Abstract
Neonates spend most of their life sleeping. During sleep, their brain experiences fast changes in its functional organization. Microstate analysis permits to capture the rapid dynamical changes occurring in the functional organization of the brain by representing the changing spatio-temporal features of the electroencephalogram (EEG) as a sequence of short-lasting scalp topographies—the microstates. In this study, we modeled the ongoing neonatal EEG into sequences of a limited number of microstates and investigated whether the extracted microstate features are altered in REM and NREM sleep (usually known as active and quiet sleep states—AS and QS—in the newborn) and depend on the EEG frequency band. 19-channel EEG recordings from 60 full-term healthy infants were analyzed using a modified version of the k-means clustering algorithm. The results show that ~ 70% of the variance in the datasets can be described using 7 dominant microstate templates. The mean duration and mean occurrence of the dominant microstates were significantly different in the two sleep states. Microstate syntax analysis demonstrated that the microstate sequences characterizing AS and QS had specific non-casual structures that differed in the two sleep states. Microstate analysis of the neonatal EEG in specific frequency bands showed a clear dependence of the explained variance on frequency. Overall, our findings demonstrate that (1) the spatio-temporal dynamics of the neonatal EEG can be described by non-casual sequences of a limited number of microstate templates; (2) the brain dynamics described by these microstate templates depends on frequency; (3) the features of the microstate sequences can well differentiate the physiological conditions characterizing AS and QS.
Highlights
Sleep plays a crucial role in the development of cortical pathways and brain networks in the neonate
This result is in agreement with adult studies in terms of the percentage of EEG variance that can be explained by the extracted microstate templates (Michel and Koenig 2018), it must be observed that the optimal number of microstate templates for neonatal EEG—as determined with the Krzanowski-Lai (KL) criterion—was higher than in the case of adult EEG
The higher number of microstate templates required to reach high GEV in neonates as compared to adults could be due to the fact that newborn EEG is typically recorded and analyzed during sleep, whereas adult studies are typically performed during awake state
Summary
Sleep plays a crucial role in the development of cortical pathways and brain networks in the neonate. These phenomena, which set up the foundation of future behavior and memory, are formed by endogenous driven brain activity during neonatal sleep (Koolen et al 2014; Lubsen et al 2011; Omidvarnia et al 2014). Falling asleep and sleep state transitions are events that involve the reorganization of functional interactions between remote brain regions (Tokariev et al 2019a; b). Such long-range neural connections are a key component in early brain functional development. Little is known about the mechanisms underlying the functional communication within the neonatal brain and advancing our knowledge of the dynamic reorganization of the functional
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