The slow (<1 Hz) oscillation, along with its alternating UP and DOWN states in individual neurons, is a defining feature of the EEG during slow-wave sleep. Although this oscillation is well preserved across mammalian species, its physiological role remains unclear. Electrophysiological and computational evidence from cortex and thalamus now indicates that the slow oscillation UP states and the ‘activated’ state of wakefulness are remarkably similar dynamic entities. This is consistent with behavioural experiments suggesting that slow oscillation UP states provide a context for the replay and possible consolidation of previous experience. In this scenario, the T-type Ca2+ channel-dependent bursts of action potentials that initiate each UP state in thalamocortical neurons, might act as triggers for synaptic and cellular plasticity in corticothalamic networks.
Thalamocortical dynamics, the millisecond to second changes in activity of thalamocortical circuits, are central to perception, action and cognition. Generated by local circuitry and sculpted by neuromodulatory systems, these dynamics reflect the expression of vigilance states. In sleep, thalamocortical dynamics are thought to mediate “offline” functions including memory consolidation and synaptic scaling. Here, I discuss thalamocortical sleep dynamics and their modulation by the ascending arousal system and locally-released neurochemicals. I focus on modulation of these dynamics by electrically-silent astrocytes, highlighting the role of purinergic signaling in this glial form of communication. Astrocytes modulate cortical slow oscillations, sleep behavior, and sleep-dependent cognitive function. The discovery that astrocytes can modulate sleep dynamics and sleep-related behaviors suggests a new way of thinking about the brain, in which integrated circuits of neurons and glia control information processing and behavioral output.
sleep; thalamocortical circuitry; oscillations; memory; astrocytes; ATP; adenosine
The slow (<1 Hz) rhythm, the most significant 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 within a corticothalamic module requires the dynamic interaction of three cardinal oscillators: a predominantly synaptically-based cortical oscillator and two intrinsic, conditional thalamic oscillators. The functional implications of this hypothesis are discussed in relation to other key 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.
There are three major oscillations in thalamocortical systems during the state of sleep with synchronization of the electroencephalogram: 1. Spindles (7 Hz to 14 Hz) are generated in the thalamus at sleep onset and are blocked during arousal or rapid-eye-movement sleep by cholinergic systems that decouple the synchronizing network of the reticular thalamic nucleus. 2. Delta potentials (1 Hz to 4 Hz) appear during late stages of electroencephalogram-synchronized sleep. At the thalamic level they are produced by the interplay between two intrinsic currents of neurons with cortical projections. Delta rhythm is suppressed by cholinergic and noradrenergic systems. 3. A slow oscillation (< 1 Hz) is generated in the cerebral cortex and has a pivotal role in grouping the thalamic-generated sleep rhythms within wave-complexes recurring periodically, every two to five seconds. The slow rhythm is blocked by cholinergic and noradrenergic projections. Sleep rhythms consist of long-lasting inhibitory components that obliterate synaptic transmission and disconnect the brain from the outside world.
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.
The cerebral cortex is permanently active during both awake and sleep states. This ongoing cortical activity has an impact on synaptic transmission and short-term plasticity. An activity pattern generated by the cortical network is a slow rhythmic activity that alternates up (active) and down (silent) states, a pattern occurring during slow wave sleep, anesthesia and even in vitro. Here we have studied 1) how network activity affects short term synaptic plasticity and, 2) how synaptic transmission varies in up versus down states.
Intracellular recordings obtained from cortex in vitro and in vivo were used to record synaptic potentials, while presynaptic activation was achieved either with electrical or natural stimulation. Repetitive activation of layer 4 to layer 2/3 synaptic connections from ferret visual cortex slices displayed synaptic augmentation that was larger and longer lasting in active than in silent slices. Paired-pulse facilitation was also significantly larger in an active network and it persisted for longer intervals (up to 200 ms) than in silent slices. Intracortical synaptic potentials occurring during up states in vitro increased their amplitude while paired-pulse facilitation disappeared. Both intracortical and thalamocortical synaptic potentials were also significantly larger in up than in down states in the cat visual cortex in vivo. These enhanced synaptic potentials did not further facilitate when pairs of stimuli were given, thus paired-pulse facilitation during up states in vivo was virtually absent. Visually induced synaptic responses displayed larger amplitudes when occurring during up versus down states. This was further tested in rat barrel cortex, where a sensory activated synaptic potential was also larger in up states.
These results imply that synaptic transmission in an active cortical network is more secure and efficient due to larger amplitude of synaptic potentials and lesser short term plasticity.
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/measure plastic changes in the cerebral cortex and we can directly assess cortico-cortical information transmission. In this manuscript we review the results of recent experiments in which TMS/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 non-pharmacological mean to controllably induce slow waves in the human cerebral cortex.
sleep homeostasis; synaptic plasticity; consciousness; slow oscillations; bistability
Activity-dependent dendritic Ca2+ signals play a critical role in multiple forms of non-linear cellular output and plasticity. In thalamocortical neurons, despite the well-established spatial separation of sensory and cortical inputs onto proximal and distal dendrites respectively, little is known about the spatio-temporal dynamics of intrinsic dendritic Ca2+ signalling during the different state-dependent firing patterns that are characteristic of these neurons. Here we demonstrate that T-type Ca2+ channels are expressed throughout the entire dendritic tree of rat thalamocortical neurons and that they mediate regenerative propagation of low threshold spikes, typical of, but not exclusive to sleep states, resulting in global dendritic Ca2+ influx. In contrast, actively backpropagating action potentials, typical of wakefulness, result in smaller Ca2+ influxes that can temporally summate to produce dendritic Ca2+ accumulations which are linearly related to firing frequency but spatially confined to proximal dendritic regions. Furthermore, dendritic Ca2+ transients evoked by both action potentials and low threshold spikes are shaped by Ca2+ uptake by sarco/endoplasmic reticulum Ca2+ ATP-ases, but do not rely upon Ca2+-induced Ca2+ release. Our data demonstrate that thalamocortical neurons are endowed with intrinsic dendritic Ca2+ signalling properties that are spatially and temporally modified in a behavioural state-dependent manner, and suggest that backpropagating action potentials faithfully inform proximal sensory but not distal corticothalamic synapses of neuronal output whereas corticothalamic synapses only “detect” Ca2+ signals associated with low threshold spikes.
thalamocortical; dendrites; T-type calcium channel; low threshold spike; action potential; calcium extrusion
During non-rapid eye movement (NREM) sleep and certain types of anaesthesia, neurons in the neocortex and thalamus exhibit a distinctive slow (<1 Hz) oscillation that consists of alternating UP and DOWN membrane potential states and which correlates with a pronounced slow (<1 Hz) rhythm in the EEG. Whilst several studies have claimed that the slow oscillation is generated exclusively in neocortical networks and then transmitted to other brain areas, substantial evidence exists to suggest that the full expression of the slow oscillation in an intact thalamocortical network requires the balanced interaction of oscillator systems in both the neocortex and thalamus. Within such a scenario, we have previously argued that the powerful low-threshold Ca2+ potential (LTCP)-mediated burst of action potentials that initiates the UP states in individual thalamocortical neurons may be a vital signal for instigating UP states in related cortical areas. To investigate these issues we constructed a computational model of the thalamocortical network which encompasses the important known aspects of the slow oscillation that have been garnered from earlier in vivo and in vitro experiments. By using this model we confirm that the overall expression of the slow oscillation is intricately reliant on intact connections between thalamus and cortex. In particular, we demonstrate that UP state-related LTCP-mediated bursts in thalamocortical neurons are proficient in triggering synchronous UP states in cortical networks, thereby bringing about a synchronous slow oscillation in the whole network. The importance of LTCP-mediated action potential bursts in the slow oscillation is also underlined by the observation that their associated dendritic Ca2+ signals are the only ones that inform corticothalamic synapses of the thalamocortical neuron output, since they, but not those elicited by tonic action potential firing, reach the distal dendritic sites where these synapses are located.
thalamic neurons; cortical neurons; probabilistic network model; dendrites; intrinsic calcium signalling
Neurons of the central nervous system display a broad spectrum of intrinsic electrophysiological properties that are absent in the traditional “integrate-and-fire” model. A network of neurons with these properties interacting through synaptic receptors with many time scales can produce complex patterns of activity that cannot be intuitively predicted. Computational methods, tightly linked to experimental data, provide insights into the dynamics of neural networks. We review this approach for the case of bursting neurons of the thalamus, with a focus on thalamic and thalamocortical slow-wave oscillations. At the single-cell level, intrinsic bursting or oscillations can be explained by interactions between calcium- and voltage-dependent channels. At the network level, the genesis of oscillations, their initiation, propagation, termination, and large-scale synchrony can be explained by interactions between neurons with a variety of intrinsic cellular properties through different types of synaptic receptors. These interactions can be altered by neuromodulators, which can dramatically shift the large-scale behavior of the network, and can also be disrupted in many ways, resulting in pathological patterns of activity, such as seizures. We suggest a coherent framework that accounts for a large body of experimental data at the ion-channel, single-cell, and network levels. This framework suggests physiological roles for the highly synchronized oscillations of slow-wave sleep.
Cortico-thalamo-cortical circuits mediate sensation and generate neural network oscillations associated with slow-wave sleep and various epilepsies. Cortical input to sensory thalamus is thought to mainly evoke feed-forward synaptic inhibition of thalamocortical (TC) cells via reticular thalamic nucleus (nRT) neurons, especially during oscillations. This relies on a stronger synaptic strength in the cortico-nRT pathway than in the cortico-TC pathway, allowing the feed-forward inhibition of TC cells to overcome direct cortico-TC excitation. We found a systemic and specific reduction in strength in GluA4-deficient (Gria4–/–) mice of one excitatory synapse of the rhythmogenic cortico-thalamo-cortical system, the cortico-nRT projection, and observed that the oscillations could still be initiated by cortical inputs via the cortico-TC-nRT-TC pathway. These results reveal a previously unknown mode of cortico-thalamo-cortical transmission, bypassing direct cortico-nRT excitation, and describe a mechanism for pathological oscillation generation. This mode could be active under other circumstances, representing a previously unknown channel of cortico-thalamo-cortical information processing.
The slow (<1 Hz) rhythm is an EEG hallmark of resting sleep. In thalamocortical (TC) neurons this rhythm correlates with a slow (<1 Hz) oscillation comprising recurring UP and DOWN membrane potential states. Recently, we showed that metabotropic glutamate receptor (mGluR) activation brings about an intrinsic slow oscillation in thalamocortical (TC) neurons of the cat dorsal lateral geniculate nucleus (LGN) in vitro which is identical to that observed in vivo. The aim of this study was to further assess the properties of this oscillation and compare them with those observed in TC neurons of three other thalamic nuclei in the cat (ventrobasal complex, VB; medial geniculate body, MGB; ventral lateral nucleus, VL) and two thalamic nuclei in rats and mice (LGN and VB). Slow oscillations were evident in all of these additional structures and shared several basic properties including, i) the stereotypical, rhythmic alternation between distinct UP and DOWN states with the UP state always commencing with a low-threshold Ca2+ potential (LTCP), and ii) an inverse relationship between frequency and injected current so that slow oscillations always increase in frequency with hyperpolarization, often culminating in delta (δ) activity at ~1-4 Hz. However, beyond these common properties there were important differences in expression between different nuclei. Most notably, 44% of slow oscillations in the cat LGN possessed UP states that comprised sustained tonic firing and/or high-threshold (HT) bursting. In contrast, slow oscillations in cat VB, MGB and VL TC neurons exhibited such UP states in only 16%, 11% and 10% of cases, respectively, whereas slow oscillations in the LGN and VB of rats and mice did so in <12% of cases. Thus, the slow oscillation is a common feature of TC neurons that displays clear species- and nuclei-related differences. The potential functional significance of these results is discussed.
EEG; delta waves; T-type calcium channels; metabotropic glutamate receptor
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.
slow wave sleep; slow oscillations; EEG; rat; cerebral cortex; multi-unit recording
During non-rapid eye movement sleep and certain types of anaesthesia, neurons in the neocortex and thalamus exhibit a distinctive slow (<1 Hz) oscillation that consists of alternating UP and DOWN membrane potential states and which correlates with a pronounced slow (<1 Hz) rhythm in the electroencephalogram. While several studies have claimed that the slow oscillation is generated exclusively in neocortical networks and then transmitted to other brain areas, substantial evidence exists to suggest that the full expression of the slow oscillation in an intact thalamocortical (TC) network requires the balanced interaction of oscillator systems in both the neocortex and thalamus. Within such a scenario, we have previously argued that the powerful low-threshold Ca2+ potential (LTCP)-mediated burst of action potentials that initiates the UP states in individual TC neurons may be a vital signal for instigating UP states in related cortical areas. To investigate these issues we constructed a computational model of the TC network which encompasses the important known aspects of the slow oscillation that have been garnered from earlier in vivo and in vitro experiments. Using this model we confirm that the overall expression of the slow oscillation is intricately reliant on intact connections between the thalamus and the cortex. In particular, we demonstrate that UP state-related LTCP-mediated bursts in TC neurons are proficient in triggering synchronous UP states in cortical networks, thereby bringing about a synchronous slow oscillation in the whole network. The importance of LTCP-mediated action potential bursts in the slow oscillation is also underlined by the observation that their associated dendritic Ca2+ signals are the only ones that inform corticothalamic synapses of the TC neuron output, since they, but not those elicited by tonic action potential firing, reach the distal dendritic sites where these synapses are located.
thalamic neurons; cortical neurons; probabilistic network model; dendrites; intrinsic calcium signalling
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.
UP/DOWN states; cerebral cortex; sleep; replay; electrophysiology; ensemble recordings; spike sequence; synfire chains
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.
slow wave sleep; slow oscillations; EEG; cerebral cortex; multi-unit recording; reaching task; sleep deprivation
In slow neocortical paroxysmal oscillations, the de- and hyperpolarizing envelopes in neocortical neurons are large compared with slow sleep oscillations. Increased local synchrony of membrane potential oscillations during seizure is reflected in larger electroencephalographic oscillations and the appearance of spike- or polyspike-wave complex recruitment at 2- to 3-Hz frequencies. The oscillatory mechanisms underlying this paroxysmal activity were investigated in computational models of cortical networks. The extracellular K+ concentration ([K+]o) was continuously computed based on neuronal K+ currents and K+ pumps as well as glial buffering. An increase of [K+]o triggered a transition from normal awake-like oscillations to 2- to 3-Hz seizure-like activity. In this mode, the cells fired periodic bursts and nearby neurons oscillated highly synchronously; in some cells depolarization led to spike inactivation lasting 50–100 ms. A [K+]o increase, sufficient to produce oscillations could result from excessive firing (e.g., induced by external stimulation) or inability of K+ regulatory system (e.g., when glial buffering was blocked). A combination of currents including high-threshold Ca2+, persistent Na+ and hyperpolarization-activated depolarizing (Ih) currents was sufficient to maintain 2- to 3-Hz activity. In a network model that included lateral K+ diffusion between cells, increase of [K+]o in a small region was generally sufficient to maintain paroxysmal oscillations in the whole network. Slow changes of [K+]o modulated the frequency of bursting and, in some case, led to fast oscillations in the 10- to 15-Hz frequency range, similar to the fast runs observed during seizures in vivo. These results suggest that modifications of the intrinsic currents mediated by increase of [K+]o can explain the range of neocortical paroxysmal oscillations in vivo.
The amount and architecture of vigilance states are governed by two distinct processes, which occur at different time scales. The first, a slow one, is related to a wake/sleep dependent homeostatic Process S, which occurs on a time scale of hours, and is reflected in the dynamics of NREM sleep EEG slow-wave activity. The second, a fast one, is manifested in a regular alternation of two sleep states – NREM and REM sleep, which occur, in rodents, on a time scale of ∼5–10 minutes. Neither the mechanisms underlying the time constants of these two processes – the slow one and the fast one, nor their functional significance are understood. Notably, both processes are primarily apparent during sleep, while their potential manifestation during wakefulness is obscured by ongoing behaviour. Here, we find, in mice provided with running wheels, that the two sleep processes become clearly apparent also during waking at the level of behavior and brain activity. Specifically, the slow process was manifested in the total duration of waking periods starting from dark onset, while the fast process was apparent in a regular occurrence of running bouts during the waking periods. The dynamics of both processes were stable within individual animals, but showed large interindividual variability. Importantly, the two processes were not independent: the periodic structure of waking behaviour (fast process) appeared to be a strong predictor of the capacity to sustain continuous wakefulness (slow process). The data indicate that the temporal organization of vigilance states on both the fast and the slow time scales may arise from a common neurophysiologic mechanism.
Brain electrical activity is largely composed of oscillations at characteristic frequencies. These rhythms are hierarchically organized and are thought to perform important pathological and physiological functions. The slow wave is a fundamental cortical rhythm that emerges in deep non-rapid eye movement sleep. In animals, the slow wave modulates delta, theta, spindle, alpha, beta, gamma and ripple oscillations, thus orchestrating brain electrical rhythms in sleep. While slow wave activity can enhance epileptic manifestations, it is also thought to underlie essential restorative processes and facilitate the consolidation of declarative memories. Animal studies show that slow wave activity is composed of rhythmically recurring phases of widespread, increased cortical cellular and synaptic activity, referred to as active- or up-state, followed by cellular and synaptic inactivation, referred to as silent- or down-state. However, its neural mechanisms in humans are poorly understood, since the traditional intracellular techniques used in animals are inappropriate for investigating the cellular and synaptic/transmembrane events in humans. To elucidate the intracortical neuronal mechanisms of slow wave activity in humans, novel, laminar multichannel microelectrodes were chronically implanted into the cortex of patients with drug-resistant focal epilepsy undergoing cortical mapping for seizure focus localization. Intracortical laminar local field potential gradient, multiple-unit and single-unit activities were recorded during slow wave sleep, related to simultaneous electrocorticography, and analysed with current source density and spectral methods. We found that slow wave activity in humans reflects a rhythmic oscillation between widespread cortical activation and silence. Cortical activation was demonstrated as increased wideband (0.3–200 Hz) spectral power including virtually all bands of cortical oscillations, increased multiple- and single-unit activity and powerful inward transmembrane currents, mainly localized to the supragranular layers. Neuronal firing in the up-state was sparse and the average discharge rate of single cells was less than expected from animal studies. Action potentials at up-state onset were synchronized within ±10 ms across all cortical layers, suggesting that any layer could initiate firing at up-state onset. These findings provide strong direct experimental evidence that slow wave activity in humans is characterized by hyperpolarizing currents associated with suppressed cell firing, alternating with high levels of oscillatory synaptic/transmembrane activity associated with increased cell firing. Our results emphasize the major involvement of supragranular layers in the genesis of slow wave activity.
current source density; unit activity; laminar recording; slow wave activity; sleep
Slow waves are the most prominent electroencephalographic (EEG) 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 (Steriade et al., 1993a; Destexhe et al., 1999; Steriade et al., 2001). Intracellular recordings indicate that the origins of the slow oscillation are cortical and that cortico-cortical connections are necessary for their synchronization (Steriade et al. 1993b; Amzica and Steriade, 1995; 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 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 (Maquet, 2000; Dang-Vu et al., 2008). Intracranial recordings in patient populations are limited by the availability of medically necessary electrode placements and can be confounded by pathology and medications (Nir et al., 2010; Cash et al., 2009; 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.
slow oscillation; source modeling; K-complex; neuroimaging; electroencephalography
Sleep electroencephalogram (EEG) brain oscillations in the low-frequency range show local signs of homeostatic regulation after learning. Such increases and decreases of slow wave activity are limited to the cortical regions involved in specific task performance during wakefulness. Here, we test the hypothesis that reorganization of motor cortex produced by long-term potentiation (LTP) affects EEG activity of this brain area during subsequent sleep.
By pairing median nerve stimulation with transcranial magnetic stimulation over the contralateral motor cortex, one can potentiate the motor output, which is presumed to reflect plasticity of the neural circuitry. This paired associative stimulation increases M1 cortical excitability at interstimulus intervals of 25 ms. We compared the scalp distribution of sleep EEG power following paired associative stimulation at 25 ms to that following a control paradigm with 50 ms intervals. It is shown that the experimental manipulation by paired associative stimulation at 25 ms induces a 48% increase in amplitude of motor evoked potentials. This LTP-like potentiation, induced during waking, affects delta and theta EEG power in both REM and non-REM sleep, measured during the following night. Slow-wave activity increases in some frontal and prefrontal derivations and decreases at sites neighboring and contralateral to the stimulated motor cortex. The magnitude of increased amplitudes of motor evoked potentials by the paired associative stimulation at 25 ms predicts enhancements of slow-wave activity in prefrontal regions.
An LTP-like paradigm, presumably inducing increased synaptic strength, leads to changes in local sleep regulation, as indexed by EEG slow-wave activity. Enhancement and depression of slow-wave activity are interpreted in terms of a simultaneous activation of both excitatory and inhibitory circuits consequent to the paired associative stimulation at 25 ms.
The firing activity of dorsal raphe neurons is related to arousal state. However, it is unclear how this firing activity is precisely related to cortical activity, in particular oscillations occurring during sleep rhythms. Here we conducted single-cell extracellular recordings and juxtacellular labelling while monitoring electrocorticogram (ECoG) activity in urethane anaesthetised rats, to relate activity in neurochemically identified groups of neurons to cortical slow-wave activity (SWA). We observed that electrophysiological heterogeneity in dorsal raphe neurons revealed different neurochemical groups of DRN neurons and was mirrored by significant differences in the phase and strength of coupling to the cortical slow oscillations. Spike firing relationship of clock-like neurons, identified as 5-HT (5-hydroxytryptamine) or serotonin neurons, was higher during the inactive component of the oscillations. In contrast, half of the identified bursting 5-HT neurons did not exhibit strong cortical entrainment; those that did fired most during the inactive component of the SWA. Two groups of putatively non-5-HT neurons (irregular slow-firing and fast-firing) exhibited significant coherence and fired most during the active component of the SWA. These findings indicate that within the DRN electrophysiologically and neurochemically discrete neuronal groups exhibit distinct relations to cortical activity.
▶DRN neurons exhibit heterogeneous firing in relation to cortical oscillations. ▶Clock-like 5-HT neurons fire most during inactive component of the oscillation. ▶Half of bursting 5-HT neurons did not exhibit coupling to the oscillation. ▶Non-5-HT neurons fired most during the active component of the oscillation.
5-HT; serotonergic; dopamine; basal ganglia; limbic system; ANOVA, analyses of variance; COV-IS, coefficient of variation of the inter-spike-interval; DRN, dorsal raphe nucleus; ECoG, electrocorticogram; PBS, phosphate-buffered saline; PBS-X, PBS containing 0.2% Triton X-100; PFC, prefrontal cortex; SWA, slow-wave activity; TH, tyrosine hydroxylase; 5-HT, 5-hydroxytryptamine
The neuronal cortical network generates slow (<1 Hz) spontaneous rhythmic activity that emerges from the recurrent connectivity. This activity occurs during slow wave sleep or anesthesia and also in cortical slices, consisting of alternating up (active, depolarized) and down (silent, hyperpolarized) states. The search for the underlying mechanisms and the possibility of analyzing network dynamics in vitro has been subject of numerous studies. This exposes the need for a detailed quantitative analysis of the membrane fluctuating behavior and computerized tools to automatically characterize the occurrence of up and down states.
Intracellular recordings from different areas of the cerebral cortex were obtained from both in vitro and in vivo preparations during slow oscillations. A method that separates up and down states recorded intracellularly is defined and analyzed here. The method exploits the crossover of moving averages, such that transitions between up and down membrane regimes can be anticipated based on recent and past voltage dynamics. We demonstrate experimentally the utility and performance of this method both offline and online, the online use allowing to trigger stimulation or other events in the desired period of the rhythm. This technique is compared with a histogram-based approach that separates the states by establishing one or two discriminating membrane potential levels. The robustness of the method presented here is tested on data that departs from highly regular alternating up and down states.
We define a simple method to detect cortical states that can be applied in real time for offline processing of large amounts of recorded data on conventional computers. Also, the online detection of up and down states will facilitate the study of cortical dynamics. An open-source MATLAB® toolbox, and Spike 2®-compatible version are made freely available.
The exact timing of cortical afferent activity is instrumental for the correct coding and retrieval of internal and external stimuli. Thalamocortical inputs represent the most significant subcortical pathway to the cortex, but the precise timing and temporal variability of thalamocortical activity is not known. To examine this question, we studied the phase of thalamic action potentials relative to cortical oscillations and established correlations among phase, the nuclear location of the thalamocortical neurons and the frequency of cortical activity.
The phase of thalamic action potentials depended on the exact frequency of the slow cortical oscillation both on long (minutes) and short (single wave) time scales. Faster waves were accompanied by phase advancement in both cases. Thalamocortical neurons located in different nuclei fired at significantly different phases of the slow waves but were active at similar phase of spindle oscillations. Different thalamic nuclei displayed distinct burst patterns. Bursts with higher number of action potentials displayed progressive phase advancement in a nucleus-specific manner. Thalamic neurons located along nuclear borders were characterized by mixed burst and phase properties.
Our data demonstrate that the temporal relationship between cortical and thalamic activity is not fixed but displays dynamic changes during oscillatory activity. The timing depends on the precise location and exact activity of thalamocortical cells and the ongoing cortical network pattern. This variability of thalamic output and its coupling to cortical activity can enable thalamocortical neurons to actively participate in the coding and retrieval of complex cortical signals.
somatosensory; thalamus; oscillator; rhythm; rat; cortex; phase shift
In this review, we summarize three sets of findings that have recently been observed in thalamic astrocytes and neurons, and discuss their significance for thalamocortical loop dynamics. (i) A physiologically relevant 'window' component of the low-voltage-activated, T-type Ca(2+) current (I(Twindow)) plays an essential part in the slow (less than 1 Hz) sleep oscillation in adult thalamocortical (TC) neurons, indicating that the expression of this fundamental sleep rhythm in these neurons is not a simple reflection of cortical network activity. It is also likely that I(Twindow) underlies one of the cellular mechanisms enabling TC neurons to produce burst firing in response to novel sensory stimuli. (ii) Both electrophysiological and dye-injection experiments support the existence of gap junction-mediated coupling among young and adult TC neurons. This finding indicates that electrical coupling-mediated synchronization might be implicated in the high and low frequency oscillatory activities expressed by this type of thalamic neuron. (iii) Spontaneous intracellular Ca(2+) ([Ca(2+)](i)) waves propagating among thalamic astrocytes are able to elicit large and long-lasting N-methyl-D-aspartate-mediated currents in TC neurons. The peculiar developmental profile within the first two postnatal weeks of these astrocytic [Ca(2+)](i) transients and the selective activation of these glutamate receptors point to a role for this astrocyte-to-neuron signalling mechanism in the topographic wiring of the thalamocortical loop. As some of these novel cellular and intracellular properties are not restricted to thalamic astrocytes and neurons, their significance may well apply to (patho)physiological functions of glial and neuronal elements in other brain areas.