Sleep Cyclic Alternating Pattern in Normal Preschool-Aged Children

Bruni, Oliviero; Ferri, Raffaele; Miano, Silvia; Verrillo, Elisabetta; Vittori, Elena; Farina, Benedetto; Smerieri, Anteo; Terzano, Mario Giovanni

doi:10.1093/sleep/28.2.220

Cited by 57 publications

(21 citation statements)

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“…Moreover, another difference between our study and that of Miano et al. (2007) regards the children’s age, which we have kept within a narrow range in consideration of the age‐dependency of CAP parameters (Bruni et al. , 2002, 2005).…”

Section: Discussionmentioning

confidence: 97%

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Sleep in children with autism with and without autistic regression

Giannotti

Cortesi

Cerquiglini

et al. 2010

Journal of Sleep Research

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Summary The purpose of the present investigation was to characterize and compare traditional sleep architecture and non‐rapid eye movement (NREM) sleep microstructure in a well‐defined cohort of children with regressive and non‐regressive autism, and in typically developing children (TD). We hypothesized that children with regressive autism would demonstrate a greater degree of sleep disruption either at a macrostructural or microstructural level and a more problematic sleep as reported by parents. Twenty‐two children with non‐regressive autism, 18 with regressive autism without comorbid pathologies and 12 with TD, aged 5–10 years, underwent standard overnight multi‐channel polysomnographic evaluation. Parents completed a structured questionnaire (Childrens’ Sleep Habits Questionnaire—CSHQ). The initial hypothesis, that regressed children have more disrupted sleep, was supported by our findings that they scored significantly higher on CSHQ, particularly on bedtime resistance, sleep onset delay, sleep duration and night wakings CSHQ subdomains than non‐regressed peers, and both scored more than typically developing controls. Regressive subjects had significantly less efficient sleep, less total sleep time, prolonged sleep latency, prolonged REM latency and more time awake after sleep onset than non‐regressive children and the TD group. Regressive children showed lower cyclic alternating pattern (CAP) rates and A1 index in light sleep than non‐regressive and TD children. Our findings suggest that, even though no particular differences in sleep architecture were found between the two groups of children with autism, those who experienced regression showed more sleep disorders and a disruption of sleep either from a macro‐ or from a microstructural viewpoint.

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Section: Discussionmentioning

confidence: 97%

“…Sleep microstructure. CAP was scored according to the currently accepted criteria (Bruni et al, 2002(Bruni et al, , 2005Terzano et al, 2001), as shown in Table 1.…”

Section: Analysis Of Polysomnographic Recordingsmentioning

confidence: 99%

Sleep in children with autism with and without autistic regression

Giannotti

Cortesi

Cerquiglini

et al. 2010

Journal of Sleep Research

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“…Rhythmic masticatory muscle activity (RMMA), physiologically characterizing SB, was found to be correlated with arousal activities [i.e., micro‐arousals and cyclic alternating pattern (CAP)] during sleep in children (Herrera et al , ) and in adults (Kato et al , ). Electroencephalographic (EEG) arousal does not change much with age in children (Scholle et al , ) while CAP phase A2 and A3, more related to RMMA, significantly decreased from preschoolers to school children (Bruni et al , , ; Terzano et al , ). This suggests that arousal fluctuation in children in relation to development can be a physiological factor underlying curvilinear changes of SB prevalence.…”

Section: Discussionmentioning

confidence: 99%

Associations of sleep bruxism with age, sleep apnea, and daytime problematic behaviors in children

et al. 2016

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“…Parrino et al (2011) propose that specific configurations of this pattern could represent a marker of sleep instability. For instance, the prevalence in pre-school children (Bruni et al, 2005) and elderly subjects (Parrino et al, 1998) of desynchronized CAP phases (A2 subtype) over synchronized patterns (A1 subtype) would suggest a greater sleep instability in these age groups. Interestingly, A1 pattern displayed a significant increase in a post-training night, compared to baseline (Ferri et al, 2008), as well as a positive correlation with morning retest performance (Ferri et al, 2008; Aricò et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

The Effects of Pre-Sleep Learning on Sleep Continuity, Stability, and Organization in Elderly Individuals

Conte¹,

Carobbi²,

Errico³

et al. 2012

Front. Neur.

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Several studies have consistently shown that pre-sleep learning is associated to changes of sleep structure. Whereas previous research has mainly focused on sleep states, namely REM and NREM amount, very little attention has been paid to the hypothesis that pre-sleep learning might improve sleep continuity, stability, and cyclic organization, which are often impaired in aging. Thus, aim of this research was to assess, in a sample of 18 healthy elderly subjects, whether a memory task administered at bedtime would determine changes in any sleep parameter, with special regard to sleep continuity, stability, and organization. To this purpose, a baseline sleep (BL), i.e., a normal sleep with 9-h time in bed (TIB), was compared to a post-training sleep (TR), with the same TIB but preceded by an intensive training session. For the latter, a verbal declarative task was used, consisting in learning paired-word lists, rehearsed, and recalled for three times in a row. To control for individual learning abilities, subjects were administered several sets of lists with increasing difficulty, until they reached an error rate ≥20% at third recall. Relative to BL, TR shows a significant reduction in the frequency of brief awakenings, arousals, state transitions, “functional uncertainty” (FU) periods, and in the percentage of time in FU over total sleep time (TST). A significant increase in the number of complete cycles, total cycle time (TCT), and TCT/TST proportion was also found. All these changes are evenly distributed over the sleep episode. No sleep stage measure display significant changes, apart from a slight reduction in the percentage of Stage 1. Scores at retest are negatively correlated with both the frequency of arousals and of state transitions. Our data suggest that pre-sleep learning can yield a beneficial re-organizing effect on elderlies’ sleep quality. The inverse correlation between recall scores and the measures of sleep continuity and stability provides further support to the role of these features in memory processes.

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Sleep Cyclic Alternating Pattern in Normal Preschool-Aged Children

Cited by 57 publications

References 0 publications

Sleep in children with autism with and without autistic regression

Sleep in children with autism with and without autistic regression

Associations of sleep bruxism with age, sleep apnea, and daytime problematic behaviors in children

The Effects of Pre-Sleep Learning on Sleep Continuity, Stability, and Organization in Elderly Individuals

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