The sleep slow oscillation as a traveling wave

Excitation of coherent oscillations in a noisy medium

We numerically study the influence of neuronal threshold modulation on the properties of cortical traveling waves. For that reason we simplify a Wilson-Cowan-type integrodifferential equation model of propagating neocortical activity to a spatially discrete version. Further we introduce a noisy threshold. Depending on the noise level we find different states of the network activity, ranging from asynchronous oscillations, traveling waves, to synchronous oscillations. Finally, we induce the transition between these different states by an external modulation.

Projections from basal forebrain to prefrontal cortex comprise cholinergic, GABAergic and glutamatergic inputs to pyramidal cells or interneurons

The present study was undertaken to characterize the pre- and postsynaptic constituents of the basal forebrain (BF) projection to the prefrontal cortex in the rat, and determine whether it includes glutamatergic in addition to established gamma-aminobutyric acid (GABA)ergic and cholinergic elements. BF fibres were labelled by anterograde transport using biotin dextran amine (BDA) and dual-stained for the vesicular transporter proteins (VTPs) for glutamate (VGluT), GABA (VGAT) or acetylcholine (VAChT). Viewed by fluorescence microscopy and estimated by stereology, proportions of BDA-labelled varicosities were found to be stained for VGluT2 (and not VGluT1 or 3), VGAT or VAChT (representing, respectively, approximately 15%, approximately 52% and approximately 19% within the infralimbic cortex). Each type was present in all, though commonly most densely in deep, cortical layers. Material was triple-stained for postsynaptic proteins to examine whether BDA+VTP+ varicosities might form excitatory or inhibitory synapses, respectively, labelled by postsynaptic density-95 kDA (PSD-95) or gephyrin (Geph). Viewed by confocal microscopy, a majority of BDA+/VGluT2+ varicosities were found to be apposed to PSD-95+ elements, and a majority of BDA+/VGAT+ varicosities to be apposed to Geph+ elements. Other series were triple-stained for cell marker proteins to assess whether the varicosities contacted interneurons or pyramidal cells. Viewed by confocal microscopy, BDA-labelled VGluT2+, VGAT+ and VAChT+ BF terminals were all found in contact with calbindin+ interneurons, whereas VGAT+ BF terminals were also seen in contact with parvalbumin+ interneurons and non-phosphorylated neurofilament+ pyramidal cells. Through distinct glutamatergic, GABAergic and cholinergic projections, the BF can thus influence cortical activity in a diverse manner.

Effects of ibotenate and 192IgG-saporin lesions of the nucleus basalis magnocellularis/substantia innominata on spontaneous sleep and wake states and on recovery sleep after sleep deprivation in rats

The basal forebrain (BF) is known for its role in cortical and behavioral activation, and has been postulated to have a role in compensatory mechanisms after sleep loss. However, specific neuronal phenotypes responsible for these roles are unclear. We investigated the effects of ibotenate (IBO) and 192IgG-saporin (SAP) lesions of the caudal BF on spontaneous sleep-waking and electroencephalogram (EEG), and recovery sleep and EEG after 6 h of sleep deprivation (SD). Relative to artificial CSF (ACSF) controls, IBO injections decreased parvalbumin and cholinergic neurons in the caudal BF by 43 and 21%, respectively, and cortical acetylcholinesterase staining by 41%. SAP injections nonsignificantly decreased parvalbumin neurons by 11%, but significantly decreased cholinergic neurons by 69% and cortical acetylcholinesterase by 84%. IBO lesions had no effect on sleep-wake states but increased baseline delta power in all states [up to 62% increase during non-rapid eye movement (NREM) sleep]. SAP lesions transiently increased NREM sleep by 13%, predominantly during the dark phase, with no effect on EEG. During the first 12 h after SD, animals with IBO and SAP lesions showed lesser rebound NREM sleep (32 and 77% less, respectively) and delta power (78 and 53% less) relative to ACSF controls. These results suggest that noncholinergic BF neurons promote cortical activation by inhibiting delta waves, whereas cholinergic BF neurons play a nonexclusive role in promoting wake. Intriguingly, these results also suggest that both types of BF neurons play important roles, probably through different mechanisms, in increased NREM sleep and EEG delta power after sleep loss.

Physiologically based calculation of steady-state evoked potentials and cortical wave velocities

Steady-state evoked potentials (SSEPs) elicited by sinusoidal stimuli are predicted from a physiologically-based model, including bielectrode and volume conduction effects. Comparison with visual SSEPs yields constraints on phase and latency of the retinothalamic transfer function that are consistent with experiment. Predictions of phase velocities measured as SSEPs cross the cortex are consistent with low values measured for slow waves in sleep, while resonant behavior induced by corticothalamic loops, especially near the alpha peak, contributes to wide scatter in waking-state phase velocity measurements comparable to effects from volume conduction. The common use of bielectrode derivations to compensate for volume conduction effects is examined and shown to be incomplete, tending to lead to underestimates of phase velocity, especially at low frequencies and near the alpha peak, due to incorrect elimination of true long-wavelength contributions to the SSEP.

Slow oscillation of membrane currents mediated by glutamatergic inputs of rat somatosensory cortical neurons: in vivo patch-clamp analysis

Using in vivo patch-clamp technique, the slow oscillation of membrane currents was characterized by its synaptic nature, correlation with electroencephalogram (EEG) and responses to different anesthetic agents, in primary somatosensory cortex (SI) neurons in urethane-anesthetized rats. In more than 90% of the SI neurons, the slow oscillation of the inward currents (0.1-2.5 Hz) with the duration of several hundreds of a millisecond was observed at the holding membrane potential of -70 mV. The reversal potential of the inward currents was approximately 0 mV and was suppressed by application of an alpha-amino-3-hydroxy-5-methyl-4-isoxazole propionate (AMPA) receptor antagonist. In most cases (> 90%) the inward current was synchronized with positive wave of the surface EEG recorded from ipsilateral and even contralateral cortical regions. The frequency as well as duration of the slow oscillation decreased by a volatile anesthetic agent, isoflurane (1.5-5.0%), and excitatory postsynaptic currents (EPSCs) were almost abolished at the highest concentration. Intraperitoneal injection of pentobarbital (25 mg/kg) also decreased the frequency of the slow oscillation without affecting short EPSCs. When gamma-aminobutyric acid A (GABA(A)) receptors were activated by local microinjection of muscimol (3 x 10(-3) m, 1-10 microL) into the thalamus, the frequency of the slow oscillation markedly decreased, but was not abolished completely. These findings suggest that the slow oscillation of the inward currents is generated by the summation of glutamatergic EPSCs, and affected by isoflurane and pentobarbital differently. In addition, GABAergic system in the thalamus can affect the frequency, but is not essentially implicated in the genesis of the slow oscillation.

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.

Sleep in the human hippocampus: a stereo-EEG study

BACKGROUND

There is compelling evidence indicating that sleep plays a crucial role in the consolidation of new declarative, hippocampus-dependent memories. Given the increasing interest in the spatiotemporal relationships between cortical and hippocampal activity during sleep, this study aimed to shed more light on the basic features of human sleep in the hippocampus.

METHODOLOGY/PRINCIPAL FINDINGS

We recorded intracerebral stereo-EEG directly from the hippocampus and neocortical sites in five epileptic patients undergoing presurgical evaluations. The time course of classical EEG frequency bands during the first three NREM-REM sleep cycles of the night was evaluated. We found that delta power shows, also in the hippocampus, the progressive decrease across sleep cycles, indicating that a form of homeostatic regulation of delta activity is present also in this subcortical structure. Hippocampal sleep was also characterized by: i) a lower relative power in the slow oscillation range during NREM sleep compared to the scalp EEG; ii) a flattening of the time course of the very low frequencies (up to 1 Hz) across sleep cycles, with relatively high levels of power even during REM sleep; iii) a decrease of power in the beta band during REM sleep, at odds with the typical increase of power in the cortical recordings.

CONCLUSIONS/SIGNIFICANCE

Our data imply that cortical slow oscillation is attenuated in the hippocampal structures during NREM sleep. The most peculiar feature of hippocampal sleep is the increased synchronization of the EEG rhythms during REM periods. This state of resonance may have a supportive role for the processing/consolidation of memory.

Sleep in children with autistic spectrum disorder: a questionnaire and polysomnographic study

OBJECTIVE

To evaluate sleep in children with autistic spectrum disorder (ASD) by means of sleep questionnaires and polysomnography; moreover, to analyze their cyclic alternating pattern (CAP).

METHODS

Thirty-one patients with ASD (28 males, 3 females, aged 3.7-19 years) and age-matched normal controls were included. ASD children were evaluated by a standard sleep questionnaire that consisted of 45 items in a Likert-type scale covering several areas of sleep disorders and by overnight polysomnography in the sleep laboratory after one adaptation night.

RESULTS

The questionnaire results showed that parents of ASD children reported a high prevalence of disorders of initiating and maintaining sleep, enuresis, repetitive behavior when falling asleep, and daytime sleepiness. Polysomnographically, ASD children showed reduced time in bed, total sleep time, sleep period time and rapid eye movement (REM) latency. ASD subjects had a CAP rate during slow-wave sleep (SWS) lower than normal controls, together with a lower percentage of A1 subtypes.

CONCLUSIONS

ASD children questionnaires showed a higher percentage of disorders of initiating and maintaining sleep than normal controls; this was not completely confirmed by sleep staging. CAP measures showed subtle alterations of NREM sleep which could be detected with an appropriate methodology of analysis. The reduction of A1 subtypes during SWS might play a role in the impairment of cognitive functioning in these subjects.

Directional information flows between brain hemispheres during presleep wake and early sleep stages

Neuroscientists' efforts to better understand the underlying processes of human consciousness are growing in a variety of multidisciplinary approaches. Relevant within these are the studies aimed at exploring the physiological substratum of the propagation and reduction of cerebral-namely, corticocortical-communication flows. However, the preferential direction of the information flow between brain hemispheres is as yet largely unknown. It is the aim of the present research to study the communication flows between brain hemispheres, their directionality, and their regional variations across wake-sleep states. A second aim is to investigate the possibility of an association between different brain rhythms and different preferred directions of the information flow. Scalp electroencephalograms (EEGs) were recorded in 10 normal volunteers from wakefulness to early sleep stages (viz., resting wakefulness, sleep stages 2 and 4, and rapid eye movement [REM] of the first sleep cycle). EEG rhythms of interest were delta (1-4 Hz), theta (5-7 Hz), alpha (8-11 Hz), sigma (12-15 Hz), and beta (16-30 Hz). The direction of the interhemispheric information flow was evaluated by computing directed transformation function from these EEG rhythms. Interhemispheric directional flows varied as a function of the state of consciousness (wake and early sleep stages) and in relation to different cerebral areas. Across wake to sleep states, we found that delta and beta rhythms convey interhemispheric signals with opposite directions: preferred right to left hemisphere direction for delta and left to right for beta rhythms. A log correlation confirmed that the trend of low to high EEG frequencies-traditionally associated with an increasing state of vigilance-was significantly related to the direction of the communication flow from the left to right hemisphere. This evidence might open the way for a variety of research lines on different psychophysiological and pathological conditions.

The contribution of apolipoprotein E alleles on cognitive performance and dynamic neural activity over six decades

Neuroimaging shows brain-functional differences due to apolipoprotein E (APOE) polymorphisms may exist decades before the increased risk period for Alzheimer's disease, but little is known about their effect on cognition and brain function in children and young adults. This study assessed 415 healthy epsilon2 and epsilon4 carriers and matched epsilon3/epsilon3 controls, spanning ages 6-65, on a range of cognitive tests. Subjects were also compared on a new dynamical measure of EEG activity during a visual working memory task using alphabetical stimuli. epsilon4 subjects had better verbal fluency compared to epsilon3, an effect that was strongest in 51-65 year-olds. No epsilon4 deficits in cognition were found. In 6-15 year-olds, there were differences in total spatio-temporal wave activity between epsilon3 and epsilon4 subjects in the theta band, approximately 200ms post-stimulus. Differences in brain function in younger epsilon4 subjects and superior verbal fluency across the entire age range suggest that the APOE epsilon4 allele is an example of antagonistic pleiotropy.

Development and plasticity of spontaneous activity and Up states in cortical organotypic slices

Cortical computations are an emergent property of neural dynamics. To understand how neural dynamics emerges within local cortical networks, we characterized the development and underlying mechanisms of spontaneous dynamics in cortical organotypic slices. We observed not only a quantitative increase in the levels of spontaneous dynamics, but a qualitative transition from brief bursts of activity to well defined Up states during the first 4 weeks in vitro. Analysis of cellular and synaptic properties indicates that these changes are driven by increasing excitatory drive accompanied by changes in the balance of excitation and inhibition. Examination of the structure of spontaneous dynamics revealed no evidence of precisely repeating patterns. Slices exposed to chronic patterned stimulation exhibited decreased levels of spontaneous activity, suggesting homeostatic control of the levels of network activity. Together, these results suggest that Up states reflect a fundamental mode of network dynamics that emerges through the orchestrated regulation of multiple cellular and synaptic properties in parallel.

Triggering sleep slow waves by transcranial magnetic stimulation

During much of sleep, cortical neurons undergo near-synchronous slow oscillation cycles in membrane potential, which give rise to the largest spontaneous waves observed in the normal electroencephalogram (EEG). Slow oscillations underlie characteristic features of the sleep EEG, such as slow waves and spindles. Here we show that, in sleeping subjects, slow waves and spindles can be triggered noninvasively and reliably by transcranial magnetic stimulation (TMS). With appropriate stimulation parameters, each TMS pulse at <1 Hz evokes an individual, high-amplitude slow wave that originates under the coil and spreads over the cortex. TMS triggering of slow waves reveals intrinsic bistability in thalamocortical networks during non-rapid eye movement sleep. Moreover, evoked slow waves lead to a deepening of sleep and to an increase in EEG slow-wave activity (0.5-4.5 Hz), which is thought to play a role in brain restoration and memory consolidation.

Enhancement of visual responsiveness by spontaneous local network activity in vivo

Spontaneous activity within local circuits affects the integrative properties of neurons and networks. We have previously shown that neocortical network activity exhibits a balance between excitatory and inhibitory synaptic potentials, and such activity has significant effects on synaptic transmission, action potential generation, and spike timing. However, whether such activity facilitates or reduces sensory responses has yet to be clearly determined. We examined this hypothesis in the primary visual cortex in vivo during slow oscillations in ketamine-xylazine anesthetized cats. We measured network activity (Up states) with extracellular recording, while simultaneously recording postsynaptic potentials (PSPs) and action potentials in nearby cells. Stimulating the receptive field revealed that spiking responses of both simple and complex cells were significantly enhanced (>2-fold) during network activity, as were spiking responses to intracellular injection of varying amplitude artificial conductance stimuli. Visually evoked PSPs were not significantly different in amplitude during network activity or quiescence; instead, spontaneous depolarization caused by network activity brought these evoked PSPs closer to firing threshold. Further examination revealed that visual responsiveness was gradually enhanced by progressive membrane potential depolarization. These spontaneous depolarizations enhanced responsiveness to stimuli of varying contrasts, resulting in an upward (multiplicative) scaling of the contrast response function. Our results suggest that small increases in ongoing balanced network activity that result in depolarization may provide a rapid and generalized mechanism to control the responsiveness (gain) of cortical neurons, such as occurs during shifts in spatial attention.

Computing the center of mass for traveling alpha waves in the human brain

The phenomenon of traveling waves of the brain is an intriguing area of research, and its mechanisms and neurobiological bases have been unknown since the 1950s. The present study offers a new method to compute traveling alpha waves using the center of mass algorithm. Electroencephalographic alpha waves are oscillations with a characteristic frequency range and reactivity to closed eyes. Several lines of evidence derived from qualitative observations suggest that the alpha waves represent a spreading wave process with specific trajectories in the human brain. We found that during a certain alpha wave peak recorded with 30 electrodes the trajectory starts and ends in distinct regions of the brain, mostly frontal-occipital, frontal-frontal, or occipital-frontal, but the position of the trajectory at the time in which the maximal positivity of the alpha wave occurs has a definite position near the central regions. Thus we observed that the trajectory always crossed around the central zones, traveling from one region to another region of the brain. A similar trajectory pattern was observed for different alpha wave peaks in one alpha burst, and in different subjects, with a mean velocity of 2.1+/-0.29 m/s. We found that all our results were clear and reproducible in all of the subjects. To our knowledge, the present method documents the first explicit description of a spreading wave process with a singular pattern in the human brain in terms of the center of mass algorithm.

Small-world network organization of functional connectivity of EEG slow-wave activity during sleep

OBJECTIVE

To analyze the functional connectivity patterns of the EEG slow-wave activity during the different sleep stages and Cyclic Alternating Pattern (CAP) conditions, using concepts derived from Graph Theory.

METHODS

We evaluated spatial patterns of EEG slow-wave synchronization between all possible pairs of electrodes (19) placed over the scalp of 10 sleeping healthy young normal subjects using two graph theoretical measures: the clustering coefficient (Cp) and the characteristic path length (Lp). The measures were obtained during the different sleep stages and CAP conditions from the real EEG connectivity networks and randomized control (surrogate) networks (Cp-s and Lp-s).

RESULTS

Cp and Cp/Cp-s increased significantly from wakefulness to sleep while Lp and Lp/Lp-s did not show changes. Cp/Cp-s was higher for A1 phases, compared to B phases of CAP.

CONCLUSIONS

The network organization of the EEG slow-wave synchronization during sleep shows features characteristic of small-world networks (high Cp combined with low Lp); this type of organization is slightly but significantly more evident during the CAP A1 subtypes.

SIGNIFICANCE

Our results show feasibility of using graph theoretical measures to characterize the complexity of brain networks during sleep and might indicate sleep, and the A1 phases of CAP in particular, as a period during which slow-wave synchronization shows optimal network organization for information processing.

Sleepy dialogues between cortex and hippocampus: who talks to whom?

During NREM sleep, neocortical neurons undergo near-synchronous transitions, every second or so, between UP states, during which they are depolarized and fire actively, and DOWN states, during which they are hyperpolarized and completely silent. In this issue of Neuron, Isomura et al. report that slow oscillations of membrane potential occur near-synchronously not only in neocortex but also in entorhinal cortex and subiculum. Within the hippocampus proper, pyramidal neurons lack the bistability of UP and DOWN states, but their firing is strongly modulated by cortical activity during the UP state. Intriguingly, many hippocampal neurons fire during the cortical DOWN state. Thus, during sleep UP states, the cortex can talk to the hippocampus, but it is unclear whether the hippocampus talks back.

Sequential structure of neocortical spontaneous activity in vivo

Even in the absence of sensory stimulation, the neocortex shows complex spontaneous activity patterns, often consisting of alternating "DOWN" states of generalized neural silence and "UP" states of massive, persistent network activity. To investigate how this spontaneous activity propagates through neuronal assemblies in vivo, we simultaneously recorded populations of 50-200 cortical neurons in layer V of anesthetized and awake rats. Each neuron displayed a virtually unique spike pattern during UP states, with diversity seen amongst both putative pyramidal cells and interneurons, reflecting a complex but stereotypically organized sequential spread of activation through local cortical networks. Spike timing was most precise during the first approximately 100 ms after UP state onset, and decayed as UP states progressed. A subset of UP states propagated as traveling waves, but waves passing a given point in either direction initiated similar local sequences, suggesting local networks as the substrate of sequential firing patterns. A search for repeating motifs indicated that their occurrence and structure was predictable from neurons' individual latencies to UP state onset. We suggest that these stereotyped patterns arise from the interplay of intrinsic cellular conductances and local circuit properties.

Integration and Segregation of Activity in Entorhinal-Hippocampal Subregions by Neocortical Slow Oscillations

Brain systems communicate by means of neuronal oscillations at multiple temporal and spatial scales. In anesthetized rats, we find that neocortical "slow" oscillation engages neurons in prefrontal, somatosensory, entorhinal, and subicular cortices into synchronous transitions between UP and DOWN states, with a corresponding bimodal distribution of their membrane potential. The membrane potential of hippocampal granule cells and CA3 and CA1 pyramidal cells lacked bimodality, yet it was influenced by the slow oscillation in a region-specific manner. Furthermore, in both anesthetized and naturally sleeping rats, the cortical UP states resulted in increased activity of dentate and most CA1 neurons, as well as the highest probability of ripple events. Yet, the CA3-CA1 network could self-organize into gamma bursts and occasional ripples during the DOWN state. Thus, neo/paleocortical and hippocampal networks periodically reset, self-organize, and temporally coordinate their cell assemblies via the slow oscillation.

A theoretical basis for standing and traveling brain waves measured with human EEG with implications for an integrated consciousness

OBJECTIVE

We propose a theoretical framework for EEG and evoked potential studies based on the single postulate that these data are composed of a combination of waves (as this term is used in the physical sciences) and thalamocortical network activity.

METHODS

Using known properties of traveling and standing waves, independent of any neocortical dynamic theory, our simple postulate leads to experimental predictions, several of which have now been verified. A mathematical-physiological theory of "brain waves" based on known (but highly idealized) properties of cortical synaptic action and corticocortical fibers is used to support the framework.

RESULTS

Brain waves are predicted with links between temporal frequencies and the spatial distributions of synaptic activity. Such dispersion relations, which essentially define more general phenomena as waves, are shown to restrict the spatial-temporal dynamics of synaptic action with many experimental EEG consequences.

CONCLUSIONS

The proposed framework accounts for several salient features of spontaneous EEG and evoked potentials.

SIGNIFICANCE

We conjecture that wave-like behavior of synaptic action may facilitate interactions between remote cell assemblies, providing an important mechanism for the functional integration underlying conscious experience.

Sleep to remember

Recently, compelling evidence has accumulated that links sleep to learning and memory. Sleep has been identified as a state that optimizes the consolidation of newly acquired information in memory. Consolidation is an active process that is presumed to rely on the covert reactivation and reorganization of newly encoded representations. Hippocampus-dependent memories benefit primarily from slow-wave sleep (SWS), whereas memories not depending on the hippocampus show greater gains over periods containing high amounts of rapid eye movement sleep. One way sleep does this is by establishing different patterns of neurotransmitters and neurohormone secretion between sleep stages. Another central role for consolidating memories is played by the slow oscillation, that is, the oscillating field potential change dominating SWS. The emergence of slow oscillations in neocortical networks depends on the prior use of these networks for encoding of information. Via efferent pathways, they synchronize the occurrence of sharp wave ripples accompanying memory reactivations in the hippocampus with thalamocortical spindle activity. Thus, hippocampal memories are fed back into neocortical networks at a time when these networks are depolarized and, because of concurrent spindle activity, can most sensitively react to these inputs with plastic changes underlying the formation of long-term memory representations.

Adenosinergic mechanisms contribute to individual differences in sleep deprivation-induced changes in neurobehavioral function and brain rhythmic activity

Large individual differences characterize the changes induced by sleep deprivation on neurobehavioral functions and rhythmic brain activity. To investigate adenosinergic mechanisms in these differences, we studied the effects of prolonged waking and the adenosine receptor antagonist caffeine on sustained vigilant attention and regional electroencephalogram (EEG) power in the ranges of theta activity (6.25-8.25 Hz) in waking and the slow oscillation (<1 Hz) in sleep. Activity in these frequencies is functionally related to sleep deprivation. In 12 subjectively caffeine-sensitive and 10 -insensitive young men, psychomotor vigilance task (PVT) performance and EEG were assessed at 3 h intervals before, during, and after one night without sleep. After 11 and 23 h waking, subjects received 200 mg caffeine and placebo in double-blind, cross-over manner. In the placebo condition, sleep deprivation impaired PVT speed more in caffeine-sensitive than in caffeine-insensitive men. This difference was counteracted by caffeine. Theta power in waking increased more in a frontal EEG derivation than in a posterior derivation. Caffeine attenuated this power gradient in caffeine sensitive subjects. Sleep loss also differently affected the power distribution <1 Hz in non-rapid eye movement sleep between caffeine sensitive and insensitive subjects. Also, this difference was mirrored by the action of caffeine. The effects of sleep deprivation and caffeine on sustained attention and regional EEG power in waking and sleep were inversely related. These findings suggest that adenosinergic mechanisms contribute to individual differences in waking-induced impairment of neurobehavioral performance and functional aspects of EEG topography associated with sleep deprivation.

Regional scalp EEG slow-wave synchronization during sleep cyclic alternating pattern A1 subtypes

The levels of EEG synchronization, in the 0.25-2.5 Hz band, during the A1 subtypes of the sleep "cyclic alternating pattern" (CAP) were measured in five healthy subjects by means of the synchronization likelihood (SL) algorithm. SL was measured for seven electrode pairs (F4-F3, C4-C3, P4-P3 for the analysis of interhemispheric SL and F4-C4, C4-P4, F3-C3, and C3-P3, for the analysis of intrahemispheric SL). During the A1 CAP subtypes, SL tended to be highest between pairs of electrodes situated over different hemispheres; in particular, SL obtained from F4-F3 was the highest, followed by that of P4-P3. These results indicate that the transient high level of synchronization in the slow-wave EEG range, during the sleep A1 CAP subtypes, is a phenomenon involving mostly the anterior parts of the brain and is probably based on interhemispheric interactions, possibly mediated by transcallosal connections.

Measurement of phase gradients in the EEG

Previous research has shown that spatio-temporal waves in the EEG are generally of long spatial wavelength and form smooth patterns of phase gradients at particular time-samples. This paper describes a method to measure smooth phase gradients of long spatial wavelength in the EEG. The method depends on the global pattern of phase at a given frequency and time and is therefore robust to variations, over time, in phase-lag between particular sites. Phases were estimated in the EEG signal using wavelet or short time-series Fourier methods. During an auditory oddball task, phases across the scalp tend to fall within a limited circular range, a range that is not indicative of phase-synchrony nor waves with multiple periods. At times the phases tended to maintain a spatially and temporally ordered relationship. The relative phases were analysed using three phase gradient basis functions, providing a measure of the amount of variance explained, across the electrodes, by smooth changes in relative phase from a single minimum or single maximum. The data from 586 adult subjects were analysed and it was found that the probability of phase gradient events varies with time and frequency in the stimulus-locked average, and with task demands. The temporal extent of spatio-temporal waves was measured by detecting smoothly changing patterns of phase latencies across the scalp. The specific spatial pattern and timing of phase gradients correspond closely to the latency distributions of certain ERPs.

Fine spatiotemporal structure of phase in human intracranial EEG

OBJECTIVE

To transfer to the clinic for humans the technology and theory for high-resolution EEG analysis that have been developed in the laboratory with animals.

METHODS

EEGs were recorded at high spatial resolution from a 1 x 1 cm 8 x 8 electrode array on the right inferior temporal gyrus of a patient undergoing preoperative monitoring for epilepsy surgery. Cosines were fitted to EEG segments to measure frequency and phase and compute location, size, latency, phase velocity, duration, and recurrence rate of radially symmetric spatial patterns called phase cones. The Hilbert transform was also used to get high temporal resolution.

RESULTS

In the awake state, the power spectral density (PSD) showed power-law decrease in log power with log frequency at 1/falpha, alpha approximately 2, but with peaks in the standard empirical ranges. The phase in beta and gamma ranges had spatial gradients in conic form. Resetting of these stable spatial patterns of phase cones was spatially coincident at intermittent discontinuities ('phase slip') recurring at theta rates. Cones had half power diameters from 2 to 50+ mm; their durations had power-law distributions with values ranging from 6 to 300+ ms depending on length of the analysis window. In slow wave sleep PSD decreased at 1/falpha, alpha approximately 3,with loss of beta-gamma spectral peaks and diminished or absent oscillations and spatiotemporal phase structure.

CONCLUSIONS

Spatiotemporal structures in awake human and rabbit EEG showed striking similarities. The only clear differences were ascribable to differing scales of measurement. These fine spatiotemporal structures of EEG were diminished or lost in slow wave sleep.

SIGNIFICANCE

The fine structure indicates that neocortical stability is sustained at self-organized criticality; that synaptic input in the awake state drives neocortex away from criticality causing beta-gamma oscillations in re-stabilizing 'neural avalanches'; and that diminished input in slow wave sleep allows return toward criticality but with some added risk of instability and seizure.

The K-complex and slow oscillation in terms of a mean-field cortical model

We use a mean-field macrocolumn model of the cerebral cortex to offer an interpretation of the K-complex of the electroencephalogram to complement those of more detailed neuron-by-neuron models. We interpret the K-complex as a momentary excursion of the cortex from a stable low-firing state to an unstable high-firing state, and hypothesize that the related slow oscillation can be considered as the periodic oscillation between two meta-stable solutions of the mean-field model. By incorporating a Hebbian-style learning rule that links the growth in synapse strength to fluctuations in soma potential, we demonstrate a self-organization behaviour that draws the modelled cortex close to the edge of stability of the low-firing state. Furthermore, a very slow oscillation can occur in the excitability of the cortex that has similarities with the infra-slow oscillation of sleep.

Imaging human EEG dynamics using independent component analysis

This review discusses the theory and practical application of independent component analysis (ICA) to multi-channel EEG data. We use examples from an audiovisual attention-shifting task performed by young and old subjects to illustrate the power of ICA to resolve subtle differences between evoked responses in the two age groups. Preliminary analysis of these data using ICA suggests a loss of task specificity in independent component (IC) processes in frontal and somatomotor cortex during post-response periods in older as compared to younger subjects, trends not detected during examination of scalp-channel event-related potential (ERP) averages. We discuss possible approaches to component clustering across subjects and new ways to visualize mean and trial-by-trial variations in the data, including ERP-image plots of dynamics within and across trials as well as plots of event-related spectral perturbations in component power, phase locking, and coherence. We believe that widespread application of these and related analysis methods should bring EEG once again to the forefront of brain imaging, merging its high time and frequency resolution with enhanced cm-scale spatial resolution of its cortical sources.

Slow-waves in the olfactory system: an olfactory perspective on cortical rhythms

Over the past few years, it has become clear that oscillatory dynamics of cortical networks are closely involved in sensory coding, attention, memory and sleep. Although most experimental and theoretical studies have focused on the neocortex, we believe that progress in understanding cortical oscillations can be advanced by also considering the olfactory system--which shares many basic properties with the neocortex and shows similar oscillatory patterns. Besides offering the advantage of a greater experimental tractability, the olfactory cortex might prove to be instrumental in uncovering general functional principles of neocortical oscillations, by virtue of the potentially important role of olfaction during neocortical evolution. In this article, we illustrate how such an evolution-based comparative approach can provide novel insights into neocortical slow-wave sleep oscillations and their relationship to respiration.

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.

Hippocampal Sharp Wave-Ripples Linked to Slow Oscillations in Rat Slow-Wave Sleep

Slow oscillations originating in the prefrontal neocortex during slow-wave sleep (SWS) group neuronal network activity and thereby presumably support the consolidation of memories. Here, we investigated whether the grouping influence of slow oscillations extends to hippocampal sharp wave-ripple (SPW) activity thought to underlie memory replay processes during SWS. The prefrontal surface EEG and multiunit activity (MUA), along with hippocampal local field potentials (LFP) from CA1, were recorded in rats during sleep. Average spindle and ripple activity and event correlation histograms of SPWs were calculated, time-locked to half-waves of slow oscillations. Results confirm decreased prefrontal MUA and spindle activity during EEG slow oscillation negativity and increases in this activity during subsequent positivity. A remarkably close temporal link was revealed between slow oscillations and hippocampal activity, with ripple activity and SPWs being also distinctly decreased during negative half-waves and increased during slow oscillation positivity. Fine-grained analyses of temporal dynamics revealed for the slow oscillation a phase delay of approximately 90 ms with reference to up and down states of prefrontal MUA, and of only approximately 60 ms with reference to changes in SPWs, indicating that up and down states in prefrontal MUA precede corresponding changes in hippocampal SPWs by approximately 30 ms. Results support the notion that the depolarizing surface-positive phase of the slow oscillation and the associated up state of prefrontal excitation promotes hippocampal SPWs via efferent pathways. The preceding disfacilitation of hippocampal events temporally coupled to the negative slow oscillation half-wave appears to serve a synchronizing role in this neocorticohippocampal interplay.

Precise long-range synchronization of activity and silence in neocortical neurons during slow-wave oscillations [corrected]

Slow-wave sleep is characterized by alternating periods of activity and silence in corticothalamic networks. Both activity and silence are stable network states, but the mechanisms of their alternation remain unknown. We show, using simultaneous multisite intracellular recordings in cats, that slow rhythm involves all neocortical neurons and that both activity and silence started almost synchronously in cells located up to 12 mm apart. Activity appeared predominantly at the area 5/7 border and spread in both anterior and posterior directions. The activity started earlier in fast-spiking cells and intrinsically bursting cells than in regular-spiking neurons. These results provide direct evidence for two mechanisms of active state generation: spread of activity from a local focus and synchronization of weaker activity, originating at multiple locations. Surprisingly, onsets of silent states were synchronized even more precisely than the onsets of activity, showing no latency bias for location or cell type. This most intriguing finding exposes a major gap in understanding the nature of state alternation. We suggest that it is the synchronous termination of activity and occurrence of silent states of the neuronal network that makes the EEG picture during slow-wave sleep so characteristic. Synchronous onset of silence in distant neurons cannot rely exclusively on properties of individual cells and synapses, such as adaptation of neuronal firing or synaptic depression; instead, it implies the existence of a network mechanism. Revealing this yet unknown large-scale mechanism, which switches network activity to silence, will aid our understanding of the origin of brain rhythms in normal function and pathology.

Large-amplitude, spatially correlated fluctuations in BOLD fMRI signals during extended rest and early sleep stages

A number of recent studies of human brain activity using blood-oxygen-level-dependent (BOLD) fMRI and EEG have reported the presence of spatiotemporal patterns of correlated activity in the absence of external stimuli. Although these patterns have been hypothesized to contain important information about brain architecture, little is known about their origin or about their relationship to active cognitive processes such as conscious awareness and monitoring of the environment. In this study, we have investigated the amplitude and spatiotemporal characteristics of resting-state activity patterns and their dependence on the subjects' alertness. For this purpose, BOLD fMRI was performed at 3.0 T on 12 normal subjects using a visual stimulation protocol, followed by a 27 min rest period, during which subjects were allowed to fall asleep. In subjects who were asleep at the end of the scan, we found (a) a higher amplitude of BOLD signal fluctuation during rest compared with subjects who were awake at the end of the scan; (b) spatially independent patterns of correlated activity that involve all of gray matter, including deep brain nuclei; (c) many patterns that were consistent across subjects; (d) that average percentage levels of fluctuation in visual cortex (VC) and whole brain were higher in subjects who were asleep (up to 1.71% and 1.16%, respectively) than in those who were awake (up to 1.15% and 0.96%) at the end of the scan and were comparable with those levels evoked by intense visual stimulation (up to 1.85% and 0.76% for two subject groups); (e) no confirmation of correlation, positive or negative, between thalamus and VC found in earlier studies. These findings suggest that resting-state activity continues during sleep and does not require active cognitive processes or conscious awareness.

Neocortical network activity in vivo is generated through a dynamic balance of excitation and inhibition

The recurrent excitatory and inhibitory connections between and within layers of the cerebral cortex are fundamental to the operation of local cortical circuits. Models of cortical function often assume that recurrent excitation and inhibition are balanced, and we recently demonstrated that spontaneous network activity in vitro contains a precise balance of excitation and inhibition; however, the existence of a balance between excitation and inhibition in the intact and spontaneously active cerebral cortex has not been directly tested. We examined this hypothesis in the prefrontal cortex in vivo, during the slow (<1 Hz) oscillation in ketamine-xylazine-anesthetized ferrets. We measured persistent network activity (Up states) with extracellular multiple unit and local field potential recording, while simultaneously recording synaptic currents in nearby cells. We determined the reversal potential and conductance change over time during Up states and found that the body of Up state activity exhibited a steady reversal potential (-37 mV on average) for hundreds of milliseconds, even during substantial (21 nS on average) changes in membrane conductance. Furthermore, we found that both the initial and final segments of the Up state were characterized by significantly more depolarized reversal potentials and concomitant increases in excitatory conductance, compared with the stable middle portions of Up states. This ongoing temporal evolution between excitation and inhibition, which exhibits remarkable proportionality within and across neurons in active local networks, may allow for rapid transitions between relatively stable network states, permitting the modulation of neuronal responsiveness in a behaviorally relevant manner.

Detection of Active and Silent States in Neocortical Neurons from the Field Potential Signal during Slow-Wave Sleep

Oscillations of the local field potentials (LFPs) or electroencephalogram (EEG) at frequencies below 1 Hz are a hallmark of the slow-wave sleep. However, the timing of the underlying cellular events, which is an alternation of active and silent states of thalamocortical network, can be assessed only approximately from the phase of slow waves. Is it possible to detect, using the LFP or EEG, the timing of each episode of cellular activity or silence? With simultaneous recordings of the LFP and intracellular activity of 2-3 neocortical cells, we show that high-gamma-range (20-100 Hz) components in the LFP have significantly higher power when cortical cells are in active states as compared with silent-state periods. Exploiting this difference we have developed a new method, which uses the LFP signal to detect episodes of activity and silence of neocortical neurons. The method allows robust, reliable, and precise detection of timing of each episode of activity and silence of the neocortical network. It works with both surface and depth EEG, and its performance is affected little by the EEG prefiltering during recording. These results open new perspectives for studying differential operation of neural networks during periods of activity and silence, which rapidly alternate on the subsecond scale.

Pattern-specific associative long-term potentiation induced by a sleep spindle-related spike train

Spindles are non-rapid eye movement (non-REM) sleep EEG rhythms (7-14 Hz) that occur independently or in association with slow oscillations (0.6-0.8 Hz). Despite their proposed function in learning and memory, their role in synaptic plasticity is essentially unknown. We studied the ability of a neuronal firing pattern underlying spindles in vivo to induce synaptic plasticity in neocortical pyramidal cells in vitro. A spindle stimulation pattern (SSP) was extracted from a slow oscillation upstate that was recorded in a cat anesthetized with ketamine-xylazine, which is known to induce a sleep-like state. To mimic the recurrence of spindles grouped by the slow oscillation, the SSP was repeated every 1.5 s (0.6 Hz). Whole-cell patch-clamp recordings were obtained from layer V pyramidal cells of rat somatosensory cortex with infrared videomicroscopy, and composite EPSPs were evoked within layers II-III. Trains of EPSPs and action potentials simultaneously triggered by the SSP induced an NMDA receptor-dependent short-term potentiation (STP) and an L-type Ca2+ channel-dependent long-term potentiation (LTP). The number of spindle sequences affected the amount of STP-LTP. In contrast, spindle trains of EPSPs alone led to long-term depression. LTP was not consistently induced by a regular firing pattern, a mirrored SSP, or a randomized SSP; however, a synthetic spindle pattern consisting of repetitive spike bursts at 10 Hz reliably induced STP-LTP. Our results show that spindle-associated spike discharges are efficient in modifying excitatory neocortical synapses according to a Hebbian rule. This is in support of a role for sleep spindles in memory consolidation.

EEG MARKERS FOR COGNITIVE DECLINE IN ELDERLY SUBJECTS WITH SUBJECTIVE MEMORY COMPLAINTS

New treatments for Alzheimer's disease require early detection of cognitive decline. Most studies seeking to identify markers of early cognitive decline have focused on a limited number of measures. We sought to establish the profile of brain function measures which best define early neuropsychological decline. We compared subjects with subjective memory complaints to normative controls on a wide range of EEG derived measures, including a new measure of event-related spatio-temporal waves and biophysical modeling, which derives anatomical and physiological parameters based on subject's EEG measurements. Measures that distinguished the groups were then related to cognitive performance on a variety of learning and executive function tasks. The EEG measures include standard power measures, peak alpha frequency, EEG desynchronization to eyes-opening, and global phase synchrony. The most prominent differences in subjective memory complaint subjects were elevated alpha power and an increased number of spatio-temporal wave events. Higher alpha power and changes in wave activity related most strongly to a decline in verbal memory performance in subjects with subjective memory complaints, and also declines in maze performance and working memory reaction time. Interestingly, higher alpha power and wave activity were correlated with improved performance in reverse digit span in the subjective memory complaint group. The modeling results suggest that differences in the subjective memory complaint subjects were due to a decrease in cortical and thalamic inhibitory gains and slowed dendritic time-constants. The complementary profile that emerges from the variety of measures and analyses points to a nonlinear progression in electrophysiological changes from early neuropsychological decline to late-stage dementia, and electrophysiological changes in subjective memory complaint that vary in their relationships to a range of memory-related tasks.

Increased Propensity to Seizures After Chronic Cortical Deafferentation In Vivo

Cortical injury may lead to clinical seizures. We investigated the changing patterns of the sleeplike slow oscillation and its tendency to develop into paroxysmal activity consisting of spike-wave (SW) complexes at 2–4 Hz after partial deafferentation of the suprasylvian gyrus. Experiments were carried out in anesthetized cats, at different time intervals (wk 1 to wk 5, W1–W5) after cortical undercut. Multisite field potentials and single or dual intracellular recordings from the whole extent of the deafferented gyrus were used. The field components of the slow oscillation increased in amplitudes and were transformed into paroxysmal patterns, expressed by increased firing rates and tendency to neuronal bursting. The incidence of SW seizures was higher with transition from semiacute (W1) to chronic (W2–W5) stages after cortical undercut. The propagation delay of low-frequency activities decreased from W1 to W5, during both the slow oscillation and seizures. The initiation of seizures took place in territories contiguous to the relatively intact cortex (area 5 in the anterior part of the gyrus), as shown by cross-correlations of field potentials from different sites and simultaneous intracellular recordings from the anterior and posterior parts of the gyrus. The increased amplitudes of both slow oscillation and SW seizures, and their enhanced synchrony expressed by shorter time of propagation, are ascribed to increased neuronal and network excitability after cortical undercut.

Information-based modeling of event-related brain dynamics

We discuss the theory and practice of applying independent component analysis (ICA) to electroencephalographic (EEG) data. ICA blindly decomposes multi-channel EEG data into maximally independent component processes (ICs) that typically express either particularly brain generated EEG activities or some type of non-brain artifacts (line or other environmental noise, eye blinks and other eye movements, or scalp or heart muscle activity). Each brain and non-brain IC is identified with an activity time course (its 'activation') and a set of relative strengths of its projections (by volume conduction) to the recording electrodes (its 'scalp map'). Many non-articraft IC scalp maps strongly resemble the projection of a single dipole, allowing the location and orientation of the best-fitting equivalent dipole (or other source model) to be easily determined. In favorable circumstances, ICA decomposition of high-density scalp EEG data appears to allow concurrent monitoring, with high time resolution, of separate EEG activities in twenty or more separate cortical EEG source areas. We illustrate the differences between ICA and traditional approaches to EEG analysis by comparing time courses and mean event related spectral perturbations (ERSPs) of scalp channel and IC data. Comparing IC activities across subjects necessitates clustering of similar Ics based on common dynamic and/or spatial features. We discuss and illustrate such a component clustering strategy. In sum, continued application of ICA methods in EEG research should continue to yield new insights into the nature and role of the complex macroscopic cortical dynamics captured by scalp electrode recordings.

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.

Interaction between neocortical and hippocampal networks via slow oscillations

Both the thalamocortical and limbic systems generate a variety of brain state-dependent rhythms but the relationship between the oscillatory families is not well understood. Transfer of information across structures can be controlled by the offset oscillations. We suggest that slow oscillation of the neocortex, which was discovered by Mircea Steriade, temporally coordinates the self-organized oscillations in the neocortex, entorhinal cortex, subiculum and hippocampus. Transient coupling between rhythms can guide bidirectional information transfer among these structures and might serve to consolidate memory traces.

Full-band EEG (fbEEG): a new standard for clinical electroencephalography

A variety of neuroimaging techniques, such as functional magnetic resonance imaging (fMRI), positron emission tomography (PET) and magnetoencephalography (MEG), have been established during the last few decades, with progressive improvements continuously taking place in the underlying technologies. In contrast to this, the recording bandwidth of the routine clinical EEG (typically around 0.5-50 Hz) that was originally set by trivial technical limitations has remained practically unaltered for over half a decade. An increasing amount of evidence shows that salient EEG signals take place and can be recorded beyond the conventional clinical EEG bandwidth. These physiological and pathological EEG activities range from 0.01 Hz to several hundred Hz, and they have been demonstrated in recordings of spontaneous activity in the preterm human brain, and during epileptic seizures, sleep, as well as in various kinds of cognitive tasks and states in the adult brain. In the present paper, we will describe the practical aspects of recording the full physiological frequency band of the EEG (Full-band EEG; FbEEG), and we review the currently available data on the clinical applications of FbEEG. Recording the FbEEG is readily attained with commercially available direct-current (DC) coupled amplifiers if the recording setup includes electrodes providing a DC-stable electrode-skin interface. FbEEG does not have trade-offs that would favor any frequency band at the expense of another. We present several arguments showing that elimination of the lower (infraslow) or higher (ultrafast) bands of the EEG frequency spectrum in routine EEG has led, and will lead, to situations where salient and physiologically meaningful features of brain activity remain undetected or become seriously attenuated and distorted. With the currently available electrode, amplifier and data acquisition technology, it is to be expected that FbEEG will become the standard approach in both clinical and basic science.

Reorganization of sleep patterns in severe OSAS under prolonged CPAP treatment

OBJECTIVE

To evaluate the immediate and long-term recovery processes of sleep and daytime vigilance in patients with sleep apnea syndrome (OSAS) after continuous CPAP treatment.

METHODS

Five consecutive polysomnographic (PSG) studies were carried out on 10 male patients with severe OSAS. The first recording (baseline) was accomplished without ventilatory support (N0). The other 4 recordings were carried out during the CPAP titration night (N1), during the second night of treatment (N2), during the third night of treatment (N3), and after 30 days of regular CPAP use (N30). Ten age-balanced healthy male subjects were selected from the Parma Sleep Center database as controls. Respiratory variables, conventional PSG variables, arousals, CAP (cyclic alternating pattern) variables, and daytime function (including MSLT) were quantified. ANOVA followed by post-hoc tests explored the differences between controls and OSAS patients in the different recording conditions (N0, N1, N2, N3, N30). The PSG measures that showed significant ANOVA values were correlated with the MSLT scores.

RESULTS

Values of control subjects were recovered by REM sleep, REM latency, subtypes A3 and arousal index during N1, by CAP rate and total arousals during N2, by deep sleep (stages 3 + 4) during N3, by light sleep (stages 1 + 2) during N30. The only measures which remained below control values even after 1 month of sustained treatment were the amount of CAP cycles and A1 subtypes. MSLT scores correlated significantly with CAP rate, deep sleep and arousals.

CONCLUSIONS

The changes induced by CPAP treatment do not restore immediately a normal sleep structure, which is re-established with different time scales

SIGNIFICANCE

The modifications of sleep patterns and the different adjustments of phase A subtypes allow us to monitor the reorganization of sleep in OSAS patients treated with CPAP and the hierarchy of the mechanisms involved in sleep regulation.