Regional slow waves and spindles in human sleep

The most prominent EEG events in sleep are slow waves, reflecting a slow (<1 Hz) oscillation between up and down states in cortical neurons. It is unknown whether slow oscillations are synchronous across the majority or the minority of brain regions--are they a global or local phenomenon? To examine this, we recorded simultaneously scalp EEG, intracerebral EEG, and unit firing in multiple brain regions of neurosurgical patients. We find that most sleep slow waves and the underlying active and inactive neuronal states occur locally. Thus, especially in late sleep, some regions can be active while others are silent. We also find that slow waves can propagate, usually from medial prefrontal cortex to the medial temporal lobe and hippocampus. Sleep spindles, the other hallmark of NREM sleep EEG, are likewise predominantly local. Thus, intracerebral communication during sleep is constrained because slow and spindle oscillations often occur out-of-phase in different brain regions.     

睡眠2期脑电信号产生的生理机制模型仿真研究

目前慢波睡眠生理机制研究已有的理论及动物实验结果显示,慢波睡眠中,皮层-丘脑系统神经元存在三种不同节律的振荡:慢振荡(<1 HZ)、δ振荡(1-4Hz)和纺锤振荡(7-14Hz)。这些神经元电活动在皮层水平广泛同步化,产生慢波睡眠脑电。提出了能分别产生这三种节律的三种神经元环路模型,并将之组合简化成一个七细胞环路模型。由这样的大量环路组成的网络模型在合适的突触连接参数范围内,能在皮层处产生人类慢波睡眠脑电2期的完整波形。这一结果说明了如何将动物实验观察到的睡眠生理机制的结果与人自然睡眠活动的脑电结果联系起来,并提示脑信息处理中由微观神经元群放电特征整合为脑的宏观功能状态的主要环节。     

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.     

Selective coupling between theta phase and neocortical fast gamma oscillations during REM-sleep in mice

Background

The mammalian brain expresses a wide range of state-dependent network oscillations which vary in frequency and spatial extension. Such rhythms can entrain multiple neurons into coherent patterns of activity, consistent with a role in behaviour, cognition and memory formation. Recent evidence suggests that locally generated fast network oscillations can be systematically aligned to long-range slow oscillations. It is likely that such cross-frequency coupling supports specific tasks including behavioural choice and working memory.

Principal Findings

We analyzed temporal coupling between high-frequency oscillations and EEG theta activity (4–12 Hz) in recordings from mouse parietal neocortex. Theta was exclusively present during active wakefulness and REM-sleep. Fast oscillations occurred in two separate frequency bands: gamma (40–100 Hz) and fast gamma (120–160 Hz). Theta, gamma and fast gamma were more prominent during active wakefulness as compared to REM-sleep. Coupling between theta and the two types of fast oscillations, however, was more pronounced during REM-sleep. This state-dependent cross-frequency coupling was particularly strong for theta-fast gamma interaction which increased 9-fold during REM as compared to active wakefulness. Theta-gamma coupling increased only by 1.5-fold.

Significance

State-dependent cross-frequency-coupling provides a new functional characteristic of REM-sleep and establishes a unique property of neocortical fast gamma oscillations. Interactions between defined patterns of slow and fast network oscillations may serve selective functions in sleep-dependent information processing.     

Localizing Movement-Related Primary Sensorimotor Cortices with Multi-Band EEG Frequency Changes and Functional MRI

Electroencephalographic (EEG) oscillations in multiple frequency bands can be observed during functional activity of the cerebral cortex. An important question is whether activity of focal areas of cortex, such as during finger movements, is tracked by focal oscillatory EEG changes. Although a number of studies have compared EEG changes to functional MRI hemodynamic responses, we can find no previous research that relates the fMRI hemodynamic activity to localization of the multiple EEG frequency changes observed in motor tasks. In the present study, five participants performed similar thumb and finger movement tasks in parallel EEG and functional MRI studies. We examined changes in five frequency bands (from 5–120 Hz) and localized them using 256 dense-array EEG (dEEG) recordings and high-resolution individual head models. These localizations were compared with fMRI localizations in the same participants. Results showed that beta-band (14–30 Hz) desynchronizations (power decreases) were the most robust effects, appearing in all individuals, consistently localized to the hand region of the primary motor cortex, and consistently aligned with fMRI localizations.     

Analysis of Epileptic Discharges from Implanted Subdural Electrodes in Patients with Sturge-Weber Syndrome

ObjectiveAlmost two-thirds of patients with Sturge-Weber syndrome (SWS) have epilepsy, and half of them require surgery for it. However, it is well known that scalp electroencephalography (EEG) does not demonstrate unequivocal epileptic discharges in patients with SWS. Therefore, we analyzed interictal and ictal discharges from intracranial subdural EEG recordings in patients treated surgically for SWS to elucidate epileptogenicity in this disorder.MethodsFive intractable epileptic patients with SWS who were implanted with subdural electrodes for presurgical evaluation were enrolled in this study. We examined the following seizure parameters: seizure onset zone (SOZ), propagation speed of seizure discharges, and seizure duration by visual inspection. Additionally, power spectrogram analysis on some frequency bands at SOZ was performed from 60 s before the visually detected seizure onset using the EEG Complex Demodulation Method (CDM).ResultsWe obtained 21 seizures from five patients for evaluation, and all seizures initiated from the cortex under the leptomeningeal angioma. Most of the patients presented with motionless staring and respiratory distress as seizure symptoms. The average seizure propagation speed and duration were 3.1 ± 3.6 cm/min and 19.4 ± 33.6 min, respectively. Significant power spectrogram changes at the SOZ were detected at 10–30 Hz from 15 s before seizure onset, and at 30–80 Hz from 5 s before seizure onset.SignificanceIn patients with SWS, seizures initiate from the cortex under the leptomeningeal angioma, and seizure propagation is slow and persists for a longer period. CDM indicated beta to low gamma-ranged seizure discharges starting from shortly before the visually detected seizure onset. Our ECoG findings indicate that ischemia is a principal mechanism underlying ictogenesis and epileptogenesis in SWS.     

The effect of dim light at night on cerebral hemodynamic oscillations during sleep: A near-infrared spectroscopy study

Recent studies have reported that dim light at night (dLAN) is associated with risks of cardiovascular complications, such as hypertension and carotid atherosclerosis; however, little is known about the underlying mechanism. Here, we evaluated the effect of dLAN on the cerebrovascular system by analyzing cerebral hemodynamic oscillations using near-infrared spectroscopy (NIRS). Fourteen healthy male subjects underwent polysomnography coupled with cerebral NIRS. The data collected during sleep with dim light (10 lux) were compared with those collected during sleep under the control dark conditions for the sleep structure, cerebral hemodynamic oscillations, heart rate variability (HRV), and their electroencephalographic (EEG) power spectrum. Power spectral analysis was applied to oxy-hemoglobin concentrations calculated from the NIRS signal. Spectral densities over endothelial very-low-frequency oscillations (VLFOs) (0.003–0.02 Hz), neurogenic VLFOs (0.02–0.04 Hz), myogenic low-frequency oscillations (LFOs) (0.04–0.15 Hz), and total LFOs (0.003–0.15 Hz) were obtained for each sleep stage. The polysomnographic data revealed an increase in the N2 stage under the dLAN conditions. The spectral analysis of cerebral hemodynamics showed that the total LFOs increased significantly during slow-wave sleep (SWS) and decreased during rapid eye movement (REM) sleep. Specifically, endothelial (median of normalized value, 0.46 vs. 0.72, p = 0.019) and neurogenic (median, 0.58 vs. 0.84, p = 0.019) VLFOs were enhanced during SWS, whereas endothelial VLFOs (median, 1.93 vs. 1.47, p = 0.030) were attenuated during REM sleep. HRV analysis exhibited altered spectral densities during SWS induced by dLAN, including an increase in very-low-frequency and decreases in low-frequency and high-frequency ranges. In the EEG power spectral analysis, no significant difference was detected between the control and dLAN conditions. In conclusion, dLAN can disturb cerebral hemodynamics via the endothelial and autonomic systems without cortical involvement, predominantly during SWS, which might represent an underlying mechanism of the increased cerebrovascular risk associated with light exposure during sleep.     

Sleep after mobile phone exposure in subjects with mobile phone‐related symptoms

Several studies show increases in activity for certain frequency bands (10–14 Hz) and visually scored parameters during sleep after exposure to radiofrequency electromagnetic fields. A shortened REM latency has also been reported. We investigated the effects of a double‐blind radiofrequency exposure (884 MHz, GSM signaling standard including non‐DTX and DTX mode, time‐averaged 10 g psSAR of 1.4 W/kg) on self‐evaluated sleepiness and objective EEG measures during sleep. Forty‐eight subjects (mean age 28 years) underwent 3 h of controlled exposure (7:30–10:30 PM; active or sham) prior to sleep, followed by a full‐night polysomnographic recording in a sleep laboratory. The results demonstrated that following exposure, time in Stages 3 and 4 sleep (SWS, slow‐wave sleep) decreased by 9.5 min (12%) out of a total of 78.6 min, and time in Stage 2 sleep increased by 8.3 min (4%) out of a total of 196.3 min compared to sham. The latency to Stage 3 sleep was also prolonged by 4.8 min after exposure. Power density analysis indicated an enhanced activation in the frequency ranges 0.5–1.5 and 5.75–10.5 Hz during the first 30 min of Stage 2 sleep, with 7.5–11.75 Hz being elevated within the first hour of Stage 2 sleep, and bands 4.75–8.25 Hz elevated during the second hour of Stage 2 sleep. No pronounced power changes were observed in SWS or for the third hour of scored Stage 2 sleep. No differences were found between controls and subjects with prior complaints of mobile phone‐related symptoms. The results confirm previous findings that RF exposure increased the EEG alpha range in the sleep EEG, and indicated moderate impairment of SWS. Furthermore, reported differences in sensitivity to mobile phone use were not reflected in sleep parameters. Bioelectromagnetics 32:4–14, 2011. © 2010 Wiley‐Liss, Inc.     

Low-frequency rhythmic electrocutaneous hand stimulation during slow-wave night sleep: Physiological and therapeutic effects

Neocortical EEG slow wave activity (SWA) in the delta frequency band (0.5–4.0 Hz) is a hallmark of slow wave sleep (SWS) and its power is a function of prior wake duration and an indicator of a sleep need. SWS is considered the most important stage for realization of recovery functions of sleep. Possibility of impact on characteristics of a night sleep by rhythmic (0.8–1.2 Hz) subthreshold electocutaneous stimulation of a hand during SWS is shown: 1st night—adaptation, 2nd night—control, 3d and 4th nights—with stimulation during SWA stages of a SWS. Stimulation caused significant increase in average duration of SWS and EEG SWA power (in 11 of 16 subjects), and also well-being and mood improvement in subjects with lowered emotional tone. It is supposed that the received result is caused by functioning of a hypothetical mechanism directed on maintenance and deepening of SWS and counteracting activating, awakening influences of the afferent stimulation. The results can be of value both for understanding the physiological mechanisms of sleep homeostasis and for development of non-pharmacological therapy of sleep disorders.     

Spontaneous hemodynamic oscillations during human sleep and sleep stage transitions characterized with near-infrared spectroscopy

Understanding the interaction between the nervous system and cerebral vasculature is fundamental to forming a complete picture of the neurophysiology of sleep and its role in maintaining physiological homeostasis. However, the intrinsic hemodynamics of slow-wave sleep (SWS) are still poorly known. We carried out 30 all-night sleep measurements with combined near-infrared spectroscopy (NIRS) and polysomnography to investigate spontaneous hemodynamic behavior in SWS compared to light (LS) and rapid-eye-movement sleep (REM). In particular, we concentrated on slow oscillations (3-150 mHz) in oxy- and deoxyhemoglobin concentrations, heart rate, arterial oxygen saturation, and the pulsation amplitude of the photoplethysmographic signal. We also analyzed the behavior of these variables during sleep stage transitions. The results indicate that slow spontaneous cortical and systemic hemodynamic activity is reduced in SWS compared to LS, REM, and wakefulness. This behavior may be explained by neuronal synchronization observed in electrophysiological studies of SWS and a reduction in autonomic nervous system activity. Also, sleep stage transitions are asymmetric, so that the SWS-to-LS and LS-to-REM transitions, which are associated with an increase in the complexity of cortical electrophysiological activity, are characterized by more dramatic hemodynamic changes than the opposite transitions. Thus, it appears that while the onset of SWS and termination of REM occur only as gradual processes over time, the termination of SWS and onset of REM may be triggered more abruptly by a particular physiological event or condition. The results suggest that scalp hemodynamic changes should be considered alongside cortical hemodynamic changes in NIRS sleep studies to assess the interaction between the autonomic and central nervous systems.     

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.     

Ketamine-induced oscillations in the motor circuit of the rat basal ganglia

Oscillatory activity can be widely recorded in the cortex and basal ganglia. This activity may play a role not only in the physiology of movement, perception and cognition, but also in the pathophysiology of psychiatric and neurological diseases like schizophrenia or Parkinson's disease. Ketamine administration has been shown to cause an increase in gamma activity in cortical and subcortical structures, and an increase in 150 Hz oscillations in the nucleus accumbens in healthy rats, together with hyperlocomotion.We recorded local field potentials from motor cortex, caudate-putamen (CPU), substantia nigra pars reticulata (SNr) and subthalamic nucleus (STN) in 20 awake rats before and after the administration of ketamine at three different subanesthetic doses (10, 25 and 50 mg/Kg), and saline as control condition. Motor behavior was semiautomatically quantified by custom-made software specifically developed for this setting.Ketamine induced coherent oscillations in low gamma (~ 50 Hz), high gamma (~ 80 Hz) and high frequency (HFO, ~ 150 Hz) bands, with different behavior in the four structures studied. While oscillatory activity at these three peaks was widespread across all structures, interactions showed a different pattern for each frequency band. Imaginary coherence at 150 Hz was maximum between motor cortex and the different basal ganglia nuclei, while low gamma coherence connected motor cortex with CPU and high gamma coherence was more constrained to the basal ganglia nuclei. Power at three bands correlated with the motor activity of the animal, but only coherence values in the HFO and high gamma range correlated with movement. Interactions in the low gamma band did not show a direct relationship to movement.These results suggest that the motor effects of ketamine administration may be primarily mediated by the induction of coherent widespread high-frequency activity in the motor circuit of the basal ganglia, together with a frequency-specific pattern of connectivity among the structures analyzed.     

A probabilistic framework for a physiological representation of dynamically evolving sleep state

This work presents a probabilistic method for mapping human sleep electroencephalogram (EEG) signals onto a state space based on a biologically plausible mathematical model of the cortex. From a noninvasive EEG signal, this method produces physiologically meaningful pathways of the cortical state over a night of sleep. We propose ways in which these pathways offer insights into sleep-related conditions, functions, and complex pathologies. To address explicitly the noisiness of the EEG signal and the stochastic nature of the mathematical model, we use a probabilistic Bayesian framework to map each EEG epoch to a distribution of likelihoods over all model sleep states. We show that the mapping produced from human data robustly separates rapid eye movement sleep (REM) from slow wave sleep (SWS). A Hidden Markov Model (HMM) is incorporated to improve the path results using the prior knowledge that cortical physiology has temporal continuity.     

Somatic evoked high-frequency magnetic oscillations reflect activity of inhibitory interneurons in the human somatosensory cortex

High-frequency potential oscillations in the range of 300–900 Hz have recently been shown to concur with the primary response (N20) of the somatosensory cortex in awake humans. However, the physiological mechanisms of the high-frequency oscillations remained undetermined. We addressed the issue by analyzing magnetic fields during wakefulness and sleep over the left hemisphere to right median nerve stimulation with a wide bandpass (0.1–2000 Hz) recording with subsequent high-pass (> 300 Hz) and low-pass (< 300 Hz) filtering. With wide bandpass recordings, high-frequency magnetic oscillations with the main signal energy at 580–780 Hz were superimposed on the N20m during wakefulness. Isofield mapping at each peak of the high-pass filtered and isolated high-frequency oscillations showed a dipolar pattern and the estimated source for these peaks was the primary somatosensory cortex (area 3b) very close to that for the N20m peak. During sleep, the high-frequency oscillations showed dramatic diminution in amplitude while the N20m amplitude exhibited a moderate increment. This reciprocal relation between the high-frequency oscillations and the N20m during a wake-sleep cycle suggests that they represent different generator substrates. We speculate that the high-frequency oscillations represent a localized activity of the GABAergic inhibitory interneurons of layer 4, which have been shown in animal experiments to respond monosynaptically to thalamo-cortical input with a high-frequency (600–900 Hz) burst of short duration spikes. On the other hand, the underlying N20m represents activity of pyramidal neurons which receive monosynaptic excitatory input from the thalamus as well as a feed-forward inhibition from the interneurons.     

The Sleep Cycle Modelled as a Cortical Phase Transition

We present a mean-field model of the cortex that attempts to describe the gross changes in brain electrical activity for the cycles of natural sleep. We incorporate within the model two major sleep modulatory effects: slow changes in both synaptic efficiency and in neuron resting voltage caused by the ∼90-min cycling in acetylcholine, together with even slower changes in resting voltage caused by gradual elimination during sleep of somnogens (fatigue agents) such as adenosine. We argue that the change from slow-wave sleep (SWS) to rapid-eye-movement (REM) sleep can be understood as a first-order phase transition from a low-firing, coherent state to a high-firing, desychronized cortical state. We show that the model predictions for changes in EEG power, spectral distribution, and correlation time at the SWS-to-REM transition are consistent not only with those observed in clinical recordings of a sleeping human subject, but also with the on-cortex EEG patterns recently reported by Destexhe et al. [J. Neurosci. 19(11), (1999) 4595–4608] for the sleeping cat.     

Functional Structure of Spontaneous Sleep Slow Oscillation Activity in Humans

Background

During non-rapid eye movement (NREM) sleep synchronous neural oscillations between neural silence (down state) and neural activity (up state) occur. Sleep Slow Oscillations (SSOs) events are their EEG correlates. Each event has an origin site and propagates sweeping the scalp. While recent findings suggest a SSO key role in memory consolidation processes, the structure and the propagation of individual SSO events, as well as their modulation by sleep stages and cortical areas have not been well characterized so far.

Methodology/Principal Findings

We detected SSO events in EEG recordings and we defined and measured a set of features corresponding to both wave shapes and event propagations. We found that a typical SSO shape has a transition to down state, which is steeper than the following transition from down to up state. We show that during SWS SSOs are larger and more locally synchronized, but less likely to propagate across the cortex, compared to NREM stage 2. Also, the detection number of SSOs as well as their amplitudes and slopes, are greatest in the frontal regions. Although derived from a small sample, this characterization provides a preliminary reference about SSO activity in healthy subjects for 32-channel sleep recordings.

Conclusions/Significance

This work gives a quantitative picture of spontaneous SSO activity during NREM sleep: we unveil how SSO features are modulated by sleep stage, site of origin and detection location of the waves. Our measures on SSOs shape indicate that, as in animal models, onsets of silent states are more synchronized than those of neural firing. The differences between sleep stages could be related to the reduction of arousal system activity and to the breakdown of functional connectivity. The frontal SSO prevalence could be related to a greater homeostatic need of the heteromodal association cortices.     

Principal component analysis of electroencephalographic activity during sleep and wakefulness in the spider monkey (Ateles geoffroyi)

The study of electroencephalographic (EEG) activity during sleep in the spider monkey has provided new insights into primitive arboreal sleep physiology and behavior in anthropoids. Nevertheless, studies conducted to date have maintained the frequency ranges of the EEG bands commonly used with humans. The aim of the present work was to determine the EEG broad bands that characterize sleep and wakefulness in the spider monkey using principal component analysis (PCA). The EEG activity was recorded from the occipital, central, and frontal EEG derivations of six young-adult male spider monkeys housed in a laboratory setting. To determine which frequencies covaried and which were orthogonally independent during sleep and wakefulness, the power EEG spectra and interhemispheric and intrahemispheric EEG correlations from 1 to 30 Hz were subjected to PCA. Findings show that the EEG bands detection differed from those reported previously in both spider monkeys and humans, and that the 1–3 and 2–13 Hz frequency ranges concur with the oscillatory activity elucidated by cellular recordings of subcortical regions. Results show that applying PCA to the EEG spectrum during sleep and wakefulness in the spider monkey led to the identification of frequencies that covaried with, and were orthogonally independent of, other frequencies in each behavioral vigilance state. The new EEG bands differ from those used previously with both spider monkeys and humans. The 1–3 and 2–13 Hz frequency ranges are in accordance with the oscillatory activity elucidated by cellular recordings of subcortical regions in other mammals.     

Long lasting modulation of cortical oscillations after continuous theta burst transcranial magnetic stimulation

Transcranial magnetic theta burst stimulation (TBS) differs from other high-frequency rTMS protocols because it induces plastic changes up to an hour despite lower stimulus intensity and shorter duration of stimulation. However, the effects of TBS on neuronal oscillations remain unclear. In this study, we used electroencephalography (EEG) to investigate changes of neuronal oscillations after continuous TBS (cTBS), the protocol that emulates long-term depression (LTD) form of synaptic plasticity. We randomly divided 26 healthy humans into two groups receiving either Active or Sham cTBS as control over the left primary motor cortex (M1). Post-cTBS aftereffects were assessed with behavioural measurements at rest using motor evoked potentials (MEPs) and at active state during the execution of a choice reaction time (RT) task in combination with continuous electrophysiological recordings. The cTBS-induced EEG oscillations were assessed using event-related power (ERPow), which reflected regional oscillatory activity of neural assemblies of θ (4-7.5 Hz), low α (8-9.5 Hz), μ (10-12.5 Hz), low β (13-19.5 Hz), and high β (20-30 Hz) brain rhythms. Results revealed 20-min suppression of MEPs and at least 30-min increase of ERPow modulation, suggesting that besides MEPs, EEG has the potential to provide an accurate cortical readout to assess cortical excitability and to investigate the interference of cortical oscillations in the human brain post-cTBS. We also observed a predominant modulation of β frequency band, supporting the hypothesis that cTBS acts more on cortical level. Theta oscillations were also modulated during rest implying the involvement of independent cortical theta generators over the motor network post cTBS. This work provided more insights into the underlying mechanisms of cTBS, providing a possible link between synchronised neural oscillations and LTD in humans.     

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.