Peter Achermann

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.

Low-frequency (<1 Hz) oscillations in the human sleep electroencephalogram

Low-frequency (< 1 Hz) oscillations in intracellular recordings from cortical neurons were first reported in the anaesthetized cat and then also during natural sleep. The slow sequences of hyperpolarization and depolarization were reflected by slow oscillations in the electroencephalogram. The aim of the present study was to examine whether comparable low-frequency components are present in the human sleep electroencephalogram. All-night sleep recordings from eight healthy young men were subjected to spectral analysis in which the low-frequency attenuation of the amplifier was compensated. During sleep stages with a predominance of slow waves and in the first two episodes of non-rapid-eye-movement sleep, the mean power spectrum showed a peak at 0.7-0.8 Hz (range 0.55-0.95 Hz). The typical decline in delta activity from the first to the second non-rapid-eye-movement sleep episode was not present at frequencies below 2 Hz. To detect very low frequency components in the pattern of slow waves and sleep spindles, a new time series was computed from the mean voltage of successive 0.5 s epochs of the low-pass (< 4.5 Hz) or band-pass (12-15 Hz) filtered electroencephalogram. Spectral analysis revealed a periodicity of 20-30 s in the prevalence of slow waves and a periodicity of 4 s in the occurrence of activity in the spindle frequency range. The results demonstrate that distinct components below 1 Hz are also present in the human sleep electroencephalogram spectrum. The differences in the dynamics between the component with a mean peak value at 0.7-0.8 Hz and delta waves above 2 Hz is in accordance with results from animal experiments.

A model of human sleep homeostasis based on EEG slow-wave activity: Quantitative comparison of data and simulations

EEG slow-wave activity (SWA; spectral power in the 0.75-4.5 Hz band) is a function of the duration of prior waking and, thereby, an indicator of sleep homeostasis. We present a model that accounts for both the declining trend of SWA during sleep and for its variation within the successive nonrapid eye movement (non-REM) sleep episodes. The values of the model parameters were estimated by an optimization procedure in which empirical SWA of baseline nights (16 subjects, 26 nights) served as a reference. A sensitivity analysis revealed the model to be quite robust to small changes (+/- 5%) of the parameter values. The estimated parameter values were used to simulate data sets from three different experimental protocols (sleep in the evening or sleep in the morning after prolonged waking, or extended sleep initiated at the habitual bedtime; n = 8 or 9). The timing of the REM trigger parameter was derived from the empirical data. A close fit was obtained between the simulated and empirical SWA data, and even the occasional late SWA peaks during extended sleep could be reproduced. Minor discrepancies suggest indirect or direct circadian influences on SWA. The simulations demonstrate that the concept of sleep homeostasis as proposed in the two-process model of sleep regulation can be refined to account in quantitative terms for empirical data and to predict the changes induced by the prolongation of waking or sleep.

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.

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.

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.

Effect of age on the sleep EEG: slow-wave activity and spindle frequency activity in young and middle-aged men.

The effect of age on sleep and the sleep EEG was investigated in middle-aged men (mean age: 62.0 years) and in young men (mean age: 22.4 years). Even though the older men reported a higher number of nocturnal awakenings, subjective sleep quality did not differ. Total sleep time, sleep efficiency, and slow wave sleep were lower in the middle-aged, while stage 1 and wakefulness after sleep onset were higher. The differences in wakefulness within nonREM-REM sleep cycles was most pronounced in the third and fourth cycle. In the older men, EEG power density in nonREM sleep was reduced in frequencies below 14.0 Hz, whereas in REM sleep age-related reductions were limited to he delta-theta (0.25-7.0 Hz) and low alpha (8.25-10.0 Hz) band. Slow-wave activity (SWA, power density in the 0.75-4.5 Hz range) decreased in the course of sleep in both age groups. The between-group difference in SWA diminished in the course of sleep, whereas the difference in activity in the frequency range of sleep spindles (12.25-14.0 Hz) increased. It is concluded that frequency and state specific changes occur as a function of age, and that sleep dependent decline in SWA and increase in sleep spindle activity are attenuated with age.

Mathematical models of sleep regulation.

The level of EEG slow-wave activity (SWA) is determined by the duration of prior sleep and waking. SWA is a marker of nonREM sleep intensity and may serve as an indicator of sleep homeostasis. The two-process model of sleep regulation posits the interaction of the homeostatic Process S and the circadian Process C. Also models of neurobehavioral functions (three-process model; interactive models of alertness and cognitive throughput) are based on the concept of an interaction between homeostatic and circadian factors. Whether the interaction is linear or non-linear is still unresolved. Models may serve as a guiding principle for specifying the relationship between processes occurring at the macroscopic and microscopic level of analysis.

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

The aim of the study was to investigate whether the electro-magnetic 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.

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.