State transitions between wake and sleep, and within the ultradian cycle, with focus on the link to neuronal activity

Late evening brain activation patterns and their relation to the internal biological time, melatonin, and homeostatic sleep debt

Sleep propensity increases sharply at night. Some evidence implicates the pineal hormone melatonin in this process. Using functional magnetic resonance imaging, brain activation during a visual search task was examined at 22:00 h (when endogenous melatonin levels normally increase). The relationships between brain activation, endogenous melatonin (measured in saliva), and self-reported fatigue were assessed. Finally, the effects of exogenous melatonin administered at 22:00 h were studied in a double blind, placebo-controlled crossover manner. We show that brain activation patterns as well as the response to exogenous melatonin significantly differ at night from those seen in afternoon hours. Thus, activation in the rostro-medial and lateral aspects of the occipital cortex and the thalamus diminished at 22:00 h. Activation in the right parietal cortex increased at night and correlated with individual fatigue levels, whereas exogenous melatonin given at 22:00 h reduced activation in this area. The right dorsolateral prefrontal cortex, an area considered to reflect homeostatic sleep debt, demonstrated increased activation at 22:00 h. Surprisingly, this increase correlated with endogenous melatonin. These results demonstrate and partially differentiate circadian effects (whether mediated by melatonin or not) and homeostatic sleep debt modulation of human brain activity associated with everyday fatigue at night.

Behavioural state linkage in the ovine fetus near term

Nine fetal sheep were surgically prepared with placement of electrocortical and electro-ocular electrodes for monitoring behavioural state activity to determine the relationship of adjacent low-voltage (LV)/rapid eye movement (REM) and high-voltage (HV)/non-(N)REM epoch durations and the inter-epoch transition time. Animals were subsequently studied over an 8-hour period with behavioural state epoch duration and transition time assessed using paired t-test and regression analysis. For all animals, the duration of LV/REM epochs averaged 14.8+/-0.8 (SEM) minutes which was significantly greater than that for HV/NREM epochs at 10.1+/-0.5 min (P<0.01). The mean duration of LV/REM to HV/NREM transition periods at 93+/-3 s was also significantly longer than that for the HV/NREM to LV/REM transition periods at 78+/-6 s (P<0.05). HV/NREM epoch duration was positively correlated with the prior LV/REM epoch duration with a group mean correlation of 0.59 (P<0.01). HV/NREM epoch duration was likewise positively correlated with the subsequent LV/REM epoch duration with a group mean correlation of 0.46 (P<0.01). We conclude that the transition time into HV/NREM is longer than that into LV/REM for the ovine fetus near term which may involve differences in the rate of maturation of cycling control mechanisms for these two behavioural states and earlier development of REM-on versus REM-off pathways. The positive LV/REM-HV/NREM linkage relationships also support a homeostatic model of behavioural state control whereby LV/REM and HV/NREM timings are both controlled by accumulation of propensity for these states during the other state and favours an interactive process between these states in the brain's growth and development.

A non-invasive technique to monitor wakefulness during electrophysiologic recording experiments in primates

Although the state of wakefulness has an impact on many physiological parameters, this variable is seldom controlled for in in vivo experiments, because the existing techniques to identify periods of wakefulness are laborious and difficult to implement. We here report on a simple non-invasive technique to achieve this goal, using the analysis of video material, collected along with the electrophysiologic data, to analyze eyelid movements. The technique was applied to recordings in non-human primates, and allowed us to automatically identify periods during which the subject has its eyes open. A comparison with frontal electroencephalographic records confirmed that such periods corresponded to wakefulness.

Differential effects of acute alcohol on prepulse inhibition and event-related potentials in adolescent and adult Wistar rats

BACKGROUND

Previous studies have demonstrated that adolescent and adult rats show differential sensitivity to many of the acute effects of alcohol. We recently reported evidence of developmental differences in the effects of acute alcohol on the cortical electroencephalogram. However, it is unclear whether developmental differences are also observed in other neurophysiological and neurobehavioral measurements known to be sensitive to alcohol exposure. The present study determined the age-related effects of acute alcohol on behavioral and event-related potential (ERP) responses to acoustic startle (AS) and prepulse inhibition (PPI).

METHODS

Male adolescent and adult Wistar rats were implanted with cortical recording electrodes. The effects of acute alcohol (0.0, 0.75, and 1.5 g/kg) on behavioral and ERP responses to AS and PPI were assessed.

RESULTS

Acute alcohol (0.75 and 1.5 g/kg) significantly reduced the behavioral and electrophysiological response to AS in adolescent and adult rats. Both 0.75 and 1.5 g/kg alcohol significantly enhanced the behavioral response to PPI in adolescent, but not in adult rats. During prepulse + pulse trials, 1.5 g/kg alcohol significantly increased the N10 pulse response in the adolescent frontal cortex. Acute alcohol (0.75 and 1.5 g/kg) also increased the N1 ERP pulse response to prepulse stimuli in frontal and parietal cortices in adult rats, but not in adolescent rats.

CONCLUSIONS

These data suggest that alcohol's effect on behavioral and electrophysiological indices of AS do not differ between adults and adolescents whereas developmental stage does appear to significantly modify alcohol-influenced response to PPI.

Differences in the sleep architecture of forager and young honeybees(Apis mellifera)

Honeybee (Apis mellifera) foragers are among the first invertebrates for which sleep behavior has been described. Foragers (typically older than 21 days) have strong circadian rhythms; they are active during the day, and sleep during the night. We explored whether young bees (∼3 days of age), which are typically active around-the-clock with no circadian rhythms, also exhibit sleep behavior. We combined 24-hour video recordings,detailed behavioral observations, and analyses of response thresholds to a light pulse for individually housed bees in various arousal states. We characterized three sleep stages in foragers on the basis of differences in body posture, bout duration, antennae movements and response threshold. Young bees exhibited sleep behavior consisting of the same three stages as observed in foragers. Sleep was interrupted by brief awakenings, which were as frequent in young bees as in foragers. Beyond these similarities, we found differences in the sleep architecture of young bees and foragers. Young bees passed more frequently between the three sleep stages, and stayed longer in the lightest sleep stage than foragers. These differences in sleep architecture may represent developmental and/or environmentally induced variations in the neuronal network underlying sleep in honeybees. To the best of our knowledge,this is the first evidence for plasticity in sleep behavior in insects.

Differential effects of acute alcohol on EEG and sedative responses in adolescent and adult Wistar rats

Age-related developmental differences in sensitivity to the acute effects of alcohol may play an important role in the development of alcoholism. The present study was designed to evaluate the acute effects of alcohol on cortical electroencephalogram (EEG) in adolescent (P36) and adult (P78) Wistar rats. Five minutes of EEG was recorded after administration of 0, 0.75 or 1.5 g/kg alcohol. The righting reflex was performed to measure the sedative effects of alcohol (3.5 g/kg) and total sleeping time for each rat. Our results showed that alcohol (1.5 g/kg) increased power in the 1-2 Hz band and decreased the power in the 32-50 Hz band in the parietal cortical region of adolescent rats. Alcohol (1.5 g/kg) also increased stability of the EEG power in the slow-wave frequency bands (2-4 Hz, 4-6 Hz, and 6-8 Hz) of adolescent rats. In the frontal cortex of adult rats, but not in adolescent rats, alcohol (1.5 or 0.75 g/kg) decreased the power in the 16-32 Hz frequency band. Alcohol (1.5 g/kg) differentially increased power in a multiple of slow-wave frequency bands (2-4 Hz and 4-6 Hz) in the parietal cortex of adult rats as compared to adolescent rats. Adolescent rats were shown significantly shorter sleeping time and higher blood alcohol levels after regaining reflex than adult rats. Our results provide additional evidence of age-related differences in the effects of acute alcohol on cortical EEG, sedation and tolerance.

CAP, epilepsy and motor events during sleep: the unifying role of arousal

Arousal systems play a topical neurophysiologic role in protecting and tailoring sleep duration and depth. When they appear in NREM sleep, arousal responses are not limited to a single EEG pattern but are part of a continuous spectrum of EEG modifications ranging from high-voltage slow rhythms to low amplitude fast activities. The hierarchic features of arousal responses are reflected in the phase A subtypes of CAP (cyclic alternating pattern) including both slow arousals (dominated by the <1Hz oscillation) and fast arousals (ASDA arousals). CAP is an infraslow oscillation with a periodicity of 20-40s that participates in the dynamic organization of sleep and in the activation of motor events. Physiologic, paraphysiologic and pathologic motor activities during NREM sleep are always associated with a stereotyped arousal pattern characterized by an initial increase in EEG delta power and heart rate, followed by a progressive activation of faster EEG frequencies. These findings suggest that motor patterns are already written in the brain codes (central pattern generators) embraced with an automatic sequence of EEG-vegetative events, but require a certain degree of activation (arousal) to become visibly apparent. Arousal can appear either spontaneously or be elicited by internal (epileptic burst) or external (noise, respiratory disturbance) stimuli. Whether the outcome is a physiologic movement, a muscle jerk or a major epileptic attack will depend on a number of ongoing factors (sleep stage, delta power, neuro-motor network) but all events share the common trait of arousal-activated phenomena.

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.

CAP and arousals are involved in the homeostatic and ultradian sleep processes

There is growing evidence that cyclic alternating pattern (CAP) and arousals are woven into the basic mechanisms of sleep regulation. In the present study, the overnight sleep cycles (SC) of 20 normal subjects were analyzed according to their stage composition, CAP rate, phase A subtypes and arousals. Individual SC were then divided into 10 normalized temporal epochs. CAP parameters and arousals were measured in each epoch and averaged in relation to the SC order. Subtypes A2 and A3 of CAP in non-rapid eye movement (NREM) sleep, and arousals, both in REM and NREM sleep when not coincident with a A2 or A3 phases, were lumped together as fast electroencephalographic (EEG) activities (FA). Subtypes A1 of CAP, characterized by slow EEG activities (SA), were analyzed separately. The time distribution of SA and FA was compared to the mathematical model of normal sleep structure including functions representing the homeostatic process S, the circadian process C, the ultradian process generating NREM/REM cycles and the slow wave activity (SWA) resulting from the interaction between homeostatic and ultradian processes. The relationship between SA and FA and the sleep-model components was evaluated by multiple regression analysis in which SA and FA were considered as dependent variables while the covariates were the process S, process C, SWA, REM-on and REM-off activities and their squared values. Regression was highly significant (P < 0.0001) for both SA and FA. SA were prevalent in the first three SC, and exhibited single or multiple peaks immediately before and in the final part of deep sleep (stages 3 + 4). The peaks of FA were delayed and prevailed during the pre-REM periods of light sleep (stages 1 + 2) and during REM sleep. SA showed an exponential decline across the successive SC, according to the homeostatic process. In contrast, the distribution of FA was not influenced by the order of SC, with periodic peaks of FA occurring before the onset of REM sleep, in accordance with the REM-on switch. The dynamics of CAP and arousals during sleep can be viewed as an intermediate level between cellular activities and macroscale EEG phenomena as they reflect the decay of the homeostatic process and the interaction between REM-off and REM-on mechanisms while are slightly influenced by circadian rhythm.

CNS determinants of sleep-related worsening of airway functions: implications for nocturnal asthma

This review summarizes the recent neuroanatomical and physiological studies that form the neural basis for the state-dependent changes in airway resistance. Here, we review only the interactions between the brain regions generating quiet (non-rapid eye movement, NREM) and active (rapid eye movement, REM) sleep stages and CNS pathways controlling cholinergic outflow to the airways. During NREM and REM sleep, bronchoconstrictive responses are heightened and conductivity of the airways is lower as compared to the waking state. The decrease in conductivity of the lower airways parallels the sleep-induced decline in the discharge of brainstem monoaminergic cell groups and GABAergic neurons of the ventrolateral periaqueductal midbrain region, all of which provide inhibitory inputs to airway-related vagal preganglionic neurons (AVPNs). Withdrawal of central inhibitory influences to AVPNs results in a shift from inhibitory to excitatory transmission that leads to an increase in airway responsiveness, cholinergic outflow to the lower airways and consequently, bronchoconstriction. In healthy subjects, these changes are clinically unnoticed. However, in patients with bronchial asthma, sleep-related alterations in lung functions are troublesome, causing intensified bronchopulmonary symptoms (nocturnal asthma), frequent arousals, decreased quality of life, and increased mortality. Unquestionably, the studies revealing neural mechanisms that underlie sleep-related alterations of airway function will provide new directions in the treatment and prevention of sleep-induced worsening of airway diseases.

The rhythm of rest and excess

There is a stark contrast between our attitudes to sleep and those of the pre-industrial age. In Shakespeare's Julius Caesar we are told to "Enjoy the honey-heavy dew of slumber". There seems little chance of this today, as we crave more, work more and expect more, and, in the process, abandon sleep. Our occupation of the night is having unanticipated costs for both our physical and mental health, which, if continued, might condemn whole sectors of our society to a dismal future.

Spectral Power Time-courses of Human Sleep EEG Reveal a Striking Discontinuity at ∼18 Hz Marking the Division between NREM-specific and Wake/REM-specific Fast Frequency Activity

Spectral power time-courses over the ultradian cycle of the sleep electroencephalogram (EEG) provide a useful window for exploring the temporal correlation between cortical EEG and sub-cortical neuronal activities. Precision in the measurement of these time-courses is thus important, but it is hampered by lacunae in the definition of the frequency band limits that are in the main based on wake EEG conventions. A frequently seen discordance between the shape of the beta power time-course across the ultradian cycle and that reported for the sequential mean firing rate of brainstem-thalamic activating neurons invites a closer examination of these band limits, especially since the sleep EEG literature indicates in several studies an intriguing non-uniformity of time-course comportment across the traditional beta band frequencies. We ascribe this tentatively to the sharp reversal of slope we have seen at approximately 18 Hz in our data and that of others. Here, therefore, using data for the first four ultradian cycles from 18 healthy subjects, we apply several criteria based on changes in time-course comportment in order to examine this non-uniformity as we move in 1 Hz bins through the frequency range 14-30 Hz. The results confirm and describe in detail the striking discontinuity of shape at around 18 Hz, with only the upper range (18-30 Hz) displaying a time-course similar to that of the firing-rate changes measured in brainstem activating neurons and acknowledged to engender states of brain activation. Fast frequencies in the lower range (15-18 Hz), on the other hand, are shown to be specific to non-rapid-eye-movement sleep. Splitting the beta band at approximately 18 Hz therefore permits a significant improvement in EEG measurement and a more precise correlation with cellular activity.