An increasing number of EEG and resting state fMRI studies in both humans and animals indicate that spontaneous low frequency fluctuations in cerebral activity at <0.1 Hz (infra-slow oscillations, ISOs) represent a fundamental component of brain functioning, being known to correlate with faster neuronal ensemble oscillations, regulate behavioural performance and influence seizure susceptibility. Although these oscillations have been commonly indicated to involve the thalamus their basic cellular mechanisms remain poorly understood. Here we show that various nuclei in the dorsal thalamus in vitro can express a robust ISO at ∼0.005–0.1 Hz that is greatly facilitated by activating metabotropic glutamate receptors (mGluRs) and/or Ach receptors (AchRs). This ISO is a neuronal population phenomenon which modulates faster gap junction (GJ)-dependent network oscillations, and can underlie epileptic activity when AchRs or mGluRs are stimulated excessively. In individual thalamocortical neurons the ISO is primarily shaped by rhythmic, long-lasting hyperpolarizing potentials which reflect the activation of A1 receptors, by ATP-derived adenosine, and subsequent opening of Ba2+-sensitive K+ channels. We argue that this ISO has a likely non-neuronal origin and may contribute to shaping ISOs in the intact brain.
Neural oscillations in the α-band (8-12Hz) are increasingly viewed as an active inhibitory mechanism that gates and controls sensory information processing as a function of cognitive relevance. Extending this view, phase-synchronization of α-oscillations across distant cortical regions could regulate integration of information. Here, we investigated whether such long-range cross-region coupling in the α-band is intrinsically and selectively linked to activity in a distinct functionally specialized brain network. If so, this would provide new insight into the functional role of α-band phase-synchrony. We adapted the phase-locking value (PLV) to assess fluctuations in synchrony that occur over time in ongoing activity. Concurrent electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) were recorded during resting wakefulness in 26 human subjects. Fluctuations in global synchrony in the upper α-band correlated positively with activity in several prefrontal and parietal regions (as measured by fMRI). fMRI intrinsic connectivity analysis confirmed that these regions correspond to the well-known fronto-parietal (FP) network. Spectral correlations with this network’s activity confirmed that no other frequency band showed equivalent results. This selective association supports an intrinsic relation between large-scale α phase-synchrony and cognitive functions associated with the FP network. This network has been suggested to implement phasic aspects of top-down modulation such as initiation and change in moment-to-moment control. Mechanistically, long-range upper α-band synchrony is well-suited to support these functions. Complementing our previous findings that related α-oscillation power to neural structures serving tonic control, the current findings link α phase-synchrony to neural structures underpinning phasic control of alertness and task requirements.
fMRI; EEG; connectivity; alpha; phase; synchrony
Electrical oscillations in neuronal network activity are ubiquitous in the brain and have been associated with cognition and behavior. Intriguingly, the amplitude of ongoing oscillations, such as measured in EEG recordings, fluctuates irregularly, with episodes of high amplitude alternating with episodes of low amplitude. Despite the widespread occurrence of amplitude fluctuations in many frequency bands and brain regions, the mechanisms by which they are generated are poorly understood. Here, we show that irregular transitions between sub-second episodes of high- and low-amplitude oscillations in the alpha/beta frequency band occur in a generic neuronal network model consisting of interconnected inhibitory and excitatory cells that are externally driven by sustained cholinergic input and trains of action potentials that activate excitatory synapses. In the model, we identify the action potential drive onto inhibitory cells, which represents input from other brain areas and is shown to desynchronize network activity, to be crucial for the emergence of amplitude fluctuations. We show that the duration distributions of high-amplitude episodes in the model match those observed in rat prefrontal cortex for oscillations induced by the cholinergic agonist carbachol. Furthermore, the mean duration of high-amplitude episodes varies in a bell-shaped manner with carbachol concentration, just as in mouse hippocampus. Our results suggest that amplitude fluctuations are a general property of oscillatory neuronal networks that can arise through background input from areas external to the network.
Rhythmic changes in electrical activity are observed throughout the brain, and arise as a result of reciprocal interactions between excitatory and inhibitory neurons. Synchronized activity of a large number of neurons gives rise to macroscopic oscillations in electrical activity, which can be measured in EEG recordings and are thought to have a key role in learning and memory. Interestingly, the amplitude of ongoing oscillations fluctuates irregularly, with high-amplitude episodes alternating with low-amplitude episodes. Although these amplitude fluctuations occur in many brain regions, the mechanisms by which they are generated are still poorly known. To get insight into potential mechanisms, we investigated whether such fluctuations occur in a computational model of a neuronal network. We show that the model generates amplitude fluctuations that are similar to those observed in experimental data and that external input from other brain areas to the inhibitory cells of the network is essential for their generation. This input can disrupt the synchrony of activity, causing transitions between episodes of high synchrony (high oscillation amplitudes) and episodes of low synchrony (low oscillation amplitudes). Episodes of high synchrony are relevant for brain function because they provide favorable conditions for learning.
There is increasing interest in the intrinsic activity in the resting brain, especially that of ultraslow and slow oscillations. Using near-infrared spectroscopy (NIRS), electroencephalography (EEG), blood pressure (BP), respiration and heart rate recordings during 5 minutes of rest, combined with cross spectral and sliding cross correlation calculations, we identified a short-lasting coupling (duration s) between prefrontal oxyhemoglobin (HbO2) in the frequency band between 0.07 and 0.13 Hz and central EEG alpha and/or beta power oscillations in 8 of the 9 subjects investigated. The HbO2 peaks preceded the EEG band power peaks by 3.7 s in 6 subjects, with moderate or no coupling between BP and HbO2 oscillations. HbO2 and EEG band power oscillations were approximately in phase with BP oscillations in the 2 subjects with an extremely high coupling (squared coherence ) between BP and HbO2 oscillation. No coupling was identified in one subject. These results indicate that slow precentral (de)oxyhemoglobin concentration oscillations during awake rest can be temporarily coupled with EEG fluctuations in sensorimotor areas and modulate the excitability level in the brains’ motor areas, respectively. Therefore, this provides support for the idea that resting state networks fluctuate with frequencies of between 0.01 and 0.1 Hz (Mantini et.al. PNAS 2007).
Thalamo-cortical networks generate specific patterns of oscillations during distinct vigilance states and epilepsy, well characterized by electroencephalography (EEG). Oscillations depend on recurrent synaptic loops, which are controlled by GABAergic transmission. In particular, GABAA receptors containing the α3 subunit are expressed predominantly in cortical layer VI and thalamic reticular nucleus (nRT) and regulate the activity and firing pattern of neurons in relay nuclei. Therefore, ablation of these receptors by gene targeting might profoundly affect thalamo-cortical oscillations. Here, we investigated the role of α3-GABAA receptors in regulating vigilance states and seizure activity by analyzing chronic EEG recordings in α3 subunit knockout (α3-KO) mice. The presence of postsynaptic α3-GABAA receptors/gephyrin clusters in the nRT and GABAA-mediated synaptic currents in acute thalamic slices were also examined.
EEG spectral analysis showed no difference between genotypes during non rapid-eye movement (NREM) sleep or at waking-NREM sleep transitions. EEG power in the spindle frequency range (10–15 Hz) was significantly lower at NREM-REM sleep transitions in mutant compared to wild-type mice. Enhancement of sleep pressure by 6 h sleep deprivation did not reveal any differences in the regulation of EEG activities between genotypes. Finally, the waking EEG showed a slightly larger power in the 11–13-Hz band in α3-KO mice. However, neither behavior nor the waking EEG showed alterations suggestive of absence seizures. Furthermore, α3-KO mice did not differ in seizure susceptibility in a model of temporal lobe epilepsy. Strikingly, despite the disruption of postsynaptic gephyrin clusters, whole-cell patch clamp recordings revealed intact inhibitory synaptic transmission in the nRT of α3-KO mice. These findings show that the lack of α3-GABAA receptors is extensively compensated for to preserve the integrity of thalamo-cortical function in physiological and pathophysiological situations.
Thalamo-cortical network; EEG rhythms; spectral analysis; gephyrin; spike-wave discharges; sleep deprivation
The present study aimed to investigate how ongoing brain rhythmical oscillations changed during the postoperative pain and whether electroacupuncture (EA) regulated these brain oscillations when it relieved pain. We established a postincisional pain model of rats with plantar incision to mimic the clinical pathological pain state, tested the analgesic effects of EA, and recorded electroencephalography (EEG) activities before and after the EA application. By analysis of power spectrum and bicoherence of EEG, we found that in rats with postincisional pain, ongoing activities at the delta-frequency band decreased, while activities at theta-, alpha-, and beta-frequency bands increased. EA treatment on these postincisional pain rats decreased the power at high-frequency bands especially at the beta-frequency band and reversed the enhancement of the cross-frequency coupling strength between the beta band and low-frequency bands. After searching for the PubMed, our study is the first time to describe that brain oscillations are correlated with the processing of spontaneous pain information in postincisional pain model of rats, and EA could regulate these brain rhythmical frequency oscillations, including the power and cross-frequency couplings.
A key feature of speech is the quasi-regular rhythmic information contained in its slow amplitude modulations. In this article we review the information conveyed by speech rhythm, and the role of ongoing brain oscillations in listeners’ processing of this content. Our starting point is the fact that speech is inherently temporal, and that rhythmic information conveyed by the amplitude envelope contains important markers for place and manner of articulation, segmental information, and speech rate. Behavioral studies demonstrate that amplitude envelope information is relied upon by listeners and plays a key role in speech intelligibility. Extending behavioral findings, data from neuroimaging – particularly electroencephalography (EEG) and magnetoencephalography (MEG) – point to phase locking by ongoing cortical oscillations to low-frequency information (~4–8 Hz) in the speech envelope. This phase modulation effectively encodes a prediction of when important events (such as stressed syllables) are likely to occur, and acts to increase sensitivity to these relevant acoustic cues. We suggest a framework through which such neural entrainment to speech rhythm can explain effects of speech rate on word and segment perception (i.e., that the perception of phonemes and words in connected speech is influenced by preceding speech rate). Neuroanatomically, acoustic amplitude modulations are processed largely bilaterally in auditory cortex, with intelligible speech resulting in differential recruitment of left-hemisphere regions. Notable among these is lateral anterior temporal cortex, which we propose functions in a domain-general fashion to support ongoing memory and integration of meaningful input. Together, the reviewed evidence suggests that low-frequency oscillations in the acoustic speech signal form the foundation of a rhythmic hierarchy supporting spoken language, mirrored by phase-locked oscillations in the human brain.
intelligibility; language; oscillations; phase locking; speech comprehension; speech rate; theta
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 mammalian brain expresses a wide range of state-dependent network oscillations which vary in frequency and spatial extension. Such rhythms can entrain multiple neurons into coherent patterns of activity, consistent with a role in behaviour, cognition and memory formation. Recent evidence suggests that locally generated fast network oscillations can be systematically aligned to long-range slow oscillations. It is likely that such cross-frequency coupling supports specific tasks including behavioural choice and working memory.
We analyzed temporal coupling between high-frequency oscillations and EEG theta activity (4–12 Hz) in recordings from mouse parietal neocortex. Theta was exclusively present during active wakefulness and REM-sleep. Fast oscillations occurred in two separate frequency bands: gamma (40–100 Hz) and fast gamma (120–160 Hz). Theta, gamma and fast gamma were more prominent during active wakefulness as compared to REM-sleep. Coupling between theta and the two types of fast oscillations, however, was more pronounced during REM-sleep. This state-dependent cross-frequency coupling was particularly strong for theta-fast gamma interaction which increased 9-fold during REM as compared to active wakefulness. Theta-gamma coupling increased only by 1.5-fold.
State-dependent cross-frequency-coupling provides a new functional characteristic of REM-sleep and establishes a unique property of neocortical fast gamma oscillations. Interactions between defined patterns of slow and fast network oscillations may serve selective functions in sleep-dependent information processing.
Injection of NMDAR antagonist into the thalamus can produce delta frequency EEG oscillations in the thalamocortical system. It is surprising that an antagonist of an excitatory neurotransmitter should trigger such activity, and the mechanism is unknown. One hypothesis is that the antagonist blocks excitation of GABAergic cells, thus producing disinhibition. To test this hypothesis, we investigated the effect of NMDAR antagonist (APV) on cells of the nucleus reticularis (nRT) in rat brain slices, a thalamic nucleus that can serve as a pacemaker for thalamocortical delta oscillations and that is composed entirely of GABAergic neurons. We found, unexpectedly, that nRT cells are hyperpolarized by APV. This occurs because these cells have an unusual form of NMDAR (probably NR2C) that contributes inward current at resting potential in response to ambient glutamate. The hyperpolarization produced by APV is sufficient to deinactivate T-type calcium channels, and these trigger rhythmic bursting at delta frequency. The APV-induced delta frequency bursting is abolished by dopamine D2 receptor antagonist, indicating that dopamine and NMDAR antagonist work synergistically to stimulate delta frequency bursting. Our results have significant implications concerning the electrophysiological basis of schizophrenia and bring together the NMDAR hypofunction, dopamine, and GABA theories of the disease. Our results suggest that NMDAR hypofunction and dopamine work synergistically on the GABAergic cells of the nRT to generate the delta frequency EEG oscillations, a thalamocortical dysrhythmia (TCD) in the awake state that is an established abnormality in schizophrenia.
resting potential; nucleus reticularis; thalamus; NMDA receptor; burst; delta oscillation; TCD
Progress in the understanding of normal and disturbed brain function is critically dependent on the methodological approach that is applied. Both electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are extremely efficient methods for the assessment of human brain function. The specific appeal of the combination is related to the fact that both methods are complementary in terms of basic aspects: EEG is a direct measurement of neural mass activity and provides high temporal resolution. FMRI is an indirect measurement of neural activity and based on hemodynamic changes, and offers high spatial resolution. Both methods are very sensitive to changes of synaptic activity, suggesting that with simultaneous EEG and fMRI the same neural events can be characterized with both high temporal and spatial resolution. Since neural oscillations that can be assessed with EEG are a key mechanism for multi-site communication in the brain, EEG-fMRI can offer new insights into the connectivity mechanisms of brain networks.
EEG; fMRI; multimodal imaging; neuroimaging; functional magnetic resonance imaging
Infraslow (< 0.1 Hz) oscillations of brain activity, measured by EEG and other methods, have become a subject of increasing interest. While their prominence during sleep has been established, the functional significance of these oscillations for sleep physiology is unknown. To clarify this role, we examined correlations between infraslow EEG oscillations and BOLD fMRI during the course of natural sleep in healthy volunteers. Infraslow EEG oscillations appear to organize a broad dissociation of activity in cortical and subcortical regions: in general, correlations between power in the infraslow EEG band and BOLD were positive in subcortical regions and negative in the cortex. Robust negative correlations were found principally in paramedian heteromodal cortices whereas positive correlations were seen in cerebellum, thalamus, basal ganglia, lateral neocortices and hippocampus. This pattern of correlations suggests a mechanism by which infraslow oscillations may organize sleep-dependent neuroplastic processes including consolidation of episodic memory.
biological rhythms and sleep; cortical oscillations; EEG; fMRI; systems consolidation
Alpha oscillations are ubiquitous in the brain, but their role in cortical processing remains a matter of debate. Recently, evidence has begun to accumulate in support of a role for alpha oscillations in attention selection and control. Here we first review evidence that 8–12 Hz oscillations in the brain have a general inhibitory role in cognitive processing, with an emphasis on their role in visual processing. Then, we summarize the evidence in support of our recent proposal that alpha represents a pulsed-inhibition of ongoing neural activity. The phase of the ongoing electroencephalography can influence evoked activity and subsequent processing, and we propose that alpha exerts its inhibitory role through alternating microstates of inhibition and excitation. Finally, we discuss evidence that this pulsed-inhibition can be entrained to rhythmic stimuli in the environment, such that preferential processing occurs for stimuli at predictable moments. The entrainment of preferential phase may provide a mechanism for temporal attention in the brain. This pulsed inhibitory account of alpha has important implications for many common cognitive phenomena, such as the attentional blink, and seems to indicate that our visual experience may at least some times be coming through in waves.
alpha; oscillation; phase; pulsed-inhibition; EEG
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.
Neocortical local field potentials have shown that gamma oscillations occur spontaneously during slow-wave sleep (SWS). At the macroscopic EEG level in the human brain, no evidences were reported so far. In this study, by using simultaneous scalp and intracranial EEG recordings in 20 epileptic subjects, we examined gamma oscillations in cerebral cortex during SWS. We report that gamma oscillations in low (30–50 Hz) and high (60–120 Hz) frequency bands recurrently emerged in all investigated regions and their amplitudes coincided with specific phases of the cortical slow wave. In most of the cases, multiple oscillatory bursts in different frequency bands from 30 to 120 Hz were correlated with positive peaks of scalp slow waves (“IN-phase” pattern), confirming previous animal findings. In addition, we report another gamma pattern that appears preferentially during the negative phase of the slow wave (“ANTI-phase” pattern). This new pattern presented dominant peaks in the high gamma range and was preferentially expressed in the temporal cortex. Finally, we found that the spatial coherence between cortical sites exhibiting gamma activities was local and fell off quickly when computed between distant sites. Overall, these results provide the first human evidences that gamma oscillations can be observed in macroscopic EEG recordings during sleep. They support the concept that these high-frequency activities might be associated with phasic increases of neural activity during slow oscillations. Such patterned activity in the sleeping brain could play a role in off-line processing of cortical networks.
Slow oscillations are a hallmark of slow wave sleep. They provide a temporal framework for a variety of phasic events to occur and interact during sleep, including the expression of high-frequency oscillations and the discharge of neurons across the entire brain. Evidence shows that the emergence of distinct high-frequency oscillations during slow oscillations facilitates the communication among brain regions whose activity was correlated during the preceding waking period. While the frequencies of oscillations involved in such interactions have been identified, their dynamics and the correlations between them require further investigation. Here we analyzed the structure and dynamics of these signals in anesthetized rats. We show that spindles and gamma oscillations coexist but have distinct temporal dynamics across the slow oscillation cycle. Furthermore, we observed that spindles and gamma are functionally coupled to the slow oscillations and between each other. Following the activation of ascending pathways from the brainstem by means of a carbachol injection in the pedunculopontine nucleus, we were able to modify the gain in the gamma oscillations that are independent of the spindles while the spindle amplitude was reduced. Furthermore, carbachol produced a decoupling of the gamma oscillations that are dependent on the spindles but with no effect on their amplitude. None of the changes in the high-frequency oscillations affected the onset or shape of the slow oscillations, suggesting that slow oscillations occur independently of the phasic events that coexist with them. Our results provide novel insights into the regulation, dynamics and homeostasis of cortical slow oscillations.
Alpha-frequency band (8–14 Hz) oscillations are among the most salient phenomena in human electroencephalography (EEG) recordings and yet their functional roles have remained unclear. Much of research on alpha oscillations in human EEG has focused on peri-stimulus amplitude dynamics, which phenomenologically support an idea of alpha oscillations being negatively correlated with local cortical excitability and having a role in the suppression of task-irrelevant neuronal processing. This kind of an inhibitory role for alpha oscillations is also supported by several functional magnetic resonance imaging and trans-cranial magnetic stimulation studies. Nevertheless, investigations of local and inter-areal alpha phase dynamics suggest that the alpha-frequency band rhythmicity may play a role also in active task-relevant neuronal processing. These data imply that inter-areal alpha phase synchronization could support attentional, executive, and contextual functions. In this review, we outline evidence supporting different views on the roles of alpha oscillations in cortical networks and unresolved issues that should be addressed to resolve or reconcile these apparently contrasting hypotheses.
synchrony; source modeling; alpha; magnetoencephalography; electroencephalography; phase; amplitude
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
Recent experiments in rats have shown the occurrence of a high amplitude slow brain wave in the EEG approximately 1 minute after decapitation, with a duration of 5–15 s (van Rijn et al, PLoS One 6, e16514, 2011) that was presumed to signify the death of brain neurons. We present a computational model of a single neuron and its intra- and extracellular ion concentrations, which shows the physiological mechanism for this observation. The wave is caused by membrane potential oscillations, that occur after the cessation of activity of the sodium-potassium pumps has lead to an excess of extracellular potassium. These oscillations can be described by the Hodgkin-Huxley equations for the sodium and potassium channels, and result in a sudden change in mean membrane voltage. In combination with a high-pass filter, this sudden depolarization leads to a wave in the EEG. We discuss that this process is not necessarily irreversible.
This review summarizes the brain mechanisms controlling sleep and wakefulness. Wakefulness promoting systems cause low-voltage, fast activity in the electroencephalogram (EEG). Multiple interacting neurotransmitter systems in the brain stem, hypothalamus, and basal forebrain converge onto common effector systems in the thalamus and cortex. Sleep results from the inhibition of wake-promoting systems by homeostatic sleep factors such as adenosine and nitric oxide and GABAergic neurons in the preoptic area of the hypothalamus, resulting in large-amplitude, slow EEG oscillations. Local, activity-dependent factors modulate the amplitude and frequency of cortical slow oscillations. Non-rapid-eye-movement (NREM) sleep results in conservation of brain energy and facilitates memory consolidation through the modulation of synaptic weights. Rapid-eye-movement (REM) sleep results from the interaction of brain stem cholinergic, aminergic, and GABAergic neurons which control the activity of glutamatergic reticular formation neurons leading to REM sleep phenomena such as muscle atonia, REMs, dreaming, and cortical activation. Strong activation of limbic regions during REM sleep suggests a role in regulation of emotion. Genetic studies suggest that brain mechanisms controlling waking and NREM sleep are strongly conserved throughout evolution, underscoring their enormous importance for brain function. Sleep disruption interferes with the normal restorative functions of NREM and REM sleep, resulting in disruptions of breathing and cardiovascular function, changes in emotional reactivity, and cognitive impairments in attention, memory, and decision making.
The present study aimed at identifying the neurophysiological responses associated with auditory stimulation during non-rapid eye movement (NREM) sleep using simultaneous electroencephalography (EEG)/functional magnetic resonance imaging (fMRI) recordings. It was reported earlier that auditory stimuli produce bilateral activation in auditory cortex, thalamus, and caudate during both wakefulness and NREM sleep. However, due to the spontaneous membrane potential fluctuations cortical responses may be highly variable during NREM. Here we now examine the modulation of cerebral responses to tones depending on the presence or absence of sleep spindles and the phase of the slow oscillation. Thirteen healthy young subjects were scanned successfully during stage 2–4 NREM sleep in the first half of the night in a 3 T scanner. Subjects were not sleep-deprived and sounds were post hoc classified according to (i) the presence of sleep spindles or (ii) the phase of the slow oscillation during (±300 ms) tone delivery. These detected sounds were then entered as regressors of interest in fMRI analyses. Interestingly wake-like responses – although somewhat altered in size and location – persisted during NREM sleep, except during present spindles (as previously published in Dang-Vu et al., 2011) and the negative going phase of the slow oscillation during which responses became less consistent or even absent. While the phase of the slow oscillation did not alter brain responses in primary sensory cortex, it did modulate responses at higher cortical levels. In addition EEG analyses show a distinct N550 response to tones during the presence of light sleep spindles and suggest that in deep NREM sleep the brain is more responsive during the positive going slope of the slow oscillation. The presence of short temporal windows during which the brain is open to external stimuli is consistent with the fact that even during deep sleep meaningful events can be detected. Altogether, our results emphasize the notion that spontaneous fluctuations of brain activity profoundly modify brain responses to external information across all behavioral states, including deep NREM sleep.
AEP; sleep; spindles; spontaneous activity; slow-wave phase; EEG/fMRI; fMRI; EEG
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.
Although the induction of behavioural unconsciousness during sleep and general anaesthesia has been shown to involve overlapping brain mechanisms, sleep involves cyclic fluctuations between different brain states known as active (paradoxical or rapid eye movement: REM) and quiet (slow-wave or non-REM: nREM) stages whereas commonly used general anaesthetics induce a unitary slow-wave brain state.
Long-duration, multi-site forebrain field recordings were performed in urethane-anaesthetized rats. A spontaneous and rhythmic alternation of brain state between activated and deactivated electroencephalographic (EEG) patterns was observed. Individual states and their transitions resembled the REM/nREM cycle of natural sleep in their EEG components, evolution, and time frame (∼11 minute period). Other physiological variables such as muscular tone, respiration rate, and cardiac frequency also covaried with forebrain state in a manner identical to sleep. The brain mechanisms of state alternations under urethane also closely overlapped those of natural sleep in their sensitivity to cholinergic pharmacological agents and dependence upon activity in the basal forebrain nuclei that are the major source of forebrain acetylcholine. Lastly, stimulation of brainstem regions thought to pace state alternations in sleep transiently disrupted state alternations under urethane.
Our results suggest that urethane promotes a condition of behavioural unconsciousness that closely mimics the full spectrum of natural sleep. The use of urethane anaesthesia as a model system will facilitate mechanistic studies into sleep-like brain states and their alternations. In addition, it could also be exploited as a tool for the discovery of new molecular targets that are designed to promote sleep without compromising state alternations.
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.
Current evidence suggests that delta oscillations (0.5–4 Hz) in the brain are generated by intrinsic network mechanisms involving cortical and thalamic circuits. Here we report that delta band oscillation in spike and local field potential (LFP) activity in the whisker barrel cortex of awake mice is phase locked to respiration. Furthermore, LFP oscillations in the gamma frequency band (30–80 Hz) are amplitude modulated in phase with the respiratory rhythm. Removal of the olfactory bulb eliminates respiration-locked delta oscillations and delta-gamma phase-amplitude coupling. Our findings thus suggest respiration-locked olfactory bulb activity as a main driving force behind delta oscillations and gamma power modulation in the whisker barrel cortex in the awake state.
Oscillatory neuronal activity in the mammalian neocortex is implicated in cognitive processes but its generation is poorly understood. In this study, the authors show that delta band oscillatory activity in mice phase-locks with respiratory activity and that this is mediated by activity in the olfactory bulb.