Different Effects of Sleep Deprivation and Torpor on EEG Slow-Wave Characteristics in Djungarian Hamsters

It has been shown previously in Djungarian hamsters that the initial electroencephalography (EEG) slow-wave activity (power in the 0.5–4.0 Hz band; SWA) in non-rapid eye movement (NREM) sleep following an episode of daily torpor is consistently enhanced, similar to the SWA increase after sleep deprivation (SD). However, it is unknown whether the network mechanisms underlying the SWA increase after torpor and SD are similar. EEG slow waves recorded in the neocortex during sleep reflect synchronized transitions between periods of activity and silence among large neuronal populations. We therefore set out to investigate characteristics of individual cortical EEG slow waves recorded during NREM sleep after 4 h SD and during sleep after emergence from an episode of daily torpor in adult male Djungarian hamsters. We found that during the first hour after both SD and torpor, the SWA increase was associated with an increase in slow-wave incidence and amplitude. However, the slopes of single slow waves during NREM sleep were steeper in the first hour after SD but not after torpor, and, in contrast to sleep after SD, the magnitude of change in slopes after torpor was unrelated to the changes in SWA. Furthermore, slow-wave slopes decreased progressively within the first 2 h after SD, while a progressive increase in slow-wave slopes was apparent during the first 2 h after torpor. The data suggest that prolonged waking and torpor have different effects on cortical network activity underlying slow-wave characteristics, while resulting in a similar homeostatic sleep response of SWA. We suggest that sleep plays an important role in network homeostasis after both waking and torpor, consistent with a recovery function for both states.

Changes of cerebral tissue oxygen saturation at sleep transitions in adolescents

In adults, cerebral oxy-([O₂Hb]) and deoxyhemoglobin concentrations ([HHb]) change characteristically at transitions of sleep stages. The aims were to assess these changes in adolescents and additionally to measure tissue oxygen saturation (StO₂) by near infrared spectroscopy (NIRS). Previously it was reported that in adults [O₂Hb] increased and [HHb] decreased at the transition from non-rapid eye movement sleep (NREMS) to REMS and wakefulness. Transitions to NREMS from REMS/wakefulness led to a decrease in [O₂Hb] and an increase in [HHb]. We measured [O₂Hb], [HHb] and tissue oxygenation (StO₂) with NIRS approximately above the left prefrontal cortex in 12 healthy adolescent males (aged 10-16 years). We found comparable signs and magnitudes of changes in [O₂Hb] and [HHb] as observed in adults. StO₂ increased at the transitions from NREMS to REMS and decreased from REMS to NREMS and at sleep onset (all p < 0.01, linear mixed effects model). Changes in oxygen metabolism during sleep transitions are similar in adolescents and adults. In addition, we show for the first time temporal changes of StO₂ at sleep transitions.

Dissipation of sleep pressure is stable across adolescence

The sleep electroencephalogram (EEG) undergoes many changes during adolescence. We assessed whether sleep homeostasis is altered across adolescent development using two measures: the dissipation of slow-wave activity (SWA, 0.6-4.6Hz) across the night and the rate of build-up of SWA in the first non-rapid eye movement (NREM) sleep episode. Furthermore, we examined the association between homeostatic and circadian measures, by correlating the build-up of SWA in the first non-rapid eye movement (NREM) sleep episode with circadian phase. Finally, we compared the dissipation of SWA in individuals with (PH+) and without (PH-) a parental history of alcohol abuse/dependence. Twenty children (8 PH+) and 25 teens (10 PH+) underwent two consecutive polysomnographic recordings at ages 9/10 and 15/16 years and again 1.5-3 years later. Thirteen young adults (ages 20-23 years; no PH+) were assessed one time. The decay of Process S was modeled for each individual at each assessment using data from both recordings. Four parameters of Process S were derived for EEG derivation C3/A2: time constant of the decay, lower asymptote (LA), the level of S at sleep onset (S(SO)), and S(SO) minus LA. We found no change in these parameters between assessments for the children and teen cohorts. Between-subject analysis of the follow-up assessment for children (ages 11-13 years) and the initial assessment for teens (ages 15/16 years) showed no difference in these parameters, nor did follow-up assessment of teens (ages 17-19 years) compared to the single assessment of young adults (ages 20-23 years). Similarly, we observed no developmental changes in the rate of the build-up of SWA in the first NREM sleep episode for our within- and between-subject analyses, or a correlation between this measure and circadian phase for either cohort. With regard to parental alcohol history, we found no difference in the dissipation of sleep pressure between PH+ and PH- children and teens. These results indicate that the dissipation of sleep pressure does not change across adolescent development, is not correlated with circadian phase, and does not differ between PH+ and PH- children and teens.

Developmental changes in brain connectivity assessed using the sleep EEG

Adolescence represents a time of significant cortical restructuring. Current theories posit that during this period connections between frequently utilized neural networks are strengthened while underutilized synaptic connections are discarded. The aim of the present study was to examine the developmental evolution of connectivity between brain regions using the sleep EEG. All-night sleep EEG recordings in two longitudinal cohorts (children and teens) followed at 1.5-3 year intervals and one cross-sectional cohort (adults) were analyzed. The children and teen cohorts were 9/10 and 15/16 years at the initial assessment; ages of the adults were 20 to 23 years. Intrahemispheric, interhemispheric, and diagonal coherence was measured between all six possible pairings of two central (C3/A2 and C4/A1) and two occipital (O2/A1 and O1/A2) derivations during slow wave, stage 2, and, REM sleep. Within-subjects analyses were performed for the children and teen cohorts, and a linear regression analysis was performed across every assessment of all cohorts. Within-subject analyses revealed a maturational increase in coherence for both age cohorts, though the frequencies, sleep states, and regions differed between cohorts. Regression analysis across all age cohorts showed an overall linear increase in left and right intrahemispheric coherence for all sleep states across frequencies. Furthermore, coherence between diagonal electrode pairs also increased in a linear manner for stage 2 and REM sleep. No age-related trend was found in interhemispheric coherence. Our results indicate that sleep EEG coherence increases with age and that these increases are confined to specific brain regions. This analysis highlights the utility of the sleep EEG to measure developmental changes in brain maturation.

Correlation between sleep and cognitive functions after hemispheric ischaemic stroke

BACKGROUND

The aim of this study was to test the hypothesis of a link between sleep and cognitive functions, particularly memory and attention, after stroke.

METHODS

We studied 11 consecutive patients with first-ever hemispheric ischaemic stroke within eight days after symptoms onset and nine of them at least three months after stroke. Sleep EEG was recorded with a portable system. Cognitive functions were assessed using a standardized battery of tests allowing the estimation of the most relevant domains of cognition. Five age-matched healthy subjects served as controls.

RESULTS

The patients were aged 43 +/- 12 years (18-59). In five patients stroke was right-sided and in six patients left-sided. In the acute stroke phase a correlation between attention and amounts of slow wave sleep (SWS), Rapid eye movement (REM) sleep and sleep efficiency was found. In the recovery phase verbal/figural memory and attention significantly improved in most patients. Furthermore, an association between (i) verbal/figural (non-verbal) memory and amounts of SWS, REM sleep and sleep efficiency, and between (ii) attention and sleep efficiency was observed.

CONCLUSIONS

The results point to a link between sleep and cognitive functions and their recovery after hemispheric stroke. Further studies are needed to determine the specific nature of this link.

Sleep homeostasis in the rat in the light and dark period

Sleep is regulated by the interaction of a homeostatic (Process S) and a circadian component. The duration of prior wakefulness is the main factor influencing subsequent sleep duration and its intensity. We investigated in the rat whether the sleep-wake history before sleep deprivation (SD) contributes to the effects of sleep loss incurred during the SD. A 24-h baseline recording was followed by 6 h SD at light onset (SD-Light, n=7), or at dark onset (SD-Dark, n=8) and 18 h recovery. Both SDs led to a pronounced increase in slow wave activity (SWA, EEG power between 0.75 and 4.0 Hz) in NREM sleep and increased sleep consolidation. The prolongation of sleep episodes was associated with increased intra-episode SWA. The amount of waking before the SD correlated positively with the SWA increase during recovery, and SWA levels before SD were negatively correlated with their subsequent increase. The time-course of SWA (Process S) as well as of single frequency bins within the SWA band was successfully simulated based on vigilance-state distribution. The time constant of the exponential monotonic decay (Td) was higher for the 0.75-1.0 Hz bin compared to all remaining frequency bins of the SWA band, reflecting a slower process determining the slow EEG component during sleep. The data show that the homeostatic response after SD, consisting of increased sleep intensity and sleep consolidation is determined by a combination of SD and the preceding vigilance-state history. The slower dynamics of low frequency delta power compared to fast delta frequencies point to heterogeneity within the traditionally defined SWA band.

Sleep-wake disturbances in sporadic Creutzfeldt-Jakob disease

BACKGROUND

The prevalence and characteristics of sleep-wake disturbances in sporadic Creutzfeldt-Jakob disease (sCJD) are poorly understood.

METHODS

Seven consecutive patients with definite sCJD underwent a systematic assessment of sleep-wake disturbances, including clinical history, video-polysomnography, and actigraphy. Extent and distribution of neurodegeneration was estimated by brain autopsy in six patients. Western blot analyses enabling classification and quantification of the protease-resistant isoform of the prion protein, PrPSc, in thalamus and occipital cortex was available in four patients.

RESULTS

Sleep-wake symptoms were observed in all patients, and were prominent in four of them. All patients had severe sleep EEG abnormalities with loss of sleep spindles, very low sleep efficiency, and virtual absence of REM sleep. The correlation between different methods to assess sleep-wake functions (history, polysomnography, actigraphy, videography) was generally poor. Brain autopsy revealed prominent changes in cortical areas, but only mild changes in the thalamus. No mutation of the PRNP gene was found.

CONCLUSIONS

This study demonstrates in sporadic Creutzfeldt-Jakob disease, first, the existence of sleep-wake disturbances similar to those reported in fatal familial insomnia in the absence of prominent and isolated thalamic neuronal loss, and second, the need of a multimodal approach for the unambiguous assessment of sleep-wake functions in these patients.

Trait-like individual differences in the human sleep electroencephalogram

We aimed to examine whether commonly observed individual differences in sleep architecture and the sleep electroencephalogram reflect individual traits, which are amenable to a genetic investigation of human sleep. We studied intra-individual stability and inter-individual variation in sleep and sleep electroencephalogram spectra across four baseline recordings of eight healthy young men. A similarity concept based on Euclidean distances between vectors was applied. Visually scored sleep variables served as feature vector components, along with electroencephalogram power spectra in non-rapid-eye-movement and rapid-eye-movement sleep. The distributions of similarity coefficients of feature vectors revealed a clear distinction between high within-subject similarity (i.e. stability), and low between-subject similarity (i.e. variation). Moreover, a cluster analysis based on electroencephalogram spectra in both non-rapid-eye-movement and rapid-eye-movement sleep segregated all four baseline nights of each individual into a distinct cluster. To investigate whether high and low sleep pressure affects the similarity coefficients, normalized non-rapid-eye-movement sleep electroencephalogram spectra of the first and second half of the recordings were compared. Because the electroencephalogram changes systematically in the course of the night, within-subject variation no longer differed from between-subject variation. In conclusion, our data provide evidence for trait-like characteristics in the sleep electroencephalogram. Further studies may help to identify distinct phenotypes to search for genes underlying functional aspects of undisturbed human sleep.

Analysis of oscillatory patterns in the human sleep EEG using a novel detection algorithm

The different brain states during sleep are characterized by the occurrence of distinct oscillatory patterns such as spindles or delta waves. Using a new algorithm to detect oscillatory events in the electroencephalogram (EEG), we studied their properties and changes throughout the night. The present approach was based on the idea that the EEG may be described as a superposition of stochastically driven harmonic oscillators with damping and frequency varying in time. This idea was implemented by fitting autoregressive models to the EEG data. Oscillatory events were detected, whenever the damping of one or more frequencies was below a predefined threshold. Sleep EEG data of eight healthy young males were analyzed (four nights per subject). Oscillatory events occurred mainly in three frequency ranges, which correspond roughly to the classically defined delta (0-4.5 Hz), alpha (8-11.5 Hz) and sigma (11.5-16 Hz) bands. Their incidence showed small intra- but large inter-individual differences, in particular with respect to alpha events. The incidence and frequency of the events was characteristic for sleep stages and non-rapid eye movement (REM)-REM sleep cycles. The mean event frequency of delta and sigma (spindle) events decreased with the deepening of sleep. It was higher in the second half of the night compared with the first one for delta, alpha and sigma oscillations. The algorithm provides a general framework to detect and characterize oscillatory patterns in the EEG and similar signals.

Exposure to pulse-modulated radio frequency electromagnetic fields affects regional cerebral blood flow

We investigated the effects of radio frequency electromagnetic fields (RF EMF) similar to those emitted by mobile phones on waking regional cerebral blood flow (rCBF) in 12 healthy young men. Two types of RF EMF exposure were applied: a 'base-station-like' and a 'handset-like' signal. Positron emission tomography scans were taken after 30 min unilateral head exposure to pulse-modulated 900 MHz RF EMF (10 g tissue-averaged spatial peak-specific absorption rate of 1 W/kg for both conditions) and sham control. We observed an increase in relative rCBF in the dorsolateral prefrontal cortex on the side of exposure. The effect depended on the spectral power in the amplitude modulation of the RF carrier such that only 'handset-like' RF EMF exposure with its stronger low-frequency components but not the 'base-station-like' RF EMF exposure affected rCBF. This finding supports our previous observation that pulse modulation of RF EMF is necessary to induce changes in the waking and sleep EEG, and substantiates the notion that pulse modulation is crucial for RF EMF-induced alterations in brain physiology.

Sleep and rest facilitate auditory learning

Sleep is superior to waking for promoting performance improvements between sessions of visual perceptual and motor learning tasks. Few studies have investigated possible effects of sleep on auditory learning. A key issue is whether sleep specifically promotes learning, or whether restful waking yields similar benefits. According to the "interference hypothesis," sleep facilitates learning because it prevents interference from ongoing sensory input, learning and other cognitive activities that normally occur during waking. We tested this hypothesis by comparing effects of sleep, busy waking (watching a film) and restful waking (lying in the dark) on auditory tone sequence learning. Consistent with recent findings for human language learning, we found that compared with busy waking, sleep between sessions of auditory tone sequence learning enhanced performance improvements. Restful waking provided similar benefits, as predicted based on the interference hypothesis. These findings indicate that physiological, behavioral and environmental conditions that accompany restful waking are sufficient to facilitate learning and may contribute to the facilitation of learning that occurs during sleep.

The dynamics of spindles and EEG slow-wave activity in NREM sleep in mice

A quantitative analysis of spindles and spindle-related EEG activity was performed in C57BL/6 mice. The hypothesis that spindles are involved in sleep regulatory mechanisms was tested by investigating their occurrence during 24 h and after 6 h sleep deprivation (SD; n = 7). In the frontal derivation distinct spindle events were characterized as EEG oscillations with a dominant frequency approximately at 11 Hz. Spindles were most prominent during NREM sleep and increased before NREM-REM sleep transitions. Whereas spindles increased concomitantly with slow wave activity (SWA, EEG power between 0.5 and 4.0 Hz) at the beginning of the NREM sleep episode, these measures showed an opposite evolution prior to the transition to REM sleep. The 24-h time course of spindles showed a maximum at the end of the 12-h light period, and was a mirror image of SWA in NREM sleep. After 6 h SD the spindles in NREM sleep were initially suppressed, and showed a delayed rebound. In contrast, spindles occurring immediately before the transition to REM sleep were enhanced during the first 2 h of recovery. The data suggest that spindles in NREM sleep may be involved in sleep maintenance, while spindles heralding the transition to REM sleep may be related to mechanisms of REM sleep initiation.

Interhemispheric coherence of the sleep electroencephalogram in mice with congenital callosal dysgenesis

Regional differences in the effect of sleep deprivation on the sleep electroencephalogram (EEG) may be related to interhemispheric synchronization. To investigate the role of the corpus callosum in interhemispheric EEG synchronization, coherence spectra were computed in mice with congenital callosal dysgenesis (B1) under baseline conditions and after 6-h sleep deprivation, and compared with the spectra of a control strain (C57BL/6). In B1 mice coherence was lower than in controls in all vigilance states. The level of coherence in each of the three totally acallosal mice was lower than in the mice with only partial callosal dysgenesis. The difference between B1 and control mice was present over the entire 0.5-25 Hz frequency range in non-rapid eye movement sleep (NREM sleep), and in all frequencies except for the high delta and low theta band (3-7 Hz) in rapid eye movement (REM) sleep and waking. In control mice, sleep deprivation induced a rise of coherence in the Delta band of NREM sleep in the first 2 h of recovery. This effect was absent in B1 mice with total callosal dysgenesis and attenuated in mice with partial callosal dysgenesis. In both strains the effect of sleep deprivation dissipated within 4 h. The results show that EEG synchronization between the hemispheres in sleep and waking is mediated to a large part by the corpus callosum. This applies also to the functional changes induced by sleep deprivation in NREM sleep. In contrast, interhemispheric synchronisation of theta oscillations in waking and REM sleep may be mediated by direct interhippocampal connections.

Dimensional complexity and spectral properties of the human sleep EEG. Electroencephalograms

OBJECTIVE

The relevance of the dimensional complexity (DC) for the analysis of sleep EEG data is investigated and compared to linear measures.

METHODS

We calculated DC of artifact-free 1 min segments of all-night sleep EEG recordings of 4 healthy young subjects. Non-linearity was tested by comparing with DC values of surrogate data. Linear properties of the segments were characterized by estimating the self-similarity exponent alpha based on the detrended fluctuation analysis which quantifies the persistence of the signal and by calculating spectral power in the delta, theta, alpha and sigma bands, respectively.

RESULTS

We found weak nonlinear signatures in all sleep stages, but most pronounced in sleep stage 2. Strong correlations between DC and linear measures were established for the self-similarity exponent alpha and delta power, respectively.

CONCLUSIONS

The dimensional complexity of the sleep EEG is influenced by both linear and nonlinear features. It cannot be directly interpreted as a nonlinear synchronization measure of brain activity, but yields valuable information when combined with the analysis of linear measures.

Electromagnetic fields, such as those from mobile phones, alter regional cerebral blood flow and sleep and waking EEG

Usage of mobile phones is rapidly increasing, but there is limited data on the possible effects of electromagnetic field (EMF) exposure on brain physiology. We investigated the effect of EMF vs. sham control exposure on waking regional cerebral blood flow (rCBF) and on waking and sleep electroencephalogram (EEG) in humans. In Experiment 1, positron emission tomography (PET) scans were taken after unilateral head exposure to 30-min pulse-modulated 900 MHz electromagnetic field (pm-EMF). In Experiment 2, night-time sleep was polysomnographically recorded after EMF exposure. Pulse-modulated EMF exposure increased relative rCBF in the dorsolateral prefrontal cortex ipsilateral to exposure. Also, pm-EMF exposure enhanced EEG power in the alpha frequency range prior to sleep onset and in the spindle frequency range during stage 2 sleep. Exposure to EMF without pulse modulation did not enhance power in the waking or sleep EEG. We previously observed EMF effects on the sleep EEG (A. A. Borbély, R. Huber, T. Graf, B. Fuchs, E. Gallmann and P. Achermann. Neurosci. Lett., 1999, 275: 207-210; R. Huber, T. Graf, K. A. Cote, L. Wittmann, E. Gallmann, D. Matter, J. Schuderer, N. Kuster, A. A. Borbély, and P. Achermann. Neuroreport, 2000, 11: 3321-3325), but the basis for these effects was unknown. The present results show for the first time that (1) pm-EMF alters waking rCBF and (2) pulse modulation of EMF is necessary to induce waking and sleep EEG changes. Pulse-modulated EMF exposure may provide a new, non-invasive method for modifying brain function for experimental, diagnostic and therapeutic purposes.

Power and coherence of sleep spindle frequency activity following hemispheric stroke

Brainstem and thalamic structures are known to play a critical role in modulating sleep-wake cycles, but the extent to which the cerebral hemispheres are involved remains unclear. To study the role of the cerebral hemispheres in generating sleep EEG patterns, all-night polysomnographic recordings were collected in subjects with brain damage (n = 30) caused by hemispheric stroke and in hospitalized controls (n = 12). Recordings were made in the acute (< or =10 days post-stroke), subchronic (11-35 days post-stroke) and chronic (>60 days post-stroke) phases of stroke. Bipolar and referential EEG derivations were recorded. Standard sleep stage scoring was conducted using the referential derivation placed opposite the lesion. Sleep stage 2 power and coherence spectra were calculated based on recordings from bipolar derivations. In the mean spectra, the highest spindle frequency peak was identified and its size was calculated relative to the background spectrum. Analysis of visually scored EEG data indicated that, compared with controls, acute phase brain-damaged subjects had lower sleep efficiency and increased waking after sleep onset. The durations of rapid eye movement and non-rapid eye movement sleep stages did not differ significantly between brain-damaged subjects and hospitalized controls. Spectral analyses revealed that, compared with hospitalized controls, brain-damaged subjects had significantly reduced spindle peak sizes in the power and coherence spectra from derivations ipsilateral to the lesion. Within-subject comparisons across time demonstrated that the power and coherence of sleep spindle frequency activity increased significantly from the acute to the chronic phases of stroke, suggesting that plastic mechanisms allowed the possibility of recovery. Our findings provide novel evidence that the cerebral hemispheres are important in generating coherent sleep spindles in humans, and they are consonant with prior empirical and theoretical evidence that corticothalamic projections modulate the generation of synchronous spindle oscillations. Because spindle oscillations are thought to be involved in blocking sensory input to the cortex during sleep, the decrease in synchronous spindle frequency activity following hemispheric stroke may contribute to the observed reduction in sleep continuity.

Brain sources of EEG gamma frequency during volitionally meditation-induced, altered states of consciousness, and experience of the self

Multichannel EEG of an advanced meditator was recorded during four different, repeated meditations. Locations of intracerebral source gravity centers as well as Low Resolution Electromagnetic Tomography (LORETA) functional images of the EEG 'gamma' (35-44 Hz) frequency band activity differed significantly between meditations. Thus, during volitionally self-initiated, altered states of consciousness that were associated with different subjective meditation states, different brain neuronal populations were active. The brain areas predominantly involved during the self-induced meditation states aiming at visualization (right posterior) and verbalization (left central) agreed with known brain functional neuroanatomy. The brain areas involved in the self-induced, meditational dissolution and reconstitution of the experience of the self (right fronto-temporal) are discussed in the context of neural substrates implicated in normal self-representation and reality testing, as well as in depersonalization disorders and detachment from self after brain lesions.

Individual 'fingerprints' in human sleep EEG topography

The sleep EEG of eight healthy young men was recorded from 27 derivations during a baseline night and a recovery night after 40 h of waking. Individual power maps of the nonREM sleep EEG were calculated for the delta, theta, alpha, sigma and beta range. The comparison of the normalized individual maps for baseline and recovery sleep revealed very similar individual patterns within each frequency band. This high correspondence was quantified and statistically confirmed by calculating the Manhattan distance between all pairs of maps within and between individuals. Although prolonged waking enhanced power in the low-frequency range (0.75-10.5 Hz) and reduced power in the high-frequency range (13.25-25 Hz), only minor effects on the individual topography were observed. Nevertheless, statistical analysis revealed frequency-specific regional effects of sleep deprivation. The results demonstrate that the pattern of the EEG power distribution in nonREM sleep is characteristic for an individual and may reflect individual traits of functional anatomy.

Unihemispheric enhancement of delta power in human frontal sleep EEG by prolonged wakefulness

EEG power spectra exhibit site-specific and state-related differences in specific frequency bands. In the present study we investigated the effect of total sleep deprivation on sleep EEG topography. Eight healthy, young, right-handed subjects were recorded during baseline sleep and recovery sleep after sleep deprivation. Forty hours of sleep deprivation affected power spectra in all derivations. However, hemispheric asymmetries were observed in the delta range. Sleep deprivation enhanced the anterior predominance of delta activity in the left hemisphere but not in the right one. This effect may reflect a functional asymmetry between the dominant and non-dominant hemisphere. The results provide further evidence for the presence of both global and local aspects of sleep regulation.

High frequency repetitive transcranial magnetic stimulation (rTMS) of the left dorsolateral cortex: EEG topography during waking and subsequent sleep

Repetitive transcranial magnetic stimulation (rTMS) is a novel research tool in neurology and psychiatry. It is currently being evaluated as a conceivable alternative to electroconvulsive therapy for the treatment of mood disorders. Eight healthy young (age range 21-25 years) right-handed men without sleep complaints participated in the study. Two sessions at a 1-week interval, each consisting of an adaptation night (sham stimulation) and an experimental night (rTMS in the left dorsolateral prefrontal cortex or sham stimulation; crossover design), were scheduled. In each subject, 40 trains of 2-s duration of rTMS (inter-train interval 28 s) were applied at a frequency of 20 Hz (i.e. 1600 pulses per session) and at an intensity of 90% of the motor threshold. Stimulations were scheduled 80 min before lights off. The waking EEG was recorded for 10-min intervals approximately 30 min prior to and after the 20-min stimulations, and polysomnographic recordings were obtained during the subsequent sleep episode (23.00-07.00 h). The power spectra of two referential derivations, as well as of bipolar derivations along the antero-posterior axis over the left and right hemispheres, were analyzed. rTMS induced a small reduction of sleep stage 1 (in min and percentage of total sleep time) over the whole night and a small enhancement of sleep stage 4 during the first non-REM sleep episode. Other sleep variables were not affected. rTMS of the left dorsolateral cortex did not alter the topography of EEG power spectra in waking following stimulation, in the all-night sleep EEG, or during the first non-REM sleep episode. Our results indicate that a single session of rTMS using parameters like those used in depression treatment protocols has no detectable side effects with respect to sleep in young healthy males.

Functional topography of the human nonREM sleep electroencephalogram

The sleep EEG of healthy young men was recorded during baseline and recovery sleep after 40 h of waking. To analyse the EEG topography, power spectra were computed from 27 derivations. Mean power maps of the nonREM sleep EEG were calculated for 1-Hz bins between 1.0 and 24.75 Hz. Cluster analysis revealed a topographic segregation into distinct frequency bands which were similar for baseline and recovery sleep, and corresponded closely to the traditional frequency bands. Hallmarks of the power maps were the frontal predominance in the delta and alpha band, the occipital predominance in the theta band, and the sharply delineated vertex maximum in the sigma band. The effect of sleep deprivation on EEG topography was determined by calculating the recovery/baseline ratio of the power spectra. Prolonged waking induced an increase in power in the low-frequency range (1-10.75 Hz) which was largest over the frontal region, and a decrease in power in the sigma band (13-15.75 Hz) which was most pronounced over the vertex. The topographic pattern of the recovery/baseline power ratio was similar to the power ratio between the first and second half of the baseline night. These results indicate that changes in sleep propensity are reflected by specific regional differences in EEG power. The predominant increase of low-frequency power in frontal areas may be due to a high 'recovery need' of the frontal heteromodal association areas of the cortex.

Dual electroencephalogram markers of human sleep homeostasis: correlation between theta activity in waking and slow-wave activity in sleep

To investigate the relationship between markers of sleep homeostasis during waking and sleep, the electroencephalogram of eight young males was recorded intermittently during a 40-h waking episode, as well as during baseline and recovery sleep. In the course of extended waking, spectral power of the electroencephalogram in the 5-8Hz band (theta activity) increased. In non-rapid eye movement sleep, power in the 0.75-4.5Hz band (slow-wave activity) was enhanced in the recovery night relative to baseline. Comparison of individual records revealed a positive correlation between the rise rate of theta activity during waking and the increase in slow-wave activity in the first non-rapid eye movement sleep episode. A topographic analysis based on 27 derivations showed that both effects were largest in frontal areas. From these results, we suggest that theta activity in waking and slow-wave activity in sleep are markers of a common homeostatic sleep process.

Exposure to pulsed high-frequency electromagnetic field during waking affects human sleep EEG

The aim of the study was to investigate whether the electromagnetic field (EMF) emitted by digital radiotelephone handsets affects brain physiology. Healthy, young male subjects were exposed for 30 min to EMF (900 MHz; spatial peak specific absorption rate 1 W/kg) during the waking period preceding sleep. Compared with the control condition with sham exposure, spectral power of the EEG in non-rapid eye movement sleep was increased. The maximum rise occurred in the 9.75-11.25 Hz and 12.5-13.25 Hz band during the initial part of sleep. These changes correspond to those obtained in a previous study where EMF was intermittently applied during sleep. Unilateral exposure induced no hemispheric asymmetry of EEG power. The present results demonstrate that exposure during waking modifies the EEG during subsequent sleep. Thus the changes of brain function induced by pulsed high-frequency EMF outlast the exposure period.

Effects of medial thalamotomy and pallido-thalamic tractotomy on sleep and waking EEG in pain and Parkinsonian patients

OBJECTIVES

Investigation of sleep and sleep EEG before and after stereotactic neurosurgery.

METHODS

All-night polysomnographic recordings were obtained in 3 neurogenic pain patients and 3 parkinsonian patients. One subject of each group was recorded in addition 3 months after surgery. Stereotactic operations were performed in the medial thalamus and on the pallido-thalamic tract to relieve neurogenic pain and parkinsonian symptoms, respectively.

RESULTS

Sleep efficiency was little affected by the surgical intervention in neurogenic pain patients and a dramatic reduction in REM sleep occurred, which had recovered in the subject recorded after 3 months. After the surgery parkinsonian patients showed an increase in total sleep time and in sleep efficiency, and a decrease in REM sleep latency. Sleep efficiency remained elevated in the 3 months follow-up. Medial thalamotomy abolished spindle frequency activity (SFA) in the power and coherence spectra in non-REM sleep stage 2 systematically. Pallido-thalamic tractotomy attenuated SFA only to varying degrees. After 3 months SFA had reemerged. The alpha peak of the waking EEG was shifted to lower frequencies after surgery in 5 of 6 patients and had reverted to the original frequency 3 months later.

CONCLUSIONS

Medial thalamotomy or pallido-thalamic tractotomy had acute and reversible effects on the EEG and long-term deleterious side effects of stereotactic surgery on sleep and sleep EEG are improbable. The results provide further evidence for the involvement of the human thalamus in the generation of sleep spindles.

Zolpidem and sleep deprivation: different effect on EEG power spectra

To study the role of GABA-ergic mechanisms in sleep regulation, the combined action of 40 h sleep deprivation and either 20 mg zolpidem or placebo on the sleep electroencephalogram (EEG) were investigated by quantitative EEG analysis in eight young men who participated in a positron emission tomography study. Compared with baseline, sleep deprivation increased low-frequency (1.25-7.0 Hz) EEG power in non-rapid eye movement (NREM) sleep in the placebo night. After administration of zolpidem, power in the 3.75-10.0 Hz range and 14. 25-16.0 Hz band was reduced. The largest decrease was observed in the theta band. Comparison with placebo revealed that zolpidem attenuated power in the entire 1.75-11.0 Hz range. The plasma concentration of zolpidem at 4.5 h after intake showed a positive correlation with the drug-induced difference in power from placebo in the 14.25-16.0 Hz band. Regional EEG analysis based on bipolar derivations along the antero-posterior axis disclosed, for NREM sleep, a drug-induced posterior shift of power in the frequency range of 7.75-9.75 Hz. Zolpidem did not affect rapid eye movemnt sleep spectra. We conclude that sleep deprivation and agonistic modulation of GABAA receptors have separate and additive effects on power spectra and that their effects are mediated by different neurophysiological mechanisms.

Functional neuroanatomy of human sleep states after zolpidem and placebo: a H215O-PET study

Changes in the functional organization of the brain during the course of sleep and waking are reflected by different patterns of regional cerebral blood flow (rCBF). To investigate the effect of the hypnotic zolpidem, a benzodiazepine receptor agonist, drug or placebo were administered to eight young, healthy men prior to bedtime. The subjects were sleep-deprived to promote sleep during the 4-h recording period in the positron emission tomography scanner. Intravenous injections of labelled water were administered during pre-drug wakefulness, and during Stage 2, Stage 4 and rapid eye movement (REM) sleep, each injection being followed by an emission scan. Statistical parametric mapping was used to investigate the effects of treatment and sleep states. During sleep (combined Stages 2 and 4, and REM sleep) relative rCBF was lower after zolpidem than after placebo in the basal ganglia and insula, and higher in the parietal cortex. A 'multiple study' analysis of REM sleep revealed that rCBF in the anterior cingulum was lower after zolpidem than after placebo, whereas rCBF in the occipital and parietal cortex, parahippocampal gyrus and cerebellum was higher. When the pooled data (drug and placebo) of Stages 2 and 4 were compared with wakefulness, rCBF was lower in prefrontal cortex and insula, and higher in the occipital and parietal cortex. The results indicate that some differences in rCBF from wakefulness to non-REM sleep are further augmented by zolpidem.

Commentary: future considerations for models of human neurobehavioral function

Modeling human neurobehavioral functions has the goal of identifying work-rest schedules that are safer and more productive. The models of Folkard et al. and of Jewett and Kronauer illustrate excellent progress toward this goal. Examination of these models reveals four additional areas that need to be addressed to facilitate continued development of accurate models of neurobehavioral functions. (1) The choice of neurobehavioral metrics may have a significant influence on model development. The lack of correlation among different neurobehavioral measures may make comparisons of models difficult. Many neurobehavioral measures are confounded by secondary and random error variance that can lead to model distortion. Although different models may ultimately be required for different neurobehavioral functions, measures that have been extensively validated to be sensitive to circadian variation and sleep loss should take priority in model development. (2) Because error variance in neurobehavioral outcomes can be substantial in uncontrolled environments, model validation should proceed from controlled laboratory protocols to real-world scenarios. Once validated, the ability of a model to predict field data can be tested. (3) While neurobehavioral models have been developed to predict behavior over time (i.e., within-subjects), to be useful in the real world, models will also ultimately have to provide estimates of between-subject variation in vulnerability to neurobehavioral dysfunction during night work or sleep loss (e.g., younger versus older workers). (4) Finally, to be theoretically accurate and practically useful, models of human neurobehavioral functions should be able to predict both cumulative effects (i.e., across days or weeks) and the influence of countermeasures (e.g., light, naps, caffeine).

Modeling circadian rhythm generation in the suprachiasmatic nucleus with locally coupled self-sustained oscillators: phase shifts and phase response curves

Circadian rhythm generation in the suprachiasmatic nucleus was modeled by locally coupled self-sustained oscillators. The model is composed of 10,000 oscillators, arranged in a square array. Coupling between oscillators and standard deviation of (randomly determined) intrinsic oscillator periods were varied. A stable overall rhythm emerged. The model behavior was investigated for phase shifts of a 24-h zeitgeber cycle. Prolongation of either the dark or the light phase resulted in a lengthening of the period, whereas shortening of the dark or the light phase shortened the period. The model's response to shifts in the light-dark cycle was dependent only on the extent of the shift and was insensitive to changes in parameters. Phase response curves (PRC) and amplitude response curves were determined for single and triple 5-h light pulses (1000 lux). Single pulses lead to type 1 PRCs with larger phase shifts for weak coupling. Triple pulses generally evoked type 1 PRCs with the exception of weak coupling, where a type 0 PRC was observed.

Sleep homeostasis and models of sleep regulation

According to the two-process model of sleep regulation, the timing and structure of sleep are determined by the interaction of a homeostatic and a circadian process. The original qualitative model was elaborated to quantitative versions that included the ultradian dynamics of sleep in relation to the non-REM-REM sleep cycle. The time course of EEG slow-wave activity, the major marker of non-REM sleep homeostasis, as well as daytime alertness were simulated successfully for a considerable number of experimental protocols. They include sleep after partial sleep deprivation and daytime napping, sleep in habitual short and long sleepers, and alertness in a forced desynchrony protocol or during an extended photoperiod. Simulations revealed that internal desynchronization can be obtained for different shapes of the thresholds. New developments include the analysis of the waking EEG to delineate homeostatic and circadian processes, studies of REM sleep homeostasis, and recent evidence for local, use-dependent sleep processes. Moreover, nonlinear interactions between homeostatic and circadian processes were identified. In the past two decades, models have contributed considerably to conceptualizing and analyzing the major processes underlying sleep regulation, and they are likely to play an important role in future advances in the field.

Pulsed high-frequency electromagnetic field affects human sleep and sleep electroencephalogram

To investigate whether the electromagnetic field (EMF) emitted by digital radiotelephone handsets affects the brain, healthy, young subjects were exposed during an entire night-time sleep episode to an intermittent radiation schedule (900 MHz; maximum specific absorption rate 1 W/kg) consisting of alternating 15-min on-15-min off intervals. Compared with a control night with sham exposure, the amount of waking after sleep onset was reduced from 18 to 12 min. Spectral power of the electroencephalogram in non-rapid eye movement sleep was increased. The maximum rise occurred in the 10-11 Hz and 13.5-14 Hz bands during the initial part of sleep and then subsided. The results demonstrate that pulsed high-frequency EMF in the range of radiotelephones may promote sleep and modify the sleep EEG.

Serotonin-2 receptors and human sleep: effect of a selective antagonist on EEG power spectra

To investigate the effect on the sleep EEG, a 1-mg oral dose of SR 46349B, a novel 5-HT2 antagonist, was administered three hours before bedtime. The drug enhanced slow wave sleep (SWS) and reduced stage 2 without affecting subjective sleep quality. In nonREM sleep (NREMS) EEG slow-wave activity (SWA; power within 0.75-4.5 Hz) was increased and spindle frequency activity (SFA; power within 12.25-15 Hz) was decreased. The relative NREMS power spectrum showed a bimodal pattern with the main peak at 1.5 Hz and a secondary peak at 6 Hz. A regional analysis based on bipolar derivations along the antero-posterior axis revealed significant 'treatment' x 'derivation' interactions within the 9-16 Hz range. In enhancing SWA and attenuating SFA, the 5-HT2 receptor antagonist mimicked the effect of sleep deprivation, whereas the pattern of the NREMS spectrum differed.

Frequency and state specific hemispheric asymmetries in the human sleep EEG

Regional differences in the sleep EEG along the antero-posterior axis have been recently described. To test for state related, hemispheric differences, sleep records from homologous fronto-central, centro-parietal and parieto-occipital derivations were obtained from 14 young right-handed males. Within the frequency range of sleep spindles (11-15 Hz) power in non-REM sleep dominated in the left hemisphere in all derivations. In the centro-parietal 4-8 Hz band a right-hemispheric predominance prevailed in non-REM sleep and a left-hemispheric predominance in REM sleep. Since the frequency bands exhibiting hemispheric asymmetries are those in which large antero-posterior power gradients had been observed, the left-right differences may arise from structural and functional asymmetries of brain regions involved in the generation of the sleep EEG.

Regional differences in the dynamics of the cortical EEG in the rat after sleep deprivation

OBJECTIVE

To investigate regional changes of the cortical sleep EEG in the rat, recordings were obtained from a frontal and an occipital derivation, on a baseline day (n = 14 male rats, Sprague-Dawley strain) and after 24 h sleep deprivation (SD, n = 7).

METHODS

Spectral analysis of the vigilance states revealed state and frequency specific differences in EEG power by two-way ANOVA and post-hoc t tests.

RESULTS

In the theta band (6.25-9.0 Hz) occipital power was larger than frontal power in waking and REM sleep, whereas frontal power was larger in the frequency range between 10.25-16.0 Hz in non-REM sleep and REM sleep. After SD frontal power in the 2-4 Hz band in non-REM sleep was increased more than occipital power and frontal power in the 10.25-16.0 Hz range was more attenuated. In REM sleep frontal power in the theta band and in the 10.25-16.0 Hz range was more increased than occipital power. Power in the waking EEG did not differ between the two derivations after SD.

CONCLUSIONS

The differential responses to SD may reflect regional use-dependent aspects of sleep regulation. These observations support the notion that sleep is not only a global phenomenon but has also local, use-dependent features.

Alpha activity in the human REM sleep EEG: topography and effect of REM sleep deprivation

The topographical distribution of alpha activity (8.125-11.125 Hz) in the REM sleep EEG, its time course within and across REM sleep episodes, and the effects of selective REM sleep deprivation were investigated in 8 young males. Power spectra of bipolar derivations along the antero-posterior axis in the left (F3C3, C3P3, P301) and right (F4C4, C4P4, P402) hemisphere were calculated. Alpha activity increased along the antero-posterior axis in both hemispheres, and was dominant in the right hemisphere. It decreased within and across REM sleep episodes. Selective REM sleep deprivation resulted in a reduction of alpha activity in the REM sleep EEG. However, the topographical distribution and the time course were not affected. It is suggested that alpha activity in the REM sleep EEG is a marker of REM sleep homeostasis.

Rest-activity rhythm of the blind mole rat Spalax ehrenbergi under different lighting conditions

The mole rat is a solitary, subterranean and photoperiodic rodent. We investigated its rest activity behavior under several lighting conditions, complemented our observations with light-induced c-fos expression, and compared the activity behavior of two chromosomal forms (2n = 58 and 60). The 26 mole rats had a clear overall preference for activity in the light or dark period, but prolonged recordings in five individuals showed that the initial preference was not stable in the nocturnal animals, they became diurnal. A 6-h advance of the light-dark (LD) cycle induced a shift of activity and the previous LD preference was reestablished. The large daily variability of activity onset did not allow this study to determine whether the animals were entrained to the LD cycle upon release into constant darkness (DD) or whether activity had been masked by light. The period of the motor activity rhythm in DD free ran in more than 50% of the animals. No differences in activity were observed between the two karyotypes. Immunohistochemistry for c-fos expression in the nucleus suprachiasmaticus at different circadian times showed that c-fos was induced only in animals exposed to a 1-h light pulse during the subjective night, but not during the subjective day or in control animals in the absence of a light pulse. The large intra- and inter-individual variability in daily motor activity both in LD and in DD suggest only a weak photic entrainment of the circadian clock to light of approximately 100 lux, and possibly a weak regulation of behavior by the circadian clock.

Coherence analysis of the human sleep electroencephalogram

Animal studies have shown that the sleep-related oscillations in the frequency range of spindles and slow-waves, and in the gamma band occur synchronously over large parts of the cerebral cortex. Coherence analysis was used to investigate these oscillations in the human sleep electroencephalogram. In all-night electroencephalogram recordings from eight young subjects power and coherence spectra within and between cerebral hemispheres were computed from bipolar derivations placed bilaterally along the antero-posterior axis. The 0.75-50 Hz range was examined with a resolution of 0.25 Hz. Distinct peaks in coherence were present in non-rapid eye movement sleep but not in rapid eye movement sleep. The most prominent and consistent peak was seen in the range of sleep spindles (13-14 Hz), and additional peaks were present in the alpha band (9-10 Hz) and low delta band (1-2 Hz). Whereas coherence in the spindle range was highest in stage 2, the alpha peak was most prominent in slow-wave sleep (stages 3 and 4). Interhemispheric coherence at 30 Hz was higher in rapid eye movement sleep than in non-rapid eye movement sleep. There were also marked sleep state-independent regional differences. Coherence between homologous interhemispheric derivations was high in the low frequency range and declined with increasing frequencies, whereas coherence of intrahemispheric and non-homologous interhemispheric derivations was at a low level throughout the spectra. It is concluded that coherence analysis may provide insights into large-scale functional connectivities of brain regions during sleep. The high coherence of sleep spindles is an indication for their widespread and quasi-synchronous occurrence throughout the cortex and may point to their specific role in the sleep process.

Temporal evolution of coherence and power in the human sleep electroencephalogram

Coherence analysis of the human sleep electroencephalogram (EEG) was used to investigate relations between brain regions. In all-night EEG recordings from eight young subjects, the temporal evolution of power and coherence spectra within and between cerebral hemispheres was investigated from bipolar derivations along the antero-posterior axis. Distinct peaks in the power and coherence spectra were present in NREM sleep but not in REM sleep. They were situated in the frequency range of sleep spindles (13-14 Hz), alpha band (9-10 Hz) and low delta band (1-2 Hz). Whereas the peaks coincided in the power and coherence spectra, a dissociation of their temporal evolution was observed. In the low delta band, only power but not coherence showed a decline across successive NREM sleep episodes. Moreover, power increased gradually in the first part of a NREM sleep episode, whereas coherence showed a rapid rise. The results indicate that the intrahemispheric and interhemispheric coherence of EEG activity attains readily a high level in NREM sleep and is largely independent of the signal amplitude.

A new method for detecting state changes in the EEG: exploratory application to sleep data

A new statistical method is described for detecting state changes in the electroencephalogram (EEG), based on the ongoing relationships between electrode voltages at different scalp locations. An EEG sleep recording from one NREM-REM sleep cycle from a healthy subject was used for exploratory analysis. A dimensionless function defined at discrete times ti, u(ti), was calculated by determining the log-likelihood of observing all scalp electrode voltages under the assumption that the data can be modeled by linear combinations of stationary relationships between derivations. The u(ti), calculated by using independent component analysis, provided a sensitive, but non-specific measure of changes in the global pattern of the EEG. In stage 2, abrupt increases in u(ti) corresponded to sleep spindles. In stages 3 and 4, low frequency (approximately equal to 0.6 Hz) oscillations occurred in u(ti) which may correspond to slow oscillations described in cellular recordings and the EEG of sleeping cats. In stage 4 sleep, additional irregular very low frequency (approximately equal to 0.05-0.2 Hz) oscillations were observed in u(ti) consistent with possible cyclic changes in cerebral blood flow or changes of vigilance and muscle tone. These preliminary results suggest that the new method can detect subtle changes in the overall pattern of the EEG without the necessity of making tenuous assumptions about stationarity.

Selective REM sleep deprivation in humans: effects on sleep and sleep EEG

To investigate rapid eye movement (REM) sleep regulation, eight healthy young men were deprived of REM sleep for three consecutive nights. In a three-night control sleep deprivation (CD) session 2 wk later, the subjects were repeatedly awakened from non-REM sleep in an attempt to match the awakenings during the REM sleep deprivation (RD) nights. During the RD nights the number of sleep interruptions required to prevent REM sleep increased within and across consecutive nights. REM sleep was reduced to 9.2% of baseline (CD nights: 80.7%) and rose to 140.1% in the first recovery night. RD gave rise to changes in the EEG power spectra of REM sleep. Power in the 8.25- to 11-Hz range was reduced in the first recovery night, an effect that gradually subsided but was still present in the third recovery night. The rising REM sleep propensity, as reflected by the increase of interventions within and across RD nights, and the moderate REM sleep rebound during recovery can be accounted for by a compensatory response that serves REM sleep homeostasis. The changes in the electroencephalogram power spectra, which were observed during enhanced REM sleep propensity, may be a sign of an altered quality of REM sleep.

Effect of frequent brief awakenings from nonREM sleep on the nonREM-REM sleep cycle

In the framework of a selective sleep deprivation study, eight young men were repeatedly awakened during 3 nights from nonREM sleep (nonREMS). The mean number of awakenings per night was 27.4, 29.5 and 32.8. In order to avoid excessive suppression of slow wave sleep, no awakening occurred in the first nonREMS episode. Compared to baseline, cycle 2 was significantly prolonged in all 3 nights, and cycle 3 in night 3 only. However, after subtracting the waking intervals, the differences from baseline was eliminated. The results show that the mechanisms underlying sleep cycle control keep track of sleep time and disregard epochs of waking.