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

Transvenous phrenic nerve stimulation for treating central sleep apnea may regulate sleep microstructure

STUDY OBJECTIVES

To assess the impact of transvenous phrenic nerve stimulation (TPNS) on non-rapid eye movement sleep microstructure quantified by cyclic alternating pattern (CAP) in individuals with central sleep apnea (CSA).

METHODS

We analyzed baseline and 6-month follow-up overnight polysomnograms (PSG) in 134 CSA patients enrolled in the remedē System Pivotal Trial implanted with TPNS randomized (1:1) to neurostimulation (treatment group) or no stimulation (control group). Differences in CAP rate, A1 index, and A2+A3 index between study arms at follow-up were assessed using Analysis of Covariance adjusted for baseline values.

RESULTS

On follow-up PSG, the treatment group showed a decrease in the frequency of A2+A3 phases compared to controls (-5.86 ± 11.82 vs. 0.67 ± 15.25, p = 0.006), while the frequency of A1 phases increased more in the treatment group (2.57 ± 11.67 vs. -2.47 ± 10.60, p = 0.011). The change in CAP rate at follow-up was comparable between study arms.

CONCLUSIONS

TPNS treatment for central sleep apnea may affect sleep microstructure. Brief phases of rapid cortical activity appear to be replaced by short phases of slower cortical activity, which may promote sleep continuity. Further investigations are warranted to elucidate the mechanisms underlying the effect of TPNS on CAP.

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.

Towards automatic EEG cyclic alternating pattern analysis: a systematic review

This study conducted a systematic review to determine the feasibility of automatic Cyclic Alternating Pattern (CAP) analysis. Specifically, this review followed the 2020 Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines to address the formulated research question: is automatic CAP analysis viable for clinical application? From the identified 1,280 articles, the review included 35 studies that proposed various methods for examining CAP, including the classification of A phase, their subtypes, or the CAP cycles. Three main trends were observed over time regarding A phase classification, starting with mathematical models or features classified with a tuned threshold, followed by using conventional machine learning models and, recently, deep learning models. Regarding the CAP cycle detection, it was observed that most studies employed a finite state machine to implement the CAP scoring rules, which depended on an initial A phase classifier, stressing the importance of developing suitable A phase detection models. The assessment of A-phase subtypes has proven challenging due to various approaches used in the state-of-the-art for their detection, ranging from multiclass models to creating a model for each subtype. The review provided a positive answer to the main research question, concluding that automatic CAP analysis can be reliably performed. The main recommended research agenda involves validating the proposed methodologies on larger datasets, including more subjects with sleep-related disorders, and providing the source code for independent confirmation.

A-phase index: an alternative view for sleep stability analysis based on automatic detection of the A-phases from the cyclic alternating pattern

STUDY OBJECTIVES

Sleep stability can be studied by evaluating the cyclic alternating pattern (CAP) in electroencephalogram (EEG) signals. The present study presents a novel approach for assessing sleep stability, developing an index based on the CAP A-phase characteristics to display a sleep stability profile for a whole night's sleep.

METHODS

Two ensemble classifiers were developed to automatically score the signals, one for "A-phase" and the other for "non-rapid eye movement" estimation. Both were based on three one-dimension convolutional neural networks. Six different inputs were produced from the EEG signal to feed the ensembles' classifiers. A proposed heuristic-oriented search algorithm individually tuned the classifiers' structures. The outputs of the two ensembles were combined to estimate the A-phase index (API). The models can also assess the A-phase subtypes, their API, and the CAP cycles and rate.

RESULTS

Four dataset variations were considered, examining healthy and sleep-disordered subjects. The A-phase average estimation's accuracy, sensitivity, and specificity range was 82%-87%, 72%-80%, and 82%-88%, respectively. A similar performance was attained for the A-phase subtype's assessments, with an accuracy range of 82%-88%. Furthermore, in the examined dataset's variations, the API metric's average error varied from 0.15 to 0.25 (with a median range of 0.11-0.24). These results were attained without manually removing wake or rapid eye movement periods, leading to a methodology suitable to produce a fully automatic CAP scoring algorithm.

CONCLUSIONS

Metrics based on API can be understood as a new view for CAP analysis, where the goal is to produce and examine a sleep stability profile.

Development and assessment of a risk prediction model for moderate-to-severe obstructive sleep apnea

Background

OSA is an independent risk factor for several systemic diseases. Compared with mild OSA, patients with moderate-to-severe OSA have more severe impairment in the function of all organs of the body. Due to the current limited medical condition, not every patient can be diagnosed and treated in time. To enable timely screening of patients with moderate-to-severe OSA, we selected easily accessible variables to establish a risk prediction model.

Method

We collected 492 patients who had polysomnography (PSG), and divided them into the disease-free mild OSA group (control group), and the moderate-to-severe OSA group according to the PSG results. Variables entering the model were identified by random forest plots, univariate analysis, multicollinearity test, and binary logistic regression method. Nomogram were created based on the binary logistic results, and the area under the ROC curve was used to evaluate the discriminative properties of the nomogram model. Bootstrap method was used to internally validate the nomogram model, and calibration curves were plotted after 1,000 replicate sampling of the original data, and the accuracy of the model was evaluated using the Hosmer-Lemeshow goodness-of-fit test. Finally, we performed decision curve analysis (DCA) of nomogram model, STOP-Bang questionnaire (SBQ), and NoSAS score to assess clinical utility.

Results

There are 6 variables entering the final prediction model, namely BMI, Hypertension, Morning dry mouth, Suffocating awake at night, Witnessed apnea, and ESS total score. The AUC of this prediction model was 0.976 (95% CI: 0.962–0.990). Hosmer-Lemeshow goodness-of-fit test χ² = 3.3222 (P = 0.1899 > 0.05), and the calibration curve was in general agreement with the ideal curve. The model has good consistency in predicting the actual occurrence of moderate-to-severe risk, and has good prediction accuracy. The DCA shows that the net benefit of the nomogram model is higher than that of SBQ and NoSAS, with has good clinical utility.

Conclusion

The prediction model obtained in this study has good predictive power for moderate-to-severe OSA and is superior to other prediction models and questionnaires. It can be applied to the community population for screening and to the clinic for prioritization of treatment.

Non-rapid eye movement sleep instability in adults with epilepsy: a systematic review and meta-analysis of cyclic alternating pattern

STUDY OBJECTIVES

Epilepsy is characterized by disrupted sleep architecture. Studies on sleep macro- and microstructure revealed that patients with epilepsy experience disturbed rapid eye movement (REM) sleep; however, no consensus has been reached on non-REM (NREM) sleep changes. Cyclic alternating pattern (CAP) is a marker of sleep instability that occurs only during NREM sleep. This meta-analysis investigated CAP differences between patients with epilepsy and healthy controls.

METHODS

This study followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines in searching PubMed, Embase, and Cochrane Central database for studies comparing polysomnographic sleep microstructures between patients with epilepsy and healthy controls. A meta-analysis using a random-effects model was performed. We compared CAP rates, percentages of phase A1, A2, A3 subtypes, and phase B durations between patients with epilepsy and healthy controls.

RESULTS

A total of 11 studies, including 209 patients with epilepsy and 197 healthy controls, fulfilled the eligibility criteria. Compared with healthy controls, patients with epilepsy had significantly increased CAP rates and decreased A1 subtype percentages, and patients with sleep-related epilepsy had increased A3 subtype percentages. Subgroup analyses revealed that antiseizure medications (ASMs) decreased CAP rates and increased phase B durations but did not affect the microstates of phase A in patients with sleep-related epilepsy.

CONCLUSIONS

This meta-analysis detected statistically significant differences in CAP parameters between patients with epilepsy and healthy controls. Our findings suggest patients with epilepsy experience NREM sleep instability. ASMs treatment may decrease NREM instability but did not alter the microstates of phase A.

Sleep and brain evolution across the human lifespan: A mutual embrace

Sleep can be considered a window to ascertain brain wellness: it dynamically changes with brain maturation and can even indicate the occurrence of concealed pathological processes. Starting from prenatal life, brain and sleep undergo an impressive developmental journey that accompanies human life throughout all its steps. A complex mutual influence rules this fascinating course and cannot be ignored while analysing its evolution. Basic knowledge on the significance and evolution of brain and sleep ontogenesis can improve the clinical understanding of patient's wellbeing in a more holistic perspective. In this review we summarized the main notions on the intermingled relationship between sleep and brain evolutionary processes across human lifespan, with a focus on sleep microstructure dynamics.

Sleep and Epilepsy, Clinical Spectrum and Updated Review

Electroencephalogram (EEG) recording is essential in the evaluation of complex movement and behaviors during sleep, but in particular for differentiating epileptic versus nonepileptic events. In general, epileptiform discharges occur with greater density in the first few nonerapid eye movement cycles, and approximately 12% to 20% of seizures occur exclusively at night. This review examines the epilepsy types and syndromes whose presentation is strongly influenced by the sleep state, with an appraisal about the role that sleep plays in facilitating seizures, while deleaneatign EEG findings and clinical manifestation. The review will summarize the typical semiology of sleep-related hypermotor seizures and contrasted with those occurring during none/rapid eye movement parasomnias and sleep-related movement disorders.

Cyclic alternating pattern in obstructive sleep apnea: A preliminary study

Obstructive sleep apnea is linked to cardiovascular disease, metabolic disorders and dementia. The precise nature of the association between respiratory events in obstructive sleep apnea, cortical or subcortical arousals, and cognitive, autonomic and oxidative stress consequences remains incompletely elucidated. Previous studies have aimed to understand the relationship between obstructive sleep apnea and arousal patterns, as defined by the cyclic alternating pattern, but results have been inconsistent, in part likely due to the presence of associated comorbidities. To better define this relationship, we analysed cyclic alternating patterns in patients with obstructive sleep apnea without any additional comorbidities. We identified 18 adult male, non-obese subjects with obstructive sleep apnea and no other comorbidities or medication history, who underwent whole-night electroencephalography and polysomnography. Cyclic alternating pattern analysis was performed and verified by certified somnologists. Pairwise linear regression analysis demonstrated an inverse relationship between obstructive sleep apnea severity and cyclic alternating pattern subtype A1, and a direct correlation with cyclic alternating pattern subtype A3. Cyclic alternating pattern subtypes A1 prevail in milder obstructive sleep apnea phenotype, whilst cyclic alternating pattern subtypes A2 and A3 overcome among moderate-to-severe obstructive sleep apnea patients. The milder obstructive sleep apnea group also presented higher sleep efficiency, and increased percentages of non-rapid eye movement stage 3 and rapid eye movement sleep, as well as longer cyclic alternating pattern sequences in N3, while severe obstructive sleep apnea patients spent more time in lighter sleep stages. These results imply/suggest a balance between cyclic alternating pattern's adaptive and maladaptive arousal processes in obstructive sleep apnea of differing severities. In milder obstructive sleep apnea (apnea-hypopnea index < 20), sleep continuity may be reinforced by cyclic alternating pattern subtype A1, whereas in more severe obstructive sleep apnea, decompensation of these sleep-stabilizing mechanisms may occur and more intrusive cyclic alternating pattern fluctuations disrupt sleep circuitry.

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.

Commonalities and Differences in NREM Parasomnias and Sleep-Related Epilepsy: Is There a Continuum Between the Two Conditions?

Introduction: Differential diagnosis between disorders of arousal (DoA) and sleep-related hypermotor epilepsy (SHE) often represents a clinical challenge. The two conditions may be indistinguishable from a semiological point of view and the scalp video-polysomnography is often uninformative. Both disorders are associated with variable hypermotor manifestations ranging from major events to fragments of a hierarchical continuum of increasing intensity, complexity, and duration. Given their semiological overlap we decided to explore the sleep texture of DoA and SHE seeking for similarities and differences.

Methods: We analyzed sleep macrostructure and CAP (cyclic alternating pattern) parameters in a cohort of 35 adult DoA patients, 40 SHE patients and 24 healthy sleepers, all recorded and scored in the same sleep laboratory. Nocturnal behavioral manifestations included minor motor events, paroxysmal arousals and major attacks in SHE, and simple, rising, or complex arousal movements in DoA.

Results: Compared to healthy controls, DoA and SHE showed similar amounts of sleep efficiency, light sleep, deep sleep, REM sleep, CAP subtypes. Both groups also showed slow wave sleep fragmentation and an increased representation of stage N3 in the second part of the night. The only discriminating elements between the two conditions regarded sleep length (more reduced in DoA) and sleep instability (more elevated in SHE). In DoA recordings, all motor episodes arose from NREM sleep: 37% during light NREM stages and 63% during stage N3 (simple arousal movements: 94%). In SHE recordings, 57% of major attacks occurred during stage N3.

Conclusions: So far, emphasis has been placed on the differentiation of sleep-related epilepsy and NREM arousal disorders. However, the impressive analogies between DoA and SHE suggest the existence of an underestimated continuum across the conditions, linked by increased levels of sleep instability, higher amounts of slow wave sleep and NREM/REM sleep imbalance. Sleep texture is extremely similar in the two conditions, although CAP metrics disclose quantitative differences. In particular, SHE patients show a higher arousal instability compared to DoA subjects. Given their clinical and epidemiological overlap, a common genetic background is also hypothesized. In such a perspective, we suggest that the consolidated dichotomy DoA vs. SHE should be reappraised.

Sleep and Epilepsy Link by Plasticity

We aimed to explore the link between NREM sleep and epilepsy. Based on human and experimental data we propose that a sleep-related epileptic transformation of normal neurological networks underlies epileptogenesis. Major childhood epilepsies as medial temporal lobe epilepsy (MTLE), absence epilepsy (AE) and human perisylvian network (PN) epilepsies - made us good models to study. These conditions come from an epileptic transformation of the affected functional systems. This approach allows a system-based taxonomy instead of the outworn generalized-focal classification. MTLE links to the memory-system, where epileptic transformation results in a switch of normal sharp wave-ripples to epileptic spikes and pathological high frequency oscillations, compromising sleep-related memory consolidation. Absence epilepsy (AE) and juvenile myoclonic epilepsy (JME) belong to the corticothalamic system. The burst-firing mode of NREM sleep normally producing sleep-spindles turns to an epileptic working mode ejecting bilateral synchronous spike-waves. There seems to be a progressive transition from AE to JME. Shared absences and similar bilateral synchronous discharges show the belonging of the two conditions, while the continuous age windows - AE affecting schoolchildren, JME the adolescents - and the increased excitability in JME compared to AE supports the notion of progression. In perisylvian network epilepsies - idiopathic focal childhood epilepsies and electrical status epilepticus in sleep including Landau-Kleffner syndrome - centrotemporal spikes turn epileptic, with the potential to cause cognitive impairment. Postinjury epilepsies modeled by the isolated cortex model highlight the shared way of epileptogenesis suggesting the derailment of NREM sleep-related homeostatic plasticity as a common step. NREM sleep provides templates for plasticity derailing to epileptic variants under proper conditions. This sleep-origin explains epileptiform discharges' link and similarity with NREM sleep slow oscillations, spindles and ripples. Normal synaptic plasticity erroneously overgrowing homeostatic processes may derail toward an epileptic working-mode manifesting the involved system's features. The impact of NREM sleep is unclear in epileptogenesis occurring in adolescence and adulthood, when plasticity is lower. The epileptic process interferes with homeostatic synaptic plasticity and may cause cognitive impairment. Its type and degree depends on the affected network's function. We hypothesize a vicious circle between sleep end epilepsy. The epileptic derailment of normal plasticity interferes with sleep cognitive functions. Sleep and epilepsy interconnect by the pathology of plasticity.

The heritability of the human K-complex: a twin study

Sleep electroencephalogram (EEG) has a trait-like nature. Several findings highlighted the heritability of spectral power in specific frequency ranges and sleep spindles during nonrapid eye movement (NREM) sleep. However, a genetic influence on the K-complex (KC), one of the electrophysiological hallmarks of NREM sleep, has never been assessed. Here, we investigated the heritability of the KC detected during NREM stage 2 comparing 10 monozygotic (MZ) and 10 dizygotic (DZ) twin pairs. Genetic variance analysis (GVA) and intraclass correlation coefficients (ICCs) were performed to assess the genetic effect and within-pair similarity for KC density, amplitude, and for the area under the curve (AUC) of the KC average waveform at Fz, Cz, and Pz scalp locations. Moreover, cluster analysis was performed on the KC average waveform profile. We observed a significant genetic effect on KC AUC at Cz and Pz, and on amplitude at Pz. Within-pair similarity (ICCs) was always significant for MZ twins except for KC density at Fz, whereas DZ twins always exhibited ICCs below the significance threshold, with the exception of density at Pz. The largest differences in within-pair similarity between MZ and DZ groups were observed again for AUC at Cz and Pz. MZ pairs accurately clustered for the KC average waveform with a higher frequency (successful clustering rate for MZ pairs: Fz = 60%; Cz = 80%; Pz = 90%) compared with DZ pairs (successful clustering rate for DZ pairs: Fz = 10%; Cz = 10%; Pz = none). Our results suggest the existence of a genetic influence on the human KC, particularly related to its morphology and maximally observable in central and parietal locations.

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

Associations between sleep and verbal memory in subjective cognitive decline: A role for semantic clustering

Age-related reductions in slow wave activity (SWA) and increased fragmentation during sleep play a key role in memory impairment. As the prefrontal cortex is necessary for the control processes relevant to memory encoding, including utilisation of internal heuristics such as semantic clustering, and is preferentially vulnerable to sleep disturbance, our study examined how SWA and sleep fragmentation relates to memory performance in individuals with Subjective Cognitive Decline (SCD). Thirty older adults with SCD (Mean Age = 69.34, SD = 5.34) completed a neurocognitive test battery, including the California Verbal Learning Test, which was used to assess semantic clustering. One week later, participants were admitted to the laboratory for a two night visit. SWA and sleep fragmentation were captured using sleep polysomnography. Next-day memory performance was tested using the Rey Auditory Verbal Learning Test. Poorer sleep (reduced SWA; increased arousals) was associated with reduced semantic clustering, which mediated impairment on verbal memory and learning tests conducted both the day after sleep was recorded (for both SWA and arousals), and a week prior (for arousals only). We demonstrate semantic clustering mediated the well described associations between sleep and verbal memory. As these strategies are a component of cognitive training interventions, future research may examine the role of simultaneous sleep interventions for improving cognitive training outcomes.

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.

Sleep cardiac dysautonomia and EEG oscillations in amyotrophic lateral sclerosis

Study Objectives

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease due to loss of motor neurons. However, the autonomic nervous system (ANS) can also be involved. The aim of this research was to assess the sleep macro- and microstructure, the cardiac ANS during sleep, and the relationships between sleep, autonomic features, and clinical parameters in a cohort of ALS patients.

Methods

Forty-two consecutive ALS patients underwent clinical evaluation and full-night video-polysomnography. Only 31 patients met inclusion criteria (absence of comorbidities, intake of cardioactive drugs, or recording artifacts) and were selected for assessment of sleep parameters, including cyclic alternating pattern (CAP) and heart rate variability (HRV). Subjective sleep quality and daytime vigilance were also assessed using specific questionnaires.

Results

Although sleep was subjectively perceived as satisfactory, compared with age- and sex-matched healthy controls, ALS patients showed significant sleep alteration: decreased total sleep time and sleep efficiency, increased nocturnal awakenings, inverted stage 1 (N1)/stage 3 (N3) ratio, reduced REM sleep, and decreased CAP rate, the latter supported by lower amounts of A phases with an inverted A1/A3 ratio. Moreover, a significant reduction in HRV parameters was observed during all sleep stages, indicative of impaired autonomic oscillations.

Conclusion

Our results indicate that sleep is significantly disrupted in ALS patients despite its subjective perception. Moreover, electroencephalogram activity and autonomic functions are less reactive, as shown by a decreased CAP rate and a reduction in HRV features, reflecting an unbalanced autonomic modulation.

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.

Strong relationship between NREM sleep, epilepsy and plastic functions - A conceptual review on the neurophysiology background

The aim of this review is to summarize and discuss the strong bond between NREM sleep and epilepsy underlain by the shared link and effect on brain plasticity. Beyond the seizure occurrence rate, sleep relatedness may manifest in the enhancement of interictal epileptic discharges (spikes and pathological ripples). The number of the discharges as well as their propagation increase during NREM sleep, unmasking the epileptic network that is hidden during wakefulness. The interictal epileptic discharges associate with different sleep constituents (sleep slow waves, spindling and high frequency oscillations); known to play essential role in memory and learning. We highlight three major groups of epilepsies, in which sleep-related plastic functions suffer an epileptic derailment. In absence epilepsy mainly involving the thalamo-cortical system, sleep spindles transform to generalized spike-wave activity. In mesio-temporal epilepsy affecting the hippocampal declarative memory system, the sharp wave ripples derail to dysfunctional epileptic oscillations (spikes and pathological ripples). Idiopathic childhood epilepsies affecting the perisylvian network may progress to catastrophic status electricus during NREM sleep. In these major epilepsies, NREM sleep has a pivotal role in the development and course of the disorder. Epilepsy is born in-, and exhibits its pathological properties during NREM sleep. Interictal discharges are important causative agents in this process.

Increased cortical involvement and synchronization during CAP A1 slow waves

Slow waves recorded with EEG in NREM sleep are indicative of the strength and spatial extent of synchronized firing in neuronal assemblies of the cerebral cortex. Slow waves often appear in the A1 part of the cyclic alternating patterns (CAP), which correlate with a number of behavioral and biological parameters, but their physiological significance is not adequately known. We automatically detected slow waves from the scalp recordings of 37 healthy patients, visually identified CAP A1 events and compared slow waves during CAP A1 with those during NCAP. For each slow wave, we computed the amplitude, slopes, frequency, synchronization (synchronization likelihood) between specific cortical areas, as well as the location of origin and scalp propagation of individual waves. CAP A1 slow waves were characterized by greater spatial extent and amplitude, steeper slopes and greater cortical synchronization, but a similar prominence in frontal areas and similar propagation patterns to other areas on the scalp. Our results indicate that CAP A1 represents a period of highly synchronous neuronal firing over large areas of the cortical mantle. This feature may contribute to the role CAP A1 plays in both normal synaptic homeostasis and in the generation of epileptiform phenomena in epileptic patients.

Local and Widespread Slow Waves in Stable NREM Sleep: Evidence for Distinct Regulation Mechanisms

Previous work showed that two types of slow waves are temporally dissociated during the transition to sleep: widespread, large and steep slow waves predominate early in the falling asleep period (type I), while smaller, more circumscribed slow waves become more prevalent later (type II). Here, we studied the possible occurrence of these two types of slow waves in stable non-REM (NREM) sleep and explored potential differences in their regulation. A heuristic approach based on slow wave synchronization efficiency was developed and applied to high-density electroencephalographic (EEG) recordings collected during consolidated NREM sleep to identify the potential type I and type II slow waves. Slow waves with characteristics compatible with those previously described for type I and type II were identified in stable NREM sleep. Importantly, these slow waves underwent opposite changes across the night, with only type II slow waves displaying a clear homeostatic regulation. In addition, we showed that the occurrence of type I slow waves was often followed by larger type II slow waves, whereas the occurrence of type II slow waves was usually followed by smaller type I waves. Finally, type II slow waves were associated with a relative increase in spindle activity, while type I slow waves triggered periods of high-frequency activity. Our results provide evidence for the existence of two distinct slow wave synchronization processes that underlie two different types of slow waves. These slow waves may have different functional roles and mark partially distinct “micro-states” of the sleeping brain.

Identifying Phase-Amplitude Coupling in Cyclic Alternating Pattern using Masking Signals

Judiciously classifying phase-A subtypes in cyclic alternating pattern (CAP) is critical for investigating sleep dynamics. Phase-amplitude coupling (PAC), one of the representative forms of neural rhythmic interaction, is defined as the amplitude of high-frequency activities modulated by the phase of low-frequency oscillations. To examine PACs under more or less synchronized conditions, we propose a nonlinear approach, named the masking phase-amplitude coupling (MPAC), to quantify physiological interactions between high (α/lowβ) and low (δ) frequency bands. The results reveal that the coupling intensity is generally the highest in subtype A1 and lowest in A3. MPACs among various physiological conditions/disorders (p < 0.0001) and sleep stages (p < 0.0001 except S4) are tested. MPACs are found significantly stronger in light sleep than deep sleep (p < 0.0001). Physiological conditions/disorders show similar order in MPACs. Phase-amplitude dependence between δ and α/lowβ oscillations are examined as well. δ phase tent to phase-locked to α/lowβ amplitude in subtype A1 more than the rest. These results suggest that an elevated δ-α/lowβ MPACs can reflect some synchronization in CAP. Therefore, MPAC can be a potential tool to investigate neural interactions between different time scales, and δ-α/lowβ MPAC can serve as a feasible biomarker for sleep microstructure.

In Search of Sleep Biomarkers of Alzheimer's Disease: K-Complexes Do Not Discriminate between Patients with Mild Cognitive Impairment and Healthy Controls

The K-complex (KC) is one of the hallmarks of Non-Rapid Eye Movement (NREM) sleep. Recent observations point to a drastic decrease of spontaneous KCs in Alzheimer's disease (AD). However, no study has investigated when, in the development of AD, this phenomenon starts. The assessment of KC density in mild cognitive impairment (MCI), a clinical condition considered a possible transitional stage between normal cognitive function and probable AD, is still lacking. The aim of the present study was to compare KC density in AD/MCI patients and healthy controls (HCs), also assessing the relationship between KC density and cognitive decline. Twenty amnesic MCI patients underwent a polysomnographic recording of a nocturnal sleep. Their data were compared to those of previously recorded 20 HCs and 20 AD patients. KCs during stage 2 NREM sleep were visually identified and KC densities of the three groups were compared. AD patients showed a significant KC density decrease compared with MCI patients and HCs, while no differences were observed between MCI patients and HCs. KC density was positively correlated with Mini-Mental State Examination (MMSE) scores. Our results point to the existence of an alteration of KC density only in a full-blown phase of AD, which was not observable in the early stage of the pathology (MCI), but linked with cognitive deterioration.

Sleep quality, arousal and pain thresholds in tension-type headache: a blinded controlled polysomnographic study

INTRODUCTION

We aimed to compare subjective and objective sleep quality in tension-type headache (TTH) patients and to evaluate the relationship between sleep quality and pain thresholds (PT) in controls and TTH patients.

METHODS

A blinded cross-sectional study where polysomnography (PSG) and PT (to pressure, heat and cold) measurements were done in 20 patients with TTH (eight episodic (ETTH) and twelve chronic (CTTH) TTH) and 29 healthy controls. Sleep diaries and questionnaires were applied.

RESULTS

TTH patients had more anxiety ( P = 0.001), insomnia ( P < 0.0005), daytime tiredness ( P < 0.0005) and reduced subjective sleep quality ( P < 0.0005) compared to healthy controls. Sleep diaries revealed more long awakenings in TTH ( P = 0.01) but no total sleep-time differences. TTH patients had more slow-wave sleep ( P = 0.002) and less fast arousals ( P = 0.004) in their PSGs. CTTH subjects had lower pressure PT ( P = 0.048) and more daytime sleepiness than the controls ( P = 0.039). Among TTH lower cold PT (CPT) correlated inversely with light sleep (N1) ( R  = -0.49, P = 0.003) while slow arousals correlated inversely with headache-frequency ( R  = -0.64, P = 0.003).

CONCLUSIONS

We hypothesize that TTH patients need more sleep than healthy controls and might be relatively sleep deprived. Inadequate sleep may also contribute to increased pain sensitivity and headache frequency in TTH.

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-related and non-sleep-related migraine: interictal sleep quality, arousals and pain thresholds

Background

The mechanisms associating sleep and migraine are unknown. No previous polysomnographic (PSG) or pain-threshold (PT) study has compared patients with sleep-related migraine attacks (SM), non-sleep related migraine attacks (NSM) and healthy controls.

Methods

We have performed a blinded, prospective exploratory study with case–control design. Thirty-four healthy controls, 15 patients with SM and 18 patients with NSM had interictal PSG heat-, cold- and pressure PT (HPT, CPT, PPT) recordings and completed diary- and questionnaire on sleep and headache related aspects.

Results

NSM patients had more slow-wave sleep (SWS) and more K-bursts than SM patients (K-bursts: p = 0.023 and SWS: p = 0.030) and controls (K-bursts: p = 0.009 and SWS: 0.041). NSM patients also had lower HPT and CPT than controls (p = 0.026 and p = 0.021). In addition, SM patients had more awakenings and less D-bursts than controls (p = 0.025 and p = 0.041).

Conclusion

SM- and NSM patients differed in objective-, but not subjective sleep quality. NSM patients had PSG findings indicating foregoing sleep deprivation. As foregoing sleep times were normal, a relative sleep deficit might explain reduced PT among NSM patients. The SM patients had signs of slightly disturbed sleep.

EEG segmentation for improving automatic CAP detection

OBJECTIVE

The aim of this study is to provide an improved method for the automatic classification of the Cyclic Alternating Pattern (CAP) sleep by applying a segmentation technique to the computation of descriptors from the EEG.

METHODS

A dataset of 16 polysomnographic recordings from healthy subjects was employed, and the EEG traces underwent first an automatic isolation of NREM sleep portions by means of an Artificial Neural Network and then a segmentation process based on the Spectral Error Measure. The information content of the descriptors was evaluated by means of ROC curves and compared with that of descriptors obtained without the use of segmentation. Finally, the descriptors were used to train a discriminant function for the automatic classification of CAP phases A.

RESULTS

A significant improvement with respect to previous scoring methods in terms of both information content carried by the descriptors and accuracy of the classification was obtained.

CONCLUSIONS

EEG segmentation proves to be a useful step in the computation of descriptors for CAP scoring.

SIGNIFICANCE

This study provides a complete method for CAP analysis, which is entirely automatic and allows the recognition of A phases with a high accuracy thanks to EEG segmentation.

Sleep quality, arousal and pain thresholds in migraineurs: a blinded controlled polysomnographic study

BACKGROUND

Our aim was to compare subjective and objective sleep quality and arousal in migraine and to evaluate the relationship between sleep quality and pain thresholds (PT) in controls, interictal, preictal and postictal migraine.

METHODS

Polysomnography and PT (to pressure, heat and cold) measurements were done in 34 healthy controls and 50 migraineurs. Subjective sleep quality was assessed by sleep diaries, Epworth sleepiness scale, Karolinska sleep questionnaire and Pittsburgh sleep quality index. Migraineurs who had their sleep registration more than 48 h from an attack were classified as interictal while those who were less than 48 h from an attack were classified as either preictal or postictal.

RESULTS

Migraineurs reported more insomnia and other sleep-related symptoms than controls, but the objective sleep differences were smaller and we found no differences in daytime sleepiness. Interictal migraineurs had more awakenings (p=0.048), a strong tendency for more slow-wave sleep (p=0.050), lower thermal pain thresholds (TPT) (heat pain thresholds p=0.043 and cold pain thresholds p=0.031) than controls. Migraineurs in the preictal phase had shorter latency to sleep onset than controls (p=0.003). Slow-wave sleep correlated negatively with pressure PT and slow bursts correlated negatively with TPT.

CONCLUSION

Lower PT in interictal migraineurs seems related to increased sleep pressure. We hypothesize that migraineurs on the average suffer from a relative sleep deprivation and need more sleep than healthy controls. Lack of adequate rest might be an attack-precipitating- and hyperalgesia-inducing factor.

CAP sleep in insomnia: new methodological aspects for sleep microstructure analysis

This work aims to propose new methodologies for the quantitative characterization of insomnia. Sleep microstructure, as expressed by Cyclic Alternatic pattern (CAP) sleep, is studied and differences between normal sleepers and insomniacs are investigated. The dynamic in the structure of CAP activation events is studied by use of wavelet analysis and the content of events, i.e. EEG dynamics, is studied in terms of complexity analysis. Both in structure and content, features exhibiting statistically significant differences are proposed, opening new perspectives for the understanding and the quantitative characterization of sleep and its disorders.

Physiopathogenetic Interrelationship between Nocturnal Frontal Lobe Epilepsy and NREM Arousal Parasomnias

Aims. To build up a coherent shared pathophysiology of NFLE and AP and discuss the underlying functional network. Methods. Reviewing relevant published data we point out common features in semiology of events, relations to macro- and microstructural dynamism of NREM sleep, to cholinergic arousal mechanism and genetic aspects. Results. We propose that pathological arousals accompanied by confused behavior with autonomic signs and/or hypermotor automatisms are expressions of the frontal cholinergic arousal function of different degree, during the condition of depressed cognition by frontodorsal functional loss in NREM sleep. This may happen either if the frontal cortical Ach receptors are mutated in ADNFLE (and probably also in genetically not proved nonlesional cases as well), or without epileptic disorder, in AP, assuming gain in receptor functions in both conditions. This hypothesis incorporates the previous “liberation theory” of Tassinari and the “state dissociation hypothesis” of Bassetti and Terzaghi). We propose that NFLE and IGE represent epileptic disorders of the two antagonistic twin systems in the frontal lobe. NFLE is the epileptic facilitation of the ergotropic frontal arousal system whereas absence epilepsy is the epileptic facilitation of burst-firing working mode of the spindle and delta producing frontal thalamocortical throphotropic sleep system. Significance. The proposed physiopathogenesis conceptualize epilepsies in physiologically meaningful networks.

Assessment of the EEG complexity during activations from sleep

The present study quantitatively analyzes the EEG characteristics during activations (Act) that occur during NREM sleep, and constitute elements of sleep microstructure (i.e. the Cyclic Alternating Pattern). The fractal dimension (FD) and the sample entropy (SampEn) measures were used to study the different sleep stages and the Act that build up the sleep structure. Polysomnographic recordings from 10 good sleepers were analyzed. The complexity indexes of the Act were compared with the non-activation (NAct) periods during non-REM sleep. In addition, complexity measures among the different Act subtypes (A1, A2 and A3) were analyzed. A3 presented a quite similar complexity independently of the sleep stage, while A1 and A2 showed higher complexity in light sleep than during deep sleep. The current results suggest that Act present a hierarchic complexity between subtypes A3 (higher), A2 (intermediate) and A1 (lower) in all sleep stages.

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.

Cyclic alternating pattern in narcolepsy patients and healthy controls after partial and total sleep deprivation

OBJECTIVE

To investigate the regulation NREM sleep at baseline and in morning recovery sleep after partial and total sleep deprivation (SD) in narcolepsy-cataplexy (NC) using cyclic alternating pattern (CAP).

METHODS

Daytime sleep under either increased (no sleep in the previous night) or decreased sleep pressure (allowing 4h of sleep, 23:00-3:00 h) was recorded in ten drug-free, HLA-positive, hypocretin deficient NC patients and ten age, gender and body mass index matched healthy controls. Baseline sleep was also recorded and used for comparison purposes. CAP parameters were scored and analyzed for each subject.

RESULTS

Narcolepsy patients had significantly lower CAP rate, CAP index, CAP time, number of CAP cycles, A1 index and number of A1 cycles in comparison to healthy controls at baseline as well as after partial and total SD. In both narcolepsy patients and healthy control subjects there was a significant decrease in these parameters after partial and total SD but the changes followed a similar pattern.

CONCLUSION

The persistence of baseline differences in CAP parameters between narcolepsy patients and healthy controls and their similar behavior after partial and total SD suggests similar homeostatic NREM sleep regulation but on a different level.

SIGNIFICANCE

CAP analysis demonstrates that NREM sleep homeostasis although altered, is functional in narcolepsy patients.

Clonidine has a paradoxical effect on cyclic arousal and sleep bruxism during NREM sleep

STUDY OBJECTIVE

Clonidine disrupts the NREM/REM sleep cycle and reduces the incidence of rhythmic masticatory muscle activity (RMMA) characteristic of sleep bruxism (SB). RMMA/SB is associated with brief and transient sleep arousals. This study investigates the effect of clonidine on the cyclic alternating pattern (CAP) in order to explore the role of cyclic arousal fluctuation in RMMA/SB.

DESIGN

Polysomnographic recordings from a pharmacological study.

SETTING

University sleep research laboratory.

PARTICIPANTS AND INTERVENTIONS

Sixteen SB subjects received a single dose of clonidine or placebo at bedtime in a crossover design.

MEASUREMENTS AND RESULTS

Sleep variables and RMMA/SB index were evaluated. CAP was scored to assess arousal instability between sleep-maintaining processes (phase A1) and stronger arousal processes (phases A2 and A3). Paired t-tests, ANOVAs, and cross-correlations were performed. Under clonidine, CAP time, and particularly the number of A3 phases, increased (P≤0.01). RMMA/SB onset was time correlated with phases A2 and A3 for both placebo and clonidine nights (P≤0.004). However, under clonidine, this positive correlation began up to 40 min before the RMMA/SB episode.

CONCLUSIONS

CAP phase A3 frequency increased under clonidine, but paradoxically, RMMA/SB decreased. RMMA/SB was associated with and facilitated in CAP phase A2 and A3 rhythms. However, SB generation could be influenced by other factors besides sleep arousal pressure. NREM/REM ultradian cyclic arousal fluctuations may be required for RMMA/SB onset.

Characterization of A phases during the cyclic alternating pattern of sleep

OBJECTIVE

This study aims to identify, starting from a single EEG trace, quantitative distinctive features characterizing the A phases of the Cyclic Alternating Pattern (CAP).

METHODS

The C3-A2 or C4-A1 EEG leads of the night recording of eight healthy adult subjects were used for this analysis. CAP was scored by an expert and the portions relative to NREM were selected. Nine descriptors were computed: band descriptors (low delta, high delta, theta, alpha, sigma and beta); Hjorth activity in the low delta and high delta bands; differential variance of the EEG signal. The information content of each descriptor in recognizing the A phases was evaluated through the computation of the ROC curves and the statistics sensitivity, specificity and accuracy.

RESULTS

The ROC curves show that all the descriptors have a certain significance in characterizing A phases. The average accuracy obtained by thresholding the descriptors ranges from 59.89 (sigma descriptor) to 72.44 (differential EEG variance).

CONCLUSIONS

The results show that it is possible to attribute a significant quantitative value to the information content of the descriptors.

SIGNIFICANCE

This study gives a mathematical confirm to the features of CAP generally described qualitatively, and puts the bases for the creation of automatic detection methods.

EEG complexity during sleep: on the effect of micro and macro sleep structure

This work investigates the relation between EEG complexity measures, in particular Fractal Dimension and Sample Entropy, and sleep structure, in terms of both macrostructure, i.e. sleep stages, and microstructure, i.e. phase A activation of CAP sleep. Activation phases are compared with the non-activation periods of non-REM sleep. The study suggests that complexity features can serve as consistent descriptors of sleep dynamics and can potentially assist in the classification of sleep stages.