On the development of sleep states in the first weeks of life

Abstract

Human newborns spend up to 18 hours sleeping. The organization of their sleep differs immensely from adult sleep, and its quick maturation and fundamental changes correspond to the rapid cortical development at this age. Manual sleep classification is specifically challenging in this population given major body movements and frequent shifts between vigilance states; in addition various staging criteria co-exist. In the present study we utilized a machine learning approach and investigated how EEG complexity and sleep stages evolve during the very first weeks of life. We analyzed 42 full-term infants which were recorded twice (at week two and five after birth) with full polysomnography. For sleep classification EEG signal complexity was estimated using multi-scale permutation entropy and fed into a machine learning classifier. Interestingly the baby’s brain signal complexity (and spectral power) revealed developmental changes in sleep in the first 5 weeks of life, and were restricted to NREM (“quiet”) and REM (“active sleep”) states with little to no changes in state wake. Data demonstrate that our classifier performs well over chance (i.e., >33% for 3-class classification) and reaches almost human scoring accuracy (60% at week-2, 73% at week-5). Altogether, these results demonstrate that characteristics of newborn sleep develop rapidly in the first weeks of life and can be efficiently identified by means of machine learning techniques.

An increase of inhibition drives the developmental decorrelation of neural activity

“…We quantified the 1/f exponent on the 1–20 Hz frequency range and confirmed that it increased with age (age coefficient = 0.26, 95% CI [0.24; 0.27], p<10 –183 , linear model) ( Figure 8C ). A second dataset ( Wielek et al, 2019 ) consisted of EEG recordings from 42 sleeping babies, recorded at 40 and 43 PCW. The analyses revealed that also for these data the PSD slope grew steeper ( Figure 8—figure supplement 1B-C ) and the 1/f exponent increased with age (age coefficient = 0.30, 95% CI [0.17; 0.42], p<10 –4 , linear mixed-effect model) ( Figure 8D ).…”

“…To stimulate IN activity, P0-P1 mice from the Dlx5/6-Cre and Gad2-IRES-Cre driver lines were injected in the mPFC with a virus encoding for ChR2 (AAV9-Ef1alpha-DIO-hChR2(ET/TC)-eYFP) as previously described ( Xu et al, 2021 ). Details on the data acquisition and experimental setup of open-access datasets that were used in this project have been previously published ( Chini et al, 2020 ; Bitzenhofer et al, 2021 ; Schetinin and Jakaite, 2017 ; Wielek et al, 2019 ).…”

“…From the EEG dataset of 1100 sleeping babies ( Schetinin and Jakaite, 2017 ), epochs whose average envelope amplitude exceeded two standard deviations from the mean were considered as possible artifacts and were removed from further analysis. No preprocessing was applied to the EEG dataset of sleeping babies recorded at 40 and 43 PCW, as PSDs were already included in the freely available data ( Wielek et al, 2019 ).…”

The Architecture of Early Childhood Sleep Over the First Two Years

“…Sleep Diary: Infant daytime sleep duration, Infant no. of night-waking, (Wielek et al, 2019 ) Sleep development 42 (27:15) 2 & 5 weeks old Polysomnography QS/NREM, AS/REM, Wake, Movement time, Transitional sleep, Power spectral density, Entropy measure (Wooding et al, 1990 ) Sleep patterns 874 (432:428) 1–12 months Sleep diary and Questionnaires TST over 24 h, Night-time sleeping, Daytime sleeping, Uninterrupted night sleeping, Sleeping, Waking & Settling times, Bedtime routines (Yoshida et al, 2015 ) Sleep development 34 (17:17) 3 & 4 months Actigraph, EEG, Sleep log Actigraph: Wakefulness, Light sleep, Deep sleep, EEG: Total sleep, Wake, REM, NREM stages 1–2, SWS, No. of sleep cycles (Zhou et al, 2015 ) Sleep development 899 (475:424) 3, 6, 9, 12, 18, & 24 BISQ Avg.…”

Newborn Incubators Do Not Protect from High Noise Levels in the Neonatal Intensive Care Unit and Are Relevant Noise Sources by Themselves

“…Therefore, the assessment of what is comfortable and what is not for an individual patient can only be based on close observation of the preterm. In contrast to adults where the sleeping time concentrates on several hours during the night, newborns have irregular sleeping patterns without an established circadian rhythm [65], which makes the organization of an open ward even more challenging. In order to adapt the acoustical environment to each patient's needs, we would need a flexible acoustic environment in each patient zone, which could be realized with advanced acoustic curtains.…”