A MEG study of sleep

Mean-field based framework for forward modeling of LFP and MEG signals

The use of mean-field models to describe the activity of large neuronal populations has become a very powerful tool for large-scale or whole brain simulations. However, the calculation of brain signals from mean-field models, such as the electric and magnetic fields, is still under development. Thus, the emergence of new methods for an accurate and efficient calculation of such brain signals is currently of great relevance. In this paper we propose a novel method to calculate the local field potentials (LFP) and magnetic fields from mean-field models. The calculation of LFP is done via a kernel method based on unitary LFP's (the LFP generated by a single axon) that was recently introduced for spiking-networks simulations and that we adapt here for mean-field models. The calculation of the magnetic field is based on current-dipole and volume-conductor models, where the secondary currents (due to the conducting extracellular medium) are estimated using the LFP calculated via the kernel method and the effects of medium-inhomogeneities are incorporated. We provide an example of the application of our method for the calculation of LFP and MEG under slow-waves of neuronal activity generated by a mean-field model of a network of Adaptive-Exponential Integrate-and-Fire (AdEx) neurons. We validate our method via comparison with results obtained from the corresponding spiking neuronal networks. Finally we provide an example of our method for whole brain simulations performed with The Virtual Brain (TVB), a recently developed tool for large scale simulations of the brain. Our method provides an efficient way of calculating electric and magnetic fields from mean-field models. This method exhibits a great potential for its application in large-scale or whole-brain simulations, where calculations via detailed biological models are not feasible.

Cortical source localization of sleep-stage specific oscillatory activity

The oscillatory features of non-REM sleep states have been a subject of intense research over many decades. However, a systematic spatial characterization of the spectral features of cortical activity in each sleep state is not available yet. Here, we used magnetoencephalography (MEG) and electroencephalography (EEG) recordings during night sleep. We performed source reconstruction based on the individual subject’s anatomical magnetic resonance imaging (MRI) scans and spectral analysis on each non-REM sleep epoch in eight standard frequency bands, spanning the complete spectrum, and computed cortical source reconstructions of the spectral contrasts between each sleep state in comparison to the resting wakefulness. Despite not distinguishing periods of high and low activity within each sleep stage, our results provide new information about relative overall spectral changes in the non-REM sleep stages.

Broadband Electrophysiological Dynamics Contribute to Global Resting-State fMRI Signal

Spontaneous activity observed with resting-state fMRI is used widely to uncover the brain's intrinsic functional networks in health and disease. Although many networks appear modular and specific, global and nonspecific fMRI fluctuations also exist and both pose a challenge and present an opportunity for characterizing and understanding brain networks. Here, we used a multimodal approach to investigate the neural correlates to the global fMRI signal in the resting state. Like fMRI, resting-state power fluctuations of broadband and arrhythmic, or scale-free, macaque electrocorticography and human magnetoencephalography activity were correlated globally. The power fluctuations of scale-free human electroencephalography (EEG) were coupled with the global component of simultaneously acquired resting-state fMRI, with the global hemodynamic change lagging the broadband spectral change of EEG by ∼5 s. The levels of global and nonspecific fluctuation and synchronization in scale-free population activity also varied across and depended on arousal states. Together, these results suggest that the neural origin of global resting-state fMRI activity is the broadband power fluctuation in scale-free population activity observable with macroscopic electrical or magnetic recordings. Moreover, the global fluctuation in neurophysiological and hemodynamic activity is likely modulated through diffuse neuromodulation pathways that govern arousal states and vigilance levels.

SIGNIFICANCE STATEMENT

This study provides new insights into the neural origin of resting-state fMRI. Results demonstrate that the broadband power fluctuation of scale-free electrophysiology is globally synchronized and directly coupled with the global component of spontaneous fMRI signals, in contrast to modularly synchronized fluctuations in oscillatory neural activity. These findings lead to a new hypothesis that scale-free and oscillatory neural processes account for global and modular patterns of functional connectivity observed with resting-state fMRI, respectively.

Large Scale Cortical Functional Networks Associated with Slow-Wave and Spindle-Burst-Related Spontaneous Activity

Cortical sensory systems are active with rich patterns of activity during sleep and under light anesthesia. Remarkably, this activity shares many characteristics with those present when the awake brain responds to sensory stimuli. We review two specific forms of such activity: slow-wave activity (SWA) in the adult brain and spindle bursts in developing brain. SWA is composed of 0.5-4 Hz resting potential fluctuations. Although these fluctuations synchronize wide regions of cortex, recent large-scale imaging has shown spatial details of their distribution that reflect underlying cortical structural projections and networks. These networks are regulated, as prior awake experiences alter both the spatial and temporal features of SWA in subsequent sleep. Activity patterns of the immature brain, however, are very different from those of the adult. SWA is absent, and the dominant pattern is spindle bursts, intermittent high frequency oscillations superimposed on slower depolarizations within sensory cortices. These bursts are driven by intrinsic brain activity, which act to generate peripheral inputs, for example via limb twitches. They are present within developing sensory cortex before they are mature enough to exhibit directed movements and respond to external stimuli. Like in the adult, these patterns resemble those evoked by sensory stimulation when awake. It is suggested that spindle-burst activity is generated purposefully by the developing nervous system as a proxy for true external stimuli. While the sleep-related functions of both slow-wave and spindle-burst activity may not be entirely clear, they reflect robust regulated phenomena which can engage select wide-spread cortical circuits. These circuits are similar to those activated during sensory processing and volitional events. We highlight these two patterns of brain activity because both are prominent and well-studied forms of spontaneous activity that will yield valuable insights into brain function in the coming years.

Slow-Wave Oscillations in Awake Healthy Subjects: Methodological and Physiological Considerations

PURPOSE

Detection of pathologic slow-wave oscillations (0.5-7 Hz) in awake subjects has gained increasing interest in clinical diagnostics. Their significance, however, is hampered by the occasional presence of slow waves in healthy subjects, as well as the abundance of artefactual signals at low measurement frequencies. The aim of this study was to assess the occurrence of slow-wave oscillations in healthy subjects and to sharpen the management of possible measurement artifacts, in order to create a normative database for neurological patients.

METHODS

The authors analyzed magnetoencephalography recordings of spontaneous brain oscillations in 139 awake healthy adults. Sources of artifacts were first identified and suppressed by temporal extension of signal space separation method, and the remaining artifact components were projected out using signal space projection. Individual amplitude spectra were compared with the channel-level average spectra over all subjects.

RESULTS

Slow-wave oscillations deviating ±2 standard deviations from the average spectrum were detected in 12 subjects (∼9%). In 10 subjects, the oscillations were considered as normal physiological phenomena. Only two subjects showed activity that could have been interpreted as pathological: one subject with widespread parietal bilateral polyrhythmic slow-wave activity and one with focal rolandic 2.7-Hz slow-wave activity.

CONCLUSIONS

The prevalence of slow-wave oscillations in a healthy adult population is low. Knowledge about their occurrence, however, is essential for interpreting their significance in brain diseases. Artifacts and benign oscillatory variants at slow frequencies have to be recognized.

Role for T-type Ca2+ channels in sleep waves

Since their discovery more than 30 years ago, low-threshold T-type Ca(2+) channels (T channels) have been suggested to play a key role in many EEG waves of non-REM sleep, which has remained exclusively linked to the ability of these channels to generate low-threshold Ca(2+) potentials and associated high-frequency bursts of action potentials. Our present understanding of the biophysics and physiology of T channels, however, highlights a much more diverse and complex picture of the pivotal contributions that they make to different sleep rhythms. In particular, recent experimental evidence has conclusively demonstrated the essential contribution of thalamic T channels to the expression of slow waves of natural sleep and the key role played by Ca(2+) entry through these channels in the activation or modulation of other voltage-dependent channels that are important for the generation of both slow waves and sleep spindles. However, the precise contribution to sleep rhythms of T channels in cortical neurons and other sleep-controlling neuronal networks remains unknown, and a full understanding of the cellular and network mechanisms of sleep delta waves is still lacking.

T-type Ca2+ channels in normal and abnormal brain functions

Low-voltage-activated T-type Ca(2+) channels are widely expressed in various types of neurons. Once deinactivated by hyperpolarization, T-type channels are ready to be activated by a small depolarization near the resting membrane potential and, therefore, are optimal for regulating the excitability and electroresponsiveness of neurons under physiological conditions near resting states. Ca(2+) influx through T-type channels engenders low-threshold Ca(2+) spikes, which in turn trigger a burst of action potentials. Low-threshold burst firing has been implicated in the synchronization of the thalamocortical circuit during sleep and in absence seizures. It also has been suggested that T-type channels play an important role in pain signal transmission, based on their abundant expression in pain-processing pathways in peripheral and central neurons. In this review, we will describe studies on the role of T-type Ca(2+) channels in the physiological as well as pathological generation of brain rhythms in sleep, absence epilepsy, and pain signal transmission. Recent advances in studies of T-type channels in the control of cognition will also be briefly discussed.

The thalamic low-threshold Ca²⁺ potential: a key determinant of the local and global dynamics of the slow (<1 Hz) sleep oscillation in thalamocortical networks

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 Ca(2+) 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 Ca(2+) 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.

Large-scale spontaneous fluctuations and correlations in brain electrical activity observed with magnetoencephalography

Knowledge about the intrinsic functional architecture of the human brain has been greatly expanded by the extensive use of resting-state functional magnetic resonance imaging (fMRI). However, the neurophysiological correlates and origins of spontaneous fMRI signal changes remain poorly understood. In the present study, we characterized the power modulations of spontaneous magnetoencephalography (MEG) rhythms recorded from human subjects during wakeful rest (with eyes open and eyes closed) and light sleep. Through spectral, correlation and coherence analyses, we found that resting-state MEG rhythms demonstrated ultraslow (<0.1 Hz) spontaneous power modulations that synchronized over a large spatial distance, especially between bilaterally homologous regions in opposite hemispheres. These observations are in line with the known spatio-temporal properties of spontaneous fMRI signals, and further suggest that the coherent power modulation of spontaneous rhythmic activity reflects the electrophysiological signature of the large-scale functional networks previously observed with fMRI in the resting brain.

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

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

Functional structure of spontaneous sleep slow oscillation activity in humans

Background

During non-rapid eye movement (NREM) sleep synchronous neural oscillations between neural silence (down state) and neural activity (up state) occur. Sleep Slow Oscillations (SSOs) events are their EEG correlates. Each event has an origin site and propagates sweeping the scalp. While recent findings suggest a SSO key role in memory consolidation processes, the structure and the propagation of individual SSO events, as well as their modulation by sleep stages and cortical areas have not been well characterized so far.

Methodology/Principal Findings

We detected SSO events in EEG recordings and we defined and measured a set of features corresponding to both wave shapes and event propagations. We found that a typical SSO shape has a transition to down state, which is steeper than the following transition from down to up state. We show that during SWS SSOs are larger and more locally synchronized, but less likely to propagate across the cortex, compared to NREM stage 2. Also, the detection number of SSOs as well as their amplitudes and slopes, are greatest in the frontal regions. Although derived from a small sample, this characterization provides a preliminary reference about SSO activity in healthy subjects for 32-channel sleep recordings.

Conclusions/Significance

This work gives a quantitative picture of spontaneous SSO activity during NREM sleep: we unveil how SSO features are modulated by sleep stage, site of origin and detection location of the waves. Our measures on SSOs shape indicate that, as in animal models, onsets of silent states are more synchronized than those of neural firing. The differences between sleep stages could be related to the reduction of arousal system activity and to the breakdown of functional connectivity. The frontal SSO prevalence could be related to a greater homeostatic need of the heteromodal association cortices.

Relationships between sleep spindles and activities of cerebral cortex as determined by simultaneous EEG and MEG recording

The purpose of this study was to clarify the relationships between the distributions and cortical sources of two types of spindles in the magnetoencephalogram (MEG) and how cortical activating areas contribute to the distribution of spindles. Spontaneous activities during sleep stage 2 were recorded from 7 normal subjects by simultaneous EEG and MEG recordings. Two types of spindles with frequency-specific topographic differences (fast spindles and slow spindles) were defined by EEG, and, subsequently, the sources of spindles were estimated as equivalent current dipoles using MEG. Activation centered in four areas, the precentral and postcentral areas in posterior frontal cortex and parietal cortex of each hemisphere. However, these areas were not always activated simultaneously. Fast spindles were associated with more frequent activation of postcentral areas with stronger activation strengths, whereas slow spindles were associated with more frequent activation of precentral areas with stronger activation strengths. When spindles were distributed symmetrically in amplitude between the hemispheres on both EEG and MEG, the four areas were activated equally and simultaneously. When spindles exhibited asymmetric distributions with amplitude differences above 30% between hemispheres, the cortical areas were activated with variable temporal relationships. Two types of spindle oscillations observed in the MEG had a common neural basis at the cortical level, with variability in patterns of activation and activation strengths resulting in the differences in distribution observed on the EEG and MEG. The differences in cortical activation patterns and activation strengths between the two types of spindles suggest that two distinct forms of spindle bursts propagate to cortex through different underlying neuronal circuits. Defining the cortical activating areas for spindles by MEG is valuable to consider the underlying neural basis.

[Magnetoencephalography: a method for the study of brain function in neurosurgery]

Magnetoencephalography (MEG) is a non-invasive method for the study of electro-magnetic brain activity. Using multi-channel recordings the topography of the magnetic field can be recorded above the scalp with a temporal resolution of less than one millisecond. The method is suitable for the description and localization of cortical brain functions. The magnetic field strength that can be measured at up to 300 sensors is in the range of a few femto Tesla (10(-15) T) to somepico Tesla (10(-12) T). In order to measure these low magnetic fields highly sensitive SQUID-detectors are used on the one hand. On the other hand appropriate shielding equipment is employed to reduce effects of noise. Besides brain responses evoked by internal and external events (event-related magnetic fields), state-dependant oscillatory brain activity MEG can be recorded (spontaneous activity). Slow cortical oscillations in the range of 1 to 4 Hz are generated by damage of brain tissue and in the surrounding of brain tumors. In neurosurgery these activities can be used to monitor therapeutic success. Furthermore, oscillatory activities provide information about cortical regions involved in motor control. The measurement of motor related activities allows for the identification of recovery processes and reorganization after brain injury. Event-related magnetic brain responses are used in pre-surgical diagnosis and planning of treatment in epilepsy. In addition, they can be utilized to assess alterations in the functional organization of the cortex following injuries, tumor growth and neurosurgical interventions.

Robust off- and online separation of intracellularly recorded up and down cortical states

Background

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.

Methodology/Principal Findings

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.

Conclusions/Significance

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.

Thalamic T-type Ca2+ channels and NREM sleep

T-type Ca2+ channels play a number of different and pivotal roles in almost every type of neuronal oscillation expressed by thalamic neurones during non-rapid eye movement (NREM) sleep, including those underlying sleep theta waves, the K-complex and the slow (<1 Hz) sleep rhythm, sleep spindles and delta waves. In particular, the transient opening of T channels not only gives rise to the 'classical' low threshold Ca2+ potentials, and associated high frequency burst of action potentials, that are characteristically present during sleep spindles and delta waves, but also contributes to the high threshold bursts that underlie the thalamic generation of sleep theta rhythms. The persistent opening of a small fraction of T channels, i.e. I(Twindow), is responsible for the large amplitude and long lasting depolarization, or UP state, of the slow (<1 Hz) sleep oscillation in thalamic neurones. These cellular findings are in part matched by the wake-sleep phenotype of global and thalamic-selective CaV3.1 knockout mice that show a decreased amount of total NREM sleep time. T-type Ca2+ channels, therefore, constitute the single most crucial voltage-dependent conductance that permeates all activities of thalamic neurones during NREM sleep. Since I(Twindow) and high threshold bursts are not restricted to thalamic neurones, the cellular neurophysiology of T channels should now move away from the simplistic, though historically significant, view of these channels as being responsible only for low threshold Ca2+ potentials.

Cerebral Electromagnetic Activity in the Subdelta Range

The frequency range between 0.1 and 0.9 Hz was investigated with magnetoelectroencephalography-EEG coregistration in 10 adult patients with epilepsy and five children with other neurologic conditions. In all instances, a dominant rhythm between 0.2 and 0.4 Hz could be observed in the waking and sleeping states. It showed a waxing and waning quality and was unrelated to eye opening or closing but increased in amplitude during sleep. The maximum was usually in the occipital areas but occasionally in the frontal regions. The rhythm was more persistent and better seen in the magnetoelectroencephalogram, but subdelta activity was also discernible in the EEG. The magnetoelectroencephalographic rhythmicity and frequency suggested possible respiration artifact. Two normal control subjects were therefore investigated by electroencephalography while respirations were monitored. A clear relation to respiration was established. It persisted during breath-holding, albeit at lower amplitude. Larger amplitude transients occurred before and at the cessation of breath-holding as well as hyperventilation. An observed frequency increase before voluntary hyperventilation suggests a relation to the readiness potential and event-related desynchronization as well as synchronization. Subdelta frequencies, which can be readily recorded without special DC amplifiers, provide additional information for clinical as well as research data. They may also be an interface between autonomic and voluntary functions, especially in regard to respiration.

Neuronal basis of the slow (<1 Hz) oscillation in neurons of the nucleus reticularis thalami in vitro

During deep sleep and anesthesia, the EEG of humans and animals exhibits a distinctive slow (<1 Hz) rhythm. In inhibitory neurons of the nucleus reticularis thalami (NRT), this rhythm is reflected as a slow (<1 Hz) oscillation of the membrane potential comprising stereotypical, recurring "up" and "down" states. Here we show that reducing the leak current through the activation of group I metabotropic glutamate receptors (mGluRs) with either trans-ACPD [(+/-)-1-aminocyclopentane-trans-1,3-dicarboxylic acid] (50-100 microM) or DHPG [(S)-3,5-dihydroxyphenylglycine] (100 microM) instates an intrinsic slow oscillation in NRT neurons in vitro that is qualitatively equivalent to that observed in vivo. A slow oscillation could also be evoked by synaptically activating mGluRs on NRT neurons via the tetanic stimulation of corticothalamic fibers. Through a combination of experiments and computational modeling we show that the up state of the slow oscillation is predominantly generated by the "window" component of the T-type Ca2+ current, with an additional supportive role for a Ca2+-activated nonselective cation current. The slow oscillation is also fundamentally reliant on an Ih current and is extensively shaped by both Ca2+- and Na+-activated K+ currents. In combination with previous work in thalamocortical neurons, this study suggests that the thalamus plays an important and active role in shaping the slow (<1 Hz) rhythm during deep sleep.

Grouping of brain rhythms in corticothalamic systems

Different brain rhythms, with both low-frequency and fast-frequency, are grouped within complex wave-sequences. Instead of dissecting various frequency bands of the major oscillations that characterize the brain electrical activity during states of vigilance, it is conceptually more rewarding to analyze their coalescence, which is due to neuronal interactions in corticothalamic systems. This concept of unified brain rhythms does not only include low-frequency sleep oscillations but also fast (beta and gamma) activities that are not exclusively confined to brain-activated states, since they also occur during slow-wave sleep. The major factor behind this coalescence is the cortically generated slow oscillation that, through corticocortical and corticothalamic drives, is effective in grouping other brain rhythms. The experimental evidence for unified oscillations derived from simultaneous intracellular recordings of cortical and thalamic neurons in vivo, while recent studies in humans using global methods provided congruent results of grouping different types of slow and fast oscillatory activities. Far from being epiphenomena, spontaneous brain rhythms have an important role in synaptic plasticity. The role of slow-wave sleep oscillation in consolidating memory traces acquired during wakefulness is being explored in both experimental animals and human subjects. Highly synchronized sleep oscillations may develop into seizures that are generated intracortically and lead to inhibition of thalamocortical neurons, via activation of thalamic reticular neurons, which may explain the obliteration of signals from the external world and unconsciousness during some paroxysmal states.

Evolution of slow-wave sleep and palliopallial connectivity in mammals and birds: a hypothesis

Mammals and birds are the only animals that exhibit rapid eye-movement (REM) sleep and slow-wave sleep (SWS). Whereas the electroencephalogram (EEG) during REM sleep resembles the low-amplitude, high-frequency EEG of wakefulness, the EEG during SWS displays high-amplitude, slow-waves (1-4Hz). The absence of similar slow-waves (SWs) in sleeping reptiles suggests that the neuroanatomical and neurophysiological traits necessary for the genesis of SWs evolved independently in the mammalian and avian ancestors. Advances in our understanding of comparative neuroanatomy and the genesis of mammalian SWs suggest that the absence of SWs in reptiles is due to limited connectivity within the pallium, the dorsal portion of the telencephalon that includes the mammalian neocortex, reptilian dorsal cortex and avian Wulst (hyperpallium), as well as the dorsal ventricular ridge in birds and reptiles and the mammalian claustrum and pallial amygdala. In mammals, the slow oscillation (<1Hz) of cortical neurons acts through reciprocal corticothalamic loops and corticocortical connections to synchronize the 1-4Hz activity of thalamocortical neurons in a manner sufficient to generate SWs detectable in the EEG. Given the role that corticocortical (or palliopallial) connections play in the genesis of SWs in mammals, the degree of palliopallial connectivity might explain why birds show SWs and reptiles do not. Indeed, whereas the mammalian neocortex and avian pallium show extensive palliopallial connectivity, the reptilian pallium exhibits limited intrapallial connections. I thus propose that the evolution of SWs is linked to the independent evolution of extensive palliopallial connectivity in mammals and birds. As suggested by experiments functionally linking SWs to performance enhancements, the palliopallial connections that give rise to SWs might also depend on SWs to maintain their efficacy.

The sleep slow oscillation as a traveling wave

During much of sleep, virtually all cortical neurons undergo a slow oscillation (<1 Hz) in membrane potential, cycling from a hyperpolarized state of silence to a depolarized state of intense firing. This slow oscillation is the fundamental cellular phenomenon that organizes other sleep rhythms such as spindles and slow waves. Using high-density electroencephalogram recordings in humans, we show here that each cycle of the slow oscillation is a traveling wave. Each wave originates at a definite site and travels over the scalp at an estimated speed of 1.2-7.0 m/sec. Waves originate more frequently in prefrontal-orbitofrontal regions and propagate in an anteroposterior direction. Their rate of occurrence increases progressively reaching almost once per second as sleep deepens. The pattern of origin and propagation of sleep slow oscillations is reproducible across nights and subjects and provides a blueprint of cortical excitability and connectivity. The orderly propagation of correlated activity along connected pathways may play a role in spike timing-dependent synaptic plasticity during sleep.

On the rhythmicity of quadratic phase coupling in the tracé alternant EEG in healthy neonates

The time-variant quadratic phase coupling (QPC) in trace alternant (TA) EEG patterns in healthy full-term neonates (quiet sleep) was investigated by means of time-variant bispectral analysis. The frequency plain 1-1.5 Hz <=> 3.5-4.5 Hz was used as the region-of-interest. QPC rhythms with a frequency of approximately 0.1 Hz were found in all neonates (n = 6). It can be demonstrated that the QPC rhythm of the TA is generated by a pattern-spanning time-variant phase-locking process characterising early functional interactions in the immature brain.

The nature of arousal in sleep

The role of arousals in sleep is gaining interest among both basic researchers and clinicians. In the last 20 years increasing evidence shows that arousals are deeply involved in the pathophysiology of sleep disorders. The nature of arousals in sleep is still a matter of debate. According to the conceptual framework of the American Sleep Disorders Association criteria, arousals are a marker of sleep disruption representing a detrimental and harmful feature for sleep. In contrast, our view indicates arousals as elements weaved into the texture of sleep taking part in the regulation of the sleep process. In addition, the concept of micro-arousal (MA) has been extended, incorporating, besides the classical low-voltage fast-rhythm electroencephalographic (EEG) arousals, high-amplitude EEG bursts, be they like delta-like or K-complexes, which reflects a special kind of arousal process, mobilizing parallely antiarousal swings. In physiologic conditions, the slow and fast MA are not randomly scattered but appear structurally distributed within sleep representing state-specific arousal responses. MA preceded by slow waves occurs more frequently across the descending part of sleep cycles and in the first cycles, while the traditional fast type of arousals across the ascending slope of cycles prevails during the last third of sleep. The uniform arousal characteristics of these two types of MAs is supported by the finding that different MAs are associated with an increasing magnitude of vegetative activation ranging hierarchically from the weaker slow EEG types (coupled with mild autonomic activation) to the stronger rapid EEG types (coupled with a vigorous autonomic activation). Finally, it has been ascertained that MA are not isolated events but are basically endowed with a periodic nature expressed in non-rapid eye movement (NREM) sleep by the cyclic alternating pattern (CAP). Understanding the role of arousals and CAP and the relationship between physiologic and pathologic MA can shed light on the adaptive properties of the sleeping brain and provide insight into the pathomechanisms of sleep disturbances. Functional significance of arousal in sleep, and particularly in NREM sleep, is to ensure the reversibility of sleep, without which it would be identical to coma. Arousals may connect the sleeper with the surrounding world maintaining the selection of relevant incoming information and adapting the organism to the dangers and demands of the outer world. In this dynamic perspective, ongoing phasic events carry on the one hand arousal influences and on the other elements of information processing. The other function of arousals is tailoring the more or less stereotyped endogenously determined sleep process driven by chemical influences according to internal and external demands. In this perspective, arousals shape the individual course of night sleep as a variation of the sleep program.

Magnetoencephalography: an investigational tool or a routine clinical technique?

Magnetoencephalography (MEG) is a relatively novel noninvasive technique, with a much shorter history than EEG, that conveys neurophysiological information complementary to that provided by EEG, with high temporal and spatial resolution. Despite its a priori, highly competitive profile, the role of MEG in the clinical setting is still controversial. We briefly review the major obstacles MEG faces in becoming a routine clinical test and the different strategies needed to bypass them. The high cost and complexity associated with MEG equipment are powerful hindrances to wide acceptance of this relatively new technique in clinical practice. The most straightforward advantage is based on the relative facility of MEG recordings in the process of source localization, which also carries some degree of uncertainty, thus partly explaining why the development of clinical applications of MEG has been so slow. Obviously, a decrease in the cost and the elaboration of semiautomatic protocols that could reduce the complexity of the studies and favor the development of consensual strategies, as well as a major effort on the part of clinicians to identify clinical issues where MEG could be decisive, would be most welcome.

Intracortical inhibition and facilitation upon awakening from different sleep stages: a transcranial magnetic stimulation study

Intracortical facilitation and inhibition, as assessed by the paired-pulse transcranial magnetic stimulation technique with a subthreshold conditioning pulse followed by a suprathreshold test pulse, was studied upon awakening from REM and slow-wave sleep (SWS). Ten normal subjects were studied for four consecutive nights. Intracortical facilitation and inhibition were assessed upon awakening from SWS and REM sleep, and during a presleep baseline. Independently of sleep stage at awakening, intracortical inhibition was found at 1-3-ms interstimulus intervals and facilitation at 7-15-ms interstimulus intervals. Motor thresholds were higher in SWS awakenings, with no differences between REM awakenings and wakefulness, while motor evoked potential amplitude to unconditioned stimuli decreased upon REM awakening as compared to the other conditions. REM sleep awakenings showed a significant increase of intracortical facilitation at 10 and 15 ms, while intracortical inhibition was not affected by sleep stage at awakening. While the dissociation between motor thresholds and motor evoked potential amplitudes could be explained by the different excitability of the corticospinal system during SWS and REM sleep, the heightened cortical facilitation upon awakening from REM sleep points to a cortical motor activation during this stage.

Infraslow oscillations modulate excitability and interictal epileptic activity in the human cortex during sleep

Human cortical activity has been intensively examined at frequencies ranging from 0.5 Hz to several hundred Hz. Recent studies have, however, reported also infraslow fluctuations in neuronal population activity, magnitude of electroencephalographic oscillations, discrete sleep events, as well as in the occurrence of interictal events. Here we use direct current electroencephalography to demonstrate large-scale infraslow oscillations in the human cortex at frequencies ranging from 0.02 to 0.2 Hz. These oscillations, which are not detectable in conventional electroencephalography because of its limited recording bandwidth (typical lower limit 0.5 Hz), were observed in widespread cortical regions. Notably, the infraslow oscillations were strongly synchronized with faster activities, as well as with the interictal epileptic events and K complexes. Our findings suggest that the infraslow oscillations represent a slow, cyclic modulation of cortical gross excitability, providing also a putative mechanism for the as yet enigmatic aggravation of epileptic activity during sleep.

Effect of total sleep deprivation on the landmarks of stage 2 sleep

OBJECTIVE

To assess the effects of total sleep deprivation on sleep spindle and K-complex (KC) density.

METHODS

Eight healthy male subjects (mean age=23.4 years) participated in the experiment: they slept in the laboratory for 3 nights (one adaptation, one baseline, one recovery); baseline and recovery night were separated by a period of 40 h of continuous wake.

RESULTS

One night of total sleep deprivation caused a doubling of slow-wave sleep (SWS) amount, an increase of sleep efficiency and a reduction of the latencies of non-rapid eye movement (NREM) sleep stages during the recovery night. These effects were accompanied by a significant reduction in spindle density in the first sleep cycle of the recovery night. Mean KC density did not change as a result of total sleep deprivation, while KC density and inter-KC intervals showed linear trends across the first 4 sleep cycles, respectively decreasing and increasing. Finally, a clear evidence of an antagonist relationship between spindle and KC changes across sleep cycles was provided.

CONCLUSIONS

The present study further supports the existence of a reciprocal relationship between SWS and sleep spindles, but fails to show an increase of KC density after total sleep deprivation. The opposite time courses of spindle and KC density across sleep cycles points to an antagonist relation between the two main phasic events of NREM sleep. The latter result, together with the increase of inter-KC distance and the decrease of KC density across subsequent sleep cycles, is consistent with the hypothesis of a role of the spontaneous KC as the "forerunner" of delta waves.

Acetylcholine systems and rhythmic activities during the waking–sleep cycle

The two processes of activation in thalamocortical systems exerted by mesopontine cholinergic neurons are (a) a direct depolarization associated with increased input resistance of thalamic relay neurons, which is antagonized by muscarinic blockers, and (b) a disinhibition of the same neurons via hyperpolarization of inhibitory thalamic reticular neurons. Low-frequency (< 15 Hz) oscillations during slow-wave sleep, characterized by rhythmic and prolonged hyperpolarizations, are suppressed by brainstem cholinergic neurons and nucleus basalis cholinergic and GABAergic neurons projecting to thalamic reticular neurons. Fast rhythms (20-60 Hz) appear during the sustained depolarization of thalamic and neocortical neurons during brain-active states that are accompanied by increased release of acetylcholine (ACh) in the thalamus and cerebral cortex. Such fast rhythms also occur during the depolarizing phases of the slow oscillation (0.5-1 Hz) in non-REM sleep. Intracellular recordings of neocortical neurons during natural states of waking and sleep demonstrate stable and increased input resistance of corticocortical and corticothalamic neurons during the sustained depolarization in wakefulness, compared to the depolarizing phase of the slow oscillation in non-REM sleep. Despite the highly increased synaptic inputs along different afferent systems that open many conductances of cortical neurons during wakefulness, the increased input resistance is attributed to the effect of acetylcholine on cortical neurons.

Sleep Oscillations Developing into Seizures in Corticothalamic Systems

PURPOSE

The aim of this article is to discuss the neuronal substrates of sleep oscillations leading to seizures consisting of spike-wave (SW) complexes at 2-4 Hz, mimicking those seen in absence epilepsy, or SW and polyspike-wave (PSW) complexes at 1.5-2.5 Hz, often associated with fast runs at 10-15 Hz, as in the Lennox-Gastaut syndrome.

METHODS

Extracellular recordings were done in permanently implanted animals during the natural waking-sleep cycle. Single and dual simultaneous recordings from cortical neurons, cortical and thalamic neurons, or cortical neurons and glial cells were performed in cats under ketamine-xylazine anesthesia.

RESULTS

(a) The minimal substrate of SW seizures is the neocortex because such seizures may occur in thalamectomized animals, in which spindles are absent. In intact-brain animals, SW seizures are initiated in neocortex and spread to the thalamus after a few seconds. The majority of thalamocortical (TC) neurons are steadily hyperpolarized throughout the cortical SW seizures. (b) In the Lennox-Gastaut syndrome, the paroxysmal depolarizing shifts (PDSs) associated with the EEG "spike" of SW/PSW complexes contain an important inhibitory component, whereas the hyperpolarization during the EEG "wave" component is not due to gamma-aminobutryic acid (GABA)ergic inhibitory postsynaptic potentials (IPSPs) but is ascribed to a mixture of disfacilitation and K+ currents. As is also the case with seizures consisting of pure SW complexes, the majority of TC neurons are hyperpolarized during the cortical paroxysms and disinhibited after the cessation of cortical seizures.

CONCLUSIONS

Seizures with SW complexes and of the Lennox-Gastaut type preferentially evolve from sleep oscillations. They are initiated in neocortex and spread to the thalamus after a few seconds. The majority of TC neurons are inhibited during these seizures.

Hyperpolarisation rectification in cat lateral geniculate neurons modulated by intact corticothalamic projections

The intrinsic properties of thalamic neurons are influenced by synaptic activities in ascending pathways and corticofugal projections, as well as by the actions of neurotransmitters released by generalised modulatory systems. We focused on the effects of corticothalamic projections on the hyperpolarisation-activated cation current Ih. Intracellular recordings of thalamocortical neurons in the dorsal lateral geniculate (dLG) nucleus were performed in cats under ketamine-xylazine anaesthesia. At variance with the conventional way of recording intracellularly from thalamic neurons after partial or total ablation of the grey and white matter overlying the dLG, we preserved intact corticothalamic neuronal loops. Stimulating electrodes inserted into the optic tract and light-emitting-diodes as photic stimulation were used to identify the dLG neurons. The expression of the depolarising sag due to Ih depended on the state of cortical networks. Thalamic dLG Ih, induced by hyperpolarising current steps, was detected during the periods of cortical disfacilitation that occur during the cortical slow (< 1 Hz) oscillation, whereas Ih was absent during the active (depolarised) periods. The possibility that the excitatory corticothalamic projections could preclude the generation of the Ih was tested by applying a concentrated K+ solution (3 M) to the primary visual cortex. The same dLG neurons that did not display Ih before application of K+ were able to produce hyperpolarisation-activated depolarising sags during K+-induced cortical depression. Our data suggest that the thalamic clock-like delta oscillation, which results from an interplay between Ih and the low-threshold calcium current (IT), as described in preparations without cerebral cortex, is prevented in dLG neurons when corticothalamic loops are intact.

EEG slow (approximately 1 Hz) waves are associated with nonstationarity of thalamo-cortical sensory processing in the sleeping human

Intracellular studies reveal that, during slow wave sleep (SWS), the entire cortical network can swing rhythmically between extremely different microstates, ranging from wakefulness-like network activation to functional disconnection in the space of a few hundred milliseconds. This alternation of states also involves the thalamic neurons and is reflected in the EEG by a slow (<1 Hz) oscillation. These rhythmic changes, occurring in the thalamo-cortical circuits during SWS, may have relevant, phasic effects on the transmission and processing of sensory information. However, brain reactivity to sensory stimuli, during SWS, has traditionally been studied by means of sequential averaging, a procedure that necessarily masks any short-term fluctuation of responsiveness. The aim of this study was to provide a dynamic evaluation of brain reactivity to sensory stimuli in naturally sleeping humans. To this aim, single-trial somatosensory evoked potentials (SEPs) were grouped and averaged as a function of the phase of the ongoing sleep slow (<1 Hz) oscillation. This procedure revealed a dynamic profile of responsiveness, which was conditioned by the phase of the spontaneous sleep EEG. Overall, the amplitude of the evoked potential changed sistematically, increasing and approaching wakefulness levels along the negative slope of the EEG oscillation and decaying below SWS average levels along the positive drift. These marked and fast changes of stimulus-correlated electrical activity involved both short (N20) and long latency (P60 and P100) components of SEPs. In addition, the observed short-term response variability appeared to be centrally generated and specifically related to the evolution of the spontaneous oscillatory pattern. The present findings demonstrate that thalamo-cortical processing of sensory information is not stationary in the very short period (approximately 500 ms) during natural SWS.

Neuronal plasticity in thalamocortical networks during sleep and waking oscillations

Spontaneous brain oscillations during states of vigilance are associated with neuronal plasticity due to rhythmic spike bursts and spike trains fired by thalamic and neocortical neurons during low-frequency rhythms that characterize slow-wave sleep and fast rhythms occurring during waking and REM sleep. Intracellular recordings from thalamic and related cortical neurons in vivo demonstrate that, during natural slow-wave sleep oscillations or their experimental models, both thalamic and cortical neurons progressively enhance their responsiveness. This potentiation lasts for several minutes after the end of oscillatory periods. Cortical neurons display self-sustained activity, similar to responses evoked during previous epochs of stimulation, despite the fact that thalamic neurons remain under a powerful hyperpolarizing pressure. These data suggest that, far from being a quiescent state during which the cortex and subcortical structures are globally inhibited, slow-wave sleep may consolidate memory traces acquired during wakefulness in corticothalamic networks. Similar phenomena occur as a consequence of fast oscillations during brain-activated states.

Novel neuronal and astrocytic mechanisms in thalamocortical loop dynamics

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.

Physiology of sleep and wakefulness as it relates to the physiology of epilepsy

This paper reviews the present knowledge about the cellular origins of vigilance states (wakefulness and slow-wave sleep) from the perspective of their involvement in the triggering of epileptic seizures. The data stem from intracellular recordings (most of them dual impalements of pairs of neurons and glia), extracellular ionic concentrations (mainly K and Ca ) and simultaneous intracortical field potentials from the cortex of cats. These data were corroborated with recordings from naturally sleeping animals and humans. It is shown that sleep is dominated by a cortically generated slow (<1 Hz) oscillation resulting from the complex interplay within networks of neurons and glia, which are modulated by the more diffuse action of extracellular currents of ions. Wakefulness is produced through the activation of brainstem and basal forebrain structures, which disrupt sleep oscillations and elicit a global change of the extraneuronal milieu, with profound modifications of glial and cerebral blood flow parameters. Paroxysmal events arising during quiet sleep evolve within the cortex from normal slow sleep oscillations. The synchronization of large cortical and eventually subcortical territories relies on the propagation of increased currents of K through the glial syncytium, which compensate for the reduced synaptic efficacy due to the depletion of extracellular Ca.

Source localization of MEG sleep spindles and the relation to sources of alpha band rhythms

OBJECTIVE

First, to determine the distribution of the estimated sources of sleep spindles, and alpha and mu rhythms based on whole-head magnetoencephalogram (MEG) recordings; second, to scrutinize the physiological relevance of the dipole fit algorithm in localizing on-going normal rhythmic activities.

METHODS

One hundred and fifty-one channels were used to record spontaneous MEG activity during wakefulness and superficial sleep in 4 normal subjects. The equivalent dipolar sources were estimated by a new 'dipole fit algorithm' and projected on the corresponding magnetic resonance images.

RESULTS

Equivalent dipoles of MEG spindles were distributed over the centro-parietal region. Those of alpha rhythms were concentrated around the occipito-parietal sulcus and those of mu rhythms were confined to the area around the central sulcus.

CONCLUSIONS

MEG sleep spindles, and alpha and mu rhythms have distinct spatial distributions of their equivalent dipolar sources. This demonstrates that various cortical regions that oscillate within the same frequency band have different spatial organizations and different functional aspects.

EEG source identification: frequency analysis during sleep

This article deals with a new approach in sleep characterization that combines EEG source localisation methods with standard frequency analysis of multielectrode EEGs. First, we describe the theoretical methodology and the benefits that we get from a three-dimensional image (LORETA) of the cerebral activity related to a frequency band. Then, this new application is used as signal-processing technique on sleep EEG recordings obtained from young male adults using four frequency bands (delta 0.5-3.5 Hz, theta 4.0-7.5 Hz, alpha 8.0-12.5 Hz and beta 13.0-32.0 Hz) in different sleep stages. Finally, we show that the obtained results are highly consistent with other physiological assessments (standard EEG mapping, functional magnetic resonance imaging, etc.), but give us more realistic additional information on the generators of electromagnetic cerebral activity.

In vivo electrophysiological evidences for cortical neuron-glia interactions during slow (<1 Hz) and paroxysmal sleep oscillations

The cortical activity results from complex interactions within networks of neurons and glial cells. The dialogue signals consist of neurotransmitters and various ions, which cross through the extracellular space. Slow (<1 Hz) sleep oscillations were first disclosed and investigated at the neuronal level where they consist of an alternation of the membrane potential between a depolarized and a hyperpolarized state. However, neuronal properties alone could not account for the mechanisms underlying the oscillatory nature of the sleeping cortex. Here I will show the behavior of glial cells during the slow sleep oscillation and its relationship with the variation of the neuronal membrane potential (pairs of neurons and glia recorded simultaneously and intracellularly) suggesting that, in contrast with previous assumptions, glial cells are not idle followers of neuronal activity. I will equally present measurements of the extracellular concentration of K(+) and Ca(2+), ions known to modulate the neuronal excitability. They are also part of the ionic flux that is spatially buffered by glial cells. The timing of the spatial buffering during the slow oscillation suggests that, during normal oscillatory activity, K(+) ions are cleared from active spots and released in the near vicinity, where they modulate the excitability of the neuronal membrane and contribute to maintain the depolarizing phase of the oscillation. Ca(2+) ions undergo a periodic variation of their extracellular concentration, which modulates the synaptic efficacy. The depolarizing phase of the slow oscillation is associated with a gradual depletion of the extracellular Ca(2+) promoting a progressive disfacilitation in the network. This functional synaptic neuronal disconnection is responsible for the ending of the depolarizing phase of the slow oscillation and the onset of a phasic hyperpolarization during which the neuronal network is silent and the intra- and extracellular ionic concentrations return to normal values. Spike-wave seizures often develop during sleep from the slow oscillation. Here I will show how the increased gap junction communication substantiates the facility of the glial syncytium to spatially buffer K(+) ions that were uptaken during the spike-wave seizures, and therefore contributing to the long-range recruitment of cortical territories. Similar mechanisms as those described during the slow oscillation promote the periodic (2-3 Hz) recurrence of spike-wave complexes.

The functional significance of K-complexes

This paper summarizes the present knowledge about the cellular bases of the sleep K-complex (KC). The KC has two phases: the initial surface-positive wave is due to the synchronous excitation of cortical neurones, while the subsequent surface-negative wave represents neuronal hyperpolarization. These variations of membrane potential occur within a slow (<1 Hz) oscillation that characterizes all sleep stages. Therefore, KCs are periodic, and their shape and frequency are modulated by the increasing degree of deafferentation attained by the corticothalamic network with the deepening of the sleep. Within this network, the rhythmic KCs recurring at the frequency of the slow oscillation play a leading role by triggering and grouping other sleep oscillations, such as spindles (7-14 Hz) and delta (1-4 Hz). The KC is mainly a spontaneous event generated in cortical networks. During nocturnal epileptic seizures, the KCs are precursors of paroxysmal spike-wave complexes.

Spatial buffering during slow and paroxysmal sleep oscillations in cortical networks of glial cells in vivo

The ability of neuroglia to buffer local increases of extracellular K(+) has been known from in vitro studies. This property may confer on these cells an active role in the modulation and spreading of cortical oscillatory activities. We addressed the question of the spatial buffering in vivo by performing single and double intraglial recordings, together with measures of the extracellular K(+) and Ca(2+) concentrations ([K(+)](out) and [Ca(2+)](out)) in the cerebral cortex of cats under ketamine and xylazine anesthesia during patterns of slow sleep oscillations and spike-wave seizures. In addition, we estimated the fluctuations of intraglial K(+) concentrations ([K(+)](in)). Measurements obtained during the slow oscillation indicated that glial cells phasically take up part of the extracellular K(+) extruded by neurons during the depolarizing phase of the slow oscillation. During this condition, the redistribution of K(+) appeared to be local. Large steady increases of [K(+)](out) and phasic potassium accumulations were measured during spike-wave seizures. In this condition, [K(+)](in) rose before [K(+)](out) if the glial cells were located at some distance from the epileptic focus, suggesting faster K(+) diffusion through the interglial syncytium. The simultaneously recorded [Ca(2+)](out) dropped steadily during the seizures to levels incompatible with efficient synaptic transmission, but also displayed periodic oscillations, in phase with the intraseizure spike-wave complexes. In view of this fact, and considering the capability of K(+) to modulate neuronal excitability both at the presynaptic and postsynaptic levels, we suggest that the K(+) long-range spatial buffering operated by glia is a parallel synchronizing and/or spreading mechanism during paroxysmal oscillations.

The brain decade in debate: VII. Neurobiology of sleep and dreams

This article is a transcription of an electronic symposium held on February 5, 2001 by the Brazilian Society of Neuroscience and Behavior (SBNeC) during which eight specialists involved in clinical and experimental research on sleep and dreaming exposed their personal experience and theoretical points of view concerning these highly polemic subjects. Unlike most other bodily functions, sleep and dreaming cannot, so far, be defined in terms of definitive functions that play an ascribable role in maintaining the organism as a whole. Such difficulties appear quite clearly all along the discussions. In this symposium, concepts on sleep function range from a protective behavior to an essential function for maturation of the nervous system. Kleitman's hypothesis [Journal of Nervous and Mental Disease (1974), 159: 293-294] was discussed, according to which the basal state is not the wakeful state but sleep, from which we awake to eat, to protect ourselves, to procreate, etc. Dreams, on the other hand, were widely discussed, being considered either as an important step in consolidation of learning or simply the conscious identification of functional patterns derived from the configuration of released or revoked memorized information.

Impact of network activities on neuronal properties in corticothalamic systems

Data from in vivo and in vitro experiments are discussed to emphasize that synaptic activities in neocortex and thalamus have a decisive impact on intrinsic neuronal properties in intact-brain preparations under anesthesia and even more so during natural states of vigilance. Thus the firing patterns of cortical neuronal types are not inflexible but may change with the level of membrane potential and during periods rich in synaptic activity. The incidences of some cortical cell classes (defined by their responses to depolarizing current pulses) are different in isolated cortical slabs in vivo or in slices maintained in vitro compared with the intact cortex of naturally awake animals. Network activities, which include the actions of generalized modulatory systems, have a profound influence on the membrane potential, apparent input resistance, and backpropagation of action potentials. The analysis of various oscillatory types leads to the conclusion that in the intact brain, there are no "pure" rhythms, generated in simple circuits, but complex wave sequences (consisting of different, low- and fast-frequency oscillations) that result from synaptic interactions in corticocortical and corticothalamic neuronal loops under the control of activating systems arising in the brain stem core or forebrain structures. As an illustration, it is shown that the neocortex governs the synchronization of network or intrinsically generated oscillations in the thalamus. The rhythmic recurrence of spike bursts and spike trains fired by thalamic and cortical neurons during states of decreased vigilance may lead to plasticity processes in neocortical neurons. If these phenomena, which may contribute to the consolidation of memory traces, are not constrained by inhibitory processes, they induce seizures in which the neocortex initiates the paroxysms and controls their thalamic reflection. The results indicate that intact-brain preparations are necessary to investigate global brain functions such as behavioral states of vigilance and paroxysmal activities.

Magnetoencephalography and magnetic source imaging in children

Magnetoencephalography is a technique that detects the magnetic fields associated with the intracellular current flow within neurons, unlike electroencephalography, which measures extracellular volume currents. Superconducting quantum interference devices are used to amplify these very small magnetic field signals. Magnetic source imaging is the combination of functional data derived from magnetoencephalographic recordings coregistered with structural magnetic resonance imaging (MRI). The utility of magnetic source imaging lies in the combination of the submillisecond temporal resolution of magnetoencephalography with the precise anatomic images provided by magnetic resonance imaging. As such, magnetic source imaging is a useful tool for noninvasive localization of the epileptogenic zone in children who are candidates for epilepsy surgery. Similarly, using magnetoencephalographic recordings with evoked and event-related potentials, magnetic source imaging holds great promise as a noninvasive method for precise localization of somatosensory, motor, language, visual, and auditory cortex. Finally, magnetic source imaging is proving a valuable research tool in the investigation of epilepsy, head trauma, brain plasticity, and disorders of language, memory, cognition, and executive function in children.

Extracellular calcium fluctuations and intracellular potentials in the cortex during the slow sleep oscillation

During slow wave sleep the main activity of cortical neurons consists of synchronous and rhythmic alternations of the membrane potential between depolarized and hyperpolarized values. The latter are long-lasting (200-600 ms) periods of silence. The mechanisms responsible for this periodical interruption of cortical network activity are unknown. Here we report a decrease of approximately 20% in the extracellular calcium concentration ([Ca](out)) progressively taking place in the cortex between the onset and the offset of the depolarizing phase of the slow sleep oscillation. Since [Ca](out) exerts a high gain modulation of synaptic transmission, we estimated the associated transmitter release probability and found a corresponding 50% drop. Thus the periods of silence occurring in the cortical network during slow wave sleep are promoted by recurrent [Ca](out) depletions.

Corticothalamic resonance, states of vigilance and mentation

During various states of vigilance, brain oscillations are grouped together through reciprocal connections between the neocortex and thalamus. The coherent activity in corticothalamic networks, under the control of brainstem and forebrain modulatory systems, requires investigations in intact-brain animals. During behavioral states associated with brain disconnection from the external world, the large-scale synchronization of low-frequency oscillations is accompanied by the inhibition of synaptic transmission through thalamocortical neurons. Despite the coherent oscillatory activity, on the functional side there is dissociation between the thalamus and neocortex during slow-wave sleep. While dorsal thalamic neurons undergo inhibitory processes due to the prolonged spike-bursts of thalamic reticular neurons, the cortex displays, periodically, a rich spontaneous activity and preserves the capacity to process internally generated signals that dominate the state of sleep. In vivo experiments using simultaneous intracellular recordings from thalamic and cortical neurons show that short-term plasticity processes occur after prolonged and rhythmic spike-bursts fired by thalamic and cortical neurons during slow-wave sleep oscillations. This may serve to support resonant phenomena and reorganize corticothalamic circuitry, determine which synaptic modifications, formed during the waking state, are to be consolidated and generate a peculiar kind of dreaming mentation. In contrast to the long-range coherent oscillations that occur at low frequencies during slow-wave sleep, the sustained fast oscillations that characterize alert states are synchronized over restricted territories and are associated with discrete and differentiated patterns of conscious events.

Brain frequency magnetic fields alter cardiac autonomic control mechanisms

OBJECTIVE

Heart rate variability (HRV) is a noninvasive indicator of sympathetic and vagal cardiovascular control known to be tightly correlated with sleep stages. Recent studies indicate that HRV in humans is altered by nocturnal exposure to power-frequency (60 Hz) magnetic fields. Given the central origin of autonomic cardiac control, we determined if field exposure in the beta(1) EEG/MEG frequency range was a more effective stimulus for HRV alteration than 60 Hz fields, and explored the mechanisms involved.

METHODS

Healthy young men were exposed (n=9) overnight to an intermittent magnetic field (16 Hz, 28.3 microTesla, microT), or sham exposed (n=9), under blind test conditions in a laboratory exposure facility.

RESULTS

Field exposure was associated (P<0.05) with reduced power in the low band of the HRV frequency spectrum, and with decreases in mean heart rate. Analysis of the timing of the R waves surrounding each on-off transition of the intermittent field revealed no evidence for a direct effect on the cardiac pacemaker.

CONCLUSIONS

Magnetic field exposure in the EEG/MEG beta(1) frequency range alters HRV via a CNS effect. Phase-resetting experiments rule out a direct effect on the cardiac pacemaker. Biophysical calculations of the intensity of the electric fields induced in brain versus heart under the present exposure conditions are also consistent with and support a central rather than a peripheral site of action.