Optimization of sigma amplitude threshold in sleep spindle detection

Sleep spindles are transient EEG waveforms of non-rapid eye movement sleep. There is considerable intersubject variability in spindle amplitudes. The problem in automatic spindle detection has been that, despite this fact, a fixed amplitude threshold has been used. Selection of the spindle detection threshold value is critical with respect to the sensitivity of spindle detection. In this study a method was developed to estimate the optimal recording-specific threshold value for each all-night recording without any visual scorings. The performance of the proposed method was validated using four test recordings each having a very different number of visually scored spindles. The optimal threshold values for the test recordings could be estimated well. The presented method seems very promising in providing information about sleep spindle amplitudes of individual all-night recordings.     

Spindles are highly heritable as identified by different spindle detectors

Study ObjectivesSleep spindles, a defining feature of stage N2 sleep, are maximal at central electrodes and are found in the frequency range of the electroencephalogram (EEG) (sigma 11–16 Hz) that is known to be heritable. However, relatively little is known about the heritability of spindles. Two recent studies investigating the heritability of spindles reported moderate heritability, but with conflicting results depending on scalp location and spindle type. The present study aimed to definitively assess the heritability of sleep spindle characteristics.MethodsWe utilized the polysomnography data of 58 monozygotic and 40 dizygotic same-sex twin pairs to identify heritable characteristics of spindles at C3/C4 in stage N2 sleep including density, duration, peak-to-peak amplitude, and oscillation frequency. We implemented and tested a variety of spindle detection algorithms and used two complementary methods of estimating trait heritability.ResultsWe found robust evidence to support strong heritability of spindles regardless of detector method (h² > 0.8). However not all spindle characteristics were equally heritable, and each spindle detection method produced a different pattern of results.ConclusionsThe sleep spindle in stage N2 sleep is highly heritable, but the heritability differs for individual spindle characteristics and depends on the spindle detector used for analysis.     

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.     

Validating an automated sleep spindle detection algorithm using an individualized approach

The goal of the current investigation was to develop a systematic method to validate the accuracy of an automated method of sleep spindle detection that takes into consideration individual differences in spindle amplitude. The benchmarking approach used here could be employed more generally to validate automated spindle scoring from other detection algorithms. In a sample of Stage 2 sleep from 10 healthy young subjects, spindles were identified both manually and automatically. The minimum amplitude threshold used by the prana ^® (PhiTools, Strasbourg, France) software spindle detection algorithm to identify a spindle was subject‐specific and determined based upon each subject’s mean peak spindle amplitude. Overall sensitivity and specificity values were 98.96 and 88.49%, respectively, when compared to manual scoring. Selecting individual amplitude thresholds for spindle detection based on systematic benchmarking data may validate automated spindle detection methods and improve reproducibility of experimental results. Given that interindividual differences are accounted for, we feel that automatic spindle detection provides an accurate and efficient alternative approach for detecting sleep spindles.     

Unilateral thalamic stroke does not decrease ipsilateral sleep spindles

STUDY OBJECTIVES: To measure the sleep spindle characteristics in patients with unilateral thalamic stroke. DESIGN: A prospective study of patients with thalamic stroke and age-matched healthy controls. SETTING: Department of Neurology of a University Hospital. PARTICIPANTS: Thirteen patients (mean age: 67 years, SD: 13,44) with an isolated, unilateral acute thalamic stroke and 18 healthy age-matched volunteers. INTERVENTIONS: A polysomnogram recording from 14 scalp EEG electrodes performed during 2 consecutive nights, the second or third week after the stroke. Only the sleep of the second night was analyzed. MEASUREMENTS AND RESULTS: Sleep spindles were counted during two separate 10-minute epochs of stage II. Spindles appearing synchronously in both sides with similar amplitude were called "bilateral." Spindles with twice the amplitude in one side than the other were "right" or "left-side predominant". There were 8 patients with posterolateral, 3 with global and 2 with anterior lesions. Eight were right and 5 left-sided. The number of spindles was similar in patients (39.8 +/- 23.4 in 20 minutes) than controls (26.07 +/- 29.07; p=0.173). Spindles with a centroparietal (34%) and centroparieto-occipital localization (22%) were the most frequent. In controls approximately 66% of the spindles had a bilateral and symmetric distribution over the scalp, 23% of the spindles were predominantly left-sided and 5% were predominantly right-sided. In patients, bilateral spindles decreased (p<0.0001) but asymmetric spindles did not change. CONCLUSION: Unilateral acute thalamic stroke does not decrease sleep spindles ipsilaterally; rather, it seems to produce a bilateral diminution in their number.     

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.     

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。     

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。     

Sleep spindle frequency changes during the menstrual cycle

SUMMARY  Five healthy adult women aged 20 to 28 had 12–15 polysomnographic recordings, as well as daily basal body temperature and multiple LH, FSH, estrogen and progesterone measurements taken during a single menstrual cycle. Sleep stages were scored both visually and with a spindle and delta-wave, real-time, automatic analysing system. A cubic growth-curve model showed that the frequency of sleep spindles changed markedly over the menstrual cycle: spindle frequency was lowest about 18 days before onset of menses and highest 3 days before onset of menses. Slow waves did not change. The percentages of Stage 1 and REM sleep showed small changes during the menstrual cycle, and other parameters of visually scored sleep showed no tendency to change. Spindle frequency may reflect the effects of sex hormones on the reticular thalamic nucleus and may be a quantitative marker of premenstrual sleep disturbances.     

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。     

The association between sleep spindles and IQ in healthy school-age children

Recent studies have suggested that sleep is associated with IQ measures in children, but the underlying mechanism remains unknown. An association between sleep spindles and IQ has been found in adults, but only two previous studies have explored this topic in children. The goal of this study was to examine whether sleep spindle frequency, amplitude, duration and/or density were associated with performance on the perceptual reasoning, verbal comprehension, working memory, and processing speed subscales of the Wechsler Intelligence Scale for Children-IV (WISC-IV). We recruited 29 typically developing children 7–11 years of age. We used portable polysomnography to document sleep architecture in the natural home environment and evaluated IQ. We found that lower sleep spindle frequency was associated with better performance on the perceptual reasoning and working memory WISC-IV scales, but that sleep spindle amplitude, duration and density were not associated with performance on the IQ test.     

Reliability of sleep spindle measurements in adolescents: How many nights are necessary?

Evidence of night‐to‐night variation in adolescent sleep spindle characteristics is lacking. Twelve adolescents (M = 15.8 ± 0.8 years, eight males) participated in a laboratory study involving 9 nights with 10 hr sleep opportunity. Sleep electroencephalograph was analysed and intra‐class coefficients calculated to determine the reliability of sleep spindles across multiple nights of recording. Slow spindle amplitude and fast spindle density, duration and amplitude characteristics all had acceptable reliability within a single night of sleep recording. Slow spindle density and duration measurements needed a minimum of 4 and 2 nights, respectively, for reliable estimation. Theoretical and methodological implications are discussed.     

Topography of age-related changes in sleep spindles

Aging induces multiple changes to sleep spindles, which may hinder their alleged functional role in memory and sleep protection mechanisms. Brain aging in specific cortical regions could affect the neural networks underlying spindle generation, yet the topography of these age-related changes is currently unknown. In the present study, we analyzed spindle characteristics in 114 healthy volunteers aged between 20 and 73 years over 5 anteroposterior electroencephalography scalp derivations. Spindle density, amplitude, and duration were higher in young subjects than in middle-aged and elderly subjects in all derivations, but the topography of age effects differed drastically. Age-related decline in density and amplitude was more prominent in anterior derivations, whereas duration showed a posterior prominence. Age groups did not differ in all-night spindle frequency for any derivation. These results show that age-related changes in sleep spindles follow distinct topographical patterns that are specific to each spindle characteristic. This topographical specificity may provide a useful biomarker to localize age-sensitive changes in underlying neural systems during normal and pathological aging.     

Automatic classification of the cats vigilance state.

A special purpose hardware system has been interfaced with a minicomputer for determining the vigilance state in the cat and for quantifying delta and sigma spindle activity in the sleep EEG. The computer agreement with manual scoring is 93.8% when the state is classified as awake. non-REM, or REM sleep. The system identifies six distinct vigilance states: REM sleep, slow-wave sleep 1 or 2 (distinguished by differences in EMG level), light sleep, resting and movement. Five day averages of vigilance state and EEG activity are presented for three animals, and the effects of 5 HTP and L-dopa on delta activity and sleep spindles have been quantified for one cat in order to demonstrate the system utility.     

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.     

Sleep spindles comprise a subset of a broader class of electroencephalogram events

Study ObjectivesSleep spindles are defined based on expert observations of waveform features in the electroencephalogram (EEG) traces. This is a potentially limiting characterization, as transient oscillatory bursts like spindles are easily obscured in the time domain by higher amplitude activity at other frequencies or by noise. It is therefore highly plausible that many relevant events are missed by current approaches based on traditionally defined spindles. Given their oscillatory structure, we reexamine spindle activity from first principles, using time-frequency activity in comparison to scored spindles.MethodsUsing multitaper spectral analysis, we observe clear time-frequency peaks in the sigma (10–16 Hz) range (TFσ peaks). While nearly every scored spindle coincides with a TFσ peak, numerous similar TFσ peaks remain undetected. We therefore perform statistical analyses of spindles and TFσ peaks using manual and automated detection methods, comparing event cooccurrence, morphological similarities, and night-to-night consistency across multiple datasets.ResultsOn average, TFσ peaks have more than three times the rate of spindles (mean rate: 9.8 vs. 3.1 events/minute). Moreover, spindles subsample the most prominent TFσ peaks with otherwise identical spectral morphology. We further demonstrate that detected TFσ peaks have stronger night-to-night rate stability (ρ = 0.98) than spindles (ρ = 0.67), while covarying with spindle rates across subjects (ρ = 0.72).ConclusionsThese results provide compelling evidence that traditionally defined spindles constitute a subset of a more generalized class of EEG events. TFσ peaks are therefore a more complete representation of the underlying phenomenon, providing a more consistent and robust basis for future experiments and analyses.     

Habitual napping moderates motor performance improvements following a short daytime nap

The effect of napping on motor performance was examined in habitual and non-habitual nappers who were randomly assigned to a nap or reading condition. Motor procedural learning and auditory discrimination tasks were administered pre- and post-condition. Both groups reported improved alertness post-nap, but not post-reading. Non-habitual nappers fell asleep faster and tended to have greater sleep efficiency, but did not differ from habitual nappers on other sleep architecture variables. Habitual nappers had greater alpha and theta EEG power in stage 1, and greater delta, alpha and sigma power in stage 2 sleep. Motor performance deteriorated for non-habitual nappers who napped, but improved for all others. The number of sleep spindles and sigma power (13.5-15 Hz) significantly predicted motor performance following the nap, for habitual nappers only. Results indicate that motor learning was consolidated in a brief nap and was associated with stage 2 spindles, but only for those who habitually take naps.     

Nicotine increases sleep spindle activity

Studies have shown that both nicotine and sleep spindles are associated with enhanced memorisation. Further, a few recent studies have shown how cholinergic input through nicotinic and muscarinic receptors can trigger or modulate sleep processes in general, and sleep spindles in particular. To better understand the interaction between nicotine and sleep spindles, we compared in a single blind randomised study the characteristics of sleep spindles in 10 healthy participants recorded for 2 nights, one with a nicotine patch and one with a sham patch. We investigated differences in sleep spindle duration, amplitude, intra‐spindle oscillation frequency and density (i.e. spindles per min). We found that under nicotine, spindles are more numerous (average increase: 0.057 spindles per min; 95% confidence interval: [0.025–0.089]; p = .0004), have higher amplitude (average amplification: 0.260 μV; confidence interval: [0.119–0.402]; p = .0032) and last longer (average lengthening: 0.025 s; confidence interval: [0.017–0.032]; p = 2.7e‐11). These results suggest that nicotine can increase spindle activity by acting on nicotinic acetylcholine receptors, and offer an attractive hypothesis for common mechanisms that may support memorisation improvements previously reported to be associated with nicotine and sleep spindles.     

Fast sleep spindle (13-15 hz) activity correlates with sleep-dependent improvement in visuomotor performance

STUDY OBJECTIVES: The relationship between memory enhancement and fast (13-16 Hz) versus slow (10-13 Hz) spindle activity during sleep was investigated. DESIGN: Standard polysomnographic recordings were conducted during an adaptation, control nonlearning, and learning night. Automatic spindle detection and measurement was utilized with visual confirmation. SETTING: Participants slept in individual, temperature-controlled bedrooms in a sleep laboratory. PARTICIPANTS: Twelve healthy student volunteers (9 women and 3 men, mean age: 22.3 years) participated. INTERVENTIONS: On the learning night, participants completed a presleep learning session on a modified version of mirror-tracing task followed by a postsleep test session. No learning or test sessions were performed on the adaptation and nonlearning nights. MEASUREMENTS AND RESULTS: Tracing time was reduced by 6.4 seconds (20.6% +/- 2.07%) from the presleep to the postsleep session. Mean amplitude and duration of fast spindles was greater on the learning night than on the nonlearning night (both P values < 0.05). Skill improvement and fast-spindle activity were positively correlated (density [r = 0.76, P < 0.01], amplitude [r = 0.69, P < 0.05], and duration [r = 0.67, P <0.05]). Significant correlations between fast-spindle activity and mirror-tracing performance were also evident for the nonlearning night. There was no significant relationship between mirror-tracing performance and slow-spindle activity on any night. CONCLUSIONS: The thalamocortical network underlying fast-spindle generation may contribute to or reflect plasticity during sleep.     

Fuzzy detection of EEG alpha without amplitude thresholding

Intelligent automated systems are needed to assist the tedious visual analysis of polygraphic recordings. Most systems need detection of different electroencephalogram (EEG) waveforms. The problem in automated detection of alpha activity is the large inter-individual variability of its amplitude and duration. In this work, a fuzzy reasoning based method for the detection of alpha activity was designed and tested using a total of 32 recordings from seven different subjects. Intelligence of the method was distributed to features extracted and the way they were combined. The ranges of the fuzzy rules were determined based on feature statistics. The advantage of the detector is that no alpha amplitude threshold needs to be selected. The performance of the alpha detector was assessed with receiver operating characteristic (ROC) curves. When the true positive rate was 94.2%, the false positive rate was 9.2%, which indicates good performance in sleep EEG analysis.