Slow Oscillation Amplitudes and Up-State Lengths Relate to Memory Improvement

There is growing evidence of the active involvement of sleep in memory consolidation. Besides hippocampal sharp wave-ripple complexes and sleep spindles, slow oscillations appear to play a key role in the process of sleep-associated memory consolidation. Furthermore, slow oscillation amplitude and spectral power increase during the night after learning declarative and procedural memory tasks. However, it is unresolved whether learning-induced changes specifically alter characteristics of individual slow oscillations, such as the slow oscillation up-state length and amplitude, which are believed to be important for neuronal replay. 24 subjects (12 men) aged between 20 and 30 years participated in a randomized, within-subject, multicenter study. Subjects slept on three occasions for a whole night in the sleep laboratory with full polysomnography. Whereas the first night only served for adaptation purposes, the two remaining nights were preceded by a declarative word-pair task or by a non-learning control task. Slow oscillations were detected in non-rapid eye movement sleep over electrode Fz. Results indicate positive correlations between the length of the up-state as well as the amplitude of both slow oscillation phases and changes in memory performance from pre to post sleep. We speculate that the prolonged slow oscillation up-state length might extend the timeframe for the transfer of initial hippocampal to long-term cortical memory representations, whereas the increase in slow oscillation amplitudes possibly reflects changes in the net synaptic strength of cortical networks.     

Polygenic impact of morningness on the overnight dynamics of sleep spindle amplitude

Sleep spindles are thalamocortical oscillations that contribute to sleep maintenance and sleep‐related brain plasticity. The current study is an explorative study of the circadian dynamics of sleep spindles in relation to a polygenic score (PGS) for circadian preference towards morningness. The participants represent the 17‐year follow‐up of a birth cohort having both genome‐wide data and an ambulatory sleep electroencephalography measurement available ( N = 154, Mean age = 16.9, SD = 0.1 years, 57% girls). Based on a recent genome‐wide association study, we calculated a PGS for circadian preference towards morningness across the whole genome, including 354 single‐nucleotide polymorphisms. Stage 2 slow (9‐12.5 Hz, N = 186 739) and fast (12.5‐16 Hz, N = 135 504) sleep spindles were detected using an automated algorithm with individual time tags and amplitudes for each spindle. There was a significant interaction of PGS for morningness and timing of sleep spindles across the night. These growth curve models showed a curvilinear trajectory of spindle amplitudes: those with a higher PGS for morningness showed higher slow spindle amplitudes in frontal derivations, and a faster dissipation of spindle amplitude in central derivations. Overall, the findings provide new evidence on how individual sleep spindle trajectories are influenced by genetic factors associated with circadian type. The finding may lead to new hypotheses on the associations previously observed between circadian types, psychiatric problems and spindle activity.     

Passive perception of auditory stimuli in healthy and mild mentally retarded adolescents from Northern Russia

Event-related potentials (ERPs) during passive perception of auditory stimuli were studied using the oddball paradigm in healthy and mild mentally retarded adolescents. The study involved 25 subjects aged 11–15 (13.1 ± 1.4) years from Northern Russia, including Arctic regions. The peak latency of the difference wave for deviant and standard stimuli in frontal central derivation was 129 ± 21 ms in the healthy children, and the mean amplitude was–2.6 ± 1.3 μV. In the mentally retarded group, a negative peak of the difference wave was observed only in 9 out of 13 adolescents, its latency was more than in the healthy adolescents (156 ± 29 ms), and the mean amplitude was–2.1 ± 1.4 μV. Differences in perception of deviant and standard stimuli were observed in the healthy adolescents, in particular, along the central line. In the adolescents with mental disorders, there was no significant difference in the fronto-central and central derivations. A discriminant analysis of the amplitudes of ERP components observed in the fronto-central derivations in response to deviant stimuli and the difference in amplitude between ERPs evoked in the fronto-central derivation by standard and deviant stimuli differentiated the adolescents with and without mental disorders. Based on the findings, ERP components in the oddball paradigm were assumed to provide potential markers of disorders in mental development.     

Evidence for fractal correlation properties in variations of peripheral arterial tone during REM sleep

Previous studies utilizing detrended fluctuation analysis (DFA) of heart rate variability during sleep revealed a higher fractal exponent during rapid eye movement (REM) sleep than non-REM sleep. The aim of this study was to determine whether the same difference exists in the variations of peripheral arterial tone (PAT). Finger pulse wave measured by a novel plethysmographic technique was monitored during sleep in 12 chronic heart failure patients, 8 heavy snorers, and 12 healthy volunteers. For each subject, at least two 15-min time series were constructed from the interpulse intervals and from pulse wave amplitudes during REM and non-REM sleep. Fractal scaling exponents of both types of time series were significantly higher for REM than non-REM sleep in all groups. In each of the groups and in both sleep stages, the fractal scaling exponents based on pulse wave amplitude were significantly higher than those based on pulse rate variability. A repeat of the analysis for short-, intermediate-, and long-term intervals revealed that the fractal-like exponents were evident only in the short- and intermediate-term intervals. Because PAT is a surrogate of sympathetic activation, our results indicate that variations in sympathetic activation during REM sleep have a fractal-like behavior.     

Inter-Hemispheric Oscillations in Human Sleep

Sleep is generally categorized into discrete stages based on characteristic electroencephalogram (EEG) patterns. This traditional approach represents sleep architecture in a static way, but it cannot reflect variations in sleep across time and across the cortex. To investigate these dynamic aspects of sleep, we analyzed sleep recordings in 14 healthy volunteers with a novel, frequency-based EEG analysis. This approach enabled comparison of sleep patterns with low inter-individual variability. We then implemented a new probability dependent, automatic classification of sleep states that agreed closely with conventional manual scoring during consolidated sleep. Furthermore, this analysis revealed a previously unrecognized, interhemispheric oscillation during rapid eye movement (REM) sleep. This quantitative approach provides a new way of examining the dynamic aspects of sleep, shedding new light on the physiology of human sleep.     

Single-trial ERP evidence for the three-stage scheme of facial expression processing

Using a rapid serial visual presentation paradigm, we previously showed that the average amplitudes of six event-related potential (ERP) components were affected by different categories of emotional faces. In the current study, we investigated the six discriminating components on a single-trial level to clarify whether the amplitude difference between experimental conditions results from a difference in the real variability of single-trial amplitudes or from latency jitter across trials. It is found that there were consistent amplitude differences in the single-trial P1, N170, VPP, N3, and P3 components, demonstrating that a substantial proportion of the average amplitude differences can be explained by the pure variability in amplitudes on a single-trial basis between experimental conditions. These single-trial results verified the three-stage scheme of facial expression processing beyond multitrial ERP averaging, and showed the three processing stages of "fear popup", "emotional/unemotional discrimination", and "complete separation" based on the single-trial ERP dynamics.     

Circadian preference modulates the neural substrate of conflict processing across the day

Human morning and evening chronotypes differ in their preferred timing for sleep and wakefulness, as well as in optimal daytime periods to cope with cognitive challenges. Recent evidence suggests that these preferences are not a simple by-product of socio-professional timing constraints, but can be driven by inter-individual differences in the expression of circadian and homeostatic sleep-wake promoting signals. Chronotypes thus constitute a unique tool to access the interplay between those processes under normally entrained day-night conditions, and to investigate how they impinge onto higher cognitive control processes. Using functional magnetic resonance imaging (fMRI), we assessed the influence of chronotype and time-of-day on conflict processing-related cerebral activity throughout a normal waking day. Sixteen morning and 15 evening types were recorded at two individually adapted time points (1.5 versus 10.5 hours spent awake) while performing the Stroop paradigm. Results show that interference-related hemodynamic responses are maintained or even increased in evening types from the subjective morning to the subjective evening in a set of brain areas playing a pivotal role in successful inhibitory functioning, whereas they decreased in morning types under the same conditions. Furthermore, during the evening hours, activity in a posterior hypothalamic region putatively involved in sleep-wake regulation correlated in a chronotype-specific manner with slow wave activity at the beginning of the night, an index of accumulated homeostatic sleep pressure. These results shed light into the cerebral mechanisms underlying inter-individual differences of higher-order cognitive state maintenance under normally entrained day-night conditions.     

Human gamma oscillations during slow wave sleep

Neocortical local field potentials have shown that gamma oscillations occur spontaneously during slow-wave sleep (SWS). At the macroscopic EEG level in the human brain, no evidences were reported so far. In this study, by using simultaneous scalp and intracranial EEG recordings in 20 epileptic subjects, we examined gamma oscillations in cerebral cortex during SWS. We report that gamma oscillations in low (30-50 Hz) and high (60-120 Hz) frequency bands recurrently emerged in all investigated regions and their amplitudes coincided with specific phases of the cortical slow wave. In most of the cases, multiple oscillatory bursts in different frequency bands from 30 to 120 Hz were correlated with positive peaks of scalp slow waves ("IN-phase" pattern), confirming previous animal findings. In addition, we report another gamma pattern that appears preferentially during the negative phase of the slow wave ("ANTI-phase" pattern). This new pattern presented dominant peaks in the high gamma range and was preferentially expressed in the temporal cortex. Finally, we found that the spatial coherence between cortical sites exhibiting gamma activities was local and fell off quickly when computed between distant sites. Overall, these results provide the first human evidences that gamma oscillations can be observed in macroscopic EEG recordings during sleep. They support the concept that these high-frequency activities might be associated with phasic increases of neural activity during slow oscillations. Such patterned activity in the sleeping brain could play a role in off-line processing of cortical networks.     

Changes in components of the auditory long-latency evoked potentials at different stages of the slow-wave sleep

In accordance with the present views, during sleep, analysis of external stimuli continues at the subconscious level, because the need to estimate the biological significance of external stimuli in order to maintain a flexible contact of a sleeping subject with the environment persists during sleep. It is known that new components of the auditory evoked potentials (AEP) appear as sleep deepens. However, the common procedure of analysis of event-related potentials averaged for a group of subjects has some drawbacks because of the interindividual variability of the event-related potentials. Therefore, an additional analysis of the interindividual variability of the AEP shape and component structure can simplify the detection of individual components of group-averaged AEP at different stages of the slow-wave sleep. The AEPs were recorded in healthy volunteers (n = 26) during falling asleep in the evening from eight EEG derivations (F3, F4, C3, C4, P3, P4, O1, O2) in reference to a linked mastoid electrode. Computer-generated sound stimuli (50 ms-pulses with the frequency of 1000 Hz, 60 dB HL) were presented binaurally through earphones with interstimulus intervals of 20-40 s. Selective summation of AEPs for all the subjects was performed for each stage of the slow-wave sleep individually for each of the eight derivations. It was shown that the account made for interindividual variability of the AEP shape facilitated the identification of individual components of the group-averaged AEP typical of wakefulness (P1, N1, P300) and those which appeared during sleep onset and at different stages of the slow-wave sleep (P2, N350, P450, N550, N900).     

Shift work and inter-individual differences in sleep and sleepiness

Inter-individual differences in tolerance for shift work have been studied primarily in terms of external factors affecting alertness on the job or the ability to rest and sleep while at home. However, there is increasing evidence that neurobiological factors play a role as well, particularly the major processes involved in the regulation of sleep and wakefulness. These include a sleep homeostatic process seeking to balance wakefulness and sleep and a circadian process seeking to promote wakefulness during the day and sleep during the night. Shift work is associated with a temporal misalignment of these two endogenous processes. During nightwork, this misalignment makes it difficult to stay awake during the nightshift and sleep during the day. However, inter-individual variability in the processes involved in sleep/wake regulation is substantial. Recent studies have demonstrated the existence of inter-individual differences in vulnerability to cognitive deficits from sleep loss. Moreover, these inter-individual differences were shown to constitute a trait. Interestingly, self-evaluations of sleepiness did not correspond well with the trait inter-individual variability in objective levels of performance impairment during sleep deprivation. Perhaps because of this discrepancy, in operational settings, the inter-individual differences in vulnerability to sleep loss do not appear to be limited due to self-selection mechanisms. Indeed, even among a highly select group of active-duty jet fighter pilots flying a series of simulated night missions, systematic inter-individual differences in performance impairment from sleep loss were still observed. There are significant personal and economic consequences to human error and accidents caused by performance deficits due to sleep loss. It is important, therefore, to study the inter-individual differences in the regulation of sleep and wakefulness in the work environment so that cognitive impairment during shift work may be better anticipated and prevented.     

Sleep/Wake Dynamics Changes during Maturation in Rats

Objectives

Conventional scoring of sleep provides little information about the process of transitioning between vigilance states. We applied the state space technique (SST) using frequency band ratios to follow normal maturation of different sleep/wake states, velocities of movements, and transitions between states of juvenile (postnatal day 34, P34) and young adult rats (P71).

Design

24-h sleep recordings of eight P34 and nine P71 were analyzed using conventional scoring criteria and SST one week following implantation of telemetric transmitter. SST is a non-categorical approach that allows novel quantitative and unbiased examination of vigilance-states dynamics and state transitions. In this approach, behavioral changes are described in a 2-dimensional state space that is derived from spectral characteristics of the electroencephalography.

Measurements and Results

With maturation sleep intensity declines, the duration of deep slow wave sleep (DSWS) and light slow wave sleep (LSWS) decreases and increases, respectively. Vigilance state determination, as a function of frequency, is not constant; there is a substantial shift to higher ratio 1 in all vigilance states except DSWS. Deep slow wave sleep decreases in adult relative to juvenile animals at all frequencies. P71 animals have 400% more trajectories from Wake to LSWS (p = 0.005) and vice versa (p = 0.005), and 100% more micro-arousals (p = 0.021), while trajectories from LSWS to DSWS (p = 0.047) and vice versa (p = 0.033) were reduced by 60%. In both juvenile and adult animals, no significant changes were found in sleep velocity at all regions of the 2-dimensional state space plot; suggesting that maturation has a partial effect on sleep stability.

Conclusions

Here, we present novel and original evidence that SST enables visualization of vigilance-state intensity, transitions, and velocities that were not evident by traditional scoring methods. These observations provide new perspectives in sleep state dynamics and highlight the usefulness of this technique in exploring the development of sleep-wake activity.     

Oscillations in the oxidation-reduction potential of the brain tissue in rats developing during wakefulness and slow-wave sleep

Variations of the brain cortex redox state potential (E) were recorded in freely moving white rats (mass of 300-350 g) with implanted platinum electrodes (with the platinum reference electrode in the nasal bone) during sleep-wake cycles. It was found that transitions from the slow-wave sleep to wakefulness were accompanied in the number of cortical areas (metabolic-active sites) by the E rise, while the transitions from the wakefulness to slow-ware sleep were associated with a drop of E. However, the episodes of the short-term arousals during the slow-wave sleep were accompanied by the respective decreases in E thus forming the irregular E variations (1.5-3 min in duration). It was also found that the oscillations of a typical pattern (quasisinusoidal with the frequency of 10-20 osc/min and the amplitudes up to several mV) could take place in the metabolic-active cortical sites. These oscillations were defined as fast E oscillations. During the slow-wave sleep, the less regular oscillations with the lower frequency (1.2-10 osc/min) and higher amplitude were recorded in the same cortical sites. These oscillations were defined as slow. It is suggested that the fast metabolic oscillations of wakefulness are mainly controlled by the mitochondria of neuronal populations, whereas the slow metabolic oscillations which occur in the slow-wave sleep are related with glycolysis in populations of glial cells.     

Description of an EEG pattern evoked in central--parietal areas by the Hathayogic exercise Agnisara

Agnisara is a Hathayogic exercise consisting essentially in alternate, forceful retractions and protrusions of the abdominal wall, performed along a 20-30 s period of apnoea. In the course of series of Agnisars spindle bursts of a "wicket" EEG wave pattern developed over the para-Rolandic areas of the cerebral cortex, at frequencies around 12-13 Hz, with waxing and waning amplitudes in the range of 50 to 100 microV. These spindle-bursts, which occurred preferably during the phase of retraction of the abdominal wall, were named "Xi" rhythm (after the Greek letter X). It is the same as the one that regularly accompanies the performance on various other Hathayogic exercises. Xi spindles were recorded in linked earlobe reference derivations from areas located bilaterally midway between F-C, C-P, and P-O standard electrode positions of the 10-20 system. This EEG pattern would be considered as the expression of the central excitation, produced by the exercise's long-lasting and repeated stimulation of visceral, and somatic receptors. Thus, this activation affects mainly cortical structures with somato-visceral representation.     

Somatosensory evoked potentials in the sleep-wakefulness cycle in healthy subjects and narcolepsy patients]

Studies of somatosensory evoked potentials (SSEPs) were conducted in various functional states of sleep-alertness cycle (relaxed alertness, 2-nd and delta-stages of slow sleep, rapid sleep) in 7 healthy subjects and 8 patients with polysymptom narcolepsy. Integrated amplitude (IA) was calculated in poststimulus intervals, accordingly to SSEPs division into groups of early (20-80 ms), mean (80-200 ms) and late (200-400 ms) components. It has been shown that in patients with polysymptom narcolepsy IA of all SSEPs components in alertness was lower than in healthy subjects; during sleep higher IA values of earlier components were found in comparison with healthy subjects and lower values--of later negative wave at slow sleep. Psychophysiological interpretation of high amplitude negative shift in the area of late SSEPs components during slow sleep is suggested.     

The relationship between the parameters of the early and late oscillations of human cortical evoked potentials and the rhythm of acoustic stimulation]

The amplitudes of all deflections of the slow auditory evoked potential (AEP) regularly decrease in alert subjects with the increase of stimulation rate. As compared with the late deflections (P2N2), the decrease of the amplitude of comparatively early deflections (N1P2) is more pronounced. It is a rather logarithmic, than a linear function of the interstimulus interval. The degree of amplitude diminution of slow AEPs due to a greater stimulation rate depends on the intensity of acoustic stimul: at greater sound intensities the decrease is more pronounced. The higher rates of stimulation produce, along with a decreased amplitude, a shorter peak latencies of all slow AEP deflections (except the peak of deflection P1). In narcotic (chloralhydrate) sleep higher rates of stimulation are not attended with any regular changes in the amplitude and peak latencies of the slow AEP.     

The effects of specific respiratory rates on heart rate and heart rate variability

In this study respiratory rates of 3, 4, 6, 8, 10, 12, and 14 breaths per minute were employed to investigate the effects of these rates on heart rate variability (HRV). Data were collected 16 times at each respiratory rate on 3 female volunteers, and 12 times on 2 female volunteers. Although mean heart rates did not differ among these respiratory rates, respiratory-induced trough heart rates at 4 and 6 breaths per minute were significantly lower than those at 14 breaths per minute. Slower respiratory rates usually produced higher amplitudes of HRV than did faster respiratory rates. However, the highest amplitudes were at 4 breaths per minute. HRV amplitude decreased at 3 breaths per minute. The results are interpreted as reflecting the possible effects of the slow rate of acetylcholine metabolism and the effect of negative resonance at 3 cycles per minute.     

Inter-Individual Differences in Neurobehavioural Impairment following Sleep Restriction Are Associated with Circadian Rhythm Phase

Although sleep restriction is associated with decrements in daytime alertness and neurobehavioural performance, there are considerable inter-individual differences in the degree of impairment. This study examined the effects of short-term sleep restriction on neurobehavioural performance and sleepiness, and the associations between individual differences in impairments and circadian rhythm phase. Healthy adults (n = 43; 22 M) aged 22.5 ± 3.1 (mean ± SD) years maintained a regular 8:16 h sleep:wake routine for at least three weeks prior to laboratory admission. Sleep opportunity was restricted to 5 hours time-in-bed at home the night before admission and 3 hours time-in-bed in the laboratory, aligned by wake time. Hourly saliva samples were collected from 5.5 h before until 5 h after the pre-laboratory scheduled bedtime to assess dim light melatonin onset (DLMO) as a marker of circadian phase. Participants completed a 10-min auditory Psychomotor Vigilance Task (PVT), the Karolinska Sleepiness Scale (KSS) and had slow eye movements (SEM) measured by electrooculography two hours after waking. We observed substantial inter-individual variability in neurobehavioural performance, particularly in the number of PVT lapses. Increased PVT lapses (r = -0.468, p < 0.01), greater sleepiness (r = 0.510, p < 0.0001), and more slow eye movements (r = 0.375, p = 0.022) were significantly associated with later DLMO, consistent with participants waking at an earlier circadian phase. When the difference between DLMO and sleep onset was less than 2 hours, individuals were significantly more likely to have at least three attentional lapses the following morning. This study demonstrates that the phase of an individual’s circadian system is an important variable in predicting the degree of neurobehavioural performance impairment in the hours after waking following sleep restriction, and confirms that other factors influencing performance decrements require further investigation.     

Water wave discrimination in the surface-feeding fish Aplocheilus lineatus

The surface-feeding fish Aplocheilus lineatus uses its cephalic lateral line to detect water surface waves caused by prey insects. The ability of Aplocheilus to discriminate between surface waves with aid of the lateral line system was tested by go/no-go conditioning. Our results show that Aplocheilus can distinguish between single-frequency surface wave stimuli with equal velocity or equal acceleration amplitudes which differ only in frequency. Frequency difference limens were about 15%, i.e. fish distinguished a 20-Hz wave stimulus from a 23-Hz stimulus in 100% of the trials. Aplocheilus can also discriminate between pure sine-wave stimuli and sine waves which show abrupt frequency changes. In contrast, fish were unable to distinguish amplitude-modulated wave stimuli (carrier frequency 20, 40 and 60 Hz, modulation frequency 10 and 20 Hz) from pure sine waves of the same frequency, even if amplitude modulation depth was 80%. Accepted: 27 December 1996     

Morning and evening-type differences in slow waves during NREM sleep reveal both trait and state-dependent phenotypes

Brain recovery after prolonged wakefulness is characterized by increased density, amplitude and slope of slow waves (SW, <4 Hz) during non-rapid eye movement (NREM) sleep. These SW comprise a negative phase, during which cortical neurons are mostly silent, and a positive phase, in which most neurons fire intensively. Previous work showed, using EEG spectral analysis as an index of cortical synchrony, that Morning-types (M-types) present faster dynamics of sleep pressure than Evening-types (E-types). We thus hypothesized that single SW properties will also show larger changes in M-types than in E-types in response to increased sleep pressure. SW density (number per minute) and characteristics (amplitude, slope between negative and positive peaks, frequency and duration of negative and positive phases) were compared between chronotypes for a baseline sleep episode (BL) and for recovery sleep (REC) after two nights of sleep fragmentation. While SW density did not differ between chronotypes, M-types showed higher SW amplitude and steeper slope than E-types, especially during REC. SW properties were also averaged for 3 NREM sleep periods selected for their decreasing level of sleep pressure (first cycle of REC [REC1], first cycle of BL [BL1] and fourth cycle of BL [BL4]). Slope was significantly steeper in M-types than in E-types in REC1 and BL1. SW frequency was consistently higher and duration of positive and negative phases constantly shorter in M-types than in E-types. Our data reveal that specific properties of cortical synchrony during sleep differ between M-types and E-types, although chronotypes show a similar capacity to generate SW. These differences may involve 1) stable trait characteristics independent of sleep pressure (i.e., frequency and durations) likely linked to the length of silent and burst-firing phases of individual neurons, and 2) specific responses to increased sleep pressure (i.e., slope and amplitude) expected to depend on the synchrony between neurons.