Quantification of Sleepiness Through Principal Component Analysis of the Electroencephalographic Spectrum

Although circadian and sleep research has made extraordinary progress in the recent years, one remaining challenge is the objective quantification of sleepiness in individuals suffering from sleep deprivation, sleep restriction, and excessive somnolence. The major goal of the present study was to apply principal component analysis to the wake electroencephalographic (EEG) spectrum in order to establish an objective measure of sleepiness. The present analysis was led by the hypothesis that in sleep-deprived individuals, the time course of self-rated sleepiness correlates with the time course score on the 2nd principal component of the EEG spectrum. The resting EEG of 15 young subjects was recorded at 2-h intervals for 32–50?h. Principal component analysis was performed on the sets of 16 single-Hz log-transformed EEG powers (1–16?Hz frequency range). The time course of self-perceived sleepiness correlated strongly with the time course of the 2nd principal component score, irrespective of derivation (frontal or occipital) and of analyzed section of the 7-min EEG record (2-min section with eyes open or any of the five 1-min sections with eyes closed). This result indicates the possibility of deriving an objective index of physiological sleepiness by applying principal component analysis to the wake EEG spectrum. (Author correspondence: putilov@ngs.ru)     

Evidence for age-associated disinhibition of the wake drive provided by scoring principal components of the resting EEG spectrum in sleep-provoking conditions

Age-associated changes in different bandwidths of the human electroencephalographic (EEG) spectrum are well documented, but their functional significance is poorly understood. This spectrum seems to represent summation of simultaneous influences of several sleep–wake regulatory processes. Scoring of its orthogonal (uncorrelated) principal components can help in separation of the brain signatures of these processes. In particular, the opposite age-associated changes were documented for scores on the two largest (1st and 2nd) principal components of the sleep EEG spectrum. A decrease of the first score and an increase of the second score can reflect, respectively, the weakening of the sleep drive and disinhibition of the opposing wake drive with age. In order to support the suggestion of age-associated disinhibition of the wake drive from the antagonistic influence of the sleep drive, we analyzed principal component scores of the resting EEG spectra obtained in sleep deprivation experiments with 81 healthy young adults aged between 19 and 26 and 40 healthy older adults aged between 45 and 66 years. At the second day of the sleep deprivation experiments, frontal scores on the 1st principal component of the EEG spectrum demonstrated an age-associated reduction of response to eyes closed relaxation. Scores on the 2nd principal component were either initially increased during wakefulness or less responsive to such sleep-provoking conditions (frontal and occipital scores, respectively). These results are in line with the suggestion of disinhibition of the wake drive with age. They provide an explanation of why older adults are less vulnerable to sleep deprivation than young adults.     

Principal components of electroencephalographic spectrum as markers of opponent processes underlying ultradian sleep cycles

Sleep-wake regulation involves reciprocal interactions between sleep- and wake-promoting processes that inhibit one another. To uncover the signatures of the opponent processes underlying ultradian sleep cycles, principal component analysis was performed on the sets of 16 single-Hz log-transformed electroencephalographic (EEG) power densities (1-16?Hz frequency range). Data were collected during unrestricted night sleep followed by 9 20-min naps (14 women aged 17-55 yrs) and during 12 20-min naps after either restriction or deprivation of sleep (9 males and 9 males, respectively, aged 18-22 yrs). It was found that any subset of power spectra could be reduced to the invariant four-principal component structure. The time courses of scores on these four components might be interpreted as the spectral EEG markers of the kinetics of two pairs of opponent chronoregulatory processes. In a sequence of ultradian sleep cycles, the 1st and 2nd components represent the alternations between competing drives for sleep and wakefulness, respectively, whereas the 3rd and 4th components reflect the alternations between light and deep sleep, respectively. The results suggest that principal component structuring of EEG spectrum can be employed for derivation of the parameters of the quantitative models conceptualizing the three major aspects of sleep-wake regulation—homeostatic, circadian, and ultradian processes.     

Spectral EEG indicator of pressure to enter into deep sleep: its responsiveness to closing the eyes for just a few minutes exhibits a pure exponential buildup during sleep deprivation

According to the two-process model of sleep–wake regulation, a homeostatic sleep pressure, i.e. a pressure to enter into deep non-rapid eyes movement (NREM) sleep, must exhibit a purely exponential buildup during prolonged wakefulness. However, this pressure is usually measured indirectly, i.e. during the following episode of actual deep NREM sleep. The purpose of this paper was to show that, despite a prominent circadian modulation of time course of any waking EEG index, the model-postulated purely exponential buildup of the homeostatic sleep pressure can be directly confirmed. During two days of sleep deprivation experiments, the EEG of healthy adults (N = 30) was recorded every other hour throughout 5-min eyes closed relaxation. Sixteen ln-transformed single-Hz power densities (from 1 to 16 Hz) were computed for each of 5 one-min intervals. Differences between these densities obtained for the first and the following intervals were calculated and averaged. The obtained 16 values were used as the frequency weighting curve for weighting densities of each set of 16 single-Hz power densities. Summing-up of these weighted densities provided a single measure that was found to co-vary with self-rated sleepiness throughout two-day interval of sleep deprivation, thus reflecting the joint influence of the circadian and homeostatic processes. However, two-day time course of responsiveness of this measure to closing the eyes for just a few minutes exhibited a purely exponential buildup. It was concluded that this result provided a direct experimental confirmation of the model-predicted exponential buildup of the homeostatic sleep pressure across prolonged episode of wakefulness.     

Principal Components of Electroencephalographic Spectrum as Markers of Opponent Processes Underlying Ultradian Sleep Cycles

Sleep-wake regulation involves reciprocal interactions between sleep- and wake-promoting processes that inhibit one another. To uncover the signatures of the opponent processes underlying ultradian sleep cycles, principal component analysis was performed on the sets of 16 single-Hz log-transformed electroencephalographic (EEG) power densities (1–16?Hz frequency range). Data were collected during unrestricted night sleep followed by 9 20-min naps (14 women aged 17–55 yrs) and during 12 20-min naps after either restriction or deprivation of sleep (9 males and 9 males, respectively, aged 18–22 yrs). It was found that any subset of power spectra could be reduced to the invariant four–principal component structure. The time courses of scores on these four components might be interpreted as the spectral EEG markers of the kinetics of two pairs of opponent chronoregulatory processes. In a sequence of ultradian sleep cycles, the 1st and 2nd components represent the alternations between competing drives for sleep and wakefulness, respectively, whereas the 3rd and 4th components reflect the alternations between light and deep sleep, respectively. The results suggest that principal component structuring of EEG spectrum can be employed for derivation of the parameters of the quantitative models conceptualizing the three major aspects of sleep-wake regulation—homeostatic, circadian, and ultradian processes. (Author correspondence: putilov@ngs.ru)     

A new SWPAQ's scale predicts the effects of sleep deprivation on the segmental structure of alpha waves

The three-dimensional cube-in-globe model predicts the possibility to delineate six main adaptive abilities of the sleep - wake cycle (Putilov & Putilov, 2005). Such prediction led to the inclusion of a new sixth scale named “daytime wakeability” (Putilov & Putilov, 2006; Putilov, 2007) in the Sleep-Wake Pattern Assessment Questionnaire (SWPAQ; Putilov, 1990, 2000). This new scale permits self-assessment of the ability to keep waking at daytime in sleep provoking conditions. In the study reported here we applied the procedure of adaptive segmentation of the EEG record (SECTION 0.1®, Human Brain Research Group, Moscow State University) to determine whether sleep deprivation changes the temporal pattern of alpha activity and, if yes, whether this change is associated with state and trait self-measures of alertness/sleepiness including a score on “daytime wakeability” scale. In the course of sustained wakefulness, EEG was recorded nine times with three-hour intervals in frontal and occipital derivations in 39 healthy subjects. The procedure of adaptive segmentation allowed cutting EEG records on quasi-stationary segments and determining such characteristics of each segment as within-segmental amplitude, coefficient of its variation and segment length. These characteristics obtained in the morning hours on the first and second experimental days were compared. They were found to increase in the second morning, when eyes are open, but do not change when eyes are closed. It was also documented that “daytime wakeability” score along with other trait and state self-measures of alertness/sleepiness can serve as predictors of the response of alpha waves to sleep deprivation.     

A model-based interpretation of the biphasic daily pattern of sleepiness

We developed a thermoregulatory model of sleep control based on the hypothesis that non-rapid eye-movement sleep participates in homeostatic thermoregulation. This model successfully reproduced several qualitative features of human sleep/wake cycles during entrained as well as the internally desynchronized states. Among the reproduced features, generation mechanisms of the biphasic sleepiness distribution are studied here in the light of the model structure. Harmonic analysis is employed for this purpose. Through linearizations and confining the harmonics of the masking process to the fundamental component, a simplified representation of sleepiness is obtained. The simplified sleepiness is constructed with the fundamental circadian, the second harmonic components, and the constant (DC). The bimodality of the sleepiness is shown to be made by the second harmonic which is added to the fundamental component. The behavior of their amplitudes and phase positions are investigated under the varied sleep/wake durations and phase differences between the oscillators. Since the sleepiness generated by our model is roughly mimicked by the simplified representation under diverse conditions, this simplification can be regarded as adequate. From the behavior of the constituents of respective harmonic components, the fundamental component is shown to originate from the sleep/wake masking process and the circadian oscillators; the second harmonic from the multiplicative interactions between the circadian oscillators and the sleep/wake masking process. These results indicate that the rhythmic processes are principal constituents of the sleepiness, at least in the steady state. Received: 17 July 1997/Accepted in revised form: 6 May 1999     

Longitudinal Change in Sleep and Daytime Sleepiness in Postpartum Women

Sleep disruption strongly influences daytime functioning; resultant sleepiness is recognised as a contributing risk-factor for individuals performing critical and dangerous tasks. While the relationship between sleep and sleepiness has been heavily investigated in the vulnerable sub-populations of shift workers and patients with sleep disorders, postpartum women have been comparatively overlooked. Thirty-three healthy, postpartum women recorded every episode of sleep and wake each day during postpartum weeks 6, 12 and 18. Although repeated measures analysis revealed there was no significant difference in the amount of nocturnal sleep and frequency of night-time wakings, there was a significant reduction in sleep disruption, due to fewer minutes of wake after sleep onset. Subjective sleepiness was measured each day using the Karolinska Sleepiness Scale; at the two earlier time points this was significantly correlated with sleep quality but not to sleep quantity. Epworth Sleepiness Scores significantly reduced over time; however, during week 18 over 50% of participants were still experiencing excessive daytime sleepiness (Epworth Sleepiness Score ≥12). Results have implications for health care providers and policy makers. Health care providers designing interventions to address sleepiness in new mothers should take into account the dynamic changes to sleep and sleepiness during this initial postpartum period. Policy makers developing regulations for parental leave entitlements should take into consideration the high prevalence of excessive daytime sleepiness experienced by new mothers, ensuring enough opportunity for daytime sleepiness to diminish to a manageable level prior to reengagement in the workforce.     

Automatic analysis of sleep using two parameters based on principal component analysis of electroencephalography spectral data

A computer program for the analysis of a sleep electroencephalogram (EEG) is presented. The method relies on two steps. First, a spectral analysis is performed for signals recorded from one or more electrode locations. Then, two EEG parameters are obtained by storing the spectral activity in a multidimensional space, whose dimension is reduced using principal component analysis (PCA) techniques. The main advantage of these parameters is in describing the process of sleep on a continuous scale as a function of time. Validation of the method was performed with the data collected from 16 subjects (8 young volunteers and 8 elderly insomniacs). Results snowed that the parameters correlate highly with the hypnograms established by conventional visual scoring. This signal parametrisation, however, offers more information regarding the time course of sleep, since small variations within individual sleep stages as well as smooth transitions between stages are assessed. Finally, the concurrent use of both parameters provides an original way of considering sleep as a dynamic process evolving cyclically in a single plane.     

Effects of Low Doses of Melatonin on Late Afternoon Napping and Mood

The effects of low doses of melatonin (0.1, 0.5 and 1 mg) given at 16:00 h on induction and quality of sleep in the late afternoon (17:00-21:00 h), as well as on subjective fatigue and mood ratings before and after sleep were studied. Ten healthy male volunteers (age 26-30 years) were given on a double-blind crossover basis, tablets containing melatonin, or placebo, with one day washout between treatments. Mood and fatigue were assessed before and after bedtime. Sleep quality was objectively monitored using wrist-worn actigraphs and subjectively by using sleep logs. Data were analysed by means of analysis of variance for repeated measures with a factor of group (placebo and the three melatonin doses). The analysis revealed dose-dependent increase by melatonin in subjective evaluation of fatigue and sleepiness, and decrease in alertness, efficiency, vigor and concentration before the nap. Melatonin did not significantly affect actigraph-measured nap sleep latency and efficiency but reduced wake time after sleep onset and delayed sleep offset time compared to placebo, Melatonin did not significantly affect sleep latency and sleep efficiency in the night following the treatment. These data indicate acute effects of low doses of melatonin given at 16:00h on sleepiness and fatigue but not on sleep efficiency or latency in healthy young individuals.     

Effects of Low Doses of Melatonin on Late Afternoon Napping and Mood

The effects of low doses of melatonin (0.1, 0.5 and 1 mg) given at 16:00 h on induction and quality of sleep in the late afternoon (17:00-21:00 h), as well as on subjective fatigue and mood ratings before and after sleep were studied. Ten healthy male volunteers (age 26-30 years) were given on a double-blind crossover basis, tablets containing melatonin, or placebo, with one day washout between treatments. Mood and fatigue were assessed before and after bedtime. Sleep quality was objectively monitored using wrist-worn actigraphs and subjectively by using sleep logs. Data were analysed by means of analysis of variance for repeated measures with a factor of group (placebo and the three melatonin doses). The analysis revealed dose-dependent increase by melatonin in subjective evaluation of fatigue and sleepiness, and decrease in alertness, efficiency, vigor and concentration before the nap. Melatonin did not significantly affect actigraph-measured nap sleep latency and efficiency but reduced wake time after sleep onset and delayed sleep offset time compared to placebo, Melatonin did not significantly affect sleep latency and sleep efficiency in the night following the treatment. These data indicate acute effects of low doses of melatonin given at 16:00h on sleepiness and fatigue but not on sleep efficiency or latency in healthy young individuals.     

Effects of activity of daily living and gender on circadian rhythms of the elderly in a nursing home

The objective of this study was to confirm the effects of ADL (Activity of Daily Living) and gender on circadian rhythms of the elderly in a nursing home. Twenty-one elderly volunteers, aged over 65 years, were divided in four groups depending on their ADL and gender: subjects with almost no problem in ADL (H males, H females) and those who were almost bedridden (L males, L females). Oral temperature, heart rate, blood pressure, time of sleep and wake, subjective sleepiness, overall feeling and vitality were measured every 4 hours during the day continuously for six days. The circadian rhythm was calculated by using the least squares fit of cosine function. Subjective sleep quality was also surveyed. In the sleep/wake rhythm, the mesor was significantly higher in L males compared to the other groups and the amplitude was significantly lower in L females compared to other groups. The subjective sleepiness was higher in L males compared to the other groups and L females showed a higher sleepiness compared to H females. No significant difference among the group was observed in subjective sleep quality. In conclusion, these results indicate that the subjective sleepiness and sleep/wake rhythm differ depending on ADL and gender, although no significant difference was observed in physiological parameters. ADL and gender based difference in subjective sleepiness and sleep/wake rhythm should be taken into account with regard to the care of the elderly in nursing homes.     

Individual differences in subjective and objective alertness during sleep deprivation are stable and unrelated

This study examines the individual reproducibility of alterations of subjective, objective, and EEG measures of alertness during 27 h of continuous wakefulness and analyzes their interrelationships. Eight subjects were studied twice under similar constant-routine conditions. Scales and performance tasks were administered at hourly intervals to define temporal changes in subjective and objective alertness. The wake EEG was recorded every 2 h, 2 min with eyes open and 2 min with eyes closed. Plasma glucose and melatonin levels were measured to estimate brain glucose utilization and individual circadian phase, respectively. Decrements of subjective alertness and performance deficits were found to be highly reproducible for a given individual. Remarkably, there was no relationship between the impairments of subjective and objective alertness. With increased duration of wakefulness, EEG activity with eyes closed increased in the delta range and decreased in the alpha range, but the magnitudes of these changes were also unrelated. These findings indicate that sleep deprivation has highly reproducible, but independent, effects on brain mechanisms controlling subjective and objective alertness.     

Duration of sleep inertia after napping during simulated night work and in extended operations

Due to the mixed findings of previous studies, it is still difficult to provide guidance on how to best manage sleep inertia after waking from naps in operational settings. One of the few factors that can be manipulated is the duration of the nap opportunity. The aim of the present study was to investigate the magnitude and time course of sleep inertia after waking from short (20-, 40- or 60-min) naps during simulated night work and extended operations. In addition, the effect of sleep stage on awakening and duration of slow wave sleep (SWS) on sleep inertia was assessed. Two within-subject protocols were conducted in a controlled laboratory setting. Twenty-four healthy young men (Protocol 1: n = 12, mean age = 25.1 yrs; Protocol 2: n = 12, mean age = 23.2 yrs) were provided with nap opportunities of 20-, 40-, and 60-min (and a control condition of no nap) ending at 02:00 h after ～20 h of wakefulness (Protocol 1 [P1]: simulated night work) or ending at 12:00 h after ～30 h of wakefulness (Protocol 2 [P2]: simulated extended operations). A 6-min test battery, including the Karolinska Sleepiness Scale (KSS) and the 4-min 2-Back Working Memory Task (WMT), was repeated every 15 min the first hour after waking. Nap sleep was recorded polysomnographically, and in all nap opportunities sleep onset latency was short and sleep efficiency high. Mixed-model analyses of variance (ANOVA) for repeated measures were calculated and included the factors time (time post-nap), nap opportunity (duration of nap provided), order (order in which the four protocols were completed), and the interaction of these terms. Results showed no test x nap opportunity effect (i.e., no effect of sleep inertia) on KSS. However, WMT performance was impaired (slower reaction time, fewer correct responses, and increased omissions) on the first test post-nap, primarily after a 40- or 60-min nap. In P2 only, performance improvement was evident 45 min post-awakening for naps of 40 min or more. In ANOVAs where sleep stage on awakening was included, the test x nap opportunity interaction was significant, but differences were between wake and non-REM Stage 1/Stage 2 or wake and SWS. A further series of ANOVAs showed no effect of the duration of SWS on sleep inertia. The results of this study demonstrate that no more than 15 min is required for performance decrements due to sleep inertia to dissipate after nap opportunities of 60 min or less, but subjective sleepiness is not a reliable indicator of this effect. Under conditions where sleep is short, these findings also suggest that SWS, per se, does not contribute to more severe sleep inertia. When wakefulness is extended and napping occurs at midday (i.e., P2), nap opportunities of 40- and 60-min have the advantage over shorter duration sleep periods, as they result in performance benefits ～45 min after waking.     

Duration of Sleep Inertia after Napping during Simulated Night Work and in Extended Operations

Due to the mixed findings of previous studies, it is still difficult to provide guidance on how to best manage sleep inertia after waking from naps in operational settings. One of the few factors that can be manipulated is the duration of the nap opportunity. The aim of the present study was to investigate the magnitude and time course of sleep inertia after waking from short (20-, 40- or 60-min) naps during simulated night work and extended operations. In addition, the effect of sleep stage on awakening and duration of slow wave sleep (SWS) on sleep inertia was assessed. Two within-subject protocols were conducted in a controlled laboratory setting. Twenty-four healthy young men (Protocol 1: n?=?12, mean age?=?25.1 yrs; Protocol 2: n?=?12, mean age?=?23.2 yrs) were provided with nap opportunities of 20-, 40-, and 60-min (and a control condition of no nap) ending at 02:00?h after ～20?h of wakefulness (Protocol 1 [P1]: simulated night work) or ending at 12:00?h after ～30?h of wakefulness (Protocol 2 [P2]: simulated extended operations). A 6-min test battery, including the Karolinska Sleepiness Scale (KSS) and the 4-min 2-Back Working Memory Task (WMT), was repeated every 15?min the first hour after waking. Nap sleep was recorded polysomnographically, and in all nap opportunities sleep onset latency was short and sleep efficiency high. Mixed-model analyses of variance (ANOVA) for repeated measures were calculated and included the factors time (time post-nap), nap opportunity (duration of nap provided), order (order in which the four protocols were completed), and the interaction of these terms. Results showed no test x nap opportunity effect (i.e., no effect of sleep inertia) on KSS. However, WMT performance was impaired (slower reaction time, fewer correct responses, and increased omissions) on the first test post-nap, primarily after a 40- or 60-min nap. In P2 only, performance improvement was evident 45?min post-awakening for naps of 40?min or more. In ANOVAs where sleep stage on awakening was included, the test x nap opportunity interaction was significant, but differences were between wake and non-REM Stage 1/Stage 2 or wake and SWS. A further series of ANOVAs showed no effect of the duration of SWS on sleep inertia. The results of this study demonstrate that no more than 15?min is required for performance decrements due to sleep inertia to dissipate after nap opportunities of 60?min or less, but subjective sleepiness is not a reliable indicator of this effect. Under conditions where sleep is short, these findings also suggest that SWS, per se, does not contribute to more severe sleep inertia. When wakefulness is extended and napping occurs at midday (i.e., P2), nap opportunities of 40- and 60-min have the advantage over shorter duration sleep periods, as they result in performance benefits ～45?min after waking.     

The effect of consecutive transmeridian flights on alertness,sleep–wake cycles and sleepiness: A case study

ABSTRACT

Travel across time zones disrupts circadian rhythms causing increased daytime sleepiness, impaired alertness and sleep disturbance. However, the effect of repeated consecutive transmeridian travel on sleep–wake cycles and circadian dynamics is unknown. The aim of this study was to investigate changes in alertness, sleep–wake schedule and sleepiness and predict circadian and sleep dynamics of an individual undergoing demanding transmeridian travel. A 47-year-old healthy male flew 16 international flights over 12 consecutive days. He maintained a sleep–wake schedule based on Sydney, Australia time (GMT + 10?h). The participant completed a sleep diary and wore an Actiwatch before, during and after the flights. Subjective alertness, fatigue and sleepiness were rated 4 hourly (08:00–00:00), if awake during the flights. A validated physiologically based mathematical model of arousal dynamics was used to further explore the dynamics and compare sleep time predictions with observational data and to estimate circadian phase changes. The participant completed 191?h and 159 736?km of flying and traversed a total of 144 time-zones. Total sleep time during the flights decreased (357.5?min actigraphy; 292.4?min diary) compared to baseline (430.8?min actigraphy; 472.1?min diary), predominately due to restricted sleep opportunities. The daily range of alertness, sleepiness and fatigue increased compared to baseline, with heightened fatigue towards the end of the flight schedule. The arousal dynamics model predicted sleep/wake states during and post travel with 88% and 95% agreement with sleep diary data. The circadian phase predicted a delay of only 34?min over the 16 transmeridian flights. Despite repeated changes in transmeridian travel direction and flight duration, the participant was able to maintain a stable sleep schedule aligned with the Sydney night. Modelling revealed only minor circadian misalignment during the flying period. This was likely due to the transitory time spent in the overseas airports that did not allow for resynchronisation to the new time zone. The robustness of the arousal model in the real-world was demonstrated for the first time using unique transmeridian travel.     

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.     

基于奇异值第一主成分的睡眠脑电分期方法研究

目的:脑电信号含多种噪声和伪迹,信噪比较低,特征提取前必须进行复杂的预处理,严重影响睡眠分期的速度。鉴于此,本文提出一种基于奇异值第一主成分的睡眠脑电分期方法,该方法抗噪性能较强,可省去预处理过程,减少计算量,提高睡眠分期的效率。方法:对未经过预处理的睡眠脑电进行奇异系统分析,研究奇异谱曲线,提取奇异值第一主成分,探索其随睡眠状态变化的规律。并通过支持向量机利用奇异值第一主成分对睡眠分期。结果:奇异值第一主成分不仅能表征脑电信号主体,而且可以抑制噪声、降低维数。随着睡眠的深入,奇异值第一主成分的值逐渐增大,但在REM期处于S1期和S2期之间。经MIT-BIH睡眠数据库中5例同导联位置的脑电数据测试(仅1导脑电数据),睡眠脑电分期的准确率达到86.4%。结论:在未对脑电信号进行预处理的情况下,提取的睡眠脑电的奇异值第一主成分能有效表征睡眠状态,是一种有效的睡眠分期依据。本文运用提出的方法仅采用1导脑电数据,就能得到较为满意的睡眠分期结果。该方法有较强的分类性能,且抗噪能力强,不需要对脑电作复杂的预处理,计算量小,方法简单,很大程度上提高了睡眠分期的效率。     

Delayed sleep/wake rhythm and excessive daytime sleepiness correlate with decreased daytime brain activity during cognitive task in university students

Insufficient sleep and irregular sleep/wake rhythm are common problems among university students. We investigated the effect of sleep/wake rhythm and excessive daytime sleepiness (EDS) on the cortical oxygenation as measured by near-infrared spectroscopy (NIRS) and cognitive performance in university students. Peak- and integral values by a word fluency task were measured with NIRS. EDS was evaluated by the Epworth sleepiness scale (ESS), and performance function was evaluated using N-back task. Peak cerebral oxygenation was significantly correlated with ESS, bedtime, wake-up time, and median time of sleep. Accuracy on 2-back task was significantly correlated with integral value. Peak- and integral values were significantly lower, and bedtime and median time of sleep were significantly delayed in the EDS group than in the non-EDS group. EDS accompanied by delayed sleep/wake rhythm and short sleep duration may play an important role in decreasing daytime brain activity and cognitive performance.