CAP components and EEG synchronization in the first 3 sleep cycles

Restless sleep disorder in children with epileptic and non-epileptic nocturnal attacks

Restless sleep disorder (RSD) is an important sleep disorder characterised by the presence of frequent large muscle movements (LMM) during sleep, which may be comorbid to other conditions/diseases. In this study, we investigated the frequency and the characteristics of RSD among children who were evaluated by polysomnography (PSG) due to epileptic and non-epileptic nocturnal attacks. We analysed consecutively children younger than 18 years who were referred for PSG recording due to abnormal motor activities during sleep. The diagnosis of nocturnal events as sleep-related epilepsy was made based on the current consensus. Patients who were referred with suspicion of sleep-related epilepsy, but who were diagnosed to have non-epileptic nocturnal events and children with a definitive diagnosis of NREM sleep parasomnias were also enrolled. Sixty-two children were analysed in this study (17 children with sleep-related epilepsy, 20 children with NREM parasomnia, and 25 children with nocturnal events not otherwise classified [neNOS]). The mean number of LMM, LMM index, LMM-associated with arousal and its index were all significantly higher in children with sleep-related epilepsy. Restless sleep disorder was present in 47.1% of patients with epilepsy, 25% of patients with parasomnia, and in 20% of patients with neNOS. The mean A3 duration and the A3 index were higher in children with sleep-related epilepsy and RSD compared with those with parasomnia and restless sleep disorder. Patients with RSD had lower ferritin levels than those without RSD in all subgroups. Our study demonstrates a high prevalence of restless sleep disorder in children with sleep-related epilepsy, associated with an increased cyclic alternating pattern.

[The role of cerebral activation in the sleep-wake cycle]

The development of views on cerebral activation in the wakefulness-sleep cycle, starting with the work of Constantin von Economo, is considered. The emphasis is on the cyclic activation of high-amplitude discharges in sleep, which, with known assumptions, can include K-complexes, as well as patterns of delta-like waves. Considering the participation of the peripheral nervous system in this, the integrative role of cyclic activation of high-amplitude discharges in the organization of the sleep-wake cycle is discussed.

Criticality of neuronal avalanches in human sleep and their relationship with sleep macro- and micro-architecture

Sleep plays a key role in preserving brain function, keeping brain networks in a state that ensures optimal computation. Empirical evidence indicates that this state is consistent with criticality, where scale-free neuronal avalanches emerge. However, the connection between sleep architecture and brain tuning to criticality remains poorly understood. Here, we characterize the critical behavior of avalanches and study their relationship with sleep macro- and micro-architectures, in particular, the cyclic alternating pattern (CAP). We show that avalanches exhibit robust scaling behaviors, with exponents obeying scaling relations consistent with the mean-field directed percolation universality class. We demonstrate that avalanche dynamics is modulated by the NREM-REM cycles and that, within NREM sleep, avalanche occurrence correlates with CAP activation phases-indicating a potential link between CAP and brain tuning to criticality. The results open new perspectives on the collective dynamics underlying CAP function, and on the relationship between sleep architecture, avalanches, and self-organization to criticality.

Automatic Cyclic Alternating Pattern (CAP) analysis: Local and multi-trace approaches

The Cyclic Alternating Pattern (CAP) is composed of cycles of two different electroencephalographic features: an activation A-phase followed by a B-phase representing the background activity. CAP is considered a physiological marker of sleep instability. Despite its informative nature, the clinical applications remain limited as CAP analysis is a time-consuming activity. In order to overcome this limit, several automatic detection methods were recently developed. In this paper, two new dimensions were investigated in the attempt to optimize novel, efficient and automatic detection algorithms: 1) many electroencephalographic leads were compared to identify the best local performance, and 2) the global contribution of the concurrent detection across several derivations to CAP identification. The developed algorithms were tested on 41 polysomnographic recordings from normal (n = 8) and pathological (n = 33) subjects. In comparison with the visual CAP analysis as the gold standard, the performance of each algorithm was evaluated. Locally, the detection on the F4-C4 derivation showed the best performance in comparison with all other leads, providing practical suggestions of electrode montage when a lean and minimally invasive approach is preferable. A further improvement in the detection was achieved by a multi-trace method, the Global Analysis—Common Events, to be applied when several recording derivations are available. Moreover, CAP time and CAP rate obtained with these algorithms positively correlated with the ones identified by the scorer. These preliminary findings support efficient automated ways for the evaluation of the sleep instability, generalizable to both normal and pathological subjects affected by different sleep disorders.

Restless sleep disorder in children with NREM parasomnias

STUDY OBJECTIVES

Restless sleep disorder (RSD) is a newly defined sleep disorder in the pediatric age group. Here, we investigated the frequency of RSD and the sleep characteristics in children with NREM (non-rapid eye movements) parasomnias associated with RSD.

METHODS

We analyzed all patients with NREM parasomnias for the last 1 year, and investigated the clinical and polysomnographic characteristics.

RESULTS

Twenty-eight children with NREM parasomnias and age- and gender-matched 20 healthy children were analyzed. The diagnosis of RSD was made in eight children with NREM parasomnias (28.6%), and none of the children had RSD in controls (p = 0.008). The most common diagnosis among children with RSD was somnambulism (six children), but not significantly (p = 0.308). Sleep efficiency was lower in children with RSD than those without RSD (p = 0.033). In cyclic alternating pattern analysis (CAP), CAP rate, durations and the indices of phases A1, A2, and A3 were significantly higher in children with NREM parasomnias in compared to controls. CAP parameters between children with or without RSD; however, were similar, except for higher index of phase A3 in children with RSD, suggesting arousal reactions accompanying RSD.

CONCLUSIONS

We demonstrated that RSD was present in almost one third of the children with NREM parasomnias. Sleep quality was worse in children with NREM parasomnias and RSD. An increase in sleep instability compatible with NREM parasomnia was present, while an increased phase A3 in RSD was remarkable. RSD is associated with a worse sleep quality and increased arousals, and should be questioned in children with NREM parasomnias.

Ultradian modulation of cortical arousals during sleep: effects of age and exposure to nighttime transportation noise

STUDY OBJECTIVES

The present study aimed at assessing the temporal non-rapid eye movement (NREM) EEG arousal distribution within and across sleep cycles and its modifications with aging and nighttime transportation noise exposure, factors that typically increase the incidence of EEG arousals.

METHODS

Twenty-six young (19-33 years, 12 women) and 16 older (52-70 years, 8 women) healthy volunteers underwent a 6-day polysomnographic laboratory study. Participants spent two noise-free nights and four transportation noise exposure nights, two with continuous and two characterized by eventful noise (average sound levels of 45 dB, maximum sound levels between 50 and 62 dB for eventful noise). Generalized mixed models were used to model the time course of EEG arousal rates during NREM sleep and included cycle, age, and noise as independent variables.

RESULTS

Arousal rate variation within NREM sleep cycles was best described by a u-shaped course with variations across cycles. Older participants had higher overall arousal rates than the younger individuals with differences for the first and the fourth cycle depending on the age group. During eventful noise nights, overall arousal rates were increased compared to noise-free nights. Additional analyses suggested that the arousal rate time course was partially mediated by slow wave sleep (SWS).

CONCLUSIONS

The characteristic u-shaped arousal rate time course indicates phases of reduced physiological sleep stability both at the beginning and end of NREM cycles. Small effects on the overall arousal rate by eventful noise exposure suggest a preserved physiological within- and across-cycle arousal evolution with noise exposure, while aging affected the shape depending on the cycle.

On the use of patterns obtained from LSTM and feature-based methods for time series analysis: application in automatic classification of the CAP A phase subtypes

The cyclic alternating pattern is a marker of sleep instability identified in the electroencephalogram signals whose sequence of transient variations compose the A phases. These phases are divided into three subtypes (A1, A2, and A3) according to the presented patterns. The traditional approach of manually scoring the cyclic alternating pattern events for the full night is unpractical, with a high probability of miss classification, due to the large quantity of information that is produced during a full night recording. To address this concern, automatic methodologies were proposed using a long short-term memory to perform the classification of one electroencephalogram monopolar derivation signal. The proposed model is composed of three classifiers, one for each subtype, performing binary classification in a one versus all procedure. Two methodologies were tested: feed the pre-processed electroencephalogram signal to the classifiers; create features from the pre-processed electroencephalogram signal which were fed to the classifiers (feature-based methods). It was verified that the A1 subtype classification performance was similar for both methods and the A2 subtype classification was higher for the feature-based methods. However, the A3 subtype classification was found to be the most challenging to be performed, and for this classification, the feature-based methods were superior. A characterization analysis was also performed using a recurrence quantification analysis to further examine the subtypes characteristics. The average accuracy and area under the receiver operating characteristic curve for the A1, A2, and A3 subtypes of the feature-based methods were respectively: 82% and 0.92; 80% and 0.88; 85% and 0.86.

Sleep Macrostructure and NREM Sleep Instability Analysis in Pediatric Developmental Coordination Disorder

Developmental Coordination Disorder (DCD) is considered to be abnormal motor skills learning, identified by clumsiness, slowness, and/or motor inaccuracy impairing the daily-life activities in all ages of life, in the absence of sensory, cognitive, or neurological deficits impairment. The present research focuses on studying DCD sleep structure and Cyclic Alternating Pattern (CAP) parameters with a full overnight polysomnography and to study the putative correlations between sleep architecture and CAP parameters with motor coordination skills. The study was a cross-sectional design involving 42 children (26M/16F; mean age 10.12 ± 1.98) selected as a DCD group compared with 79 children (49M/30F; mean age 9.94 ± 2.84) identified as typical (no-DCD) for motor ability and sleep macrostructural parameters according to the MABC-2 and polysomnographic (PSG) evaluations. The two groups (DCD and non-DCD) were similar for age (p = 0.715) and gender (p = 0.854). More significant differences in sleep architecture and CAP parameters were found between two groups and significant correlations were identified between sleep parameters and motor coordination skills in the study population. In conclusion, our data show relevant abnormalities in sleep structure of DCD children and suggest a role for rapid components of A phases on motor coordination development

Isolated rapid eye movement sleep behavior disorder and cyclic alternating pattern: is sleep microstructure a predictive parameter of neurodegeneration?

Objective

To evaluate the role of sleep cyclic alternating pattern (CAP) in patients with isolated REM sleep behavior disorder (IRBD) and ascertain whether CAP metrics might represent a marker of phenoconversion to a defined neurodegenerative condition.

Methods

Sixty-seven IRBD patients were included and classified into patients who phenoconverted to a neurodegenerative disease (RBD converters: converter REM sleep behavior disorder [cRBD]; n = 34) and remained disease-free (RBD non-converters: non-converter REM sleep behavior disorder [ncRBD]; n = 33) having a similar follow-up duration. Fourteen age- and gender-balanced healthy controls were included for comparisons.

Results

Compared to controls, CAP rate and CAP index were significantly decreased in IRBD mainly due to a decrease of A1 phase subtypes (A1 index) despite an increase in duration of both CAP A and B phases. The cRBD group had significantly lower values of CAP rate and CAP index when compared with the ncRBD group and controls. A1 index was significantly reduced in both ncRBD and cRBD groups compared to controls. When compared to the ncRBD group, A3 index was significantly decreased in the cRBD group. The Kaplan-Meier curve applied to cRBD estimated that a value of CAP rate below 32.9% was related to an average risk of conversion of 9.2 years after baseline polysomnography.

Conclusion

IRBD is not exclusively a rapid eye movement (REM) sleep parasomnia, as non-rapid eye movement (non-REM) sleep microstructure can also be affected by CAP changes. Further studies are necessary to confirm that a reduction of specific CAP metrics is a marker of neurodegeneration in IRBD.

Visual and automatic classification of the cyclic alternating pattern in electroencephalography during sleep

Cyclic alternating pattern (CAP) is a neurophysiological pattern that can be visually scored by international criteria. The aim of this study was to verify the feasibility of visual CAP scoring using only one channel of sleep electroencephalogram (EEG) to evaluate the inter-scorer agreement in a variety of recordings, and to compare agreement between visual scoring and automatic scoring systems. Sixteen hours of single-channel European data format recordings from four different sleep laboratories with either C4-A1 or C3-A2 channels and with different sampling frequencies were used in this study. Seven independent scorers applied visual scoring according to international criteria. Two automatic blind scorings were also evaluated. Event-based inter-scorer agreement analysis was performed. The pairwise inter-scorer agreement (PWISA) was between 55.5 and 84.3%. The average PWISA was above 60% for all scorers and the global average was 69.9%. Automatic scoring systems showed similar results to those of visual scoring. The study showed that CAP could be scored using only one EEG channel. Therefore, CAP scoring might also be integrated in sleep scoring features and automatic scoring systems having similar performances to visual sleep scoring systems.

EEG beta power and heart rate variability describe the association between cortical and autonomic arousals across sleep

Cortical and autonomic arousals have been found to be closely associated. As arousal events are not evenly dispersed across sleep, we hypothesized the relationship between high frequency electroencephalogram (EEG) power and autonomic arousal indices differ between non-rapid eye movement (NREM) and rapid eye movement (REM) sleep. One night of polysomnographic recording was performed on a group of 18 subjects using a portable recorder. The EEG was collected from C3/Fz. Sleep stages and cortical arousals were visually scored. Cardiac autonomic modulation was assessed from heart rate variability, where the high frequency power (HF) indicates parasympathetic modulation, and the low frequency to high frequency power ratio (LF/HF) represents sympathetic modulation. During NREM sleep, EEG beta power was significantly correlated with LF/HF (r=0.40 ± 0.06), and the relationships were more positive than during REM sleep (LF/HF: r=0.20 ± 0.08; EOG power: r=-0.13 ± 0.05). The relationship of beta power with LF/HF was associated with the incidence of cortical arousal, particularly during NREM sleep. With respect to alpha power, it was only marginally related to HF or LF/HF. In addition, the coefficients of determination were lower for alpha power than for beta power in terms of the relationships to HF, LF/HF and EOG power. This study shows a higher relationship between cortical and autonomic activation during NREM sleep, and the association is better described by beta power. This finding suggests NREM sleep may be of greater therapeutic potential in view of reducing cardiovascular disease associated with sleep fragmentation, and beta power may provide a better index to evaluate the effect.

Are Absence Epilepsy and Nocturnal Frontal Lobe Epilepsy System Epilepsies of the Sleep/Wake System?

System epilepsy is an emerging concept interpreting major nonlesional epilepsies as epileptic dysfunctions of physiological systems. I extend here the concept of reflex epilepsy to epilepsies linked to input dependent physiological systems. Experimental and clinical reseach data were collected to create a coherent explanation of underlying pathomechanism in AE and NFLE. We propose that AE should be interpreted as epilepsy linked to the corticothalamic burst-firing mode of NREM sleep, released by evoked vigilance level oscillations characterized by reactive slow wave response. In the genetic variation of NFLE the ascending cholinergic arousal system plays an essential role being in strong relationship with a gain mutation of the nicotinic acethylcholin receptors, rendering the arousal system hyperexcitable. I try to provide a more unitary interpretation for the variable seizure manifestation integrating them as different degree of pathological arosuals and alarm reactions. As a supporting hypothesis the similarity between arousal parasomnias and FNLE is shown, underpinned by overlaping pathomechanism and shared familiarity, but without epileptic features. Lastly we propose that both AE and NFLE are system epilepsies of the sleep-wake system representing epileptic disorders of the antagonistic sleep/arousal network. This interpretation may throw new light on the pathomechanism of AE and NFLE.

A review of signals used in sleep analysis

This article presents a review of signals used for measuring physiology and activity during sleep and techniques for extracting information from these signals. We examine both clinical needs and biomedical signal processing approaches across a range of sensor types. Issues with recording and analysing the signals are discussed, together with their applicability to various clinical disorders. Both univariate and data fusion (exploiting the diverse characteristics of the primary recorded signals) approaches are discussed, together with a comparison of automated methods for analysing sleep.

How sleep activates epileptic networks?

Background. The relationship between sleep and epilepsy has been long ago studied, and several excellent reviews are available. However, recent development in sleep research, the network concept in epilepsy, and the recognition of high frequency oscillations in epilepsy and more new results may put this matter in a new light. Aim. The review address the multifold interrelationships between sleep and epilepsy networks and with networks of cognitive functions. Material and Methods. The work is a conceptual update of the available clinical data and relevant studies. Results and Conclusions. Studies exploring dynamic microstructure of sleep have found important gating mechanisms for epileptic activation. As a general rule interictal epileptic manifestations seem to be linked to the slow oscillations of sleep and especially to the reactive delta bouts characterized by A1 subtype in the CAP system. Important link between epilepsy and sleep is the interference of epileptiform discharges with the plastic functions in NREM sleep. This is the main reason of cognitive impairment in different forms of early epileptic encephalopathies affecting the brain in a special developmental window. The impairment of cognitive functions via sleep is present especially in epileptic networks involving the thalamocortical system and the hippocampocortical memory encoding system.

Sleep bruxism is associated with a rise in arterial blood pressure

STUDY OBJECTIVES

Sleep bruxism (SB) is a movement disorder identified by grinding of teeth and rhythmic masticatory muscle activity (RMMA). RMMA is associated with body movements and cortical arousals. Increases in autonomic sympathetic activities that characterize sleep cortical arousal precede RMMA/SB. Based on these findings, this study examined whether RMMA/SB episodes are also associated with significant changes in arterial blood pressure (BP).

DESIGN

Participants underwent 3 nights of full polysomnography that included noninvasive beat-to-beat BP recording. Single RMMA/SB episodes and arousal episodes were analyzed in stage 2 sleep and categorized as: (i) RMMA/SB + arousal; (ii) RMMA/SB + body movement; (iii) RMMA/SB + arousal + body movement; or (iv) arousal alone. Sleep and RMMA/SB data were compared to a Non SB group. RMMA/SB clusters (RMMA/SB episodes ≤ 30 sec apart) were also analyzed.

SETTING

Sleep Laboratory at l'Hôpital du Sacré-Coeur de Montréal.

PARTICIPANTS

Ten young, healthy participants with SB (mean age = 26 ± 1.8 years) and 9 without SB (mean age = 29 ± 1.2 years).

INTERVENTIONS

N/A MEASUREMENTS AND RESULTS: BP increased with all RMMA/SB and arousal episodes (P ≤ 0.05). The average maximum BP surges (systolic/diastolic ± SE mm Hg) were: 25.6 ± 3.3/12.6 ± 2.0 for RMMA/SB + arousal; 30.1 ± 1.7/19.1 ± 1.9 for RMMA/SB + body movement; 26.0 ± 2.8/15.1 ± 2.0 for RMMA/SB + arousal + body movement; 19.4 ± 2.3/8.9 ± 1.2 for arousal alone; and for RMMA/SB clusters: Episode: 1: 26.2 ± 8.7/16.4 ± 5.7; Episode 2: 21.1 ± 7.9/12.6 ± 6.4.

CONCLUSION

Rhythmic masticatory muscle activity/sleep bruxism (RMMA/SB) is associated with blood pressure fluctuations during sleep. Arousals and body movements often occur with RMMA/SB and can impact the magnitude of this BP surge.

Cyclic alternating pattern (CAP): the marker of sleep instability

Cyclic alternating pattern CAP is the EEG marker of unstable sleep, a concept which is poorly appreciated among the metrics of sleep physiology. Besides, duration, depth and continuity, sleep restorative properties depend on the capacity of the brain to create periods of sustained stable sleep. This issue is not confined only to the EEG activities but reverberates upon the ongoing autonomic activity and behavioral functions, which are mutually entrained in a synchronized oscillation. CAP can be identified both in adult and children sleep and therefore represents a sensitive tool for the investigation of sleep disorders across the lifespan. The present review illustrates the story of CAP in the last 25 years, the standardized scoring criteria, the basic physiological properties and how the dimension of sleep instability has provided new insight into pathophysiolology and management of sleep disorders.

Commentary from the Italian Association of Sleep Medicine on the AASM manual for the scoring of sleep and associated events: for debate and discussion

In 2007, the American Academy of Sleep Medicine (AASM) completed a new manual for the scoring of sleep and associated events. The AASM manual is divided into separate sections relative to the parameters reported for polysomnography. The present commentary, accomplished by a Task Force of the Italian Association of Sleep Medicine, focuses on sleep scoring data, arousal rules, movement and respiratory events. Comparisons with the previous Rechtschaffen and Kales system are detailed and a number of methodological weaknesses are pointed out. Major comments address the 30-s scoring epochs, the restrictive approach to arousals and EEG activating patterns, the incomplete quantification of motor events and the thresholds for the definition of hypopnea. Since the new AASM manual is an iterative process, proposals for discussion and re-examination of the agreed criteria with other national and international organizations are encouraged.

Ontogeny of EEG-sleep from neonatal through infancy periods

Serial neonatal and infant electroencephalographic (EEG)-polysomnographic studies document the ontogeny of cerebral and noncerebral physiologic behaviors based on visual inspection or computer analyses. EEG patterns and their relationship to other physiologic signals serve as templates for normal brain organization and maturation, subserving multiple interconnected neuronal networks. Interpretation of serial EEG-sleep patterns also helps track the continuity of brain functions from intrauterine to extrauterine time periods. Recognition of the ontogeny of behavioral and electrographic patterns provides insight into the developmental neurophysiological expression of neural plasticity. Sleep ontogenesis from neonatal and infancy periods documents expected patterns of postnatal brain maturation, which allows for alterations from genetically programmed neuronal processes under stressful and/or pathological conditions. Automated analyses of cerebral and noncerebral signals provide time- and frequency-dependent computational phenotypes of brain organization and maturation in healthy or diseased states. Research pertaining to the developmental origins of health and disease can use these computational phenotypes to design longitudinal studies for the assessment of gene-environment interactions. Computational strategies may ultimately improve our diagnostic skills to identify special-needs children and to track the neurorehabilitative care of the high-risk fetus, neonate, and infant.

Cyclic alternating pattern sequences and non-cyclic alternating pattern periods in human sleep

OBJECTIVE

The CAP cycle is a module of activation (phase A) and inhibition (phase B) which repeats itself in sequences. The study aims at testing the hypothesis that the duration of CAP sequences is determined primarily by the number and not by the length of CAP cycles.

METHODS

The polysomnographic recordings of 24 normal subjects, 12 males and 12 females, ranging in age from 20 to 35 years (mean 27.8+/-7.2), were examined.

RESULTS

A total of 1053 CAP sequences were counted with an average of 43.9 sequences per night. The mean duration of CAP sequences was 2 min and 33 s. Each CAP sequence was composed of an average of 5.6 CAP cycles. All subjects presented CAP sequences lasting at least 5 min and 30s. The mean duration of CAP cycles was 26.9+/-4.1s. CAP cycles including subtypes A1 presented the highest correlation with the CAP sequence length (r=0.92; p<0.0001).

CONCLUSIONS

The progressive increase of CAP sequences length is linked to the progressive accumulation of CAP cycles.

SIGNIFICANCE

CAP sequences can be considered as strings of time-constant modules, i.e., CAP cycles, which are involved in the dynamic tailoring of sleep structure.

Sleep cycling alternating pattern (CAP) expression is associated with hypersomnia and GH secretory pattern in Prader–Willi syndrome

BACKGROUND AND PURPOSE

Hypersomnia, sleep-disordered breathing and narcoleptic traits such as rapid eye movement (REM) sleep onset periods (SOREMPs) have been reported in Prader-Willi syndrome (PWS). In a group of young adult patients with genetically confirmed PWS we evaluated sleep and breathing polysomnographically, including cycling alternating pattern (CAP), and we analyzed the potential interacting role of sleep variables, sleep-related breathing abnormalities, hypersomnia, severity of illness variables and growth hormone (GH) secretory pattern.

PATIENTS AND METHODS

Eleven males and 7 females (mean age: 27.5+/-5.5 years) were submitted to a full night of complete polysomnography and the multiple sleep latency test (MSLT). GH secretory pattern was evaluated by a standard GH-releasing hormone plus arginine test. Sixteen non-obese healthy subjects without sleep disturbances were recruited as controls.

RESULTS

Compared to controls PWS patients showed reduced mean MSLT score (P<0.001), reduced mean latency of sleep (P=0.03), increased REM sleep periods (P=0.01), and increased mean CAP rate/non-rapid eye movement (NREM) (P<0.001). Only four PWS patients had apnea/hypopnea index (AHI)>or=10. Conversely, significant nocturnal oxygen desaturation was frequent (83% of patients) and independent from apneas or hypopneas. In the PWS group, CAP rate/NREM showed a significant negative correlation with MSLT score (P=0.02) independently from arousals, respiratory disturbance variables, severity of illness measured by Holm's score or body mass index (BMI). PWS patients with CAP expression characterized by higher proportion of A1 subtypes presented less severe GH deficiency (P=0.01).

CONCLUSIONS

Our study suggests a relationship between hypersomnia and CAP rate, and between CAP expression and GH secretory pattern in PWS, possibly reflecting underlying central dysfunctions.

Sleep bruxism is associated to micro-arousals and an increase in cardiac sympathetic activity

Sleep bruxism (SB) subjects show a higher incidence of rhythmic masticatory muscle activity (RMMA) than control subjects. RMMA is associated with sleep micro-arousals. This study aims to: (i) assess RMMA/SB episodes in relation to sleep cycles; (ii) establish if RMMA/SB and micro-arousals occur in relation to the slow wave activity (SWA) dynamics; (iii) analyze the association between RMMA/SB and autonomic cardiac activity across sleep cycles. Two nights of polygraphic recordings were made in three study groups (20 subjects each): moderate to high SB, low SB and control. RMMA episodes were considered to occur in clusters when several groups of RMMA or non-specific oromotor episodes were separated by less than 100 s. Correlations between sleep, RMMA/SB index and heart rate variability variables were assessed for the first four sleep cycles of each study group. Statistical analyses were done with SYSTAT and SPSS. It was observed that 75.8% of all RMMA/SB episodes occurred in clusters. Micro-arousal and SB indexes were highest during sleep cycles 2 and 3 (P < 0.001). Within each cycle, micro-arousal and RMMA/SB indexes showed an increase before each REM sleep (P <or= 0.02). The cross-correlation plot for micro-arousal index showed positive association from 4 min preceding SB onset in the moderate to high SB subjects (P <or= 0.06). The cross-correlation plot revealed that SWA decreases following SB onset (P <or= 0.05). Further cross-correlation analysis revealed that a shift in sympatho-vagal balance towards increased sympathetic activity started 8 min preceding SB onset (P <or= 0.03). In moderate to severe SB subjects, a clear increase in sympathetic activity precedes SB onset.

Neurophysiological aspects of primary insomnia: Implications for its treatment

Insomnia has usually been studied from a behavioral perspective. Somatic and/or cognitive conditioned arousal was shown to play a central role in sleep complaints becoming chronic, and was used as a starting point for the development of treatment modalities. The introduction of the neurocognitive perspective, with its focus on cortical or CNS arousal, has given rise to a renewed interest in the neurophysiological characteristics of insomnia. Recent research, using quantitative EEG, neuroimaging techniques and the study of the microstructure of sleep, suggests a state of hyperarousal with a biological basis. Furthermore, insomnia might not be restricted to sleep complaints alone because it appears to be a 24-h disorder, affecting several aspects of daytime functioning as well. These new findings have implications for the treatments used and indicate that a focus on cortical or CNS arousal should be pursued. As such, the use of EEG neurofeedback, a self-regulation method based on the paradigm of operant conditioning, might be a promising treatment modality. Preliminary results for insomnia and successful applications for other disorders suggest that this treatment can have the necessary stabilizing effects on the EEG activity, possibly resulting in a normalizing effect on daytime as well as nighttime functioning.

CAP, epilepsy and motor events during sleep: the unifying role of arousal

Arousal systems play a topical neurophysiologic role in protecting and tailoring sleep duration and depth. When they appear in NREM sleep, arousal responses are not limited to a single EEG pattern but are part of a continuous spectrum of EEG modifications ranging from high-voltage slow rhythms to low amplitude fast activities. The hierarchic features of arousal responses are reflected in the phase A subtypes of CAP (cyclic alternating pattern) including both slow arousals (dominated by the <1Hz oscillation) and fast arousals (ASDA arousals). CAP is an infraslow oscillation with a periodicity of 20-40s that participates in the dynamic organization of sleep and in the activation of motor events. Physiologic, paraphysiologic and pathologic motor activities during NREM sleep are always associated with a stereotyped arousal pattern characterized by an initial increase in EEG delta power and heart rate, followed by a progressive activation of faster EEG frequencies. These findings suggest that motor patterns are already written in the brain codes (central pattern generators) embraced with an automatic sequence of EEG-vegetative events, but require a certain degree of activation (arousal) to become visibly apparent. Arousal can appear either spontaneously or be elicited by internal (epileptic burst) or external (noise, respiratory disturbance) stimuli. Whether the outcome is a physiologic movement, a muscle jerk or a major epileptic attack will depend on a number of ongoing factors (sleep stage, delta power, neuro-motor network) but all events share the common trait of arousal-activated phenomena.

CAP and arousals are involved in the homeostatic and ultradian sleep processes

There is growing evidence that cyclic alternating pattern (CAP) and arousals are woven into the basic mechanisms of sleep regulation. In the present study, the overnight sleep cycles (SC) of 20 normal subjects were analyzed according to their stage composition, CAP rate, phase A subtypes and arousals. Individual SC were then divided into 10 normalized temporal epochs. CAP parameters and arousals were measured in each epoch and averaged in relation to the SC order. Subtypes A2 and A3 of CAP in non-rapid eye movement (NREM) sleep, and arousals, both in REM and NREM sleep when not coincident with a A2 or A3 phases, were lumped together as fast electroencephalographic (EEG) activities (FA). Subtypes A1 of CAP, characterized by slow EEG activities (SA), were analyzed separately. The time distribution of SA and FA was compared to the mathematical model of normal sleep structure including functions representing the homeostatic process S, the circadian process C, the ultradian process generating NREM/REM cycles and the slow wave activity (SWA) resulting from the interaction between homeostatic and ultradian processes. The relationship between SA and FA and the sleep-model components was evaluated by multiple regression analysis in which SA and FA were considered as dependent variables while the covariates were the process S, process C, SWA, REM-on and REM-off activities and their squared values. Regression was highly significant (P < 0.0001) for both SA and FA. SA were prevalent in the first three SC, and exhibited single or multiple peaks immediately before and in the final part of deep sleep (stages 3 + 4). The peaks of FA were delayed and prevailed during the pre-REM periods of light sleep (stages 1 + 2) and during REM sleep. SA showed an exponential decline across the successive SC, according to the homeostatic process. In contrast, the distribution of FA was not influenced by the order of SC, with periodic peaks of FA occurring before the onset of REM sleep, in accordance with the REM-on switch. The dynamics of CAP and arousals during sleep can be viewed as an intermediate level between cellular activities and macroscale EEG phenomena as they reflect the decay of the homeostatic process and the interaction between REM-off and REM-on mechanisms while are slightly influenced by circadian rhythm.

K-complex, a reactive EEG graphoelement of NREM sleep: an old chap in a new garment

This review summarises data gathered on the KC phenomenon over the past 70 yr. The following issues are discussed: definitions, morphology and topography of KC, the regular participation in NREM sleep, elicitability features of evoked KC, autonomic and motor concomitants, relationship of KC with information processing during NREM sleep, relationship of KC and deltas of NREM sleep, and relationship of KC with sleep cyclicity. KC is a complex multifunctional phenomenon of the sleeping brain involved in information processing and defence against the arousal effect of sensory stimuli. To put the old chap in a new garment, the relationship of KC with synchronisation-type and desynchronisation-type micro-arousals, and the 'cyclic alternating pattern', will be discussed, with an emphasis on the sleep-protecting role of KC and synchronisation-type answers in sleep regulation executed by phasic events. Lastly, the role of KC providing gating functions in idiopathic generalized epilepsies and other, different, sleep disorders are characterised. A 'theoretical epilogue' is appended to show some system theoretical and regulational aspects.

Reorganization of sleep patterns in severe OSAS under prolonged CPAP treatment

OBJECTIVE

To evaluate the immediate and long-term recovery processes of sleep and daytime vigilance in patients with sleep apnea syndrome (OSAS) after continuous CPAP treatment.

METHODS

Five consecutive polysomnographic (PSG) studies were carried out on 10 male patients with severe OSAS. The first recording (baseline) was accomplished without ventilatory support (N0). The other 4 recordings were carried out during the CPAP titration night (N1), during the second night of treatment (N2), during the third night of treatment (N3), and after 30 days of regular CPAP use (N30). Ten age-balanced healthy male subjects were selected from the Parma Sleep Center database as controls. Respiratory variables, conventional PSG variables, arousals, CAP (cyclic alternating pattern) variables, and daytime function (including MSLT) were quantified. ANOVA followed by post-hoc tests explored the differences between controls and OSAS patients in the different recording conditions (N0, N1, N2, N3, N30). The PSG measures that showed significant ANOVA values were correlated with the MSLT scores.

RESULTS

Values of control subjects were recovered by REM sleep, REM latency, subtypes A3 and arousal index during N1, by CAP rate and total arousals during N2, by deep sleep (stages 3 + 4) during N3, by light sleep (stages 1 + 2) during N30. The only measures which remained below control values even after 1 month of sustained treatment were the amount of CAP cycles and A1 subtypes. MSLT scores correlated significantly with CAP rate, deep sleep and arousals.

CONCLUSIONS

The changes induced by CPAP treatment do not restore immediately a normal sleep structure, which is re-established with different time scales

SIGNIFICANCE

The modifications of sleep patterns and the different adjustments of phase A subtypes allow us to monitor the reorganization of sleep in OSAS patients treated with CPAP and the hierarchy of the mechanisms involved in sleep regulation.

Topographic mapping of the spectral components of the cyclic alternating pattern (CAP)

BACKGROUND AND PURPOSE

The aim of this study was to define quantitatively the spectrum content of the sleep pattern termed 'cyclic alternating pattern' (CAP) A phases, their scalp topography and their probable cortical generators, by using data from sleep polygraphic recordings that included a large number of scalp EEG channels.

PATIENTS AND METHODS

Polysomnographic recording that include 19 EEG channels were obtained from 5 normal healthy young controls. After sleep staging, for each subject, 5 different CAP A phase subtype epochs were selected, which served for subsequent analysis. Following the analysis of power spectra calculated on the C4 channel by means of the fast Fourier transform, two different frequency bands were detected: 0.25-2.5 and 7-12Hz, representing the frequency peak in the profiles of the different CAP subtypes. All the subsequent analyses were performed on these two bands. Scalp topographic color mapping was carried out using the data from all the 19 EEG channels recorded, and by means of the 4-nearest neighbor algorithm. Individual average maps were obtained for both frequency bands. Finally, we used the low resolution brain electromagnetic tomography (LORETA) functional imaging for the source analysis of the two EEG frequency components of CAP A phases.

RESULTS

The quantitative spectral analysis of the different A phase subtypes shows the existence of two distinct spectral components characterizing CAP subtypes A1 (0.25-2.5Hz) and A3 (7-12Hz). These two components coexist in CAP A2 subtypes. The topography of these two components shows a clear prevalence over the anterior frontal regions for the 0.25-2.5Hz band and over the parietal-occipital areas for the 7-12Hz band. Finally, the generators of the low-frequency component of CAP seemed to be localized mostly over the frontal midline cortex; on the contrary, those of the high-frequency band involved both midline and hemispheric areas within the parietal and occipital areas.

CONCLUSIONS

The results of this study confirm the presence of two fundamentally distinct frequency bands which are expressed individually (A1 and A3) or in association (A2) in the different CAP A phase subtypes. The analysis of scalp distribution maps indicates that the two frequency components recognized are distributed over clearly different areas of the scalp. Moreover, the LORETA analysis indicates that also the probable cortical generators of these two frequency bands are different and well separated and distinct.

Is insomnia a neurophysiological disorder? The role of sleep EEG microstructure

Unlike other sleep disorders, such as sleep-related breathing disorders and periodic limb movement (PLM), the nature and severity of which are quantified by specific respiratory and motor indexes, no apparent organ dysfunction underlies several cases of insomnia (in particular primary insomnia), which can be objectively diagnosed only through the structural alterations of sleep. Polysomnography (PSG) investigation indicates that insomnia is the outcome of a neurophysiological disturbance that impairs the regulatory mechanisms of sleep control, including sleep duration, intensity, continuity and stability. In particular, analysis of sleep microstructure has permitted to establish that etiologic factors of different nature (including depressive disorders) exert a common destabilizing action on sleep, which is reflected in an increase of cyclic alternating pattern (CAP) rate. These premises allow us to attribute a more objective identity to insomnia, which risks otherwise to be considered as an unexplainable mental complaint. In conclusion, PSG remains the "gold standard" for measuring sleep, and especially insomnia.

The clinical neurophysiology of the restless legs syndrome and periodic limb movements. Part I: diagnosis, assessment, and characterization

OBJECTIVE

The restless legs syndrome is a common sensorimotor disorder impacting on sleep which has been known for centuries, but only recently become recognized as a significant clinical and pathophysiological problem. The definition of RLS has evolved until certain key clinical features have been defined as diagnostic, while others are strongly associated: the urge to move is seen as primary. Epidemiology suggests ethnic variation with highest frequency in populations of European origin; family and genetic studies support a genetic basis to many idiopathic cases while links to secondary disorders usually involving low iron stores are also known. Abnormalities of brain iron transport and consequent dysfunction of the dopamine system are suspected sources of the disorder.

METHODS

The literature was searched for all references relating clinical neurophysiologic investigations to the diagnosis, assessment, and characterization of RLS.

RESULTS

RLS is defined clinically and diagnosed by medical history while its frequent concomitant, periodic limb movements (PLM), must be diagnosed by polysomnography or movement recording. Severity of RLS is generally assessed by subjective measures, but sleep recording and measurement of PLM frequency and association with sleep disruption are also used to measure severity. A provocative test, the suggested immobilization test, can also be used with both subjective and movement recording. RLS and PLM in RLS are both associated with the circadian cycle and are maximal early in the sleep period. PLM appear to be associated both with unstable EEG phases involving the cyclic alternating pattern and cyclical autonomic changes whose initiation may precede the muscle activity.

CONCLUSIONS

While RLS remains a subjective disorder, neurophysiologic measures have been important, especially for assessment. Ambulatory methodologies may offer the most accurate and economical means of assessing motor activity as a key marker of RLS and of accurately measuring PLM from night to night. As the pathophysiology of RLS is better understood, more focused techniques may be developed to measure its presence and severity in individual patients.

The nature of arousal in sleep

The role of arousals in sleep is gaining interest among both basic researchers and clinicians. In the last 20 years increasing evidence shows that arousals are deeply involved in the pathophysiology of sleep disorders. The nature of arousals in sleep is still a matter of debate. According to the conceptual framework of the American Sleep Disorders Association criteria, arousals are a marker of sleep disruption representing a detrimental and harmful feature for sleep. In contrast, our view indicates arousals as elements weaved into the texture of sleep taking part in the regulation of the sleep process. In addition, the concept of micro-arousal (MA) has been extended, incorporating, besides the classical low-voltage fast-rhythm electroencephalographic (EEG) arousals, high-amplitude EEG bursts, be they like delta-like or K-complexes, which reflects a special kind of arousal process, mobilizing parallely antiarousal swings. In physiologic conditions, the slow and fast MA are not randomly scattered but appear structurally distributed within sleep representing state-specific arousal responses. MA preceded by slow waves occurs more frequently across the descending part of sleep cycles and in the first cycles, while the traditional fast type of arousals across the ascending slope of cycles prevails during the last third of sleep. The uniform arousal characteristics of these two types of MAs is supported by the finding that different MAs are associated with an increasing magnitude of vegetative activation ranging hierarchically from the weaker slow EEG types (coupled with mild autonomic activation) to the stronger rapid EEG types (coupled with a vigorous autonomic activation). Finally, it has been ascertained that MA are not isolated events but are basically endowed with a periodic nature expressed in non-rapid eye movement (NREM) sleep by the cyclic alternating pattern (CAP). Understanding the role of arousals and CAP and the relationship between physiologic and pathologic MA can shed light on the adaptive properties of the sleeping brain and provide insight into the pathomechanisms of sleep disturbances. Functional significance of arousal in sleep, and particularly in NREM sleep, is to ensure the reversibility of sleep, without which it would be identical to coma. Arousals may connect the sleeper with the surrounding world maintaining the selection of relevant incoming information and adapting the organism to the dangers and demands of the outer world. In this dynamic perspective, ongoing phasic events carry on the one hand arousal influences and on the other elements of information processing. The other function of arousals is tailoring the more or less stereotyped endogenously determined sleep process driven by chemical influences according to internal and external demands. In this perspective, arousals shape the individual course of night sleep as a variation of the sleep program.