Sleep respiratory disturbances and arousals at moderate altitude have overlapping electroencephalogram spectral signatures

An ascent to altitude has been shown to result in more central apneas and a shift towards lighter sleep in healthy individuals. This study employs spectral analysis to investigate the impact of respiratory disturbances (central/obstructive apnea and hypopnea or periodic breathing) at moderate altitude on the sleep electroencephalogram (EEG) and to compare EEG changes resulting from respiratory disturbances and arousals. Data were collected from 51 healthy male subjects who spent 1 night at moderate altitude (2590 m). Power density spectra of Stage 2 sleep were calculated in a subset (20) of these participants with sufficient artefact‐free data for (a) epochs with respiratory events without an accompanying arousal, (b) epochs containing an arousal and (c) epochs of undisturbed Stage 2 sleep containing neither arousal nor respiratory events. Both arousals and respiratory disturbances resulted in reduced power in the delta, theta and spindle frequency range and increased beta power compared to undisturbed sleep. The similarity of the EEG changes resulting from altitude‐induced respiratory disturbances and arousals indicates that central apneas are associated with micro‐arousals, not apparent by visual inspection of the EEG. Our findings may have implications for sleep in patients and mountain tourists with central apneas and suggest that respiratory disturbances not accompanied by an arousal may, none the less, impact sleep quality and impair recuperative processes associated with sleep more than previously believed.     

Pulse wave amplitude drops during sleep are reliable surrogate markers of changes in cortical activity

Background:During sleep, sudden drops in pulse wave amplitude (PWA) measured by pulse oximetry are commonly associated with simultaneous arousals and are thought to result from autonomic vasoconstriction. In the present study, we determine whether PWA drops were associated with changes in cortical activity as determined by EEG spectral analysis.Methods:A 20% decrease in PWA was chosen as a minimum for a drop. A total of 1085 PWA drops from 10 consecutive sleep recordings were analyzed. EEG spectral analysis was performed over 5 consecutive epochs of 5 seconds: 2 before, 1 during, and 2 after the PWA drop. EEG spectral analysis was performed over delta, theta, alpha, sigma, and beta frequency bands. Within each frequency band, power density was compared across the five 5-sec epochs. Presence or absence of visually scored EEG arousals were adjudicated by an investigator blinded to the PWA signal and considered associated with PWA drop if concomitant.Results:A significant increase in EEG power density in all EEG frequency bands was found during PWA drops (P < 0.001) compared to before and after drop. Even in the absence of visually scored arousals, PWA drops were associated with a significant increase in EEG power density (P < 0.001) in most frequency bands.Conclusions:Drops in PWA are associated with a significant increase in EEG power density, suggesting that these events can be used as a surrogate for changes in cortical activity during sleep. This approach may prove of value in scoring respiratory events on limited-channel (type III) portable monitors.Citation:Delessert A; Espa F; Rossetti A; Lavigne G; Tafti M; Heinzer R. Pulse wave amplitude drops during sleep are reliable surrogate markers of changes in cortical activity. SLEEP 2010;33(12):1687-1692.     

Effect of prolonged wakefulness on electroencephalographic oscillatory activity during sleep

The human sleep electroencephalogram (EEG) is characterized by the occurrence of distinct oscillatory events such as delta waves, sleep spindles and alpha activity. We applied a previously proposed algorithm for the detection of such events and investigated their incidence and frequency in baseline and recovery sleep after 40 h of sustained wakefulness in 27 healthy young subjects. The changes in oscillatory events induced by sleep deprivation were compared to the corresponding spectral changes. Both approaches revealed, on average, an increase in low frequency activity and a decrease in spindle activity after sleep deprivation. However, the increase of oscillatory events in the delta range and decrease in the sigma range occurred in a more restricted frequency range compared to spectral changes. The mean relative power spectra showed a significant increase in theta and alpha activity after sleep deprivation while, on average, the event analysis showed only a weak effect in the theta band. The reason for this discrepancy is that the spectral analysis does not distinguish between diffuse activity and clearly visible temporally localized oscillations, while the event analysis would detect only the latter. Additionally, only a few individuals clearly showed activity in the theta or alpha frequency bands. Conversely, event analysis revealed that some individuals showed an increased rate of sleep spindles after sleep deprivation, a fact that was not evident in the relative power spectra due to a decrease in background activity. The two methods complement each other and facilitate the interpretation of distinct changes induced by prolonged wakefulness in sleep EEG.     

Method for detection of respiratory cycle-related EEG changes in sleep-disordered breathing

STUDY OBJECTIVES: In sleep-disordered breathing (SDB), visual or computerized analysis of electroencephalogram (EEG) signals shows that disruption of sleep architecture occurs in association with apneas and hypopneas. We developed a new signal analysis algorithm to investigate whether brief changes in cortical activity can also occur with individual respiratory cycles. DESIGN: Retrospective. SETTING: University sleep laboratory. PARTICIPANTS: A 6 year-old boy with SDB. INTERVENTION: Polysomnography before and after clinically indicated adenotonsillectomy. MEASUREMENTS: For the first 3 hours of nocturnal sleep, a computer algorithm divided nonapneic respiratory cycles into 4 segments and, for each, computed mean EEG powers within delta, theta, alpha, sigma, and beta frequency ranges. Differences between segment-specific EEG powers were tested by analysis of variance. Respiratory cycle-related EEG changes (RCREC) were quantified. RESULTS: Preoperative RCREC were statistically significant in delta (P < .0001), theta (P < .001), and sigma (P < .0001) but not alpha or beta (P > .01) ranges. One year after the operation, RCREC in all ranges showed statistical significance (P < .01), but delta, theta, and sigma RCREC had decreased, whereas alpha and beta RCREC had increased. Preoperative RCREC also were demonstrated in a sequence of 101 breaths that contained no apneas or hypopneas (P < .0001). Several tested variations in the signal-analysis approach, including analysis of the entire nocturnal polysomnogram, did not meaningfully improve the significance of RCREC. CONCLUSIONS: In this child with SDB, the EEG varied with respiratory cycles to a quantifiable extent that changed after adenotonsillectomy. We speculate that RCREC may reflect brief but extremely numerous microarousals.     

Determining a continuous marker for sleep depth

Detection and quantification of sleep arousals is an important issue, as the frequent arousals are known to reduce the quality of sleep and cause daytime sleepiness. In typical sleep staging, electroencephalograph (EEG) is the core signal and based on the visual inspection of the frequency content of EEG, non-rapid eye movement sleep is staged into four somewhat rough categories. In this study, we aimed at developing a continuous marker based on a more rigorous spectral analysis of EEG to measure or quantify the depth of sleep. In order to develop such a marker, we obtained the time-frequency map of two EEG channels around sleep arousals and identified the frequency bands that show the most change during arousals. We then evaluated classification performance of the potential signals for representing the depth of sleep, using receiver operating characteristic analysis. Our comparisons based on the area under the curve values revealed that the sum of absolute powers in alpha and beta bands is a good continuous marker to represent the depth of sleep. Higher values of this marker indicate low-quality sleep and vice versa. We believe that use of this marker will lead to a better quantification of sleep quality.     

Cross-correlation of EEG frequency bands and heart rate variability for sleep apnoea classification

Sleep apnoea is a sleep breathing disorder which causes changes in cardiac and neuronal activity and discontinuities in sleep pattern when observed via electrocardiogram (ECG) and electroencephalogram (EEG). Using both statistical analysis and Gaussian discriminative modelling approaches, this paper presents a pilot study of assessing the cross-correlation between EEG frequency bands and heart rate variability (HRV) in normal and sleep apnoea clinical patients. For the study we used EEG (delta, theta, alpha, sigma and beta) and HRV (LF_nu, HF_nu and LF/HF) features from the spectral analysis. The statistical analysis in different sleep stages highlighted that in sleep apnoea patients, the EEG delta, sigma and beta bands exhibited a strong correlation with HRV features. Then the correlation between EEG frequency bands and HRV features were examined for sleep apnoea classification using univariate and multivariate Gaussian models (UGs and MGs). The MG outperformed the UG in the classification. When EEG and HRV features were combined and modelled with MG, we achieved 64% correct classification accuracy, which is 2 or 8% improvement with respect to using only EEG or ECG features. When delta and acceleration coefficients of the EEG features were incorporated, then the overall accuracy improved to 71%.     

Circadian and homeostatic modulation of sleep in older adults during a 90-minute day study

STUDY OBJECTIVES: To identify age-associated changes in circadian and homeostatic characteristics of sleep in healthy elderly and young adults using electroencephalogram (EEG) power spectral analysis during a 90-minute sleep-wake schedule. DESIGN: Controlled clinical experiment. SETTING: University sleep laboratory. PARTICIPANTS: 16 older (77 +/- 5 years) and 19 younger adults (23 +/- 3 years). INTERVENTIONS: Subjects followed a 90-minute sleep-wake schedule (30 minutes in bed, 60 minutes awake) for 60 hours. Sleep was recorded for each bed-rest episode, and core body temperature was continuously recorded. The EEG power density was determined for non-rapid eye movement sleep in each bed-rest episode. Power density data were analyzed with mixed-effects models to assess rhythmic and linear components. RESULTS: Younger subjects had greater power in delta, theta, and sigma power bands across the study interval. Significant circadian rhythms were observed in delta, sigma, and beta power bands. Age-related differences in circadian modulation of EEG activity, indicated by significant interaction terms, were present in alpha and beta bands. A significant linear component was present in delta and theta power bands, with no significant age-interaction effect. CONCLUSIONS: Despite overall differences in the level of EEG power, older and younger adults exhibited similar rhythmic and linear patterns in most frequency bands. Age appears to affect circadian rhythmicity in higher EEG frequencies and homeostatic drive in lower EEG frequencies.     

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.     

Periodic amplitude modulation of EEG.

Time variation of the EEG spectral parameters was analyzed during a 10 min resting period in 40 healthy subjects. Spectral band powers over the theta and alpha bands were calculated for each non-overlapping 2.5 s long EEG segment. The time variation of the band powers was further analyzed by computing the power spectra. The results showed that both theta and alpha band powers oscillate at an average frequency 0.024 Hz and 0.057 Hz. This indicates, that the background EEG activity is modulated by periodical slow components. We hypothesize that this modulation reflects spontaneous periodic changes of cortical excitability with control at the brainstem level.     

Age-related modifications of NREM sleep EEG: from childhood to middle age

This study investigated the modifications in non-rapid eye movement (NREM) sleep electroencephalogram (EEG) power in 54 subjects, from children to middle-aged adults. Spectral analyses were performed on 5 h of NREM sleep. A marked decrease of absolute slow-wave activity (SWA) was observed with increasing age; children had significantly more SWA than adolescents, young and middle-aged adults. The decline of SWA across the night seems to level off with increasing age, suggesting an age-related attenuation of homeostatic sleep pressure. Absolute theta power was higher for children compared with the other three groups, and adolescents had more theta power than young and middle-aged adults. In comparison to young and middle-aged adults, alpha power was higher for children and adolescents. Children and adolescents had more sigma power than middle-aged adults. Absolute beta power was higher for children than for the other age groups. Therefore, the major alterations of NREM sleep EEG occurring between childhood and middle age are not restricted to SWA, but encompassed the theta, alpha, sigma and beta frequency bands.     

Night-to-night arousal variability and interscorer reliability of arousal measurements

STUDY OBJECTIVES: Measurement of arousals from sleep is clinically important, however, their definition is not well standardized, and little data exist on reliability. The purpose of this study is to determine factors that affect arousal scoring reliability and night-to-night arousal variability. DESIGN: The night-to-night arousal variability and interscorer reliability was assessed in 20 subjects with and without obstructive sleep apnea undergoing attended polysomnography during two consecutive nights. Five definitions of arousal were studied, assessing duration of electroencephalographic (EEG) frequency changes, increases in electromyographic (EMG) activity and leg movement, association with respiratory events, as well as the American Sleep Disorders Association (ASDA) definition of arousals. SETTING: NA. PATIENTS: NA. INTERVENTIONS: NA. RESULTS: Interscorer reliability varied with the definition of arousal and ranged from an Intraclass correlation (ICC) of 0.19 to 0.92. Arousals that included increases in EMG activity or leg movement had the greatest reliability, especially when associated with respiratory events (ICC 0.76 to 0.92). The ASDA arousal definition had high interscorer reliability (ICC 0.84). Reliability was lowest for arousals consisting of EEG changes lasting <3 seconds (ICC 0.19 to 0.37). The within subjects night-to-night arousal variability was low for all arousal definitions CONCLUSION: In a heterogeneous population, interscorer arousal reliability is enhanced by increases in EMG activity, leg movements, and respiratory events and decreased by short duration EEG arousals. The arousal index night-to-night variability was low for all definitions.     

Spontaneous arousals during quiet sleep in piglets: a visual and wavelet-based analysis

STUDY OBJECTIVES: The objectives of the study were to characterize spontaneous arousals during NREM sleep in piglets and to compare two methods of identifying these events: a "visual" technique using spectral analysis and an automated technique using wavelets. Our goal was to understand the benefits and limits of these methods when applied to sleep in human infants. DESIGN: Arousals were identified by evaluating rapid changes in EEG low frequency activity, blood pressure (BP), and heart rate (HR). A cortical arousal was defined as a rapid decrease in EEG low frequency activity. An autonomic arousal was defined by a transient increase in heart rate or a transient change in mean arterial BP (MAP). SETTING: Laboratory study in sleeping and awake piglets. PARTICIPANTS: Five 1-2 week old piglets. INTERVENTIONS: Chronically instrumented with a femoral arterial line, EEG, EOG, EMG electrodes, and a micro-dialysis probe with its tip located in the rostral ventral medulla. Artificial CSF (aCSF) was dialyzed into the RVM throughout the experiments Measurements: For the visual analysis, the average delta power (0.5-4 Hz) for each 5-second epoch was determined using spectral analysis. MAP and HR were analyzed in 1-second bins. Video images were analyzed for body movements and eye openings. Transient changes in blood pressure, HR, and delta power were then visually identified. For the wavelet analysis, a quantitative, automated technique with a defined "wakefulness threshold" was used to identify rapid decreases in EEG low frequency activity and the rate of change of MAP. RESULTS: Using the visual method, 117 episodes associated with stereotypical hemodynamic, EEG, and behavioral changes (startle) were identified. Seventy five events occurred in isolation or were first in a series of "multiple" events, 41 "multiple" events were defined as events occurring <20 seconds following a previous event. Eighteen events were associated with the termination of apnea. In isolated events or those occurring first in a series, the onset of changes in HR and BP clearly preceded the decrease in EEG amplitude and delta power. Using wavelet analysis, 73 EEG arousals and 115 MAP transients were identified independently; 62% of the EEG events were associated with a transient change in MAP and HR, and in these cases the onset of the hemodynamic events preceded EEG arousals. EEG arousals and MAP transients, however, also occurred alone and not associated with a stereotypical pattern of a startle, changes in MAP and HR and the EEG. CONCLUSIONS: Many of these spontaneous arousals represent integrated EEG, hemodynamic, and behavioral processes similar to arousal phenomena described in adult rats and human infants, but the pattern of spontaneous arousals appears to be more heterogeneous than has been described for arousals induced by exogenous stimuli. Both the visual and wavelet analysis identified these events, but the wavelet technique has the potential advantage of better time resolution and automation of the analysis.     

Effect of Continuous Positive Airway Pressure on Sleep Structure in Heart Failure Patients with Central Sleep Apnea

Study Objectives:

At termination of obstructive apneas, arousal is a protective mechanism that facilitates restoration of upper airway patency and airflow. Treating obstructive sleep apnea (OSA) by continuous positive airway pressure (CPAP) reduces arousal frequency indicating that such arousals are caused by OSA. In heart failure (HF) patients with central sleep apnea (CSA), however, arousals frequently occur several breaths after apnea termination, and there is uncertainty as to whether arousals from sleep are a consequence of CSA. If so, they should diminish in frequency when CSA is attenuated. We therefore sought to determine whether attenuation of CSA by CPAP reduces arousal frequency.

Design:

Randomized controlled clinical trial.

Patients and Setting:

We examined data from 205 HF patients with CSA (apnea-hypopnea index [AHI] ≥ 15, > 50% were central) randomized to CPAP or control who had polysomnograms performed at baseline and 3 months later.

Measurements and Results:

In the control group, there was no change in AHI or frequency of arousals. In the CPAP-treated group, the AHI decreased significantly (from [mean ± SD] 38.9 ± 15.0 to 17.6 ± 16.3, P < 0.001) but neither the frequency of arousals nor sleep structure changed significantly.

Conclusion:

These data suggest that attenuation of CSA by CPAP does not reduce arousal frequency in HF patients. We conclude that arousals were not mainly a consequence of CSA, and may not have been acting as a defense mechanism to terminate apneas in the same way they do in OSA.

Citation:

Ruttanaumpawan P; Logan AG; Floras JS; Bradley TD. Effect of Continuous Positive Airway Pressure on Sleep Structure in Heart Failure Patients with Central Sleep Apnea. SLEEP 2009;32(1):91-98.     

Differences of brain electrical activity between moderate and severe obstructive sleep apneic patients: a LORETA study

The effects of initiation of continuous positive airway pressure (CPAP) therapy on electroencephalographic (EEG) background activity were investigated in patients exhibiting both moderate (n = 13) and severe (n = 12) obstructive sleep apnea syndromes in the testing of the potential differences of alterations of brain electrical activity caused by chronic hypoxia between these two groups. A normal control group (n = 14) was also examined. Two EEG examinations were achieved in each group: before and after first‐time CPAP therapy. Low‐resolution electromagnetic tomography (LORETA) was implemented towards localizing the generators of EEG activity in separate frequency bands. Prior to CPAP treatment, as a common direction of change, analysis with LORETA demonstrated increased activity in comparison with the patient and control groups. In the moderate group, significant changes were detected in the alpha2 band in the posterior cingulate cortex as well as in the beta1 band in the right posterior parietal cortex and the left supramarginal gyrus. In the severe group, significant changes were found in theta and alpha1 bands in the posterior cingulate cortex. Following CPAP treatment, these significant differences vanished in the severe group. In the moderate group, significantly decreased activity was seen in the beta3 band in the right fusiform gyrus. These findings potentially suggest a normalizing effect of CPAP therapy on EEG background activity in both groups of obstructive sleep apnea syndrome patients. Compensatory alterations of brain electrical activity in regions associated with influencing successful memory retrieval, emotional perception, default mode network, anorexia and fear network caused by chronic intermittent hypoxia could possibly be reversed with the use of CPAP therapy.     

Automatic sleep scoring: a search for an optimal combination of measures

Objective

The objective of this study is to find the best set of characteristics of polysomnographic signals for the automatic classification of sleep stages.

Methods

A selection was made from 74 measures, including linear spectral measures, interdependency measures, and nonlinear measures of complexity that were computed for the all-night polysomnographic recordings of 20 healthy subjects. The adopted multidimensional analysis involved quadratic discriminant analysis, forward selection procedure, and selection by the best subset procedure. Two situations were considered: the use of four polysomnographic signals (EEG, EMG, EOG, and ECG) and the use of the EEG alone.

Results

For the given database, the best automatic sleep classifier achieved approximately an 81% agreement with the hypnograms of experts. The classifier was based on the next 14 features of polysomnographic signals: the ratio of powers in the beta and delta frequency range (EEG, channel C3), the fractal exponent (EMG), the variance (EOG), the absolute power in the sigma 1 band (EEG, C3), the relative power in the delta 2 band (EEG, O2), theta/gamma (EEG, C3), theta/alpha (EEG, O1), sigma/gamma (EEG, C4), the coherence in the delta 1 band (EEG, O1-O2), the entropy (EMG), the absolute theta 2 (EEG, Fp1), theta/alpha (EEG, Fp1), the sigma 2 coherence (EEG, O1-C3), and the zero-crossing rate (ECG); however, even with only four features, we could perform sleep scoring with a 74% accuracy, which is comparable to the inter-rater agreement between two independent specialists.

Conclusions

We have shown that 4-14 carefully selected polysomnographic features were sufficient for successful sleep scoring. The efficiency of the corresponding automatic classifiers was verified and conclusively demonstrated on all-night recordings from healthy adults.     

Sleep and EEG profile in neonatal hippocampal lesion model of schizophrenia

Sleep architecture, EEG power pattern and locomotor activity were investigated in a putative animal model of schizophrenia. The model was prepared by excitotoxic damage of the ventral hippocampus on postnatal day 7 (PD 7), after which locomotor activity and electroencephalographic (EEG) sleep profile were compared between lesioned and sham operated animals respectively, at prepuberty (postnatal day PD 35) and postpuberty (PD 56). An enhancement of locomotor activity was observed in lesioned adult PD 56, but not in juvenile PD 35 rats. Spontaneous EEG/EMG recordings during 24 h showed no major differences between both groups at PD 35 and at PD 56. However, quantitative analysis of the EEG revealed an enhancement of power in delta (delta), theta (theta) and alpha (alpha) activities in lesioned animals at PD 35 during wakefulness in both light and dark phases. At PD 56, the power in the delta and theta bands was increased during the light and dark periods in both wakefulness and non-REM sleep. These findings suggest that ventral hippocampus lesion is not associated with disturbance of sleep architecture in rats, while consistent changes were observed in the dynamic of EEG slow wave frequency domain. Thus, the data indicate that neonatal lesion of ventral hippocampus did not mimic sleep abnormalities observed in schizophrenia, however this rodent model may model some EEG features seen in schizophrenia such as a frontally pronounced slowing of the slow EEG activity in delta and theta frequency bands.     

Sleep-disordered breathing in a predominantly African-American pediatric population

The goal of this study was to characterize sleep and respiratory parameters in children with sleep-disordered breathing (SDB) as compared to children without SDB. Data are from 198 children and adolescents referred for sleep center evaluation, 128 of whom were diagnosed with SDB. In children with SDB, obesity (> 95% wgt for age) was more common than being severely underweight (< 5% wgt for age), but only the older children with SDB were heavier than age-matched normal sleepers. Children with SDB had increased EEG arousals; sleep architecture was not otherwise significantly different from the non-SDB group. African-American children with SDB had significantly greater oxygen desaturation with obstructive events compared to Caucasian and Latino children. It appears that the role of obesity as a risk factor for obstructive sleep apnea (OSA) increases in children above the age of 8-years. Additionally, African-American children with SDB may be at increased risk for hypoxemia and cardiovascular consequences of SDB.     

Sleep–wake fluctuations and respiratory events during Cheyne–Stokes respiration in patients with heart failure

Fluctuations in sleep–wake state are thought to contribute to the respiratory instability of Cheyne–Stokes respiration in patients with heart failure by promoting the rhythmic occurrence of central apnea and ventilatory overshoot. There are no data, however, on the relationship between vigilance state and respiratory events. In this study we used a novel method to detect the occurrence of state transitions (time resolution: 0.25 s, minimum duration of state changes: 2 s) and to assess their time relationship with apnoeic events. We also evaluated whether end‐apnoeic arousals are associated with a ventilatory overshoot. A polysomnographic, daytime laboratory recording (25 min) was performed during Cheyne–Stokes respiration in 16 patients with heart failure. Automatic state classification included wakefulness and non‐rapid eye movement sleep stages 1–2. As a rule, wakefulness occurred during hyperpnoeic phases, and non‐rapid eye movement sleep occurred during apnoeic events. Ninety‐two percent of the observed central apneas (N = 272) were associated with a concurrent wakefulness → non‐rapid eye movement sleep → wakefulness transition. The delay between wakefulness → non‐rapid eye movement sleep transitions and apnea onset was ?0.3 [?3.1, 3.0] s [median (lower quartile, upper quartile); P = 0.99 testing the null hypothesis: median delay = 0], and the delay between non‐rapid eye movement sleep → wakefulness transitions and apnea termination was 0.2 [?0.5, 1.2] s (P = 0.7). A positive/negative delay indicates that the state transition occurred before/after the onset or termination of apnea. Non‐rapid eye movement sleep → wakefulness transitions synchronous with apnea termination were associated with a threefold increase in tidal volume and a twofold increase in ventilation (all P < 0.001), indicating ventilatory overshoot. These findings highlight that wakefulness → non‐rapid eye movement sleep → wakefulness transitions parallel apnoeic events during Cheyne–Stokes respiration in patients with heart failure. The relationships between state changes and respiratory events are consistent with the notion that state fluctuations promote ventilatory instability.     

DISCRIMINATION AMONG STATES OFCONSCIOUSNESS USING EEG SPECTRA

EEG recordings were made during waking (W) and the five sleep stages (REM, 1, 2, 3, and 4) on thirteen young adult males. For each stage, one-minute sections of the pa ietal EEG trace were digitized and subjected to Fourier analysis. The resulting spectral intensities were divided into five frequency bands; delta, theta, alpha, sigma, and beta. Linear discriminators for all six stages were calculated using stepwise multiple regression. The overall percent agreement with visual scoring was very poor, ranging from zero for stage 3 to 91% for stage 4. Linear discrimination between pairs of stages yielded slightly better results, but stages 1 and REM were indistinguishable. Delta is the best overall discriminator, increasing significantly through stages W, 1, 2, 3, and 4. Sigma is unique to sleep and is highest for stage 2. Theta is unimportant and beta plays no role at all. Spectral analysis of the parietal EEG lead is not sufficient to differentiate among the six states of consciousness studied here. The use of detectors for such phasic events as eye movement and K-complexes might aid sleep stage discrimination considerably.     

Electroencephalogram differences in two subtypes of attention-deficit/hyperactivity disorder

This study investigated EEG differences between children with two subtypes of Attention-Deficit/Hyperactivity Disorder (ADHD) and normal control subjects. EEG was recorded during an eyes-closed resting condition and Fourier transformed to provide absolute and relative power estimates for the delta, theta, alpha, and beta bands, and the mean frequency for each band was calculated. Ratio coefficients were also calculated between frequency bands. Mean group differences were found in the theta, alpha, and beta bands between all three groups. Similarly, differences were found between all three groups for the theta/alpha and theta/beta ratios and for the mean frequency of the total EEG. These results support a model of ADHD resulting from a developmental deviation rather than a maturational lag in the central nervous system. Differences between the clinical groups in frontal activity suggest that different neuroanatomical systems are involved in the different subtypes of ADHD.