Section of Psychopharmacology and Sleep Research
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University of Zürich - Institute of Pharmacology and Toxicology Section of Psychopharmacology and Sleep Research |
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.
J Biol Rhythms, 14, 460-468 (1999).
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.
J Biol Rhythms, 14, 557-568 (1999).
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.
Neurosci Lett, 275, 207-210 (1999).
The amygdala projects massively via its central nucleus (CNA) into brain stem regions involved in alerting and ponto-geniculo-occipital (PGO) wave generation. Electrical stimulation of CNA is known to enhance the acoustic startle response (ASR) and influence spontaneous PGO waves. The role of the amygdala in the modulation of ASR and elicited PGO waves (PGOE) was investigated in albino rats. Electrically stimulating CNA within 25 ms prior to an auditory stimulus enhanced ASR and PGOE amplitude in a similar way, with the largest response occurring when the electrical and auditory stimuli were given simultaneously. The data suggest that CNA modulates alerting mechanisms.
Physiol Behav, 66, 119-124 (1999).
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).
J Biol Rhythms, 14, 598-601 (1999).
The prion protein (PrP) is a glycoprotein anchored to cell membranes and expressed in most cell types. Its structural features indicate possible relations to signal peptidases (Glockshuber et al. 1998). Since mutations in this protein lead to severe neurodegeneration and death in humans and animals, it is possible that the loss of its normal function contributes to the development of the pathology. Little is known about its normal function, but there are indications that it may play a role in circadian rhythm and sleep regulation in mice. We explored further whether PrP plays a role in sleep regulation by comparing sleep and the effects of 6 h sleep deprivation in PrP knockout mice and isogenic wild-type mice of the 129/Ola strain. The mice did not differ in the amount and distribution of the vigilance states or in the power spectra. The most remarkable difference was the larger and long-lasting increase of slow-wave activity (mean EEG power density 0.75-4.0 Hz) in non-rapid-eye-movement (NREM) sleep during recovery from sleep deprivation in the null mice. The results confirm our previous findings in mice with a mixed background. This observation applies also to slow-wave activity in NREM sleep episodes following spontaneous waking bouts of different duration. Sleep fragmentation in both genotypes was larger than in mice with the mixed background. A new aspect was revealed by the spectral analysis of the EEG, where the null mice had a lower peak frequency within the theta band in REM sleep and waking, and not in NREM sleep. Behavioural observations concomitant with the EEG indicated that the EEG difference in waking may be attributed to the smaller amount of exploratory behaviour in the null mice. The difference between the genotypes in theta peak frequency was not an overall effect on the EEG, since it was absent in NREM sleep. PrP therefore may be affecting the theta-generating mechanisms in the hippocampus during waking and REM sleep. It remains unresolved whether PrP plays a role in sleep consolidation, nevertheless the data suggest that it is involved in sleep regulation. A passive avoidance test showed a difference between the genotypes. It is not probable that this was due to memory differences, since the genotypes reacted similarly in a delayed T-maze alternation procedure. The behavioural differences need to be pursued further.
J Sleep Res, 8 Suppl 1, 30-36 (1999).
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.
Neuropsychopharmacology, 21, 455-466 (1999).
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.
Clin Neurophysiol, 110, 632-635 (1999).
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.
Neurosci Lett, 271, 139-142 (1999).
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.
Clin Neurophysiol, 110, 869-875 (1999).
Long-term effects of 24-h sleep deprivation (SD) on sleep and sleep EEG were analyzed in male rats during 4 recovery days (Rec). An increase of total sleep time and non-rapid eye-movement (NREM) sleep was present during Rec 1-4, and of REM sleep in Rec 1 and in the dark periods of Rec 2 and 3. After the initial increase of slow-wave activity (SWA, mean EEG power density in the 0.75-4.0 Hz range) in NREM sleep, SWA declined below baseline until Rec 3. Sleep continuity was increased in Rec 1. The persistent effects of SD which are probably due to homeostatic and circadian facets of sleep regulation, must be taken into account in the design of SD studies.
Neurosci Lett, 261, 61-64 (1999).