Spontaneous neural activity during human slow wave sleep

Large-scale microelectrode recordings of high-frequency gamma oscillations in human cortex during sleep

Gamma oscillations (40-120 Hz), usually associated with waking functions, can be recorded in the deepest stages of sleep in animals. The full details of their large-scale coordination across multiple cortical networks are still unknown. Furthermore, it is not known whether oscillations with similar characteristics are also present in the human brain. In this study, we examined the existence of gamma oscillations during polysomnographically defined sleep-wake states using large-scale microelectrode recordings (up to 56 channels), with single-cell and spike-time precision, in epilepsy patients. We report that low (40-80 Hz) and high (80-120 Hz) gamma oscillations recurrently emerged over time windows of several hundreds of milliseconds in all investigated cortical areas during slow-wave sleep. These patterns were correlated with positive peaks of EEG slow oscillations and marked increases in local cellular discharges, suggesting that they were associated with cortical UP states. These gamma oscillations frequently appeared at approximately the same time in many different cortical areas, including homotopic regions, forming large spatial patterns. Coincident firings with millisecond precision were strongly enhanced during gamma oscillations but only between cells within the same cortical area. Furthermore, in a significant number of cases, cortical gamma oscillations tended to occur within 100 ms after hippocampal ripple/sharp wave complexes. These data confirm and extend earlier animal studies reporting that gamma oscillations are transiently expressed during UP states during sleep. We speculate that these high-frequency patterns briefly restore "microwake" activity and are important for consolidation of memory traces acquired during previous awake periods.

Understanding non rapid eye movement sleep through neuroimaging

Non rapid eye movement (nonREM) sleep has long been considered as a state of brain quiescence, partly because brain oxygen metabolism, cerebral blood flow and glucose metabolism were shown to be decreased during nonREM sleep compared with wakefulness and REM sleep. However, emission techniques used for these measurements are characterized by relatively low temporal and spatial resolutions, whereby brain activity is averaged over minutes (the time required to obtain a single acquisition). Event-related functional magnetic resonance imaging (fMRI) acquires images with relatively high spatial and temporal resolution. Simultaneous electroencephalography (EEG) and fMRI can detect transient increases in activity associated with slow waves and slow and fast spindles during nonREM sleep. EEG/fMRI data show regionally specific increases in activity in relation to slow waves (brainstem, cerebellum, ventral prefrontal cortex, and posterior cingulate cortex/precuneus, parahippocampus areas) and slow (thalamus, anterior cingulate, insula) and fast spindles (additional responses in cingulate motor areas and sensorimotor contrices); some of which are involved in memory processing. These data demonstrate that nonREM sleep is not a state of brain quiescence, but a highly active state during which brain activity is consistently synchronized to slow waves and spindles in specific brain regions. These neural activity patterns have possible implications for memory processing.

[Sleep and episodic memory: a review of the literature in young healthy subjects and potential links between sleep changes and memory impairment observed during aging and Alzheimer's disease]

INTRODUCTION

A large body of evidence indicates that sleep favors memory consolidation.

STATE OF THE ART

This process would occur, mainly during slow-wave sleep, by means of a dialogue between the hippocampus and neocortical areas. Low levels of acetylcholine and cortisol are also needed to favor the transfer of memory traces toward the neocortex, where they will be stored for the long-term.

PERSPECTIVES

The aim of this article is, first, to give an overview of studies conducted in young healthy subjects and underpinning the hypothesis that sleep is involved in memory consolidation. Then, we will investigate the potential links between changes in sleep architecture and episodic memory impairment in both aging and Alzheimer's disease. Finally, we will see how these results can affect clinical practice.

CONCLUSION

Sleep-dependent memory consolidation is impaired both in aging and Alzheimer's disease. These findings suggest the importance of taking into account sleep when assessing memory function in patients.

Effects of sleep deprivation on sleep homeostasis and restoration during methadone-maintenance: a [31]P MRS brain imaging study

Insomnia afflicts many individuals, but particularly those in chronic methadone treatment. Studies examining sleep deprivation (SD) have begun to identify sleep restoration processes involving brain bioenergetics. The technique ([31])P magnetic resonance spectroscopy (MRS) can measure brain changes in the high-energy phosphates: alpha-, beta-, and gamma-nucleoside triphosphate (NTP). In the present study, 21 methadone-maintained (MM) and 16 control participants underwent baseline (BL), SD (40 wakeful hours), recovery1 (RE1), and recovery2 (RE2) study nights. Polysomnographic sleep was recorded each night and ([31])P MRS brain scanning conducted each morning using a 4T MR scanner (dual-tuned proton/phosphorus head-coil). Interestingly, increases in total sleep time (TST) and sleep efficiency index (SEI) commonly associated with RE sleep were not apparent in MM participants. Analysis of methadone treatment duration revealed that the lack of RE sleep increases in TST and SEI was primarily exhibited by short-term MM participants (methadone <12 months), while RE sleep in long-term MM (methadone >12 months) participants was more comparable to control participants. Slow wave sleep increased during RE1, but there was no difference between MM and control participants. Spectral power analysis revealed that compared to control participants; MM participants had greater delta, theta, and alpha spectral power during BL and RE sleep. ([31])P MRS revealed that elevations in brain beta-NTP (a direct measure of ATP) following RE sleep were greater in MM compared to control participants. Results suggest that differences in sleep and brain chemistry during RE in MM participants may be reflective of a disruption in homeostatic sleep function.

Dreaming and the brain: from phenomenology to neurophysiology

Dreams are a remarkable experiment in psychology and neuroscience, conducted every night in every sleeping person. They show that the human brain, disconnected from the environment, can generate an entire world of conscious experiences by itself. Content analysis and developmental studies have promoted understanding of dream phenomenology. In parallel, brain lesion studies, functional imaging and neurophysiology have advanced current knowledge of the neural basis of dreaming. It is now possible to start integrating these two strands of research to address fundamental questions that dreams pose for cognitive neuroscience: how conscious experiences in sleep relate to underlying brain activity; why the dreamer is largely disconnected from the environment; and whether dreaming is more closely related to mental imagery or to perception.

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.

Asymmetry and sexual dimorphism of the medial frontal gyrus visible surface in humans

Background/Aim. Studies of visible (extrasulcal) surface of the brain hemispheres are not feasible for measurements of the brain size, but are valuable for analysis and quantification of sexual dimorphism and/or asymmetries of the human brain. Morphological and morphometric investigations of the brain may contribute in genetic studies of the human nervous system. The aim of this study was to determine and to quantify sexual dimorphism and the right/left morphological asymmetry of the visible surface of medial frontal gyrus (gyrus frontalis medialis - GFM). Methods. Measurements and analysis of the visible surface of GFM were done on 84 hemispheres (42 brains from the persons of both sexes: 26 males and 16 females, 20-65 years of age). After fixation in 10% formalin and dissection, digital morphometric measurements were performed. We studied these in relation to the side of the hemisphere and the person's sex. Standardized digital AutoCAD planimetry of the visible surface of GFM was enabled by the use of coordinate system of intercommissural line. Results. In the whole sample, the visible surface of the right GFM (21.39 cm2) was statistically significantly greater (p < 0.05) than the left GFM (18.35 cm2) indicating the right/left asymmetry of the visible surface of GFM. Also, the visible surface of the right GFM in the males (22.66 cm2) was significantly greater (p < 0.05) than in the females (19.35 cm2), while the difference in size of the left GFM between the males and the females was not significant (p > 0.05). Conclusion. Morphological analysis of visible surface of GFM performed by digital planimetry showed sexual dimorphism of the visible surface and the presence of right/left asymmetry of GFM.

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.

Correlated low-frequency BOLD fluctuations in the resting human brain are modulated by recent experience in category-preferential visual regions

The resting brain is associated with significant intrinsic activity fluctuations, such as the correlated low-frequency (LF) blood oxygen level-dependent (BOLD) fluctuations measured by functional magnetic resonance imaging. Despite a recent expansion of studies investigating resting-state LF-BOLD correlations, their nature and function are poorly understood. A major constraint on LF-BOLD correlations appears to be stable properties of anatomic connectivity. There is also evidence that coupling can be modulated by recent or ongoing task performance, suggesting that certain components of correlated dynamics are malleable on short timescales. Here, we compared activity during extended periods of rest following performance of 2 distinct cognitive tasks using different categories of visual stimuli-faces and complex scenes. Prolonged exposure to these distinct categories of visual information caused frontal networks to couple differentially with posterior category-preferential visual regions during subsequent periods of rest. In addition, we report preliminary evidence suggesting that conditions exist in which the degree of modulation of LF-BOLD correlations predicts subsequent memory. The finding that resting-state LF-BOLD correlations are modulated by recent experience in functionally specific brain regions engaged during prior task performance clarifies their role as a dynamic phenomenon which may be involved in mnemonic processes.

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.

Spontaneous brain activity in the newborn brain during natural sleep--an fMRI study in infants born at full term

Recent progress in functional neuroimaging research has provided the opportunity to probe at the brain's intrinsic functional architecture. Synchronized spontaneous neuronal activity is present in the form of resting-state networks in the brain even in the absence of external stimuli. The objective of this study was to investigate the presence of resting-state networks in the unsedated infant brain born at full term. Using functional MRI, we investigated spontaneous low-frequency signal fluctuations in 19 healthy full-term infants. Resting-state functional MRI data acquired during natural sleep was analyzed using independent component analysis. We found five resting-state networks in the unsedated infant brain born at full term, encompassing sensory cortices, parietal and temporal areas, and the prefrontal cortex. In addition, we found evidence for a resting-state network that enclosed the bilateral basal ganglia.

Ultrahigh-frequency EEG during fMRI: pushing the limits of imaging-artifact correction

Although solutions for imaging-artifact correction in simultaneous EEG-fMRI are improving, residual artifacts after correction still considerably affect the EEG spectrum in the ultrafast frequency band above 100 Hz. Yet this band contains subtle but valuable physiological signatures such as fast gamma oscillations or evoked high-frequency (600 Hz) bursts related to spiking of thalamocortical and cortical neurons. Here we introduce a simultaneous EEG-fMRI approach that integrates hard and software modifications for continuous acquisition of ultrafast EEG oscillations during fMRI. Our approach is based upon and extends the established method of averaged artifact subtraction (AAS). Particularly for recovery of ultrahigh-frequency EEG signatures, AAS requires invariantly sampled and constant imaging-artifact waveforms to achieve optimal imaging-artifact correction. Consequently, we adjusted our acquisition setup such that both physiological ultrahigh-frequency EEG and invariantly sampled imaging artifacts were captured. In addition, we extended the AAS algorithm to cope with other, non-sampling related sources of imaging-artifact variations such as subject movements. A cascaded principal component analysis finally removed remaining imaging-artifact residuals. We provide a detailed evaluation of averaged ultrahigh-frequency signals and unaveraged broadband EEG spectra up to 1 kHz. Evoked nanovolt-sized high-frequency bursts were successfully recovered during periods of MR data acquisition afflicted by imaging artifacts in the millivolt range. Compared to periods without imaging artifacts they exhibited the same mean amplitudes, latencies and waveforms and a signal-to-noise ratio of 72%. Furthermore we identified consistent dipole sources. In conclusion, ultrafast EEG oscillations can be continuously monitored during fMRI using the proposed approach.

Feeling out the elephant in the room: why do temporal lobe seizures cause unconsciousness?

Remote Effects of Focal Hippocampal Seizures on the Rat Neocortex. Englot DJ, Mishra AM, Mansuripur PK, Herman P, Hyder F, Blumenfeld H. J Neurosci 2008;28(36):9066–9081. Seizures have both local and remote effects on nervous system function. Whereas propagated seizures are known to disrupt cerebral activity, little work has been done on remote network effects of seizures that do not propagate. Human focal temporal lobe seizures demonstrate remote changes including slow waves on electroencephalography (EEG) and decreased cerebral blood flow (CBF) in the neocortex. Ictal neocortical slow waves have been interpreted as seizure propagation; however, we hypothesize that they reflect a depressed cortical state resembling sleep or coma. To investigate this hypothesis, we performed multimodal studies of partial and secondarily generalized limbic seizures in rats. Video/EEG monitoring of spontaneous seizures revealed slow waves in the frontal cortex during behaviorally mild partial seizures, contrasted with fast polyspike activity during convulsive generalized seizures. Seizures induced by hippocampal stimulation produced a similar pattern, and were used to perform functional magnetic resonance imaging weighted for blood oxygenation and blood volume, demonstrating increased signals in hippocampus, thalamus and septum, but decreases in orbitofrontal, cingulate, and retrosplenial cortex during partial seizures, and increases in all of these regions during propagated seizures. Combining these results with neuronal recordings and CBF measurements, we related neocortical slow waves to reduced neuronal activity and cerebral metabolism during partial seizures, but found increased neuronal activity and metabolism during propagated seizures. These findings suggest that ictal neocortical slow waves represent an altered cortical state of depressed function, not propagated seizure activity. This remote effect of partial seizures may cause impaired cerebral functions, including loss of consciousness.

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.