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.     

Heartbeat‐related EEG amplitude and phase modulations from wakefulness to deep sleep: Interactions with sleep spindles and slow oscillations

Based on physiological models of neurovisceral integration, different studies have shown how cognitive processes modulate heart rate and how the heartbeat, on the other hand, modulates brain activity. We tried to further determine interactions between cardiac and electrical brain activity by means of EEG. We investigated how the heartbeat modulates EEG in 23 healthy controls from wakefulness to deep sleep and showed that frontocentral heartbeat evoked EEG amplitude and phase locking (as measured by intertrial phase locking), at about 300‐400 ms after the R peak, decreased with increasing sleep depth with a renewed increase during REM sleep, which underpins the assumption that the heartbeat evoked positivity constitutes an active frontocortical response to the heartbeat. Additionally, we found that individual heart rate was correlated with the frequency of the EEG's spectral peak (i.e., alpha peak frequency during wakefulness). This correlation was strongest during wakefulness and declined linearly with increasing sleep depth. Furthermore, we show that the QRS complex modulates spindle phase possibly related to the correspondence between the frequency of the QRS complex and the spindle frequency of about 12–15 Hz. Finally, during deep sleep stages, a loose temporal coupling between heartbeats and slow oscillation (0.8 Hz) could be observed. These findings indicate that cardiac activity such as heart rate or individual heartbeats can modulate or be modulated by ongoing oscillatory brain activity.     

Topographic distribution of sleep spindles in young healthy subjects

The application of an automatic sleep spindle detection procedure allowed the documentation of the topographic distribution of spindle characteristics, such as number, amplitude, frequency and duration, as a function of sleep depth and of recording time. Multichannel all-night EEG recordings were performed in 10 normal healthy subjects aged 20–35 years. Although the interindividual variability in the number of sleep spindles was very high (2.7±2.1 spindles per minute stage 2 sleep), all but two subjects showed maximal spindle activity in centro-parietal midline leads. Moreover, this topography was seen in all sleep stages and changed only slightly – to a more central distribution – towards the end of the night. On the other hand, slow (11.5–14 Hz) and fast (14–16 Hz) spindles showed a completely different topography, with slow spindles distributed anteriorly and fast spindles centro-parietally. The number of sleep spindles per min was significant depending on sleep stages, with the expected highest occurrence in stage 2, and on recording time, with a decrease in spindle density from the beginning towards the end of the night. However, spindle amplitude, frequency and individual duration was not influenced by sleep depth or time of the night.     

Relationship between electroencephalogram slow-wave magnitude and heart rate variability during sleep in humans

To explore whether depth of sleep is related to changes in autonomic control, continuous power-spectral analysis of the electroencephalogram (EEG) and heart rate variability (HRV) was performed in ten normal subjects during nocturnal sleep. Quiet sleep (QS) was associated with an increase in high-frequency power (HF) of HRV (0.15-0.4 Hz) but a decrease in low-frequency power (LF) (0.04-0.15 Hz) to HF ratio (LF/HF) compared with awakening. During QS, LF/HF was significantly and negatively correlated with delta power of EEG (0.5-4.0 Hz), whereas mean R-R interval and HF were not. We conclude that during QS, cardiac sympathetic regulation is negatively related to the depth of sleep, although vagal regulation is not. Our methodology offers a quantitative analysis to study the interaction between cerebral cortical and autonomic functions.     

时频分析用于睡眠脑电图的梭形波识别

本文提出了一 种新的睡眠梭形 波（ｓｌｅｅｐ ｓｐｉｎｄｌｅ） 识别 方法, 它是基 于离 散 Ｇａｂｏｒ 谱分 解—一 种高 分辨率时频分析 的方法。我们对 睡眠脑电信号 进行了分析和识 别,结果表明,利 用离散 Ｇａｂｏｒ 谱方 法可准确地从睡 眠脑电波中识 别出梭形波,为 睡眠自动分阶 的实 现提供 了有效 特征。 该方法 识别梭 形波的准确率已 达到神经内 科专 家目 测的 水平。 睡眠 梭形波 的自 动识 别为 研究 睡眠 的神 经内 科专家解除了阅 读睡眠脑电图 谱的繁冗工作, 为进一步研究睡 眠生理提供了有 用的信息。     

A new method for detecting state changes in the EEG: exploratory application to sleep data

A new statistical method is described for detecting state changes in the electroencephalogram (EEG), based on the ongoing relationships between electrode voltages at different scalp locations. An EEG sleep recording from one NREM-REM sleep cycle from a healthy subject was used for exploratory analysis. A dimensionless function defined at discrete times t_i, u(t_i), was calculated by determining the log-likelihood of observing all scalp electrode voltages under the assumption that the data can be modeled by linear combinations of stationary relationships between derivations. The u(t_i), calculated by using independent component analysis, provided a sensitive, but non-specific measure of changes in the global pattern of the EEG. In stage 2, abrupt increases in u(t_i) corresponded to sleep spindles. In stages 3 and 4, low frequency (≈ 0.6 Hz) oscillations occurred in u(t_i) which may correspond to slow oscillations described in cellular recordings and the EEG of sleeping cats. In stage 4 sleep, additional irregular very low frequency (≈ 0.05–0.2 Hz) oscillations were observed in u(t_i) consistent with possible cyclic changes in cerebral blood flow or changes of vigilance and muscle tone. These preliminary results suggest that the new method can detect subtle changes in the overall pattern of the EEG without the necessity of making tenuous assumptions about stationarity.     

Systematic performance evaluation of a continuous-scale sleep depth measure

In this article, systematic performance evaluation of a continuous-scale sleep depth measure will be discussed. Our main objective has been to select the adjustable analysis parameters such that the best possible correspondence between method output and standard visual sleep staging could be achieved. Sleep depth estimation was based on continuous monitoring of short-time EEG synchronization through the local mean frequency of the EEG. During the experiments, total amount of 752 different combinations of four adjustable parameters were compared based on all-night sleep EEG recordings of 15 healthy subjects. Optimization strategy applied was based on maximizing the weighted average of pair-wise separabilities of EEG mean frequency distributions in all the standard sleep stage pairs. Finally, robustness of the optimized parameters was verified with an independent dataset of 34 all-night sleep recordings.

Our results show that clear topological differences between brain hemispheres and different electrode locations exist. Performance improvements of even 20–30% units can be achieved by proper selection of analysis parameters and the EEG derivation used for the analysis. Remarkable independence of system performance on the analysis window length leads to improved temporal resolution compared to that achieved through standard visual analysis. In addition to giving practical suggestions on the parameter selection, we also propose a possible method for improving stage separability especially between S2 and REM.     

多分辨率小波信号分解用于大鼠睡眠纺锤波的分析

本研究首先设计了慢波睡眠期脑电信号的合成仿真信号 ,对小波基函数进行了选择 ,结果证明Coiflet 5阶小波变换对大鼠慢波睡眠期EEG信号具有较好的分解结果。据此 ,应用多分辨率小波分析法设计了提取睡眠纺锤波的算法 ,并利用该算法对安定用药后和睡眠剥夺后大鼠慢波睡眠期纺锤波的持续时间和能量变化进行了分析 ,结果表明 :安定具有延长慢波睡眠期纺锤波持续时间的作用 ,而睡眠剥夺可以增加慢波睡眠期纺锤波的能量。这些结果说明 ,小波分析算法可以提供功率谱分析无法表现的时频信息。     

Sleep misperception,EEG characteristics and Autonomic Nervous System activity in primary insomnia: A retrospective study on polysomnographic data

Misperception of Sleep Onset Latency, often found in Primary Insomnia, has been cited to be influenced by hyperarousal, reflected in EEG- and ECG-related indices. The aim of this retrospective study was to examine the association between Central Nervous System (i.e. EEG) and Autonomic Nervous System activity in the Sleep Onset Period and the first NREM sleep cycle in Primary Insomnia (n = 17) and healthy controls (n = 11). Furthermore, the study examined the influence of elevated EEG and Autonomic Nervous System activity on Stage2 sleep-protective mechanisms (K-complexes and sleep spindles). Confirming previous findings, the Primary Insomnia-group overestimated Sleep Onset Latency and this overestimation was correlated with elevated EEG activity. A higher amount of beta EEG activity during the Sleep Onset Period was correlated with the appearance of K-complexes immediately followed by a sleep spindle in the Primary Insomnia-group. This can be interpreted as an extra attempt to protect sleep continuity or as a failure of the sleep-protective role of the K-complex by fast EEG frequencies following within one second. The strong association found between K-alpha (K-complex within one second followed by 8–12 Hz EEG activity) in Stage2 sleep and a lower parasympathetic Autonomic Nervous System dominance (less high frequency HR) in Slow-wave sleep, further assumes a state of hyperarousal continuing through sleep in Primary Insomnia.     

The effects of age and gender on sleep EEG power spectral density in the middle years of life (ages 20-60 years old)

The effects of age and gender on sleep EEG power spectral density were assessed in a group of 100 subjects aged 20 to 60 years. We propose a new statistical strategy (mixed-model using fixed-knot regression splines) to analyze quantitative EEG measures. The effect of gender varied according to frequency, but no interactions emerged between age and gender, suggesting that the aging process does not differentially influence men and women. Women had higher power density than men in delta, theta, low alpha, and high spindle frequency range. The effect of age varied according to frequency and across the night. The decrease in power with age was not restricted to slow-wave activity, but also included theta and sigma activity. With increasing age, the attenuation over the night in power density between 1.25 and 8.00 Hz diminished, and the rise in power between 12.25 and 14.00 Hz across the night decreased. Increasing age was associated with higher power in the beta range. These results suggest that increasing age may be related to an attenuation of homeostatic sleep pressure and to an increase in cortical activation during sleep.     

Cortical locations of maximal spindle activity: magnetoencephalography (MEG) study

The aim of this study was to determine the main cortical regions related to maximal spindle activity of sleep stage 2 in healthy individual subjects during a brief morning nap using magnetoencephalography (MEG). Eight volunteers (mean age: 26.1 ± 8.7, six women) all right handed, free of any medical psychiatric or sleep disorders were studied. Whole-head 148-channel MEG and a conventional polysomnography montage (EEG; C3, C4, O1 and O2 scalp electrodes and EOG, EMG and ECG electrodes) were used for data collection. Sleep MEG/EEG spindles were visually identified during 15 min of stage 2 sleep for each participant. The distribution of brain activity corresponding to each spindle was calculated using a combination of independent component analysis and a current source density technique superimposed upon individual MRIs. The absolute maximum of spindle activation was localized to frontal, temporal and parietal lobes. However, the most common cortical regions for maximal source spindle activity were precentral and/or postcentral areas across all individuals. The present study suggests that maximal spindle activity localized to these two regions may represent a single event for two types of spindle frequency: slow (at 12 Hz) and fast (at 14 Hz) within global thalamocortical coherence.     

Sleep Spindle Activity Is Correlated With Reading Abilities in Developmental Dyslexia

Study Objectives:

To analyze sleep architecture of children with dyslexia, by means of conventional parameters and EEG spectral analysis and to correlate sleep parameters and EEG spectra with neuropsychological measures.

Design:

Cross-sectional study involving validated sleep questionnaires, neuropsychological scales, and polysomnographic recordings.

Setting:

Sleep laboratory in academic center.

Participants:

Sixteen subjects with developmental dyslexia (mean age 10.8 years) and 11 normally reading children (mean age 10.1 years). All the subjects underwent overnight polysomnographic recording; EEG power spectra were computed from the Cz derivation and spindle density was calculated during sleep stages N2.

Intervention:

N/A

Measurements and Results:

Dyslexic children showed an increase in power of frequency bands between 0.5–3 Hz and 11–12 Hz in stage N2 and between 0.5–1 Hz in stage N3; they also showed significantly increased spindle density during N2. The power of the sigma band in N2 was positively correlated with the Word reading and MT reading tests; similarly, spindle density was significantly correlated with the Word reading test. The increased spindle activity and EEG sigma power in dyslexic subjects were found to be correlated with the degree of dyslexic impairment.

Conclusions:

The correlation found between sleep spindle activity and reading abilities in developmental dyslexia supports the hypothesis of a role for NREM sleep and spindles in sleep-related neurocognitive processing.

Citation:

Bruni O; Ferri R; Novelli L; Terribili M; Troianiello M; Finotti E; Leuzzi V; Curatolo P. Sleep spindle activity is correlated with reading abilities in developmental dyslexia. SLEEP 2009;32(10):1333-1340.     

Computerized endopharyngeal myotonometry (CEM): a new method to evaluate the tissue tone of the soft palate in patients with obstructive sleep apnoea syndrome

This study compared the tissue tone of the soft palate in nonsnoring subjects and patients with obstructive sleep apnoea syndrome (OSAS) during wakefulness. Here, tissue tone means the biomechanical property of the tissue which can be characterized by two main parameters: stiffness and elasticity. Tissue tone includes both structural and neural components. A new method to evaluate the tissue tone of the soft palate was used - computerized endopharyngeal myotonometry (CEM). This method records and analyses the response of the soft palate tissues to a brief mechanical impact. The method enabled us to evaluate the most important parameters of tissue tone: stiffness, which is expressed as a frequency; and elasticity, expressed as a logarithmic decrement of the damped oscillation. First, a self-reported questionnaire was completed about the medical history of the subjects. Subjects then underwent a physical examination of the oropharynx and polysomnography with overnight pulse oximetry. The results of the CEM method indicated that patients with OSAS show an increased stiffness of the soft palate tissues (20.3, SD 4.7 Hz) compared with nonsnoring subjects (12.2, SD 1.8 Hz). In patients with sleep apnoea, elasticity is not increased in a similar way to stiffness. Thus, the disproportion between tissue stiffness and elasticity of the soft palate is a measure of the pathological changes in patients with sleep apnoea.     

Apnea patients show a frontopolar inter-hemispheric spindle frequency difference

Sleep apnea syndrome is known to disturb sleep. The purpose of the present work was to study spindle frequency in apnea patients. All-night sleep EEG recordings of 15 apnea patients and 15 control subjects with median ages of 47 and 46 years, respectively, were studied. A previously presented and validated multi-channel spindle analysis method was applied for automatic detection and frequency analysis of bilateral frontopolar and central spindles. Bilateral frontopolar spindles of apnea patients were found to show lower frequencies on the left hemisphere than on the right. Such an inter-hemispheric spindle frequency difference in apnea patients is a novel finding. It could be that the hypoxias and hypercapnias caused by apneic episodes result in local disruption in the regulation of sleep in the frontal lobes.     

一种高分辨率的时频分析方法用于睡眠脑电图梭形波识别的研究

提出了一种新的睡眠梭形波(sleep spindle)识别方法——离散Gabor谱分解,在研究睡眠脑电波特征的基础上利用这一高分辨率的时频分析方法对睡眠脑电进行了分析处理。结果显示,离散Gabor谱方法可有效地从睡眠脑电波中识别出梭形波,为睡眠自动分阶的实现提供了特征。该方法识别梭形波的准确率已接近神经内科专家目测的水平,识别准确率达到93%以上。睡眠梭形波的自动识别为研究睡眠的神经内科专家解除了阅读睡眠脑电图谱的繁冗工作,为进一步研究睡眠生理提供了有用的信息。     

Effects of evening bright light exposure on melatonin, body temperature and sleep

SUMMARY  Five male subjects were exposed to a single 2-h period of bright (2500 lux) or dim (<100 lux) light prior to sleep on two consecutive nights. The two conditions were repeated the following week in opposite order. Bright light significantly suppressed salivary melatonin and raised rectal temperature 0.3°C (which remained elevated during the first 1.5 h of sleep), without affecting tympanic temperature. Bright light also increased REM latency, NREM period length, EEG spectral power in low frequency, 0.75-8 Hz and sigma, 12–14 Hz (sleep spindle) bandwidths during the first hour of sleep, and power of all frequency bands (0.5–32 Hz) within the first NREMP. Potentiation of EEG slow wave activity (0.5-4.0 Hz) by bright light persisted through the end of the second NREMP. The enhanced low-frequency power and delayed REM sleep after bright light exposure could represent a circadian phase-shift and/or the effect of an elevated rectal temperature, possibly mediated by the suppression of melatonin.     

Increased EEG sigma and beta power during NREM sleep in primary insomnia

The hyperarousal model of primary insomnia suggests that a deficit of attenuating arousal during sleep might cause the experience of non-restorative sleep. In the current study, we examined EEG spectral power values for standard frequency bands as indices of cortical arousal and sleep protecting mechanisms during sleep in 25 patients with primary insomnia and 29 good sleeper controls. Patients with primary insomnia demonstrated significantly elevated spectral power values in the EEG beta and sigma frequency band during NREM stage 2 sleep. No differences were observed in other frequency bands or during REM sleep. Based on prior studies suggesting that EEG beta activity represents a marker of cortical arousal and EEG sleep spindle (sigma) activity is an index of sleep protective mechanisms, our findings may provide further evidence for the concept that a simultaneous activation of wake-promoting and sleep-protecting neural activity patterns contributes to the experience of non-restorative sleep in primary insomnia.     

Temporal evolution of coherence and power in the human sleep electroencephalogram

Coherence analysis of the human sleep electroencephalogram (EEG) was used to investigate relations between brain regions. In all-night EEG recordings from eight young subjects, the temporal evolution of power and coherence spectra within and between cerebral hemispheres was investigated from bipolar derivations along the antero-posterior axis. Distinct peaks in the power and coherence spectra were present in NREM sleep but not in REM sleep. They were situated in the frequency range of sleep spindles (13–14 Hz), alpha band (9–10 Hz) and low delta band (1–2 Hz). Whereas the peaks coincided in the power and coherence spectra, a dissociation of their temporal evolution was observed. In the low delta band, only power but not coherence showed a decline across successive NREM sleep episodes. Moreover, power increased gradually in the first part of a NREM sleep episode, whereas coherence showed a rapid rise. The results indicate that the intrahemispheric and interhemispheric coherence of EEG activity attains readily a high level in NREM sleep and is largely independent of the signal amplitude.     

Effects of systemic atropine sulfate administration on the frequency content of the cat sensorimotor EEG during sleep and waking

Sensorimotor electroencephalogram (EEG) frequencies in cats were evaluated with power spectral analysis before and after 3 doses of atropine sulfate. All doses of atropine tested caused enhanced EEG slow waves (0-7 Hz) and spindles (8-15 Hz) during waking immobility, and postdrug frequency profiles during slow-wave sleep and waking immobility were identical. With 0.75 mg/kg atropine, movement (head movement, locomotion) resulted in EEG desynchronization and reduced power in all frequencies less than 24 Hz. After 1.5 or 3.0 mg/kg atropine, power in low frequencies remained elevated during movement, but power in spindle frequencies was significantly reduced compared with other states. During active REM sleep after 1.5 mg/kg atropine, power in spindle frequencies was significantly lower than that during quiet REM sleep. These results indicate that the sensorimotor cortical EEG in cats is under the control of multiple systems. At least 1 of these systems is active during movement, and its actions are resistant to muscarinic receptor blockade.     

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%.