Sleep Spindle Features and Neurobehavioral Performance in Healthy School-Aged Children.

PURPOSE: In adults, central fast-frequency sleep spindles are involved in learning and memory functions. The density of local spindles is higher than global spindles, emphasizing the importance of local plastic neural processes. In children, findings on the association of spindles with cognition are more variable. Hence, we aim to study whether the local spindles are also important for neurobehavioral performance in children. METHODS: We studied the correlations between local (occurring in only one channel: Fp1, Fp2, C3, or C4), bilateral, and diffuse (occurring in all four channels) spindles and neurobehavioral performance in 17 healthy children (median age 9.6 years). RESULTS: Local spindles were not as frequent as bilateral spindles (P-values < 0.05). Central spindle types had significant correlations with sensorimotor and language functions (e.g., the density of bilateral central spindles correlated positively with the Object Assembly in NEPSY, r = 0.490). Interestingly, frontopolar spindles correlated with behavior (e.g., the more bilateral the frontopolar spindles, the less hyperactive the children, r = -0.618). CONCLUSIONS: In children, the local spindles, but also more widespread central spindles, seem to be involved in the cognitive processes. Based on our findings, it is important that ageadjusted frequency limits are used in studies evaluating the frequencies of spindles in children.

Slow-wave activity and sigma activities are associated with psychomotor development at 8 months of age.

STUDY OBJECTIVES: The electrophysiological properties of non-rapid eye movement sleep (NREM) EEG are homeostatically modulated on global and local use-dependent levels. Furthermore, the local NREM quality reflects age-dependent brain maturation and individual, age-independent, and psychomotor potential. Cortical maturation and its electrophysiological marker, Slow-wave activity (SWA), as well as sleep spindles are known to change in topography and quality during the early years of life, but their associations with psychomotor development in infants are unknown. Therefore, we aimed to evaluate the local properties of SWA and spindles (sigma power) and ascertain whether they correlate with psychomotor development in 8-month-old infants. METHODS: Ambulatory polysomnographies were recorded in 56 infants at 8 months of age to calculate the local SWA and sigma powers. The associations between the SWA and sigma powers and psychomotor development (Bayley-III) were examined in 36 of these infants. RESULTS: In both hemispheres, the highest SWA and sigma powers were found occipitally and centrally, respectively, with higher powers in the right hemisphere than in the left. The Bayley-III correlated with local SWA and sigma powers: the occipital SWA and centro-occipital sigma correlated with cognitive scales, and the frontal and occipital SWA and centro-occipital sigma correlated with language and fine motor scales. Most of the correlations were unilateral. CONCLUSIONS: In 8-month-old infants, the NREM sleep quality shows local differences that are mostly attributable to the topical phase of brain maturation. The local NREM parameters correlate with psychomotor development.

Prolonged partial obstruction during sleep is a NREM phenomenon.

OBJECTIVE: Prolonged partial obstruction (PPO) is a common finding in sleep studies. Although not verified, it seems to emerge in deep sleep. We study the effect of PPO on sleep architecture or sleep electroencephalography (EEG) frequency. METHODS: Fifteen OSA patients, 15 PPO + OSA patients and 15 healthy subjects underwent a polysomnography. PPO was detected from Emfit mattress signal. Visual sleep parameters and median NREM sleep frequency of the EEG channels were evaluated. RESULTS: The amount of deep sleep (N3) did not differ between the PPO + OSA and control groups (medians 11.8% and 13.8%). PPO + OSA-patients' N3 consisted mostly of PPO. PPO + OSA patients had lighter sleep than healthy controls in three brain areas (Fp2-A1, C4-A1, O1-A2, p-values < 0.05). CONCLUSION: PPO evolved in NREM sleep and especially in N3 indicating that upper airway obstruction does not always ameliorate in deep sleep but changes the type. Even if PPO + OSA-patients had N3, their NREM sleep was lighter in three EEG locations. This might reflect impaired recovery function of sleep.

Local changes in computational non-rapid eye movement sleep depth in infants.

OBJECTIVE: Deep NREM sleep and its hallmark EEG phenomenon slow wave activity (SWA) are under homeostatic control in adults. SWA is also locally regulated as it increases in the brain areas that have been used intensively. Moreover, in children, SWA is a marker of cortical maturation. In the present study the local properties of NREM sleep depth were evaluated using the quantitative mean frequency method. We aimed to study if age is related to NREM sleep depth in young infants. In addition, we studied if young infants have local differences in their NREM sleep. METHODS: Ambulatory over-night polysomnographies were recorded in 59 healthy and full-term infants at the age of one month. The infants were divided into two age groups (<44 weeks and ≥44 weeks) to allow maturational evaluations. RESULTS: The quantitative sleep depth analysis showed differences between the age groups. In addition, there were local sleep depth differences within the age groups. CONCLUSIONS: The sleep depth change with age is most likely related to cortical maturation, whereas the local sleep depth gradients might also reflect the use-dependent properties of SWA. SIGNIFICANCE: The results support the idea that young infants have frontal cortical processing.

Local Differences in Computational Sleep Depth Parameters in Healthy School-aged Children.

OBJECTIVE: Slow wave sleep in children reflects several processes, such as sleep pressure, synaptic density, and cortical maturation. Deep sleep in children is abundant and our aim was to discover whether examining electroencephalography (EEG) mean frequency would help separate these processes. METHODS: Sleep EEG of 28 generally healthy 7- to 11-year-old children (14 first graders, 14 third graders, 14 girls, 14 boys) was analyzed. Median non-rapid eye movement (NREM) sleep EEG frequency (median sleep depth, in Hz) and the amount of computational deep sleep using the thresholds of 2 Hz and 4 Hz (DS2% and DS4%, respectively) were calculated from the frontopolar, central, and occipital EEG derivations. RESULTS: Median NREM sleep frequency was lower in the left frontopolar area than more posteriorly in the whole study group, in the third graders and in the girls. In the left hemisphere, the amount of DS4% was higher frontopolarly than occipitally in the third graders and in the girls. The amount of DS2% was higher frontopolarly than centrally in all groups except in the first graders. In the whole study group, DS4% declined smoothly across the NREM episodes, whereas DS2% centered in the first NREM sleep episode. DISCUSSION: The median NREM sleep EEG frequency results might denote earlier frontal maturation in girls than in boys. Interestingly, we found frontopolar predominance in slow mean EEG frequency in both hemispheres, even if frontal slow wave activity is found to enhance until adolescence. As with infants, it seems that slower sleep EEG frequencies do not reflect sleep pressure as well as <4 Hz activity in school-aged children either. CONCLUSION: Our analysis method suggests that in addition to slow wave activity, EEG frequency analysis might be useful in differentiating between the different sleep related processes in children.

Sleep During Menopausal Transition: A 6-Year Follow-Up.

Study Objectives: Menopausal transition is associated with increased dissatisfaction with sleep, but the effects on sleep architecture are conflicting. This prospective 6-year follow-up study was designed to evaluate the changes in sleep stages and sleep continuity that occur in women during menopausal transition. Methods: Sixty women (mean age 46.0 years, SD 0.9) participated. All women were premenopausal at baseline, and at the 6-year follow-up, women were in different stages of menopausal transition. Polysomnography was used to study sleep architecture at baseline and follow-up. The effects of aging and menopause (assessed as change in serum follicle-stimulating hormone [S-FSH]) on sleep architecture were evaluated using linear regression models. Results: After controlling for body mass index, vasomotor, and depressive symptoms, aging of 6 years resulted in shorter total sleep time (B -37.4, 95% confidence interval [CI] -71.5 to (-3.3)), lower sleep efficiency (B -6.5, 95%CI -12.7 to (-0.2)), as well as in increased transitions from slow-wave sleep (SWS) to wakefulness (B 1.0, 95%CI 0.1 to 1.9), wake after sleep onset (B 37.7, 95%CI 12.5 to 63.0), awakenings per hour (B 1.8, 95%CI 0.8 to 2.8), and arousal index (B 2.3, 95%CI 0.1 to 4.4). Higher S-FSH concentration in menopausal transition was associated with increased SWS (B 0.09, 95%CI 0.01 to 0.16) after controlling for confounding factors. Conclusions: A significant deterioration in sleep continuity occurs when women age from 46 to 52 years, but change from premenopausal to menopausal state restores some SWS.

CPAP Treatment Partly Normalizes Sleep Spindle Features in Obstructive Sleep Apnea.

Objective. Obstructive sleep apnea (OSA) decreases sleep spindle density and frequency. We evaluated the effects of continuous positive airway pressure (CPAP) treatment on different features of sleep spindles. Methods. Twenty OSA patients underwent two night polysomnographies in a diagnostic phase and one night polysomnography after 6 months of CPAP treatment. The control group comprised 20 healthy controls. Sleep spindles were analyzed by a previously developed automated method. Unilateral and bilateral spindles were identified in central and frontopolar brain locations. Spindle density and frequency were determined for the first and last half of the NREM time. Results. The density of bilateral central spindles, which did not change in the untreated OSA patients, increased towards the morning hours during CPAP treatment and in the controls. Central spindles did not become faster with sleep in OSA patients and the central spindles remained slow in the left hemisphere even with CPAP. Conclusion. CPAP treatment normalized spindle features only partially. The changes may be associated with deficits in thalamocortical spindle generating loops. Significance. This study shows that some sleep spindle changes persist after CPAP treatment in OSA patients. The association of these changes to daytime symptoms in OSA patients needs to be further evaluated.

Sleep apnea reduces the amount of computational deep sleep in the right frontopolar area in school-aged children.

OBJECTIVE: Obstructive sleep apnea (OSA) causes different symptoms in children, even though polysomnographic parameters that assess sleep quality may remain normal. Our spectral analysis of NREM sleep revealed local deep sleep reductions in adult OSA patients. We hypothesize that our method would also reveal local changes in pediatric OSA patients. METHODS: Polysomnographies were part of a larger study evaluating snoring in school-aged children. All right-handed children with OSA with matched peers (n=10+10) were included. The median sleep depth (in Hz) and the amount of deep sleep <4Hz (DS%) were extracted for the whole NREM sleep time and for the first four NREM sleep episodes from frontopolar, central and occipital EEG-channels. RESULTS: The main findings were that NREM sleep was lighter and DS% decreased in the right frontopolar area (p-values 0.034 and 0.019) in the OSA group when compared with the control group. CONCLUSION: Local sleep quality changes might provide new insights to evaluate the effects of pediatric OSA as our method revealed a local computational deep sleep decrease in the right frontopolar area in the OSA group. SIGNIFICANCE: The presented findings might implicate delayed local cortical development in children's OSA, which may account for the cognitive problems found in pediatric OSA.

Evaluation of the different sleep-disordered breathing patterns of the compressed tracheal sound.

OBJECTIVE: Suitability of the compressed tracheal sound signal for screening different sleep-disordered breathing patterns was evaluated. The previous results suggest that the plain pattern in the compressed sound signal represents mostly normal, unobstructed breathing, the thick pattern consists of periodic apneas/hypopneas and during the thin pattern, flow limitation in the nasal cannula signal is abundant. METHODS: Twenty-seven patients underwent a polysomnography with a tracheal sound and oesophageal pressure monitoring. The tracheal sound data was compressed and scored visually into three different breathing patterns. The percentage of oesophageal pressure values under -8cm H2O, the minimum pressure value and the average duration of the breathing cycles were extracted from 10-min episodes of those plain, thick and thin patterns. In addition, the spectral contents of the tracheal sound during the different breathing patterns were evaluated. RESULTS: The percentage of time when the oesophageal pressure negativity increased was highest during the thin pattern and lowest during the plain pattern. In addition, the thin pattern presented most high frequency components in the 1001-2000Hz frequency band of the tracheal sound. CONCLUSIONS: The results confirmed our previous findings that both the thick and thin patterns seem to consist of obstructed breathing, whereas during the plain pattern the breathing is normal, unobstructed. SIGNIFICANCE: Most screening methods for sleep-disordered breathing reveal only periodic apneas/hypopneas, but with the compressed sound signal the sustained partial obstruction can be estimated as well.

Identification of deep sleep and awake with computational EEG measures.

The objective of the present work was to examine identification of deep sleep and awake with computational analysis of sleep EEG traces from central brain regions. All-night EEG traces from a total of 56 male subjects, 22 healthy control subjects and 34 age-matched apnea patients, were examined. A spectral mean frequency measure, a Hilbert transform based EEG amplitude and a correlation coefficient method were compared. The EEG amplitude provided a good identification of deep sleep, reaching 86.25% but was relatively poor in the identification of wakefulness, reaching 39.06%. Mean frequency provided a relatively good identification of deep sleep and awake, reaching 84.66% and 77.67%, respectively, while the correlation coefficient produced the lowest results of 37.89% and 44.43%. Optimal threshold values for deep sleep and awake identification were determined as 4.20 and 9.76 Hz, respectively, for the mean frequency measure. Mean frequency measure can be used to provide overall context information about sleep depth for automated sleep EEG analysis methods.

Visual dysfunction and computational sleep depth changes in obstructive sleep apnea syndrome.

The aims of this study are to clarify whether patients with obstructive sleep apnea syndrome (OSAS) have a decline in verbally or visually-based cognitive abilities and whether the possible decline is related to particular sleep depth changes. In addition, the effect of continuous positive airway pressure (CPAP) on the possible changes is investigated. Fifteen OSAS patients and 15 healthy controls joined two full-night polysomnographies, including a computational measure of deep sleep percentage (DS%) bilaterally from the frontal, central and occipital channels, and a neuropsychological assessment. After a 6-month CPAP the patients underwent one more full-night polysomnography with computational DS% analysis and a neuropsychological assessment. At the baseline, the OSAS patients had poorer performance in the Picture Completion, in the Digit Symbol and in copying the Rey-Osterrieth Complex Figure Test (ROCFT) compared to the controls. The patients also showed reduced DS% in all 6 electrographic (EEG) channels compared to controls. The patients had an inter-hemispheric difference showing less deep sleep in the right hemisphere than in the left hemisphere both frontopolarly and centrally, while the controls showed this inter-hemispheric difference only frontopolarly. After CPAP the patients still had poorer performance in the Picture Completion and in the ROCFT. The patients continued to show reduced DS% in all 3 channels of the right hemisphere and occipitally in the left hemisphere, also the inter-hemispheric difference frontopolarly and centrally remained. OSAS patients have mild visually based cognitive dysfunction and reduced amount of deep sleep in the right hemisphere even after CPAP.

Compressed tracheal sound analysis in screening of sleep-disordered breathing.

OBJECTIVE: To evaluate the suitability of compressed tracheal sound signal for screening sleep-disordered breathing. METHODS: Thirty-three consecutive patients underwent a polysomnography with a tracheal sound analysis. Nineteen patients were healthy except for the sleep complaint, 9 were hypertonic and 3 were hypertonic and had elevated cholesterol. Minimum and maximum values of each consecutive, non-overlapping segment of 15s of original sound data were extracted. All these compressed tracheal sound traces were divided into plain, thin and thick signal periods. Also pure, 10-min episodes of plain, thin and thick tracheal sound periods were selected and the nasal pressure flow shapes during these pure sound periods were examined. RESULTS: There was a significant positive correlation between the total nocturnal amount of thick periods and AHI. Apneas and hypopneas were most common during the 10-min episodes of thick sound periods. The proportion of round (normal, non-flattened) inspiratory flow shape was highest during the pure plain periods. CONCLUSIONS: Breathing consisting of apneas and hypopneas can quite reliably be visualised with compressed tracheal sound analysis. The other interesting outcome of the study is that even prolonged flow limitation might be revealed with the method. SIGNIFICANCE: Compressed tracheal sound analysis might provide a promising screening method for obstructive apneas and hypopneas.

Reducing the effects of electrocardiographic artifacts on electro-oculography in automatic sleep analysis.

Removal of electrocardiographic (ECG) artifacts of QRS complexes from a single channel electroencephalography (EEG) and electro-oculography (EOG) can be problematic especially when no reference ECG signal is available. This study examined a simple estimation method excluding the possible QRS part of the EOG trace before spectrum estimation. The method was tested using a simple sleep classifier based on 0.5-30 Hz mean frequency of single channel sleep EOG, with the left EOG electrode referenced to the left mastoid (EOG L-M1). When QRS peaks were automatically excluded from the least square (LS) mean frequency estimation the average optimal mean frequency threshold decreased from 9.3 Hz to 8.8 Hz and agreement and Cohen's Kappa increased respectively from 89% to 90% and from 0.44 to 0.50 when compared to the traditional spectral estimation.

Development and comparison of four sleep spindle detection methods.

OBJECTIVE: The objective of the present work was to develop and compare methods for automatic detection of bilateral sleep spindles. METHODS AND MATERIALS: All-night sleep electroencephalographic (EEG) recordings of 12 healthy subjects with a median age of 40 years were studied. The data contained 6043 visually scored bilateral spindles occurring in frontopolar or central brain location. In the present work a new sigma index for spindle detection was developed, based on the fast Fourier transform (FFT) spectrum, aiming at approximating our previous fuzzy spindle detector. The sigma index was complemented with spindle amplitude analysis, based on finite impulse response (FIR) filtering, to form of a combination detector of bilateral spindles. In this combination detector, the spindle amplitude distribution of each recording was estimated and used to tune two different amplitude thresholds. This combination detector was compared to bilaterally extracted sigma indexes and fuzzy detections, which aim to be independent of absolute spindle amplitudes. As a fourth method a fixed spindle amplitude detector was included. RESULTS: The combination detector provided the best overall performance; in S2 sleep a 70% true positive rate was reached with a specificity of 98.6%, and a false-positive rate of 32%. The bilateral sigma indexes provided the second best results, followed by fuzzy detector, while the fixed amplitude detector provided the poorest results so that in S2 sleep a 70% true positive rate was reached with a specificity of 97.7% and false-positive rate of 46%. The spindle amplitude distributions automatically determined for each recording by the combination detector were compared to amplitudes of visually scored spindles and they proved to correspond well. Inter-hemispheric amplitude variation of visually scored bilateral spindles is also presented. CONCLUSION: Flexibility is beneficial in the detection of bilateral spindles. The present work advances automated spindle detection and increases the knowledge of bilateral sleep spindle characteristics.

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.

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.

Topographic differences in mean computational sleep depth between healthy controls and obstructive sleep apnoea patients.

In this work, topographic differences in computational sleep depth between healthy controls and obstructive sleep apnoea syndrome (OSAS) patients have been examined. Sleep depth estimation was based on continuous monitoring of the mean frequency of the EEG. During the experiments, all-night sleep EEG recordings of carefully age and gender matched sets of 16 healthy controls and 16 OSAS patients were compared on six electrode locations (Fp1-M2, Fp2-M1, C3-M2, C4-M1, O1-M2, and O2-M1). To optimise the diagnostic ability of the method, we examined the influence of 45 sets of adjustable analysis parameters on the ability of the method to show differences in computational sleep depth between the diagnostic groups. The results show clearly that although the visual scores for a set of epochs are the same for both clinical groups, computational sleep depth measure still shows deeper local sleep for healthy controls, both during NREM and REM sleep. Although the best achievable performance in different sleep stages is reached in different EEG derivations and with different parameter values, computation of sleep depth with 1-s output resolution in non-overlapping segments of 2s (400 samples) with maximum analysis band frequency of 20.5 Hz and 51-point moving median smoothing on Fp2-M1 or O1-M2 leads to near-optimal performance in deep sleep or wakefulness/light sleep, respectively.

Computer program for automated sleep depth estimation.

In this article, we present a new implementation of an amplitude-independent method for continuous-scale sleep depth estimation. Having been implemented as an add-on analysis module under commercially available biosignal recording and analysis software, it can be easily applied in clinical routine. The software gives the user full freedom to change all the analysis parameters inside theoretical limits. Computational sleep depth profiles produced by the presented software compare favourably with visual classifications. Future work will concentrate on systematic optimization of analysis parameters, further evaluation of the method with disturbed sleep and application of the method for automated adaptive sleep analysis.

Determination of dominant simulated spindle frequency with different methods.

Accurate analysis of EEG sleep spindle frequency is challenging. The frequency content of true sleep spindles is not known. Therefore, simulated spindle activity was studied in the present work. Five types of simulated test signals were designed, all containing a dominant spindle represented by a 13-Hz sine wave as such or with a waxing and waning pattern accompanied by a secondary spindle activity in three test signals. Background EEG was included in four test signals, modeled either as small additional sinusoids across the spindle frequency range or as filtered Gaussian noise segments. The purpose of this study was to investigate how accurately the dominant spindle frequency of 13 Hz could be resolved with different methods in the presence of the interfering waveforms. A matching pursuit (MP) based approach, discrete Fourier transform (DFT) with Hanning windowing with and without zero padding, Hankel total least squares (HTLS) and wavelet methods were compared in the analyses. MP method provided best overall performance, followed closely by DFT with zero padding. Comparative studies like this are important to decide the method of choice in clinical sleep EEG analysis.

Automatic detection of spiking events in EMFi sheet during sleep.

In this paper we present a new method for detection of spiking events caused by the increased respiratory resistance (IRR) from ballistocardiographic (BCG) data recorded with EMFi sheet. Spiking is a phenomenon where BCG wave complexes increase in amplitude during IRR. In this study data from six patients with a total of 1503 visually scored spiking events were studied. The algorithm monitors amplitude levels of BCG complexes and detects large relative increases. In this work 10 different variations of the algorithm were compared in order to find the best variation, which can cope with different recordings. The best variation of the algorithm was able to detect spiking events with 80% true positive and 19% false positive rates. The detection is not dependent on absolute waveform amplitudes and therefore does not require any recording-specific tuning prior to application. It is important to recognize spiking events in order to evaluate the severity of respiratory disturbance during sleep.