EEG spectral power and cognitive performance during sleep inertia: the effect of normal sleep duration and partial sleep deprivation

Sleep inertia (SI) is a transient period occurring immediately after awakening, usually characterized by performance decrement. When sleep is sufficient, SI is moderate, and produces few or no deficit. When it is associated with prior sleep deprivation, SI shows dose-dependent negative effects on cognitive performance, especially when subjects have been awaken in slow wave sleep (SWS). In the present study, spectral analysis was applied during the last 10 min before and the first 10 min after awakening, and during 1 h after awakening while subjects performed the Stroop test. Seventeen subjects were divided into a Control group who slept 8 h, and a Sleep Deprived group who slept only 2 h. The results show that performance was normal in the Control group, whereas reaction time was increased during the first half hour and error level during the second half hour in the Sleep Deprived group. Spectral analysis applied on the waking EEG during the whole test session showed that alpha activity was increased in both groups, but theta power only in the Sleep Deprived group. There was a high positive correlation in sleep deprived subjects between delta power during the last 10 min of sleep and subsequent performance decrement in speed and accuracy. Comparison of individual records showed a high positive correlation between spectral power before and after awakening in the Control group (generally in the sense of an increased frequency band), but no correlation was found in the Sleep Deprived group who exhibited a rather disorganized pattern. We discuss these results in terms of incoherence in the EEG continuity during sleep offset after prior sleep loss, which could partly account for the performance decrement observed during SI in sleep deprived subjects.     

Automatic analysis of electro-encephalogram sleep spindle frequency throughout the night

A fully automatic method to analyse electro-encephalogram (EEG) sleep spindle frequency evolution during the night was developed and tested. Twenty allnight recordings were studied from ten healthy control subjects and ten sleep apnoea patients. A total of 22 868 spindles were detected. The overall mean spindle frequency was significantly higher in the control subjects than in the apnoea patients (12.5Hz against 11.7Hz, respectively; p<0.004). The proposed method further identified the sleep depth cycles, and the mean spindle frequency was automatically determined inside each sleep depth cycle. In control subjects, the mean spindle frequency increased from 12.0Hz in the first sleep depth cycle to 12.6Hz in the fifth cycle. No such increase was observed in the sleep apnoea patients. This difference in the spindle frequency evolution was statistically significant (p<0.004). The advantage of the method is that no EEG amplitude thresholds are needed.     

Power spectral analysis and cortical coupling of EEG for young and old normal adults

Power spectral analysis and cortical coupling were computed on eyes closed EEG recorded from 80 normal volunteers: 20 females and 20 males aged 25-35 years and 20 females and 20 males aged 55-70 years. Recordings were from Fz, Cz, C3, Pz and Oz areas. The results indicate that with increased age there was a greater uniformity of EEG activity across the brain. Magnitude of EEG power was significantly less variable across recording sites for the old than for the young. In addition, cortical coupling values were reliably higher for the older subjects indicating a greater congruity among EEG patterns. The EEG power and cortical coupling measures were significantly correlated and thus may indicate an underlying mechanism common to both. The results support a theory of decreased central inhibitory function in old age and may reflect an age-related breakdown of functional autonomy of cortical areas. Gender had no significant effect on either EEG power or cortical coupling.     

EEG spectral power analysis of phasic and tonic REM sleep in young and older male subjects

EEG spectral power was studied during periods of rapid eye movements (REMs) and tonic intervals in REM sleep of 7 young and 7 older male subjects. Significant symmetrical decreases in alpha and beta1 power at central and occipital sites, concurrent with an increase in frontal theta power, were observed during the production of REMs. The former findings are discussed as sleep analogues to changes in alpha and beta1 during waking, showing increased information processing and behavioural activation, and that of theta is tentatively presented as reflecting an increase in afferent thresholds. Independent of the phasic-tonic REM distinction, total EEG power markedly decreased as a function of time of night and did not interact with age. Significant age differences in the overall spectral composition of the EEG were obtained, namely, a lower level of delta power and a relative shift towards more power in frequencies above 12 Hz for the older group. Further, older subjects also demonstrated a more uniform topographical distribution of alpha and sigma power.     

EEG delta power during sleep in young and old rats

Delta EEG power density, which has been viewed as a measure of intensity of NREM sleep, declines across the lifetime in humans, cats, and hamsters, but data in rats have been unclear. It is also uncertain whether older rats differ from younger animals in the degree of change in delta power during recovery sleep following short-term sleep deprivation. We have examined delta power density in NREM sleep under baseline conditions and following 48 h of sleep deprivation in young (3 months), middle-aged (12 months), and older (24 months) rats. The presence or absence of age effects was highly dependent on the method of normalizing the data. When expressed as a fraction of total NREM EEG power, there was no age effect on baseline delta power density, or on the change from baseline to recovery conditions. When expressed as a multiple of delta power in REM under the same condition, the younger rats had higher delta power density than the middle-aged and older rats. For all the ages combined, there was an increase in delta power density in the recovery condition. When examined by age, the younger rats (which started from a higher level of delta power density than the other groups) did not have an increase in delta during recovery; the middle-aged rats tended to, and the older rats (which started from lower baseline levels) significantly increased delta power density in the recovery condition. This suggests that the lower delta power seen during baseline in older rats is not due to decreased ability to generate delta activity.     

EEG sleep, depression, and aging

—To date little attention has been paid to the posssible age-dependent relationships of EEG sleep measures in depression or to the implications of such relationships for diagnostic sensitivity and specificity. In a study of 108 patients with major depressive disorders (67 inpatients, 41 outpatients), age was shown to be a very powerful determinant of electroencephalographic (EEG) sleep patterns. Thus, among other sleep variables, sleep efficiency, delta sleep percent, and REM latency all showed significant linear declines with increasing age. Similar trends were seen in both inpatients and outpatients. Some variables were without age trends (age-stable), including sleep latency, REM sleep percent, and REM activity. These findings confirm those of an earlier report from our laboratory [45] and suggest that age-corrected sleep variables can be developed for clinical diagnostic application. Thus, using normative data from Gillin et al. [19] for comparison, a sensitivity level of 65% for age-corrected REM latency was demonstrated, together with a specificity of 95% and a diagnostic confidence of 92%. Data from a pilot study comparing EEG sleep measures in depression and dementia are also presented; these data suggest the potential utility of EEG sleep measures in the differential diagnosis of these two disorders, especially in patients with mixed symptoms. Additional areas for further research are reviewed with enumeration of specific testable hypotheses.     

EEG sleep, depression, and aging

—To date little attention has been paid to the posssible age-dependent relationships of EEG sleep measures in depression or to the implications of such relationships for diagnostic sensitivity and specificity. In a study of 108 patients with major depressive disorders (67 inpatients, 41 outpatients), age was shown to be a very powerful determinant of electroencephalographic (EEG) sleep patterns. Thus, among other sleep variables, sleep efficiency, delta sleep percent, and REM latency all showed significant linear declines with increasing age. Similar trends were seen in both inpatients and outpatients. Some variables were without age trends (age-stable), including sleep latency, REM sleep percent, and REM activity. These findings confirm those of an earlier report from our laboratory [45] and suggest that age-corrected sleep variables can be developed for clinical diagnostic application. Thus, using normative data from Gillin et al. [19] for comparison, a sensitivity level of 65% for age-corrected REM latency was demonstrated, together with a specificity of 95% and a diagnostic confidence of 92%. Data from a pilot study comparing EEG sleep measures in depression and dementia are also presented; these data suggest the potential utility of EEG sleep measures in the differential diagnosis of these two disorders, especially in patients with mixed symptoms. Additional areas for further research are reviewed with enumeration of specific testable hypotheses.     

Period-amplitude analysis and power spectral analysis: a comparison based on all-night sleep EEG recordings

Both period-amplitude analysis (PAA) and power spectral analysis (PSA) were performed on all-night human sleep EEG recordings obtained from 11 subjects. The comparison of the two methods was based on the PAA variables time in band (a wave incidence measure) and rectified amplitude, and on the PSA variables spectral power density and spectral amplitude (the square root of power). The mean time course of these variables was determined for the first 4 nonREM-REM sleep cycles. Spectral power density and spectral amplitude in the delta range were high in nonREM sleep and low in REM sleep, and showed a declining trend over consecutive nonREM sleep episodes. In the frequency range below 2 Hz, rectified amplitude was highly correlated with both time in band and spectral amplitude, and there was no evidence for a dissociation between wave amplitude and wave incidence measures. However, in frequencies above 2 Hz, the modulation of time in band was a mirror image of that below 2 Hz. This result does not reflect a property of the data, but is inherent to the methodology applied. The reversal point of modulation was merely shifted when the high-pass filter settings were changed. It is concluded that band-pass filtering is necessary prior to PAA even for the analysis of the lowest frequency range, and that the indiscriminate use of PAA may give rise to spurious results.     

Topographic mapping of EEG during sleep

Summary Topographic aspects of all night sleep EEG were investigated in 10 healthy volunteers (age 20–35 years). EEG brain maps showed an increase of delta power from stage 1 to 4, a decrease of alpha power most pronounced parieto-occipitally and a slowing of the dominant alpha frequency. Differences of EEG power in different sleep stages (as compared to wakefulness) are displayed topographically. Analysis of the course of stage 2 showed an increase of delta power and a decrease of theta power in the first sections of the night, and an increase of beta power later in the night.     

Effect of 38 h of total sleep deprivation on the waking EEG in women: sex differences

38 h of sleep deprivation in women resulted in decreased alpha, increased theta and increased intrahemispheric correlation during rest and increased theta and reaction time during task. F3–O1 coherent activity was selectively decreased consistent with the role of sleep for recovery of frontal functions. Sleep deprivation effects were milder in women than in men, however, recovery was not complete suggesting that women need more sleep than men to recover.     

Improved computational fronto-central sleep depth parameters show differences between apnea patients and control subjects

All-night EEG recordings from 12 male apnea patients and 12 age-matched healthy control subjects were studied in the present work. The spectral mean frequency was used to provide computational sleep depth curves from two frontopolar and two central EEG channels. Our previously presented computational parameters quantifying the properties of the sleep depth curves were improved. The resulting light sleep percentage (LS%) values were higher in apnea patients than in control subjects in the right central brain position (P = 0.028), in concordance to our previous work. Moreover, apnea patients showed higher LS% values in the right frontopolar position (P = 0.008). Also, apnea patients showed a smaller anteroposterior sleep depth difference than control subjects on the right hemisphere (P = 0.002). These are interesting new findings, achieved by the present methodology. Thus, the developed computational parameters were able to quantify, at least to some degree, the disruption of sleep process caused by the recurrent apneic events.     

Autonomic control of the cardiovascular system during sleep in normal subjects

The autonomic control of heart rate and blood pressure during sleep is controversial: although it has been reported that vagal activity is more often lower in rapid eye movement sleep (REM) than in other stages of sleep (non-REM, NREM), the opposite has also been described. Initially, it was reported that baroreflex sensitivity (BRS) increases during sleep (REM and NREM), but in later studies, this was only partially confirmed. We therefore studied autonomic control of the cardiovascular (CV) system during sleep in 12 normal adults. The spectral components of the heart rate R-R interval, blood pressure (BP), and BRS were computed at low (LF) and actual breathing frequency (high frequency, HF). Analysis of sleep stage and a cycle-by-cycle stage II analysis were performed. CV variability is affected largely by sleep-stage and sleep-cycle organisation: NREM and the last cycle exhibit the greatest vagal activity and the lowest sympathetic activity. BRS estimation for both the LF and HF bands confirmed previous results obtained by pharmacological and spontaneous slope methods: BRS is greater during sleep than during nocturnal wake periods, and further increased in REM. BRS is frequency dependent: in NREM, the higher value of HF BRS compared to LF BRS favours the HF control of BP variability, whereas higher BRS HF and LF components contribute to the strongest control in REM. BRS variability exhibits no significant pattern during the night. Our results suggest that both sleep-cycle organisation and BRS estimation in the LF and HF bands should be considered in sleep studies of autonomic CV control. Electronic Publication     

468例癫癎患者睡眠期癎样放电与睡眠结构变化分析

目的：观察癫 患者的睡眠时相与 样放电的关系,并初步探讨癫 异常脑波活动对睡眠的影响。方法：对４６８例癫　患者进行２４小时动态脑电图（ＡＥＥＧ）监测,观察发作间期清醒与睡眠脑电图　样放电的发作频率,分析５８例癫　患者及对照组睡眠脑电图中睡眠时程、觉醒次数、睡眠纺锤波的变化。结果：４６８例患者中出现　样放电３６２例,睡眠期　样放电检出率８８％,觉醒期检出率５８％。样放电主要出现于ＮＲＥＭ睡眠Ⅰ－Ⅱ期。与对照组比较,癫　组ＮＲＥＭ　Ⅰ－Ⅱ睡眠期延长,ＮＲＥＭ Ⅲ－Ⅳ期缩短;觉醒次数增加,觉醒次数与　样放电频率呈正相关;并有睡眠纺锤波减少及不对称。结论：癫　患者的　样放电主要出现于ＮＲＥＭ睡眠Ⅰ－Ⅱ期,癫　活动对睡眠有一定影响,癫　患者睡眠质量下降。     

Power spectral EEG analysis and EEG variability in obsessive-compulsive disorder

Spectral EEG characteristics of thirteen patients with severe Obsessive-Compulsive Disorder (OCD) were investigated topographically. The finding of predominantly left posterior frontal to mid-temporal theta-2 is discussed in light of previous EEG studies and recent neuroradiologic findings.     

Spectral analysis of EEG responses

The techniques used and the results obtained in a spectral analysis of two specific responses in the human electroencephalogram are presented in this paper. The purposes are to show how the techniques may be applied to the necessarily short lengths of EEG data and to illustrate these techniques and the useful results obtained by relevant examples. The necessary data-processing procedures and precautions for transforming from the time to frequency domain are presented in a tutorial fashion. The importance of augmenting zeros, choice of the most appropriate data window and pretransformation of the data to avoid the combined effects of energy loss and low frequency content biasing caused by windowing is explained. The pros and cons of the tapered-cosine (Tukey) and Kaiser-Bessel windows are illustrated. The usefulness of applying certain statistical tests, which are based on a physical model of the responses, to the harmonic components of the responses is demonstrated. Thus a comparison is made between the features of auditory evoked responses and of the contingent negative variation, and the usefulness of predictive statistical diagnosis in differentiating between subject groups is illustrated by application to normal subjects and Huntington's chorea patients.     

Poststimulus EEG spectral analysis and P300: attention, task, and probability

Event-related potentials (ERPs) were elicited with auditory stimuli, and spectral analysis was performed on the poststimulus electroencephalographic (EEG) activity to assess how variables that influence the P300 affect spectral parameters of the resultant ERP. In Experiment 1, a no-stimulus condition was compared with a single repeated tone that was either ignored or counted. In Experiment 2, an auditory oddball paradigm was used in which the subject ignored all stimuli, counted only the target, or counted both the target and the standard stimuli in different conditions. In Experiment 3, stimulus probability was manipulated in separate conditions (.20, .50, .80), with the subject required to count the target stimulus. Delta and theta band spectral power increased whenever P300 amplitude increased. However, as the attentional requirements increased across tasks, alpha-1 and alpha-2 power and mean frequency increased. The findings indicate that auditory stimulus processing modulates the EEG more than just by adding ERP components to the epoch.     

Source models of sleep spindles using MEG and EEG measurements

Summary MEG measurements can detect brain sources that are difficult to detect with EEG measurements. The purpose of this study was to investigate models of sleep spindles using both MEG and EEG activity that had been recorded simultaneously. The components of magnetic fields perpendicular to the surface of the head were measured using a DC-SQUID with a first-derivative gradiometer. We propose three models for sleep spindles. In the first model, the source slides into the superficial region of the head so as to be perpendicular to it's surface, and with this model, the power spectrum of the MEG is decreased. In the second model, the source slides into the deeper structures, so that it is perpendicular to the surface. Here, the power spectra of both the MEG and the EEG are decreased. The third model has the source perpendicular to the surface, leaning and sliding into the deeper structures. Here, the power spectrum of the EEG is decreased but that of the MEG is not.     

Physiological arousal and attention during a week of continuous sleep restriction

Waking brain physiology underlying deficits from continuous sleep restriction (CSR) is not well understood. Fourteen good sleepers participated in a 21-day protocol where they slept their usual amount in a baseline week, had their time in bed restricted by 33% in a CSR week, and slept the desired amount in a recovery week. Participants slept at home, completing diaries and wearing activity monitors to verify compliance. Each day participants completed an RT task and mood and sleepiness ratings every 3 h. Laboratory assessment of electrophysiology and performance took place at the end of baseline, three times throughout the CSR week, and at the beginning of recovery. Participants reported less sleep during CSR which was confirmed by activity monitors. Correspondingly, well-being and neurobehavioural performance was impaired. Quantitative EEG analysis revealed significantly reduced arousal between the 1st and 7th days of restriction and linear effects at anterior sites (Fp2, Fz, F8, T8). At posterior sites (P4, P8), reductions occurred only later in the week between the 4th and 7th nights of restriction. Both the immediate linear decline in arousal and precipitous drop later in the week were apparent at central sites (C4, Cz). Thus, frontal regions were affected immediately, while parietal regions showed maintenance of function until restriction was more severe. The P300 ERP component showed evidence of reduced attention by the 7th day of restriction (at Pz, P4). EEG and ERPs deficits were more robust in the right-hemisphere, which may reflect greater vulnerability to sleep loss in the non-dominant hemisphere.     

The effect of light on sleep and the EEG of young rats

Sleep states, the power spectra of the cortical electroencephalogram (EEG) and cortical temperature (T _crt) were determined in young rats (age 23–24 days). Recordings were made for 1 day under habitual 12 h light: 12 h dark (LD 1212) conditions and on the subsequent day under continuous darkness (DD). The amount and distribution of the vigilance states differed little between experimental conditions. Sleep occurred predominantly during the actual (LD) or habitual (DD) 12-h light period. The EEG power density in the actual light period was lower than in the habitual light period. These differences were largest in the delta range for the EEG of non-rapid eye movement of sleep (NREMS) and in the theta range for the EEG of REM sleep (REMS) and waking. EEG power density in NREMS was somewhat lower in the LD dark period than in the corresponding DD period. The typical 24-h pattern of EEG power density in NREMS, which reflects processes underlying sleep regulation, was little affected by the experimental conditions. It is concluded that the light during an LD 1212 schedule suppresses the EEG but has little effect on the vigilance states.     

Adaptive frequency decomposition of EEG with subsequent expert system analysis

We present a hybrid system for automatic analysis of clinical routine EEG, comprising a spectral analysis and an expert system. EEG raw data are transformed into the time–frequency domain by the so-called adaptive frequency decomposition. The resulting frequency components are converted into pseudo-linguistic facts via fuzzification. Finally, an expert system applies symbolic rules formulated by the neurologist to evaluate the extracted EEG features. The system detects artefacts, describes alpha rhythm by frequency, amplitude, and stability and after artefact rejection detects pathologic slow activity. All results are displayed as linguistic terms, numerical values and maps of temporal extent, giving an overview about the clinical routine EEG.