The sleep slow oscillation as a traveling wave

The memory function of sleep

Sleep has been identified as a state that optimizes the consolidation of newly acquired information in memory, depending on the specific conditions of learning and the timing of sleep. Consolidation during sleep promotes both quantitative and qualitative changes of memory representations. Through specific patterns of neuromodulatory activity and electric field potential oscillations, slow-wave sleep (SWS) and rapid eye movement (REM) sleep support system consolidation and synaptic consolidation, respectively. During SWS, slow oscillations, spindles and ripples - at minimum cholinergic activity - coordinate the re-activation and redistribution of hippocampus-dependent memories to neocortical sites, whereas during REM sleep, local increases in plasticity-related immediate-early gene activity - at high cholinergic and theta activity - might favour the subsequent synaptic consolidation of memories in the cortex.

Sequential Reinstatement of Neocortical Activity during Slow Oscillations Depends on Cells' Global Activity

During Slow Wave Sleep (SWS), cortical activity is dominated by endogenous processes modulated by slow oscillations (0.1–1 Hz): cell ensembles fluctuate between states of sustained activity (UP states) and silent epochs (DOWN states). We investigate here the temporal structure of ensemble activity during UP states by means of multiple single unit recordings in the prefrontal cortex of naturally sleeping rats. As previously shown, the firing rate of each PFC cell peaks at a distinct time lag after the DOWN/UP transition in a consistent order. We show here that, conversely, the latency of the first spike after the UP state onset depends primarily on the session-averaged firing rates of cells (which can be considered as an indirect measure of their intrinsic excitability). This latency can be explained by a simple homogeneous process (Poisson model) of cell firing, with sleep averaged firing rates employed as parameters. Thus, at DOWN/UP transitions, neurons are affected both by a slow process, possibly originating in the cortical network, modulating the time course of firing for each cell, and by a fast, relatively stereotyped reinstatement of activity, related mostly to global activity levels.

The slow (<1 Hz) rhythm of non-REM sleep: a dialogue between three cardinal oscillators

The slow (<1 Hz) rhythm, the most important electroencephalogram (EEG) signature of non-rapid eye movement (NREM) sleep, is generally viewed as originating exclusively from neocortical networks. Here we argue that the full manifestation of this fundamental sleep oscillation in a corticothalamic module requires the dynamic interaction of three cardinal oscillators: one predominantly synaptically based cortical oscillator and two intrinsic, conditional thalamic oscillators. The functional implications of this hypothesis are discussed in relation to other EEG features of NREM sleep, with respect to coordinating activities in local and distant neuronal assemblies and in the context of facilitating cellular and network plasticity during slow-wave sleep.

An analysis of the transitions between down and up states of the cortical slow oscillation under urethane anaesthesia

We study the dynamics of the transition between the low- and high-firing states of the cortical slow oscillation by using intracellular recordings of the membrane potential from cortical neurons of rats. We investigate the evidence for a bistability in assemblies of cortical neurons playing a major role in the maintenance of this oscillation. We show that the trajectory of a typical transition takes an approximately exponential form, equivalent to the response of a resistor-capacitor circuit to a step-change in input. The time constant for the transition is negatively correlated with the membrane potential of the low-firing state, and values are broadly equivalent to neural time constants measured elsewhere. Overall, the results do not strongly support the hypothesis of a bistability in cortical neurons; rather, they suggest the cortical manifestation of the oscillation is a result of a step-change in input to the cortical neurons. Since there is evidence from previous work that a phase transition exists, we speculate that the step-change may be a result of a bistability within other brain areas, such as the thalamus, or a bistability among only a small subset of cortical neurons, or as a result of more complicated brain dynamics.

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.

Cortical firing and sleep homeostasis

The need to sleep grows with the duration of wakefulness and dissipates with time spent asleep, a process called sleep homeostasis. What are the consequences of staying awake on brain cells, and why is sleep needed? Surprisingly, we do not know whether the firing of cortical neurons is affected by how long an animal has been awake or asleep. Here, we found that after sustained wakefulness cortical neurons fire at higher frequencies in all behavioral states. During early NREM sleep after sustained wakefulness, periods of population activity (ON) are short, frequent, and associated with synchronous firing, while periods of neuronal silence are long and frequent. After sustained sleep, firing rates and synchrony decrease, while the duration of ON periods increases. Changes in firing patterns in NREM sleep correlate with changes in slow-wave activity, a marker of sleep homeostasis. Thus, the systematic increase of firing during wakefulness is counterbalanced by staying asleep.

Breakdown of effective connectivity during slow wave sleep: investigating the mechanism underlying a cortical gate using large-scale modeling

Effective connectivity between cortical areas decreases during slow wave sleep. This decline can be observed in the reduced interareal propagation of activity evoked either directly in cortex by transcranial magnetic stimulation (TMS) or by sensory stimulation. We present here a large-scale model of the thalamocortical system that is capable of reproducing these experimental observations. This model was constructed according to a large number of physiological and anatomical constraints and includes over 30,000 spiking neurons interconnected by more than 5 million synaptic connections and organized into three cortical areas. By simulating the different effects of arousal promoting neuromodulators, the model can produce a waking or a slow wave sleep-like mode. In this work, we also seek to explain why intercortical signal transmission decreases in slow wave sleep. The traditional explanation for reduced brain responses during this state, a thalamic gate, cannot account for the reduced propagation between cortical areas. Therefore we propose that a cortical gate is responsible for this diminished intercortical propagation. We used our model to test three candidate mechanisms that might produce a cortical gate during slow wave sleep: a propensity to enter a local down state following perturbation, which blocks the propagation of activity to other areas, increases in potassium channel conductance that reduce neuronal responsiveness, and a shift in the balance of synaptic excitation and inhibition toward inhibition, which decreases network responses to perturbation. Of these mechanisms, we find that only a shift in the balance of synaptic excitation and inhibition can account for the observed in vivo response to direct cortical perturbation as well as many features of spontaneous sleep.

Sleep-dependent improvement in visuomotor learning: a causal role for slow waves

STUDY OBJECTIVES

Sleep after learning often benefits memory consolidation, but the underlying mechanisms remain unclear. In previous studies, we found that learning a visuomotor task is followed by an increase in sleep slow wave activity (SWA, the electroencephalographic [EEG] power density between 0.5 and 4.5 Hz during non-rapid eye movement sleep) over the right parietal cortex. The SWA increase correlates with the postsleep improvement in visuomotor performance, suggesting that SWA may be causally responsible for the consolidation of visuomotor learning. Here, we tested this hypothesis by studying the effects of slow wave deprivation (SWD).

DESIGN

After learning the task, subjects went to sleep, and acoustic stimuli were timed either to suppress slow waves (SWD) or to interfere as little as possible with spontaneous slow waves (control acoustic stimulation, CAS).

SETTING

Sound-attenuated research room.

PARTICIPANTS

Healthy subjects (mean age 24.6 +/- 1.0 years; n = 9 for EEG analysis, n = 12 for behavior analysis; 3 women).

MEASUREMENTS AND RESULTS

Sleep time and efficiency were not affected, whereas SWA and the number of slow waves decreased in SWD relative to CAS. Relative to the night before, visuomotor performance significantly improved in the CAS condition (+5.93% +/- 0.88%) but not in the SWD condition (-0.77% +/- 1.16%), and the direct CAS vs SWD comparison showed a significant difference (P = 0.0007, n = 12, paired t test). Changes in visuomotor performance after SWD were correlated with SWA changes over right parietal cortex but not with the number of arousals identified using clinically established criteria, nor with any sign of "EEG lightening" identified using a novel automatic method based on event-related spectral perturbation analysis.

CONCLUSION

These results support a causal role for sleep slow waves in sleep-dependent improvement of visuomotor performance.

Impact of alcoholism on sleep architecture and EEG power spectra in men and women

STUDY OBJECTIVES

To determine the impact of alcoholism on sleep architecture and sleep EEG power spectra in men and women with uncomplicated alcoholism.

DESIGN AND PARTICIPANTS

42 alcoholics (27 men) and 42 controls (19 men) screened for medical, psychiatric, and sleep problems participated in a full night of polysomnography following an adaptation night. Data were collected from multiple scalp sites and subjected to power spectral analysis. Sleep architecture and EEG spectral power measures were evaluated for the effects of diagnosis and sex using age as a covariate.

RESULTS

Compared with controls, alcoholics had less slow wave sleep and increased proportions of stage 1 and REM sleep. Spectral analysis of NREM sleep showed reduced levels of slow wave activity (SWA, 0.3-4 Hz) and slow theta (theta) power (4-6 Hz) in alcoholics. The differences in SWA extended across the slow band (0.3-1 Hz) and all delta (delta) frequencies and were most prominent over frontal scalp regions. No group differences were seen in the power spectra of REM sleep. Women had more SWA and theta power than men, but there were no sex by diagnosis interactions for any measures, suggesting that alcoholism does not differentially influence men and women.

CONCLUSION

Long-term alcoholism affects sleep even after long periods of abstinence in both men and women. Measures of frontal slow wave activity were particularly sensitive markers of this long-lasting effect. Sleep EEG measures would thus seem to provide a functional correlate of the changes in brain structure seen in frontal cortex of long-term alcoholics.

Estimation of Eeg Signal Dispersion During Seizure Propagation

Localization of the seizure focus in the brain is a challenging problem in the field of epilepsy. The complexity of the seizure-related EEG waveform, its non-stationarity and degradation with distance due to the dispersive nature of the brain as a propagation medium, make localization difficult. Yet, precise estimation of the focus is critical, particularly when surgical resection is the only therapeutic option. The first step to solving this inverse problem is to estimate and account for frequency- or mode-specific signal dispersion, which is present in both scalp and intracranial EEG recordings during seizures. We estimated dispersion curves in both types of signals using a spatial correlation method and mode-based semblance analysis. We showed that, despite the assumption of spatial stationarity and a simplified array geometry, there is measurable inter-modal and intra-modal dispersion during seizures in both types of EEG recordings, affecting the estimated arrival times and consequently focus localization.

Slow oscillation electrical brain stimulation during waking promotes EEG theta activity and memory encoding

The application of transcranial slow oscillation stimulation (tSOS; 0.75 Hz) was previously shown to enhance widespread endogenous EEG slow oscillatory activity when applied during a sleep period characterized by emerging endogenous slow oscillatory activity. Processes of memory consolidation typically occurring during this state of sleep were also enhanced. Here, we show that the same tSOS applied in the waking brain also induced an increase in endogenous EEG slow oscillations (0.4-1.2 Hz), although in a topographically restricted fashion. Applied during wakefulness tSOS, additionally, resulted in a marked and widespread increase in EEG theta (4-8 Hz) activity. During wake, tSOS did not enhance consolidation of memories when applied after learning, but improved encoding of hippocampus-dependent memories when applied during learning. We conclude that the EEG frequency and related memory processes induced by tSOS critically depend on brain state. In response to tSOS during wakefulness the brain transposes stimulation by responding preferentially with theta oscillations and facilitated encoding.

Spatio-temporal EEG waves in first episode schizophrenia

OBJECTIVE

Schizophrenia is characterized by a deficit in context processing, with physiological correlates of hypofrontality and reduced amplitude P3b event-related potentials. We hypothesized an additional physiological correlate: differences in the spatio-temporal dynamics of cortical activity along the anterior-posterior axis of the scalp.

METHODS

This study assessed latency topographies of spatio-temporal waves under task conditions that elicit the P3b. EEG was recorded during separate auditory and visual tasks. Event-related spatio-temporal waves were quantified from scalp EEG of subjects with first episode schizophrenia (FES) and matched controls.

RESULTS

The P3b-related task conditions elicited a peak in spatio-temporal waves in the delta band at a similar latency to the P3b event-related potential. Subjects with FES had fewer episodes of anterior to posterior waves in the 2-4 Hz band compared to controls. Within the FES group, a tendency for fewer episodes of anterior to posterior waves was associated with high Psychomotor Poverty symptom factor scores.

CONCLUSIONS

Subjects with FES had altered global EEG dynamics along the anterior-posterior axis during task conditions involving context update.

SIGNIFICANCE

The directional nature of this finding and its association with Psychomotor Poverty suggest this result is related to findings of hypofrontality in schizophrenia.

The impact of alcoholism on sleep evoked Delta frequency responses

BACKGROUND

K-complexes (KCs) are evoked delta frequency electroencephalogram (EEG) responses during sleep that occur when large numbers of healthy cortical cells burst fire in a synchronized manner. The KC amplitude and incidence are sensitive measures of normal healthy brain aging. Given the known neurodegenerative consequences of alcohol abuse it was hypothesized that alcoholism would be associated with further KC amplitude and incidence reductions.

METHODS

Eighty-four subjects (42 alcoholics) screened for medical, psychiatric, and sleep problems participated. The protocol involved the presentation of auditory stimuli during stage 2 sleep throughout a night in the laboratory. The KCs were identified and averaged, to enable measurement of the P2, N550, and P900 peaks.

RESULTS

Compared with control subjects, alcoholic men and women had lower KC incidence (p < .001) and P2 (p < .001), N550 (p < .05), and P900 (p < .05) amplitudes. There was a significant diagnosis x site interaction (p < .001), indicating the group difference was largest at frontal sites. Longer sobriety correlated with increased N550 amplitude (p < .01).

CONCLUSIONS

The KC incidence and amplitude were negatively impacted in alcoholic men and women with exacerbation of the normal aging effects, particularly over frontal scalp regions. The observed relationship between improvements in KC measures and increased time of abstinence suggests that these measures might provide a useful marker of brain recovery with continued abstinence from alcohol.

The comodulation measure of neuronal oscillations with general harmonic wavelet bicoherence and application to sleep analysis

Brain functions are related to neuronal networks of different sizes and distribution, and neuronal networks of different sizes oscillate at different frequencies. Thus the synchronization of neuronal networks is often reflected by cross-frequency interaction. The description of this cross-frequency interaction is therefore a crucial issue in understanding the modulation mechanisms between neuronal populations. A number of different kinds of interaction between frequencies have been reported. In this paper, we develop a general harmonic wavelet transform based bicoherence using a phase randomization method. This allows us to measure the comodulation of oscillations between different frequency bands in neuronal populations. The performance of the method is evaluated by a simulation study. The results show that the improved wavelet bicoherence method can detect a reliable phase coupling value, and also identify zero bicoherence for waves that are not phase-coupled. Spurious bicoherences can be effectively eliminated through the phase randomization method. Finally, this method is applied to electrocorticogram data recorded from rats during transitions between slow-wave sleep, rapid-eye movement sleep and waking. The phase coupling in rapid-eye movement sleep is statistically lower than that during slow-wave sleep, and slightly less than those in the wakeful state. The degree of phase coupling in rapid-eye movement sleep after slow-wave sleep is greater than in rapid-eye movement sleep prior to waking. This method could be applied to investigate the cross-frequency interactions in other physiological signals.

Decoupling of the brain's default mode network during deep sleep

The recent discovery of a circuit of brain regions that is highly active in the absence of overt behavior has led to a quest for revealing the possible function of this so-called default-mode network (DMN). A very recent study, finding similarities in awake humans and anesthetized primates, has suggested that DMN activity might not simply reflect ongoing conscious mentation but rather a more general form of network dynamics typical of complex systems. Here, by performing functional MRI in humans, it is shown that a natural, sleep-induced reduction of consciousness is reflected in altered correlation between DMN network components, most notably a reduced involvement of frontal cortex. This suggests that DMN may play an important role in the sustenance of conscious awareness.

Sleep-dependent directional coupling between human neocortex and hippocampus

Complex interactions between neocortex and hippocampus are the neural basis of memory formation. Two-step theories of memory formation suggest that initial encoding of novel information depends on the induction of rapid plasticity within the hippocampus, and is followed by a second sleep-dependent step of memory consolidation. These theories predict information flow from the neocortex into the hippocampus during waking state and in the reverse direction during sleep. However, experimental evidence that interactions between hippocampus and neocortex have a predominant direction which reverses during sleep rely on cross-correlation analysis of data from animal experiments and yielded inconsistent results. Here, we investigated directional coupling in intracranial EEG data from human subjects using a phase-modeling approach which is well suited to reveal functional interdependencies in oscillatory data. In general, we observed that the anterior hippocampus predominantly drives nearby and remote brain regions. Surprisingly, however, the influence of neocortical regions on the hippocampus significantly increased during sleep as compared to waking state. These results question the standard model of hippocampal-neocortical interactions and suggest that sleep-dependent consolidation is accomplished by an active retrieval of hippocampal information by the neocortex.

The human K-complex represents an isolated cortical down-state

The electroencephalogram (EEG) is a mainstay of clinical neurology and is tightly correlated with brain function, but the specific currents generating human EEG elements remain poorly specified because of a lack of microphysiological recordings. The largest event in healthy human EEGs is the K-complex (KC), which occurs in slow-wave sleep. Here, we show that KCs are generated in widespread cortical areas by outward dendritic currents in the middle and upper cortical layers, accompanied by decreased broadband EEG power and decreased neuronal firing, which demonstrate a steep decline in network activity. Thus, KCs are isolated "down-states," a fundamental cortico-thalamic processing mode already characterized in animals. This correspondence is compatible with proposed contributions of the KC to sleep preservation and memory consolidation.

Spontaneous events outline the realm of possible sensory responses in neocortical populations

Neocortical assemblies produce complex activity patterns both in response to sensory stimuli and spontaneously without sensory input. To investigate the structure of these patterns, we recorded from populations of 40-100 neurons in auditory and somatosensory cortices of anesthetized and awake rats using silicon microelectrodes. Population spike time patterns were broadly conserved across multiple sensory stimuli and spontaneous events. Although individual neurons showed timing variations between stimuli, these were not sufficient to disturb a generally conserved sequential organization observed at the population level, lasting for approximately 100 ms with spiking reliability decaying progressively after event onset. Preserved constraints were also seen in population firing rate vectors, with vectors evoked by individual stimuli occupying subspaces of a larger but still constrained space outlined by the set of spontaneous events. These results suggest that population spike patterns are drawn from a limited "vocabulary," sampled widely by spontaneous events but more narrowly by sensory responses.

Slow waves, synaptic plasticity and information processing: insights from transcranial magnetic stimulation and high-density EEG experiments

Sleep slow waves are the main phenomenon underlying NREM sleep. They are homeostatically regulated, they are thought to be linked to learning and plasticity processes and, at the same time, they are associated with marked changes in cortical information processing. Using transcranial magnetic stimulation (TMS) and high-density (hd) EEG we can measure slow waves, induce and measure plastic changes in the cerebral cortex and directly assess corticocortical information transmission. In this manuscript we review the results of recent experiments in which TMS with hd-EEG is used to demonstrate (i) a causal link between cortical plastic changes and sleep slow waves and (ii) a causal link between slow waves and the decreased ability of thalamocortical circuits to integrate information and to generate conscious experience during NREM sleep. The data presented here suggest a unifying mechanism linking slow waves, plasticity and cortical information integration; moreover, they suggest that TMS can be used as a nonpharmacological means to controllably induce slow waves in the human cerebral cortex.

Sleep function: current questions and new approaches

The mammalian brain oscillates through three distinct global activity states: wakefulness, non-rapid eye movement (NREM) sleep and REM sleep. The regulation and function of these 'vigilance' or 'behavioural' states can be investigated over a broad range of temporal and spatial scales and at different levels of functional organization, i.e. from gene expression to memory, in single neurons, cortical columns or the whole brain and organism. We summarize some basic questions that have arisen from recent approaches in the quest for the functions of sleep. Whereas traditionally sleep was viewed to be regulated through top-down control mechanisms, recent approaches have emphasized that sleep is emerging locally and regulated in a use-dependent (homeostatic) manner. Traditional markers of sleep homeostasis, such as the electroencephalogram slow-wave activity, have been linked to changes in connectivity and plasticity in local neuronal networks. Thus waking experience-induced local network changes may be sensed by the sleep homeostatic process and used to mediate sleep-dependent events, benefiting network stabilization and memory consolidation. Although many questions remain unanswered, the available data suggest that sleep function will best be understood by an analysis which integrates sleep's many functional levels with its local homeostatic regulation.

Directional information flows between brain hemispheres across waking, non-REM and REM sleep states: an EEG study

The present electroencephalographic (EEG) study evaluated the hypothesis of a preferred directionality of communication flows between brain hemispheres across 24 h (i.e., during the whole daytime and nighttime), as an extension of a recent report showing changes in preferred directionality from pre-sleep wake to early sleep stages. Scalp EEGs were recorded in 10 normal volunteers during daytime wakefulness (eyes closed; first period: from 10:00 to 13:00 h; second period: from 14:00 to 18:00 h; third period: from 19:00 to 22:00 h) and nighttime sleep (four NREM-REM cycles). EEG rhythms of interest were delta (1-4 Hz), theta (5-7 Hz), alpha (8-11 Hz), sigma (12-15 Hz) and beta (16-28 Hz). The direction of the inter-hemispheric information flow was evaluated by computing the directed transfer function (DTF) from these EEG rhythms. Inter-hemispheric directional flows varied as a function of the state of consciousness (wake, NREM sleep, REM sleep) and in relation to different cerebral areas. During the daytime, alpha and beta rhythms conveyed inter-hemispheric signals with preferred Left-to-Right hemisphere direction in parietal and central areas, respectively. During the NREM sleep periods of nighttime, the direction of inter-hemispheric DTF information flows conveyed by central beta rhythms was again preponderant from Left-to-Right hemisphere in the stage 2, independent of cortical areas. No preferred direction emerged across the REM periods. These results support the hypothesis that specific directionality of communication flows between brain hemispheres is associated with wakefulness, NREM (particularly stage 2) and REM states during daytime and nighttime. They also reinforce the suggestive hypothesis of a relationship between inter-hemispheric directionality of EEG functional coupling and frequency of the EEG rhythms.

Laterality of neocortical slow-wave oscillations in anesthetized mice

In the slow-wave (SW) state, the vast majority of cortical neurons exhibit mostly synchronized oscillatory activity. In this study, we examined the right-left hemispheric difference in slow-wave timings in urethane-anesthetized mice. We found that interhemispheric cross-correlograms of local field potentials (LFPs) peaked asymmetrically. Double in vivo whole-cell patch-clamp recordings also revealed the interhemispheric temporal disparity of slow wave-relevant synaptic barrages. The data suggest the hemispheric laterality in the slow wave origin.

Source modeling sleep slow waves

Slow waves are the most prominent electroencephalographic (EEG) feature of sleep. These waves arise from the synchronization of slow oscillations in the membrane potentials of millions of neurons. Scalp-level studies have indicated that slow waves are not instantaneous events, but rather they travel across the brain. Previous studies of EEG slow waves were limited by the poor spatial resolution of EEGs and by the difficulty of relating scalp potentials to the activity of the underlying cortex. Here we use high-density EEG (hd-EEG) source modeling to show that individual spontaneous slow waves have distinct cortical origins, propagate uniquely across the cortex, and involve unique subsets of cortical structures. However, when the waves are examined en masse, we find that there are diffuse hot spots of slow wave origins centered on the lateral sulci. Furthermore, slow wave propagation along the anterior-posterior axis of the brain is largely mediated by a cingulate highway. As a group, slow waves are associated with large currents in the medial frontal gyrus, the middle frontal gyrus, the inferior frontal gyrus, the anterior cingulate, the precuneus, and the posterior cingulate. These areas overlap with the major connectional backbone of the cortex and with many parts of the default network.

Triggering slow waves during NREM sleep in the rat by intracortical electrical stimulation: effects of sleep/wake history and background activity

In humans, non-rapid eye movement (NREM) sleep slow waves occur not only spontaneously but can also be induced by transcranial magnetic stimulation. Here we investigated whether slow waves can also be induced by intracortical electrical stimulation during sleep in rats. Intracortical local field potential (LFP) recordings were obtained from several cortical locations while the frontal or the parietal area was stimulated intracortically with brief (0.1 ms) electrical pulses. Recordings were performed in early sleep (1st 2-3 h after light onset) and late sleep (6-8 h after light onset). The stimuli reliably triggered LFP potentials that were visually indistinguishable from naturally occurring slow waves. The induced slow waves shared the following features with spontaneous slow waves: they were followed by spindling activity in the same frequency range ( approximately 15 Hz) as spontaneously occurring sleep spindles; they propagated through the neocortex from the area of the stimulation; and compared with late sleep, waves triggered during early sleep were larger, had steeper slopes and fewer multipeaks. Peristimulus background spontaneous activity had a profound influence on the amplitude of the induced slow waves: they were virtually absent if the stimulus was delivered immediately after the spontaneous slow wave. These results show that in the rat a volley of electrical activity that is sufficiently strong to excite and recruit a large cortical neuronal population is capable of inducing slow waves during natural sleep.

A perturbational approach for evaluating the brain's capacity for consciousness

How do we evaluate a brain's capacity to sustain conscious experience if the subject does not manifest purposeful behaviour and does not respond to questions and commands? What should we measure in this case? An emerging idea in theoretical neuroscience is that what really matters for consciousness in the brain is not activity levels, access to sensory inputs or neural synchronization per se, but rather the ability of different areas of the thalamocortical system to interact causally with each other to form an integrated whole. In particular, the information integration theory of consciousness (IITC) argues that consciousness is integrated information and that the brain should be able to generate consciousness to the extent that it has a large repertoire of available states (information), yet it cannot be decomposed into a collection of causally independent subsystems (integration). To evaluate the ability to integrate information among distributed cortical regions, it may not be sufficient to observe the brain in action. Instead, it is useful to employ a perturbational approach and examine to what extent different regions of the thalamocortical system can interact causally (integration) and produce specific responses (information). Thanks to a recently developed technique, transcranial magnetic stimulation and high-density electroencephalography (TMS/hd-EEG), one can record the immediate reaction of the entire thalamocortical system to controlled perturbations of different cortical areas. In this chapter, using sleep as a model of unconsciousness, we show that TMS/hd-EEG can detect clear-cut changes in the ability of the thalamocortical system to integrate information when the level of consciousness fluctuates across the sleep-wake cycle. Based on these results, we discuss the potential applications of this novel technique to evaluate objectively the brain's capacity for consciousness at the bedside of brain-injured patients.

Electrophysiological correlates of the brain's intrinsic large-scale functional architecture

Spontaneous fluctuations in the blood-oxygen-level-dependent (BOLD) signals demonstrate consistent temporal correlations within large-scale brain networks associated with different functions. The neurophysiological correlates of this phenomenon remain elusive. Here, we show in humans that the slow cortical potentials recorded by electrocorticography demonstrate a correlation structure similar to that of spontaneous BOLD fluctuations across wakefulness, slow-wave sleep, and rapid-eye-movement sleep. Gamma frequency power also showed a similar correlation structure but only during wakefulness and rapid-eye-movement sleep. Our results provide an important bridge between the large-scale brain networks readily revealed by spontaneous BOLD signals and their underlying neurophysiology.

Spontaneous neural activity during human slow wave sleep

Slow wave sleep (SWS) is associated with spontaneous brain oscillations that are thought to participate in sleep homeostasis and to support the processing of information related to the experiences of the previous awake period. At the cellular level, during SWS, a slow oscillation (<1 Hz) synchronizes firing patterns in large neuronal populations and is reflected on electroencephalography (EEG) recordings as large-amplitude, low-frequency waves. By using simultaneous EEG and event-related functional magnetic resonance imaging (fMRI), we characterized the transient changes in brain activity consistently associated with slow waves (>140 microV) and delta waves (75-140 microV) during SWS in 14 non-sleep-deprived normal human volunteers. Significant increases in activity were associated with these waves in several cortical areas, including the inferior frontal, medial prefrontal, precuneus, and posterior cingulate areas. Compared with baseline activity, slow waves are associated with significant activity in the parahippocampal gyrus, cerebellum, and brainstem, whereas delta waves are related to frontal responses. No decrease in activity was observed. This study demonstrates that SWS is not a state of brain quiescence, but rather is an active state during which brain activity is consistently synchronized to the slow oscillation in specific cerebral regions. The partial overlap between the response pattern related to SWS waves and the waking default mode network is consistent with the fascinating hypothesis that brain responses synchronized by the slow oscillation restore microwake-like activity patterns that facilitate neuronal interactions.

Interaction of slow cortical rhythm with somatosensory information processing in urethane-anesthetized rats

Slow cortical rhythm (SCR) is a rhythmic alteration of active (hypopolarized), and silent (hyperpolarized) epochs in cortical cells. SCR was found to influence sensory information processing in various models, but these studies yielded inconsistent results. We examined sensory processing in anesthetized rats during SCR by recording multiple unit activity (MUA) and evoked field potentials (eFPs). Evoked field potentials as well as spontaneous FP changes around spontaneous activations were analyzed by subsequent current source density (CSD) analysis. MUA responses and eFPs were recorded from the hindlimb area (HL) of the somatosensory cortex (SI) to electrical stimuli of the tibial nerve during active and silent states, respectively. Stimulus-associated MUA above the ongoing background activity did not differ significantly in active vs. silent states. Short-latency (<50 ms) eFP responses consisted of a sequence of deep-negative and deep-positive waves. Parameters of the first negative deflection were similar in both states. Stimulation in the silent state occasionally induced 500-700 ms long spindles in the alpha range (10-16 Hz). Spindles were never observed in responses to active state stimulation. CSD analysis showed moderately different cortical sink-source patterns when the stimulus was applied during active vs. silent state. Sinks first appeared in layer IV, V and VI, corresponding sources were in layer I/II, V and VI. Stronger activation appeared in the infraganular layers in the case of active state. CSD of spontaneous FPs revealed some sequential activation pattern in the cortex when strongest and earlier sink appeared in layer III during active states.

Spontaneous neuronal burst discharges as dependent and independent variables in the maturation of cerebral cortex tissue cultured in vitro: a review of activity-dependent studies in live 'model' systems for the development of intrinsically generated bioelectric slow-wave sleep patterns

A survey is presented of recent experiments which utilize spontaneous neuronal spike trains as dependent and/or independent variables in developing cerebral cortex cultures when synaptic transmission is interfered with for varying periods of time. Special attention is given to current difficulties in selecting suitable preparations for carrying out biologically relevant developmental studies, and in applying spike-train analysis methods with sufficient resolution to detect activity-dependent age and treatment effects. A hierarchy of synchronized nested burst discharges which approximate early slow-wave sleep patterns in the intact organism is established as a stable basis for isolated cortex function. The complexity of reported long- and short-term homeostatic responses to experimental interference with synaptic transmission is reviewed, and the crucial role played by intrinsically generated bioelectric activity in the maturation of cortical networks is emphasized.

The neural correlates of consciousness: an update

This review examines recent advances in the study of brain correlates of consciousness. First, we briefly discuss some useful distinctions between consciousness and other brain functions. We then examine what has been learned by studying global changes in the level of consciousness, such as sleep, anesthesia, and seizures. Next we consider some of the most common paradigms used to study the neural correlates for specific conscious percepts and examine what recent findings say about the role of different brain regions in giving rise to consciousness for that percept. Then we discuss dynamic aspects of neural activity, such as sustained versus phasic activity, feedforward versus reentrant activity, and the role of neural synchronization. Finally, we briefly consider how a theoretical analysis of the fundamental properties of consciousness can usefully complement neurobiological studies.

The functional connectivity of different EEG bands moves towards small-world network organization during sleep

OBJECTIVE

To analyze the functional connectivity patterns of the different EEG bands during wakefulness and sleep (different sleep stages and cyclic alternating pattern (CAP) conditions), using concepts derived from Graph Theory.

METHODS

We evaluated spatial patterns of EEG band synchronization between all possible pairs of electrodes (19) placed over the scalp of 10 sleeping healthy young normal subjects using two graph theoretical measures: the clustering coefficient (Cp) and the characteristic path length (Lp). The measures were obtained during wakefulness and the different sleep stages/CAP conditions from the real EEG connectivity networks and randomized control (surrogate) networks (Cp-s and Lp-s).

RESULTS

We found values of Cp and Lp compatible with a small-world network organization in all sleep stages and for all EEG bands. All bands below 15Hz showed an increase of these features during sleep (and during CAP-A phases in particular), compared to wakefulness.

CONCLUSIONS

The results of this study seem to confirm our initial hypothesis that during sleep there exists a clear trend for the functional connectivity of the EEG to move forward to an organization more similar to that of a small-world network, at least for the frequency bands lower than 15Hz.

SIGNIFICANCE

Sleep network "reconfiguration" might be one of the key mechanisms for the understanding of the "global" and "local" neural plasticity taking place during sleep.

The multifaceted role of inhibition in epilepsy: seizure-genesis through excessive GABAergic inhibition in autosomal dominant nocturnal frontal lobe epilepsy

PURPOSE OF REVIEW

While epilepsy describes a heterogeneous array of syndromes, the conventional view is that there is a common underlying failure in the ability of GABAergic inhibition to overcome excessive synaptic excitation. This review explores the possibility that enhanced GABAergic inhibition in the neocortex could also be proepileptogenic.

RECENT FINDINGS

Recently, two mouse strains carrying mutant alleles of the alpha4 subunit of the nicotinic acetylcholine receptor that are associated with autosomal dominant nocturnal frontal lobe epilepsy have been found to show spontaneous seizures. Recordings from neocortical pyramidal neurons in vitro show that the autosomal dominant nocturnal frontal lobe epilepsy mutations are associated with large selective increases in nicotine-evoked GABAergic inhibition, which may be key factor in epileptogenesis, as the seizures in vivo are blocked by subconvulsive doses of the GABAA receptor antagonist, picrotoxin.

SUMMARY

The precise links between the observed gain of neocortical inhibition and development of seizures in autosomal dominant nocturnal frontal lobe epilepsy mice remain unknown. Recent insights into the functional properties of cortical GABAergic circuits, however, suggest several possible pathways to be explored, whose elucidation could enable selective therapeutic interventions.

Functional integration across a gradient of corticostriatal channels controls UP state transitions in the dorsal striatum

Coordinated near-threshold depolarized states in cortical and striatal neurons may contribute to form functionally segregated channels of information processing. Recent anatomical studies have identified pathways that could support spiraling interactions across corticostriatal channels, but a functional outcome of such spiraling remains to be identified. Here, we examined whether plateau depolarizations (UP states) in striatal neurons relate better to active epochs in local field potentials recorded from closely related cortical areas than to those recorded in less-related cortical areas. Our results show that, in anesthetized rats, the coordination between cortical areas and striatal regions obeys a mediolateral gradient and keeps track of slow wave trajectory across the neocortex. Moreover, activity in one cortical area induced phase advances in UP state onset and phase delays in UP state termination in nonmatching striatal regions, reflecting the existence of functional connections that could encode large-scale interactions between corticostriatal channels as subthreshold influences on striatal projection neurons.

Characteristics of temporal fluctuations in the hyperpolarized state of the cortical slow oscillation

We present evidence for the hypothesis that transitions between the low- and high-firing states of the cortical slow oscillation correspond to neuronal phase transitions. By analyzing intracellular recordings of the membrane potential during the cortical slow oscillation in rats, we quantify the temporal fluctuations in power and the frequency centroid of the power spectrum in the period of time before "down" to "up" transitions. By taking appropriate averages over such events, we present these statistics as a function of time before transition. The results demonstrate an increase in fluctuation power and time scale broadly consistent with the slowing of systems close to phase transitions. The analysis is complicated and limited by the difficulty in identifying when transitions begin, and removing dc trends in membrane potential.

Breathing rhythms and emotions

Respiration is primarily regulated for metabolic and homeostatic purposes in the brainstem. However, breathing can also change in response to changes in emotions, such as sadness, happiness, anxiety or fear. Final respiratory output is influenced by a complex interaction between the brainstem and higher centres, including the limbic system and cortical structures. Respiration is important in maintaining physiological homeostasis and co-exists with emotions. In this review, we focus on the relationship between respiration and emotions by discussing previous animal and human studies, including studies of olfactory function in relation to respiration and the piriform-amygdala in relation to respiration. In particular, we discuss oscillations of piriform-amygdala complex activity and respiratory rhythm.

Sleep homeostasis and cortical synchronization: I. Modeling the effects of synaptic strength on sleep slow waves

STUDY OBJECTIVES

Sleep slow-wave activity (SWA, electroencephalogram [EEG] power between 0.5 and 4.0 Hz) is homeostatically regulated, increasing with wakefulness and declining with sleep. Sleep SWA is thought to reflect sleep need, but the mechanisms of its homeostatic regulation remain unknown. Based on a recent hypothesis, we sought to determine whether a decrease in cortical synaptic strength can account for changes in sleep SWA.

DESIGN

A large-scale computer model of the sleeping thalamocortical system was used to reproduce in detail the cortical slow oscillations underlying EEG slow waves.

SETTING

N/A.

PATIENTS OR PARTICIPANTS

N/A.

INTERVENTIONS

Simulated reductions in the strength of corticocortical synapses.

MEASUREMENTS AND RESULTS

Decreased synaptic strength led to (1) decreased single cell membrane potential oscillations and reduced network synchronization, (2) decreased rate of neural recruitment and decruitment, and (3) emergence of local clusters of synchronized activity. These changes were reflected in the local EEG as (1) decreased incidence of high-amplitude slow waves, (2) decreased wave slope, and (3) increased number of multipeak waves. Spectral analysis confirmed that these changes were associated with a decrease in SWA.

CONCLUSIONS

A decrease in cortical synaptic strength is sufficient to account for changes in sleep SWA and is accompanied by characteristic changes in slow-wave parameters. Experimental results from rat cortical depth recordings and human high-density EEG show similar changes in slow-wave parameters with decreasing SWA, suggesting that the underlying mechanism may indeed be a net decrease in synaptic strength.

Sleep homeostasis and cortical synchronization: III. A high-density EEG study of sleep slow waves in humans

STUDY OBJECTIVES

The mechanisms responsible for the homeostatic decrease of slow-wave activity (SWA, defined in this study as electroencephalogram [EEG] power between 0.5 and 4.0 Hz) during sleep are unknown. In agreement with a recent hypothesis, in the first of 3 companion papers, large-scale computer simulations of the sleeping thalamocortical system showed that a decrease in cortical synaptic strength is sufficient to account for the decline in SWA. In the model, the reduction in SWA was accompanied by decreased incidence of high-amplitude slow waves, decreased wave slopes, and increased number of waves with multiple peaks. In a second companion paper in the rat, local field potential recordings during early and late sleep confirmed the predictions of the model. Here, we investigated the model's predictions in humans by using all-night high-density (hd)-EEG recordings to explore slow-wave parameters over the entire cortical mantle.

DESIGN

256-channel EEG recordings in humans over the course of an entire night's sleep.

SETTING

Sound-attenuated sleep research room

PATIENTS OR PARTICIPANTS

Seven healthy male subjects

INTERVENTIONS

N/A.

MEASUREMENTS AND RESULTS

During late sleep (non-rapid eye movement [NREM] episodes 3 and 4, toward morning), when compared with early sleep (NREM sleep episodes 1 and 2, at the beginning of the night), the analysis revealed (1) reduced SWA, (2) fewer large-amplitude slow waves, (3) decreased wave slopes, (4) more frequent multipeak waves. The decrease in slope between early and late sleep was present even when waves were directly matched by wave amplitude and slow-wave power in the background EEG. Finally, hd-EEG showed that multipeak waves have multiple cortical origins.

CONCLUSIONS

In the human EEG, the decline of SWA during sleep is accompanied by changes in slow-wave parameters that were predicted by a computer model simulating a homeostatic reduction of cortical synaptic strength.