is characterized by EEG spindles and large-amplitude delta-frequency (0-3.5 Hz) waves. Rapid-eye movement (REM) sleep is characterized by irregular gamma-frequency cortical EEG patterns and rhythmic theta-frequency (5-9 Hz) hippocampal EEG activity. It is unknown whether rest and activity in Drosophila are associated with distinct electrophysiological correlates. To address this issue, we monitored motor activity levels and recorded LFPs in the medial brain between the mushroom bodies, structures implicated in the modulation of locomotor activity, of Drosophila. The results indicate that LFPs can be reliably recorded from the brains of awake, moving fruit flies, that targeted genetic manipulations can be used to localize sources of LFP activity, and that brain electrical activity of Drosophila is reliably correlated with activity state.     

Sound Asleep: Processing and Retention of Slow Oscillation Phase-Targeted Stimuli

The sleeping brain retains some residual information processing capacity. Although direct evidence is scarce, a substantial literature suggests the phase of slow oscillations during deep sleep to be an important determinant for stimulus processing. Here, we introduce an algorithm for predicting slow oscillations in real-time. Using this approach to present stimuli directed at both oscillatory up and down states, we show neural stimulus processing depends importantly on the slow oscillation phase. During ensuing wakefulness, however, we did not observe differential brain or behavioral responses to these stimulus categories, suggesting no enduring memories were formed. We speculate that while simpler forms of learning may occur during sleep, neocortically based memories are not readily established during deep sleep.     

Analysis of the Temporal Organization of Sleep Spindles in the Human Sleep EEG Using a Phenomenological Modeling Approach

The sleep electroencephalogram (EEG) is characterized by typical oscillatory patterns such as sleep spindles and slow waves. Recently, we proposed a method to detect and analyze these patterns using linear autoregressive models for short (≈?1 s) data segments. We analyzed the temporal organization of sleep spindles and discuss to what extent the observed interevent intervals correspond to properties of stationary stochastic processes and whether additional slow processes, such as slow oscillations, have to be assumed. We have found evidence for such an additional slow process, most pronounced in sleep stage 2.     

Transcranial electrical currents to probe EEG brain rhythms and memory consolidation during sleep in humans

Previously the application of a weak electric anodal current oscillating with a frequency of the sleep slow oscillation (～0.75 Hz) during non-rapid eye movement sleep (NonREM) sleep boosted endogenous slow oscillation activity and enhanced sleep-associated memory consolidation. The slow oscillations occurring during NonREM sleep and theta oscillations present during REM sleep have been considered of critical relevance for memory formation. Here transcranial direct current stimulation (tDCS) oscillating at 5 Hz, i.e., within the theta frequency range (theta-tDCS) is applied during NonREM and REM sleep. Theta-tDCS during NonREM sleep produced a global decrease in slow oscillatory activity conjoint with a local reduction of frontal slow EEG spindle power (8-12 Hz) and a decrement in consolidation of declarative memory, underlining the relevance of these cortical oscillations for sleep-dependent memory consolidation. In contrast, during REM sleep theta-tDCS appears to increase global gamma (25-45 Hz) activity, indicating a clear brain state-dependency of theta-tDCS. More generally, results demonstrate the suitability of oscillating-tDCS as a tool to analyze functions of endogenous EEG rhythms and underlying endogenous electric fields as well as the interactions between EEG rhythms of different frequencies.     

Local sleep homeostasis in the avian brain: convergence of sleep function in mammals and birds?

The function of the brain activity that defines slow wave sleep (SWS) and rapid eye movement (REM) sleep in mammals is unknown. During SWS, the level of electroencephalogram slow wave activity (SWA or 0.5-4.5 Hz power density) increases and decreases as a function of prior time spent awake and asleep, respectively. Such dynamics occur in response to waking brain use, as SWA increases locally in brain regions used more extensively during prior wakefulness. Thus, SWA is thought to reflect homeostatically regulated processes potentially tied to maintaining optimal brain functioning. Interestingly, birds also engage in SWS and REM sleep, a similarity that arose via convergent evolution, as sleeping reptiles and amphibians do not show similar brain activity. Although birds deprived of sleep show global increases in SWA during subsequent sleep, it is unclear whether avian sleep is likewise regulated locally. Here, we provide, to our knowledge, the first electrophysiological evidence for local sleep homeostasis in the avian brain. After staying awake watching David Attenborough's The Life of Birds with only one eye, SWA and the slope of slow waves (a purported marker of synaptic strength) increased only in the hyperpallium--a primary visual processing region--neurologically connected to the stimulated eye. Asymmetries were specific to the hyperpallium, as the non-visual mesopallium showed a symmetric increase in SWA and wave slope. Thus, hypotheses for the function of mammalian SWS that rely on local sleep homeostasis may apply also to birds.     

Dynamic Interaction of Spindles and Gamma Activity during Cortical Slow Oscillations and Its Modulation by Subcortical Afferents

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

Dynamics of spontaneous activity in random networks with multiple neuron subtypes and synaptic noise

During slow-wave sleep, brain electrical activity is dominated by the slow (< 1 Hz) electroencephalogram (EEG) oscillations characterized by the periodic transitions between active (or Up) and silent (or Down) states in the membrane voltage of the cortical and thalamic neurons. Sleep slow oscillation is believed to play critical role in consolidation of recent memories. Past computational studies, based on the Hodgkin-Huxley type neuronal models, revealed possible intracellular and network mechanisms of the neuronal activity during sleep, however, they failed to explore the large-scale cortical network dynamics depending on collective behavior in the large populations of neurons. In this new study, we developed a novel class of reduced discrete time spiking neuron models for large-scale network simulations of wake and sleep dynamics. In addition to the spiking mechanism, the new model implemented nonlinearities capturing effects of the leak current, the Ca²⁺ dependent K⁺ current and the persistent Na⁺ current that were found to be critical for transitions between Up and Down states of the slow oscillation. We applied the new model to study large-scale two-dimensional cortical network activity during slow-wave sleep. Our study explained traveling wave dynamics and characteristic synchronization properties of transitions between Up and Down states of the slow oscillation as observed in vivo in recordings from cats. We further predict a critical role of synaptic noise and slow adaptive currents for spike sequence replay as found during sleep related memory consolidation.     

Large-scale cortical dynamics of sleep slow waves

Slow waves constitute the main signature of sleep in the electroencephalogram (EEG). They reflect alternating periods of neuronal hyperpolarization and depolarization in cortical networks. While recent findings have demonstrated their functional role in shaping and strengthening neuronal networks, a large-scale characterization of these two processes remains elusive in the human brain. In this study, by using simultaneous scalp EEG and intracranial recordings in 10 epileptic subjects, we examined the dynamics of hyperpolarization and depolarization waves over a large extent of the human cortex. We report that both hyperpolarization and depolarization processes can occur with two different characteristic time durations which are consistent across all subjects. For both hyperpolarization and depolarization waves, their average speed over the cortex was estimated to be approximately 1 m/s. Finally, we characterized their propagation pathways by studying the preferential trajectories between most involved intracranial contacts. For both waves, although single events could begin in almost all investigated sites across the entire cortex, we found that the majority of the preferential starting locations were located in frontal regions of the brain while they had a tendency to end in posterior and temporal regions.     

Sleepy dialogues between cortex and hippocampus: who talks to whom?

During NREM sleep, neocortical neurons undergo near-synchronous transitions, every second or so, between UP states, during which they are depolarized and fire actively, and DOWN states, during which they are hyperpolarized and completely silent. In this issue of Neuron, Isomura et al. report that slow oscillations of membrane potential occur near-synchronously not only in neocortex but also in entorhinal cortex and subiculum. Within the hippocampus proper, pyramidal neurons lack the bistability of UP and DOWN states, but their firing is strongly modulated by cortical activity during the UP state. Intriguingly, many hippocampal neurons fire during the cortical DOWN state. Thus, during sleep UP states, the cortex can talk to the hippocampus, but it is unclear whether the hippocampus talks back.     

Relationship between sleep and eye state in Cetaceans and Pinnipeds

We recorded EEG from both hemispheres and documented the state of the two eyes in two species of Cetaceans (one beluga and one bottlenose dolphin) and one species of Pinnipeds (two northern fur seals). In the dolphin and beluga we found that episodes of unihemispheric slow wave sleep (USWS) were associated with asymmetry in eye state. During USWS and asymmetrical SWS the eye contralateral to the sleeping hemisphere was mostly closed or in an intermediate state while the eye contralateral to the waking hemisphere was more often open or in an intermediate state. Bilateral eye opening indicated waking in about 80% cases and unilateral eye closure indicated USWS with an accuracy of about 75%. Bilateral eye closure was rare (< 2% of the observation time) and was not necessarily associated with high amplitude SWS. In fur seals, episodes of one eye briefly opening usually occurred in the beginning of sleep episodes and lasted several minutes. Those episodes were frequently associated with lower amplitude EEG slow waves in the contralateral brain hemisphere. During most of their sleep on land, fur seals had both eyes tightly closed. No EEG asymmetry was recorded at this time. Although eye state and EEG stage are correlated in the bottlenose dolphin, beluga and fur seals, short episodes of EEG synchrony (less then 1 min) occur contralateral to an open eye and waking (a more activated EEG) activity can be present contralateral to a closed eye. The available data suggest that two functions of USWS/EEG asymmetry during SWS in Cetaceans and fur seals are multisensory control of the environment and maintenance of motion and postures of sleep. The adaptive advantages of USWS throughout the evolution of Cetaceans and Pinnipeds from terrestrial mammals to present forms could include 1) the avoidance of predators and maintenance of contact with other animals of the same species; 2) continuance of regular breathing; 3) and effective thermoregulation in the water environment.     

Electroencephalogram bands modulated by vigilance states in an anuran species: a factor analytic approach

Dramatic changes in neocortical electroencephalogram (EEG) rhythms are associated with the sleep–waking cycle in mammals. Although amphibians are thought to lack a neocortical homologue, changes in rest–activity states occur in these species. In the present study, EEG signals were recorded from the surface of the cerebral hemispheres and midbrain on both sides of the brain in an anuran species, Babina daunchina, using electrodes contacting the meninges in order to measure changes in mean EEG power across behavioral states. Functionally relevant frequency bands were identified using factor analysis. The results indicate that: (1) EEG power was concentrated in four frequency bands during the awake or active state and in three frequency bands during rest; (2) EEG bands in frogs differed substantially from humans, especially in the fast frequency band; (3) bursts similar to mammalian sleep spindles, which occur in non-rapid eye movement mammalian sleep, were observed when frogs were at rest suggesting sleep spindle-like EEG activity appeared prior to the evolution of mammals.     

The Temporal Structure of Behaviour and Sleep Homeostasis

The amount and architecture of vigilance states are governed by two distinct processes, which occur at different time scales. The first, a slow one, is related to a wake/sleep dependent homeostatic Process S, which occurs on a time scale of hours, and is reflected in the dynamics of NREM sleep EEG slow-wave activity. The second, a fast one, is manifested in a regular alternation of two sleep states – NREM and REM sleep, which occur, in rodents, on a time scale of ∼5–10 minutes. Neither the mechanisms underlying the time constants of these two processes – the slow one and the fast one, nor their functional significance are understood. Notably, both processes are primarily apparent during sleep, while their potential manifestation during wakefulness is obscured by ongoing behaviour. Here, we find, in mice provided with running wheels, that the two sleep processes become clearly apparent also during waking at the level of behavior and brain activity. Specifically, the slow process was manifested in the total duration of waking periods starting from dark onset, while the fast process was apparent in a regular occurrence of running bouts during the waking periods. The dynamics of both processes were stable within individual animals, but showed large interindividual variability. Importantly, the two processes were not independent: the periodic structure of waking behaviour (fast process) appeared to be a strong predictor of the capacity to sustain continuous wakefulness (slow process). The data indicate that the temporal organization of vigilance states on both the fast and the slow time scales may arise from a common neurophysiologic mechanism.     

Changes in seizure activity thresholds of the cat brain in various stages of sleep and wakefulness

Changes in seizure activity of the brain evoked by electrical stimulation of the dorsal hippocampus in various stages of sleep and wakefulness were studied in adult cats. During slow sleep, when the EEG is dominated by high-voltage slow waves, near-threshold epileptogenic hippocampal stimulation evokes well-marked paroxysmal discharges. During wakefulness or the paradoxical phase of sleep, when the EEG is desynchronized, this hippocampal stimulation is less effective: either no seizure discharges are produced or they are weak. Activation of the mesencephalic reticular formation before epileptogenic hippocampal stimulation hinders the appearance of seizure activity whereas activation after hippocampal stimulation does not inhibit paroxysmal discharges already in progress; on the contrary, in some cases they are actually strengthened a little. One of the main factors limiting the appearance and spread of seizure activity is considered to be the tonic inhibitory influence of the neocortex on other parts of the brain.     

Systems neuroscience: the slowly sleeping slab and slice

The physiological functions of structured spontaneous activity in the brain, such as the slow oscillations characteristic of certain sleep states, remain unclear, but new studies using brain slices or slabs are starting to shed light on the underlying neural mechanisms.     

Modeling the effect of sleep regulation on a neural mass model

In mammals, sleep is categorized by two main sleep stages, rapid eye movement (REM) and non-REM (NREM) sleep that are known to fulfill different functional roles, the most notable being the consolidation of memory. While REM sleep is characterized by brain activity similar to wakefulness, the EEG activity changes drastically with the emergence of K-complexes, sleep spindles and slow oscillations during NREM sleep. These changes are regulated by circadian and ultradian rhythms, which emerge from an intricate interplay between multiple neuronal populations in the brainstem, forebrain and hypothalamus and the resulting varying levels of neuromodulators. Recently, there has been progress in the understanding of those rhythms both from a physiological as well as theoretical perspective. However, how these neuromodulators affect the generation of the different EEG patterns and their temporal dynamics is poorly understood. Here, we build upon previous work on a neural mass model of the sleeping cortex and investigate the effect of those neuromodulators on the dynamics of the cortex and the corresponding transition between wakefulness and the different sleep stages. We show that our simplified model is sufficient to generate the essential features of human EEG over a full day. This approach builds a bridge between sleep regulatory networks and EEG generating neural mass models and provides a valuable tool for model validation.     

From slow waves to sleep homeostasis: new perspectives

EEG slow waves are the epitome of deep nonREM sleep. The level of slow-wave activity (SWA; defined as spectral power in the 0.5-4.5 Hz band) in the initial part of sleep is determined by prior sleep and waking, and thereby represents a marker of a homeostatic sleep regulating process (Process S). Models based on SWA were successful in simulating sleep architecture in a variety of experimental protocols. SWA is an exceptional sleep variable in that it is little influenced by circadian phase and variations of the photoperiod. There is recent evidence that it is not waking per se but the absence of sleep, which engenders a rise in sleep propensity. Thus animals emerging from the hypometabolic states of hibernation or daily torpor exhibit an increase in SWA akin to sleep deprivation. Recent human studies showed SWA to be a marker of a local, use-dependent facet of sleep. Selective activation of specific cortical areas during waking enhanced SWA over the activated region during sleep. A frontal predominance of power in the 2-Hz band was documented in the initial part of a normal sleep episode. Sleep homeostasis may be a valuable concept for exploring the evolutionary origin of sleep. Thus 'rest homeostasis' has been demonstrated in invertebrate species, and the search for homologies of rest and sleep on a molecular genetic level has begun. Conceptualizing and characterizing sleep as a regulated process may eventually shed light on its function.     

Quantitative electroencephalographic changes due to middle cerebral artery occlusion by endothelin 1 in conscious rats.

The powerful vasoconstrictor peptide endothelin-1 (ET1) has been shown to reduce local cerebral blood flow in brain areas supplied by the middle cerebral artery (MCA) to a pathologically low level upon intracerebral injection adjacent to the MCA. This reduction manifests itself as an ischemic infarct, that is fully developed within 3 days after ET1 injection. The aim of the present study is to examine the effect of ET1 on electroencephalographic (EEG) activity. ET1 was microinjected unilaterally at a dose of 60 pmol in 3 microl of saline to the MCA in conscious rats. EEG signals were recorded from the frontoparietal cortical area, supplied by MCA, from the first up to the fourteenth day after ET1 injection. EEG activity was analyzed by the fast Fourier transformation. A significant shift to a lower EEG frequency, i.e., augmentation of slow waves and a reduction of alpha-like and faster EEG waves was found post-ET1. This effect was maximal after 3-7 days when the most severe destruction of neurons in this cortical area occurs, as has been previously demonstrated. The results suggest that the quantitative EEG analysis may provide useful additional information about the functional disturbances associated with focal cerebral ischemia.