Neonatal EEG/Sleep State Analyses: A Complex Phenotype of Developmental Neural Plasticity

Scher, Mark S.; Loparo, Kenneth A.

doi:10.1159/000216537

Cited by 49 publications

(34 citation statements)

References 283 publications

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“…Comparative sleep study results from other authors suggested that the sleep cycle of full term newborns showed ultradian rhythm, with the duration of each cycle lasts about 30-70 minutes, [16] which differed from our observation of the SWC duration, which lasts between 43.0-99.5 minutes. The difference may come from the methodology and defi nition of SWC.…”

Section: Discussioncontrasting

confidence: 99%

Newborns’ sleep-wake cycle development on amplitude integrated electroencephalography

Zhou

Lian

2016

World J Pediatr

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Section: Discussioncontrasting

confidence: 99%

Newborns’ sleep-wake cycle development on amplitude integrated electroencephalography

Zhou

Lian

2016

World J Pediatr

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“…60 The FGR children in this study showed an increase in θ power, potentially reflecting alterations in hippocampal and cortical activity, however what this increase means is unclear and deserves further study. Further investigation on early life programming with gene-environment interactions (epigenetics) that influence developmental brain plasticity during critical or sensitive periods of brain and sleep maturation would be imperative to further explore these mechanisms, 61 particularly, as it is known that fetal state behaviors predict adolescent performance later in life. 62 Currently, sleep in childhood is not routinely monitored in children born preterm or FGR.…”

Section: Discussionmentioning

confidence: 99%

Being Born Too Small and Too Early May Alter Sleep in Childhood

Yiallourou

Arena

Wallace

et al. 2017

Sleep

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Study Objectives: Fetal growth restriction (FGR) occurs in up to 10% of pregnancies and is associated with increased risk of prematurity and neurodevelopmental impairment. FGR also alters sleep-state distribution in utero and maturation in infancy. Currently, limited data on the long-term associations of FGR and childhood sleep exist. Accordingly, we assessed the associations between preterm birth and FGR and sleep in children aged 5-12 years.Methods: Seventeen children born preterm and FGR, 15 children born preterm but appropriately grown (appropriate birth weight for gestational age [AGA]), and 20 term AGA children (controls) were studied using overnight polysomnography. Sleep macroarchitecture was assessed using standard criteria, and sleep microarchitecture was assessed using spectral analysis of the electroencephalogram (C4-M1) with total, δ (0.5-3.9 Hz), θ (4.0-7.9Hz), α (8.0-11.9 Hz), σ (12.0-13.9 Hz), and β power (14.0-30 Hz) calculated.Results: For sleep macroarchitecture, preterm FGR children had higher N2% compared with term AGA children (p < .05). Preterm AGA children had reduced total sleep time, NREM%, and sleep efficiency compared with term AGA children (p < .05 for all). For sleep microarchitecture, preterm FGR children had a higher amount of total, δ and α power compared with both groups (p < .05). Sigma and β power was lowest in the preterm AGA group compared with both groups (p < .05 for both).Conclusions: Prematurity and FGR were associated with altered sleep macro-and microarchitecture measures indicative of reduced sleep quantity and quality in childhood. As sleep disturbance can affect both behavior and neurodevelopment in children, sleep in FGR and preterm children warrants further investigation. Keywords: fetal growth restriction, preterm birth, pediatric, EEG spectral analysis, sleep. Statement of SignificanceFetal growth restriction (FGR) is a major obstetric complication affecting up to 10% of pregnancies leading to increased risk of preterm birth and neurodevelopmental impairment. FGR alters the development of sleep in fetal life and infancy; however, few studies have investigated the long-term impact on sleep. This novel study assessed both sleep macro-and microarchitecture in children born preterm and FGR. Being born preterm and FGR was associated with reduced sleep quality, whereas being born preterm with an appropriate birth weight for gestational age was associated with both reduced sleep quantity and quality. This study highlights the potential need for clinical follow-up of sleep and investigation of the effects of poor sleep on neurodevelopment in this population.

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“…The study of neonatal sleep is of great importance as it helps determining the degree of maturity of the neonatal brain and can be useful in the assessment of a possible risk of certain disabilities [1][2][3][4]. For example, neonatal sleep was found to be relevant to some syndromes such as sudden infant death syndrome (SIDS) which was found to be related to the immaturity of the respiratory center in the brain.…”

Section: Introductionmentioning

confidence: 99%

Newborn sleep stage identification using multiscale entropy

Fraiwan

Lweesy

2014

2nd Middle East Conference on Biomedical Engineering

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Neonatal sleep stage identification is of great importance as it helps diagnosis of certain possible disabilities in newborns. The sleep stage identification is normally done manually for an entire sleep recording which requires great human resources; therefore a reliable automated sleep stage identification system offers a helpful tool for specialists. This study demonstrated a new method for automated sleep stage scoring in neonates. The automated approach comprises two major steps: feature extraction and classification. This study presented a new approach for feature extraction based on multiscale entropy (MSE), a recently developed method for the analysis of time series and physiological signals. The features were extracted from a single EEG recording where 13 recordings from preterm infants and 14 from full term infants were used. The classification was done using the Weka software with three different classifiers: neural networks, random forests, and classification via regression. The performance of the proposed method was found to be comparable to the methods reported in the literature. The reported accuracy was found to be 0.813 for preterm subjects and 0.864 for fullterm subjects.

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Neonatal EEG/Sleep State Analyses: A Complex Phenotype of Developmental Neural Plasticity

Cited by 49 publications

References 283 publications

Newborns’ sleep-wake cycle development on amplitude integrated electroencephalography

Newborns’ sleep-wake cycle development on amplitude integrated electroencephalography

Being Born Too Small and Too Early May Alter Sleep in Childhood

Newborn sleep stage identification using multiscale entropy

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