Cyclic Alternating Pattern Subtypes Research Articles

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.

Non-REM sleep instability in children with restless sleep disorder

Study objectivesRestless sleep disorder (RSD) is a newly recognized condition characterized by motor movements involving large muscle groups with frequent repositioning or bed sheets disruption. We analyzed cyclic alternating pattern (CAP) in these children, a marker of sleep instability that might be associated with the motor episodes of RSD and may play a role in their daytime symptoms. MethodsPolysomnographic recordings from thirty-eight children who fulfilled RSD diagnostic criteria (23 boys and 15 girls), 23 children with restless legs syndrome (RLS, 18 boys and 5 girls) and 19 controls (10 boys and 9 girls) were included. For CAP analysis, a previously developed, highly precise automated system, based on a deep learning recurrent neural network, was used. ResultsAge and gender were not statistically different between groups. RSD patients showed a lower percentage of A3 CAP subtypes than controls (median 9.8 vs. 18.2, p = 0.0089), accompanied by shorter duration of the B phase of the CAP cycle (median 28.2 vs. 29.8 in controls, 30.2 in RLS, p = 0.005) and shorter CAP cycle duration than both controls and RLS subjects (median 33.8 vs. 35.0 in controls, 35.8 in RLS, p = 0.002). Finally, RSD children also showed a longer duration of CAP cycle sequences, when compared to controls (median 172.7 vs. 141.9, p = 0.0063). ConclusionsIn conclusion, our study indicates that NREM sleep EEG shows an increased instability in RSD; these findings add to the current knowledge on the mechanisms of this newly recognized sleep disorder and suggest that sleep instability might be a favoring mechanism for the emergence of the motor episodes characterizing RSD.

0943 Increased Non-REM Sleep Instability in Children with Restless Sleep Disorder

Abstract Introduction Restless sleep disorder (RSD) is a newly recognized condition characterized by motor movements involving large muscle groups with frequent repositioning or bed sheets disruption. We analyzed cyclic alternating pattern (CAP) in these children, a marker of sleep instability that might be associated with the motor episodes of RSD and may play a role in their daytime symptoms. Methods Polysomnographic recordings from thirty-eight children who fulfilled RSD diagnostic criteria (23 boys and 15 girls), 23 children with restless legs syndrome (RLS, 18 boys and 5 girls) and 19 controls (10 boys and 9 girls) were included. For CAP analysis, a previously developed, highly precise automated system, based on a deep learning recurrent neural network, was used. Results Age and gender were not statistically different between groups. RSD patients showed a lower percentage of A3 CAP subtypes than controls (median 9.8 vs. 18.2, p=0.0089), accompanied by shorter duration of the B phase of the CAP cycle (median 28.2 vs. 29.8 in controls, 30.2 in RLS, p=0.005) and shorter CAP cycle duration than both controls and RLS subjects (median 33.8 vs. 35.0 in controls, 35.8 in RLS, p=0.002). Finally, RSD children also showed a longer duration of CAP cycle sequences, when compared to controls (median 172.7 vs. 141.9, p=0.0063). Conclusion In conclusion, our study indicates that NREM sleep EEG shows an increased instability in RSD; these findings add to the current knowledge on the mechanisms of this newly recognized sleep disorder and suggest that sleep instability might be a favoring mechanism for the emergence of the motor episodes characterizing RSD. Support Partial support by a grant of the Italian Ministry of Health RC n. 2751598 (R.F.)

Sleep architecture in children with spinal muscular atrophy type 2

ObjectiveThere have been few published reports on the sleep patterns of patients with spinal muscular atrophy (SMA) type 2, and none on sleep microstructure. The aim of this study was to analyze sleep architecture and microstructure in a group of children with SMA type 2, compared with age-matched and sex-matched controls. MethodsSeventeen SMA type 2 children (seven males, mean age 4.2 years) and 12 controls (five males, mean age 5.0 years) underwent full polysomnography to evaluate sleep architecture and microstructure by means of the Cyclic Alternating Pattern (CAP). ResultsCompared with the control children, the SMA type 2 patients showed a mild increase in the apnea/hypopnea index. Sleep was characterized by a decrease in the number of sleep stage shifts per hour, of percentage of stage N3, of stage R, and of sleep efficiency. On the contrary, significant increases of awakenings per hour, wake after sleep onset, and percentage of stage N1 were found. The CAP analysis revealed a significant increase in the percentage of A1 CAP subtypes, a reduction of that of A3 subtypes, and of A2 and A3 indexes. ConclusionsThe results indicated an abnormality of sleep macrostructure and microstructure in SMA type 2 patients, which was characterized by a reduction of A2 and A3 subtypes (low and high power arousals), supporting the concept of a decreased arousability in SMA type 2 patients. Similar to a previous report on SMA type 1, the findings might be additional proof of central nervous system involvement, although these alterations are less severe than those observed in infants with SMA type 1.

Sleep architecture in infants with spinal muscular atrophy type 1

ObjectiveFew reports on sleep patterns of patients with spinal muscular atrophy type 1 (SMA1) have been published and none on sleep microstructure. The aim of this study was to analyze sleep architecture and microstructure in a group of infants with SMA1, compared with age- and sex-matched controls. MethodsTwelve SMA1 patients (six males, mean age 5.9 months) and 10 controls (five males, mean age 4.8 months) underwent full polysomnography to evaluate their sleep architecture and microstructure by means of the cyclic alternating pattern (CAP). ResultsCompared with control children, SMA1 patients showed increased sleep latency and apnea/hypopnea index. CAP analysis revealed a significant increase in the percentage of A1 CAP subtypes, a reduction of that of A3 subtypes and of A2 and A3 indexes (number/h), indicating a dysfunction of the arousal system in these patients. ConclusionThe results indicate the presence of an abnormality of sleep microstructure in SMA1 patients, characterized by a reduction of A2 and A3 CAP subtypes. We hypothesize that SMA1 patients have reduced arousability during non-rapid eye movement sleep, which could be interpreted as additional evidence of central nervous system involvement in this disease.

SLEEP cyclic alternating pattern (CAP) changes from school-age to adolescence in healthy subjects

Cyclic Alternating Pattern (CAP) is a well recognized process underlying sleep instability. CAP organization has been reported in several age-groups, but follow-up data in healthy children or adolescents is scarce. Objective: To assess sequential changes in CAP characteristics from school-age to adolescence in the same group of healthy subjects. We studied a sample of 45 healthy school-age children. All were participants in an ongoing cohort follow-up study since infancy. PSG recordings were performed at 10 years and repeated in adolescence. CAP was visually identified in non- REM sleep stages S1, S2 and SWS, according to international rules. The age of the subjects was 10.3 ± 0.2 and 15.6 ± 0.5 years at the time of the two assessments. CAP number, CAP rate, CAP duration but not CAP time were positively correlated between 10 and 15 years (all p < 0.05). Between-age differences were as follows: an increase in CAP time (145.8 ± 44.0 vs. 183.6 ± 53.7 min., p < 0.0001), CAP rate (41.9 ± 11.6 vs. 47.5 ± 12.0%, p < 0.01), A3 percentage (18.3 ± 9.8 vs. 27.4 ± 10.7, p < 0.0001), A3 index (9.0 ± 5.1 vs. 16.9 ± 8.1, p < 0.0001), and a decrease in A1 percentage (68.2 ± 13.3 vs. 59.7 ± 12.1, p < 0.002). We also found a lengthening of CAP cycles with a shortening of the B phase (both p < 0.03). According to sleep stages, an increase in CAP rate and A1 index was apparent in SWS, whereas A1 index was decreased in S1 and S2 (all p < 0.004). Finally, A3 index resulted higher in all non-REM sleep stages (all p < 0.004). These preliminary data show several changes in CAP parameters between 10 and 15 years. Given that the main modifications with advancing age were an increase in A3 and a reduction in A1 CAP subtypes, they provide support for a reduction in sleep stability towards adolescence in healthy subjects. Financial support: Fondecyt 1110513 and NIH HD33487 grants. (*) CONICYT PhD program fellowship.

Cyclic alternating pattern in sleep and its relationship to creativity

Background/objectives Sleep has been shown to enhance creativity, but the reason for this enhancement is not entirely known. There are several different physiologic states associated with sleep. In addition to rapid (REM) and non-rapid eye movement (NREM) sleep, NREM sleep can be broken down into Stages (1–4) that are characterized by the degree of EEG slow-wave activity. In addition, during NREM sleep the cyclic alternating pattern (CAPs) of EEG activity has been described which can also be divided into three subtypes (A1–A3) according to the frequency of the EEG waves. Differences in CAP subtype ratios have been previously linked to cognitive performances. The purpose of this study was to asses the relationship between CAP activity during sleep and creativity. Methods The participants were eight healthy young adults (four women) who underwent three consecutive nights of polysomnographic recording and took the Abbreviated Torrance Test for Adults (ATTA) on the second and third mornings after the recordings. Results There were positive correlations between Stage 1 of NREM sleep and some measures of creativity such as fluency ( R = .797; p = .029) and flexibility ( R = .43; p = .002), between Stage 4 of NREM sleep and originality ( R = .779; p = .034) and a global measure of figural creativity ( R = .758; p = .040). There was also a negative correlation between REM sleep and originality ( R = −.827; p = .042). During NREM sleep the CAP rate, which in young people reflects primarily the A1 subtype, also correlated with originality ( R = .765; p = .038). Conclusions NREM sleep is associated with low levels of cortical arousal, and low cortical arousal may enhance the ability of people to access to the remote associations that are critical for creative innovations. In addition, A1 CAP subtypes reflect frontal activity, and the frontal lobes are important for divergent thinking, also a critical aspect of creativity.

Effects of NREM sleep instability on cognitive processing

Objective Cyclic alternating pattern (CAP) A1 subtypes, characterized by high-voltage slow waves, are generated by the frontal cortex and are suspected to have a role in cognitive processing during NREM sleep. Conversely, CAP A2 and A3 subtypes are characterized by variable amounts of rapid EEG potentials arising from the parietal–occipital areas and often coincide with arousals. We tested the hypothesis that CAP subtypes differentially correlate with cognitive functions. Subjects and methods Eight healthy participants were recruited. Two nocturnal polysomnography studies and a series of neuropsychological tests were obtained in the subjects during the morning and afternoon of the first day and on the morning of the second day. Results In agreement with our original hypothesis, we found that CAP A1 subtypes were correlated with better neuropsychological functioning the day after, for verbal fluency, working memory, and both delayed recall and recognition of words. These same neuropsychological test results were found to be negatively correlated with CAP A2 subtypes. CAP A3 subtypes were negatively correlated with the Trial Making test Parts A and B. Conclusions The results suggest that CAP A1 might be related to better cognitive functioning, whereas CAP A2 and A3 correlated with worse cognitive functioning. Further studies are needed to better understand how CAP influences cognitive performance, especially frontally-dependent functions and memory.

Slow EEG Amplitude Oscillations During NREM Sleep and Reading Disabilities in Children With Dyslexia

Study Objectives: To analyze non-rapid eye movement (NREM) sleep microstructure of children with dyslexia, by means of cyclic alternating pattern (CAP) analysis and to correlate CAP parameters with neuropsychological measures. Design: Cross-sectional study using polysomnographic recordings and neuropsychological assessments. Setting: Sleep laboratory in academic center. Participants: Sixteen subjects with developmental dyslexia (mean age 10.8 years) and 11 normally reading children (mean age 10.1 years) underwent overnight polysomnographic recording. Intervention: N/A. Measurements and Results: Sleep architecture parameters only showed some statistically significant differences: number of sleep stage shifts per hour of sleep, percentage of N3, and number of R periods were significantly lower in dyslexic children versus controls. CAP analysis revealed a higher total CAP rate and A1 index in stage N3. A2% and A2 index in stage N2 and N3 were lower in dyslexic children while no differences were found for A3 CAP subtypes. The correlation analysis between CAP parameters and cognitive-behavioral measures showed a significant positive correlation between A1 index in N3 with Verbal IQ, full-scale IQ, and Memory and Learning Transfer reading test; while CAP rate in N3 was positively correlated with verbal IQ. Conclusions: To overcome reading difficulties, dyslexic subjects overactivate thalamocortical and hippocampal circuitry to transfer information between cortical posterior and anterior areas. The overactivation of the ancillary frontal areas could account for the CAP rate modifications and mainly for the increase of CAP rate and of A1 index in N3 that seem to be correlated with IQ and reading abilities.

NREM sleep alterations in narcolepsy/cataplexy

Objective NREM sleep patterns of narcoleptic patients with cataplexy were studied, focusing on their sleep ‘microstructure’, by analyzing the cyclic alternating pattern (CAP). Methods Forty-nine HLA DQB1*0602-positive patients with narcolepsy/cataplexy (32 men and 17 women, aged 18–46 years) were included together with 37 age-matched normal controls. Each subject underwent one polysomnographic night recording after an adaptation night. Sleep stages were scored following standard criteria and CAP A phases were detected and classified into 3 subtypes (A1, A2, and A3). Power spectra for frequencies between 0.5 and 25 Hz were obtained for each CAP condition, separately in sleep stage 2 and SWS. Results Narcoleptic patients displayed reduced total CAP rate. A selective reduction in the number of A1 subtypes/hour and a reduced A3 index were found in narcoleptics who had also a smaller average number of CAP sequences. Narcoleptic patients had higher power spectra for fast frequencies mostly during SWS, while REM sleep power spectra showed significantly higher power density for frequency bins 0.5–1.5, 8.5–9.5, and 17.5–25 Hz. Similarly, CAP A1 subtypes and NCAP epochs during SWS displayed significantly higher power density for fast frequency bins. Conclusions The main finding of this study is that the occurrence of the A1 CAP subtypes is impaired during NREM sleep in narcoleptic patients. Thus, narcolepsy seems to be accompanied not only by alterations of REM but also NREM sleep which is subtly but significantly impaired, as reflected by CAP and the corresponding EEG spectral analysis. Significance Our findings might indicate that in narcolepsy very-slow oscillation processes less effective than normal might be present, with a subtly impaired capability of grouping the other sleep EEG activities; this aspect deserves further insight in order to obtain a better understanding of its functional meaning.

All-night EEG power spectral analysis of the cyclic alternating pattern components in young adult subjects

Objective To analyze in detail the frequency content of the different EEG components of the Cyclic Alternating Pattern (CAP), taking into account the ongoing EEG background and the nonCAP (NCAP) periods in the whole night polysomnographic recordings of normal young adults. Methods Sixteen normal healthy subjects were included in this study. Each subject underwent one polysomnographic night recording; sleep stages were scored following standard criteria. Subsequently, each CAP A phase was detected in all recordings, during NREM sleep, and classified into 3 subtypes (A1, A2, and A3). The same channel used for the detection of CAP A phases (C3/A2 or C4/A1) was subdivided into 2-s mini-epochs. For each mini-epoch, the corresponding CAP condition was determined and power spectra calculated in the frequency range 0.5–25 Hz. Average spectra were obtained for each CAP condition, separately in sleep stage 2 and SWS, for each subject. Finally, the first 6 h of sleep were subdivided into 4 periods of 90 min each and the same spectral analysis was performed for each period. Results During sleep stage 2, CAP A subtypes differed from NCAP periods for all frequency bins between 0.5 and 25 Hz; this difference was most evident for the lowest frequencies. The B phase following A1 subtypes had a power spectrum significantly higher than that of NCAP, for frequencies between 1 and 11 Hz. The B phase after A2 only differed from NCAP for a small but significant reduction in the sigma band power; this was evident also after A3 subtypes. During SWS, we found similar results. The comparison between the different CAP subtypes also disclosed significant differences related to the stage in which they occurred. Finally, a significant effect of the different sleep periods was found on the different CAP subtypes during sleep stage 2 and on NCAP in both sleep stage 2 and SWS. Conclusions CAP subtypes are characterized by clearly different spectra and also the same subtype shows a different power spectrum, during sleep stage 2 or SWS. This finding underlines a probable different functional meaning of the same CAP subtype during different sleep stages. We also found 3 clear peaks of difference between CAP subtypes and NCAP in the delta, alpha, and beta frequency ranges which might indicate the presence of 3 frequency components characterizing CAP subtypes, in different proportion in each of them. The B component of CAP differs from NCAP because of a decrease in power in the sigma frequency range. Significance This study shows that A components of CAP might correspond to periods in which the very-slow delta activity of sleep groups a range of different EEG activities, including the sigma and beta bands, while the B phase of CAP might correspond to a period in which this activity is quiescent or inhibited.

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 7–12 Hz, 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 (0.25–2.5 Hz) and A3 (7–12 Hz). 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 0.25–2.5 Hz band and over the parietal–occipital areas for the 7–12 Hz 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.

New Models for Old: Taking the Neural Network Seriously

Cyclic alternating pattern (CAP) A1 subtypes, characterized by high-voltage slow waves, are generated by the frontal cortex and are suspected to have a role in cognitive processing during NREM sleep. Conversely, CAP A2 and A3 subtypes are characterized by variable amounts of rapid EEG potentials arising from the parietal–occipital areas and often coincide with arousals. We tested the hypothesis that CAP subtypes differentially correlate with cognitive functions.Eight healthy participants were recruited. Two nocturnal polysomnography studies and a series of neuropsychological tests were obtained in the subjects during the morning and afternoon of the first day and on the morning of the second day.In agreement with our original hypothesis, we found that CAP A1 subtypes were correlated with better neuropsychological functioning the day after, for verbal fluency, working memory, and both delayed recall and recognition of words. These same neuropsychological test results were found to be negatively correlated with CAP A2 subtypes. CAP A3 subtypes were negatively correlated with the Trial Making test Parts A and B.The results suggest that CAP A1 might be related to better cognitive functioning, whereas CAP A2 and A3 correlated with worse cognitive functioning. Further studies are needed to better understand how CAP influences cognitive performance, especially frontally-dependent functions and memory.