Regional slow waves and spindles in human sleep

Density and frequency caudo-rostral gradients of sleep spindles recorded in the human cortex

STUDY OBJECTIVE

This study aims at providing a quantitative description of intrinsic spindle frequency and density (number of spindles/min) in cortical areas using deep intracerebral recordings in humans.

PATIENTS OR PARTICIPANTS

Thirteen patients suffering from pharmaco-resistant focal epilepsy and investigated through deep intracortical EEG in frontal, parietal, temporal, occipital, insular, and limbic cortices including the hippocampus were included.

METHODS

Spindle waves were detected from the ongoing EEG during slow wave sleep (SWS) by performing a time-frequency analysis on filtered signals (band-pass filter: 10-16 Hz). Then, spindle intrinsic frequency was determined using a fast Fourier transform, and spindle density (number of spindles per minute) was computed.

RESULTS

Firstly, we showed that sleep spindles were recorded in all explored cortical areas, except temporal neocortex. In particular, we observed the presence of spindles during SWS in areas such as the insular cortex, medial parietal cortex, occipital cortex, and cingulate gyrus. Secondly, we demonstrated that both spindle frequency and density smoothly change along the caudo-rostral axis, from fast frequent posterior spindles to slower and less frequent anterior spindles. Thirdly, we identified the presence of spindle frequency oscillations in the hippocampus and the entorhinal cortex.

CONCLUSIONS

Spindling activity is widespread among cortical areas, which argues for the fundamental role of spindles in cortical functions. Mechanisms of caudo-rostral gradient modulation in spindle frequency and density may result from a complex interplay of intrinsic properties and extrinsic modulation of thalamocortical and corticothalamic neurons.

A metabolic-transcriptional network links sleep and cellular energetics in the brain

This review proposes a mechanistic link between cellular metabolic status, transcriptional regulatory changes and sleep. Sleep loss is associated with changes in cellular metabolic status in the brain. Metabolic sensors responsive to cellular metabolic status regulate the circadian clock transcriptional network. Modifications of the transcriptional activity of circadian clock genes affect sleep/wake state changes. Changes in sleep state reverse sleep loss-induced changes in cellular metabolic status. It is thus proposed that the regulation of circadian clock genes by cellular metabolic sensors is a critical intermediate step in the link between cellular metabolic status and sleep. Studies of this regulatory relationship may offer insights into the function of sleep at the cellular level.

Properties of slow oscillation during slow-wave sleep and anesthesia in cats

Deep anesthesia is commonly used as a model of slow-wave sleep (SWS). Ketamine-xylazine anesthesia reproduces the main features of sleep slow oscillation: slow, large-amplitude waves in field potential, which are generated by the alternation of hyperpolarized and depolarized states of cortical neurons. However, direct quantitative comparison of field potential and membrane potential fluctuations during natural sleep and anesthesia is lacking, so it remains unclear how well the properties of sleep slow oscillation are reproduced by the ketamine-xylazine anesthesia model. Here, we used field potential and intracellular recordings in different cortical areas in the cat to directly compare properties of slow oscillation during natural sleep and ketamine-xylazine anesthesia. During SWS cortical activity showed higher power in the slow/delta (0.1-4 Hz) and spindle (8-14 Hz) frequency range, whereas under anesthesia the power in the gamma band (30-100 Hz) was higher. During anesthesia, slow waves were more rhythmic and more synchronous across the cortex. Intracellular recordings revealed that silent states were longer and the amplitude of membrane potential around transition between active and silent states was bigger under anesthesia. Slow waves were mostly uniform across cortical areas under anesthesia, but in SWS, they were most pronounced in associative and visual areas but smaller and less regular in somatosensory and motor cortices. We conclude that, although the main features of the slow oscillation in sleep and anesthesia appear similar, multiple cellular and network features are differently expressed during natural SWS compared with ketamine-xylazine anesthesia.

Slow and fast rhythms generated in the cerebral cortex of the anesthetized mouse

A characterization of the oscillatory activity in the cerebral cortex of the mouse was realized under ketamine anesthesia. Bilateral recordings were obtained from deep layers of primary visual, somatosensory, motor, and medial prefrontal cortex. A slow oscillatory activity consisting of up and down states was detected, the average frequency being 0.97 Hz in all areas. Different parameters of the oscillation were estimated across cortical areas, including duration of up and down states and their variability, speed of state transitions, and population firing rate. Similar values were obtained for all areas except for prefrontal cortex, which showed significant faster down-to-up state transitions, higher firing rate during up states, and more regular cycles. The wave propagation patterns in the anteroposterior axis in motor cortex and the mediolateral axis in visual cortex were studied with multielectrode recordings, yielding speed values between 8 and 93 mm/s. The firing of single units was analyzed with respect to the population activity. The most common pattern was that of neurons firing in >90% of the up states with 1–6 spikes. Finally, fast rhythms (beta, low gamma, and high gamma) were analyzed, all of them showing significantly larger power during up states than in down states. Prefrontal cortex exhibited significantly larger power in both beta and gamma bands (up to 1 order of magnitude larger in the case of high gamma) than the rest of the cortical areas. This study allows us to carry out interareal comparisons and provides a baseline to compare against cortical emerging activity from genetically altered animals.

Ongoing physiological processes in the cerebral cortex

Functional magnetic resonance imaging (fMRI) has revealed that the human brain undergoes prominent, regional hemodynamic fluctuations when a subject is at rest. These ongoing fluctuations exhibit distinct patterns of spatiotemporal synchronization that have been dubbed "resting state functional connectivity", and which currently serve as a principal tool to investigate neural networks in the normal and pathological human brain. Despite the wide application of this approach in human neuroscience, the neural mechanisms that give rise to spontaneous fMRI correlations are largely unknown. Here we review results of recent electrophysiological studies in the cerebral cortex of humans and nonhuman primates that link neural activity to ongoing fMRI fluctuations. We begin by describing results obtained with simultaneous fMRI and electrophysiological measurements that allow for the identification of direct neural correlates of resting state functional connectivity. We next highlight experiments that investigate the correlational structure of spontaneous neural signals, including the spatial variation of signal coherence over the cortical surface, across cortical laminae, and between the two hemispheres. In the final section we speculate on the origins and potential consequences of ongoing signals for normal brain function, and point out inherent limitations of the fMRI correlation approach.

Activity of cortical and thalamic neurons during the slow (<1 Hz) rhythm in the mouse in vivo

During NREM sleep and under certain types of anaesthesia, the mammalian brain exhibits a distinctive slow (<1 Hz) rhythm. At the cellular level, this rhythm correlates with so-called UP and DOWN membrane potential states. In the neocortex, these UP and DOWN states correspond to periods of intense network activity and widespread neuronal silence, respectively, whereas in thalamocortical (TC) neurons, UP/DOWN states take on a more stereotypical oscillatory form, with UP states commencing with a low-threshold Ca²⁺ potential (LTCP). Whilst these properties are now well recognised for neurons in cats and rats, whether or not they are also shared by neurons in the mouse is not fully known. To address this issue, we obtained intracellular recordings from neocortical and TC neurons during the slow (<1 Hz) rhythm in anaesthetised mice. We show that UP/DOWN states in this species are broadly similar to those observed in cats and rats, with UP states in neocortical neurons being characterised by a combination of action potential output and intense synaptic activity, whereas UP states in TC neurons always commence with an LTCP. In some neocortical and TC neurons, we observed ‘spikelets’ during UP states, supporting the possible presence of electrical coupling. Lastly, we show that, upon tonic depolarisation, UP/DOWN states in TC neurons are replaced by rhythmic high-threshold bursting at ~5 Hz, as predicted by in vitro studies. Thus, UP/DOWN state generation appears to be an elemental and conserved process in mammals that underlies the slow (<1 Hz) rhythm in several species, including humans.

Ostriches sleep like platypuses

Mammals and birds engage in two distinct states of sleep, slow wave sleep (SWS) and rapid eye movement (REM) sleep. SWS is characterized by slow, high amplitude brain waves, while REM sleep is characterized by fast, low amplitude waves, known as activation, occurring with rapid eye movements and reduced muscle tone. However, monotremes (platypuses and echidnas), the most basal (or 'ancient') group of living mammals, show only a single sleep state that combines elements of SWS and REM sleep, suggesting that these states became temporally segregated in the common ancestor to marsupial and eutherian mammals. Whether sleep in basal birds resembles that of monotremes or other mammals and birds is unknown. Here, we provide the first description of brain activity during sleep in ostriches (Struthio camelus), a member of the most basal group of living birds. We found that the brain activity of sleeping ostriches is unique. Episodes of REM sleep were delineated by rapid eye movements, reduced muscle tone, and head movements, similar to those observed in other birds and mammals engaged in REM sleep; however, during REM sleep in ostriches, forebrain activity would flip between REM sleep-like activation and SWS-like slow waves, the latter reminiscent of sleep in the platypus. Moreover, the amount of REM sleep in ostriches is greater than in any other bird, just as in platypuses, which have more REM sleep than other mammals. These findings reveal a recurring sequence of steps in the evolution of sleep in which SWS and REM sleep arose from a single heterogeneous state that became temporally segregated into two distinct states. This common trajectory suggests that forebrain activation during REM sleep is an evolutionarily new feature, presumably involved in performing new sleep functions not found in more basal animals.

Topographical aspects in the dynamics of sleep homeostasis in young men: individual patterns

BACKGROUND

Sleep homeostasis refers to the increase of sleep pressure during waking and the decrease of sleep intensity during sleep. Electroencephalography (EEG) slow-wave activity (SWA; EEG power in the 0.75-4.5 Hz range) is a marker of non-rapid eye movement (NREM) sleep intensity and can be used to model sleep homeostasis (Process S). SWA shows a frontal predominance, and its increase after sleep deprivation is most pronounced in frontal areas. The question arises whether the dynamics of the homeostatic Process S also show regional specificity. Furthermore, the spatial distribution of SWA is characteristic for an individual and may reflect traits of functional anatomy. The aim of the current study was to quantify inter-individual variation in the parameters of Process S and investigate their spatial distribution. Polysomnographic recordings obtained with 27 EEG derivations of a baseline night of sleep and a recovery night of sleep after 40 h of sustained wakefulness were analyzed. Eight healthy young subjects participated in this study. Process S was modeled by a saturating exponential function during wakefulness and an exponential decline during sleep. Empirical mean SWA per NREM sleep episode at episode midpoint served for parameter estimation at each derivation. Time constants were restricted to a physiologically meaningful range.

RESULTS

For both, the buildup and decline of Process S, significant topographic differences were observed: The decline and buildup of Process S were slowest in fronto-central areas while the fastest dynamics were observed in parieto-occipital (decrease) and frontal (buildup) areas. Each individual showed distinct spatial patterns in the parameters of Process S and the parameters differed significantly between individuals.

CONCLUSIONS

For the first time, topographical aspects of the buildup of Process S were quantified. Our data provide an additional indication of regional differences in sleep homeostasis and support the notion of local aspects of sleep regulation.

Selective optical drive of thalamic reticular nucleus generates thalamic bursts and cortical spindles

The thalamic reticular nucleus (TRN) is hypothesized to regulate neocortical rhythms and behavioral states. Using optogenetics and multi-electrode recording in behaving mice, we found that brief selective drive of TRN switched the thalamocortical firing mode from tonic to bursting and generated state-dependent neocortical spindles. These findings provide causal support for the involvement of the TRN in state regulation in vivo and introduce a new model for addressing the role of this structure in behavior.

Local sleep in awake rats

When the brain is awake, neurons in the cerebral cortex fire irregularly and the electroencephalogram (EEG) displays low amplitude, high frequency fluctuations. After falling asleep, neurons start oscillating between ON periods, when they fire as during wake, and OFF periods, when they stop firing altogether, and the EEG displays high amplitude slow waves. But what happens to neuronal firing after a long period of wake? We show here in freely behaving rats that, after prolonged wake, cortical neurons can go briefly “OFF line” as they do in sleep, accompanied by slower waves in the local EEG. Strikingly, neurons often go OFF line in one cortical area and not in another. During these periods of “local sleep”, whose incidence increases with wake duration, rats appear awake, active, and display a wake EEG. However, they are progressively impaired in a sugar pellet reaching task. Thus, though both the EEG and behavior indicate wakefulness, local populations of neurons in the cortex may be falling asleep, with negative consequences on performance.

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

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