Search

Objective: Early prediction of neurological deficits following neonatal hypoxic-ischemic encephalopathy (HIE) may help to target support. Neonatal animal models suggest that recovery following hypoxia-ischemia depends upon cortical bursting. To test whether this holds in human neonates, we correlated the magnitude of cortical bursting during recovery (≥postnatal day 3) with neurodevelopmental outcomes., Methods: We identified 41 surviving infants who received therapeutic hypothermia for HIE (classification at hospital discharge: 19 mild, 18 moderate, 4 severe) and had 9-channel electroencephalography (EEG) recordings as part of their routine care. We correlated burst power with Bayley-III cognitive, motor and language scores at median 24 months. To examine whether EEG offered additional prognostic information, we controlled for structural MRI findings., Results: Higher power of central and occipital cortical bursts predicted worse cognitive and language outcomes, and higher power of central cortical bursts predicted worse motor outcome, all independently of structural MRI findings., Conclusions: Clinical EEG after postnatal day 3 may provide additional prognostic information by indexing persistent active mechanisms that either support recovery or exacerbate brain damage, especially in infants with less severe encephalopathy., Significance: These findings could allow for the effect of clinical interventions in the neonatal period to be studied instantaneously in the future., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.)

Delta and theta power across fronto-central regions is lower during phasic (saccadic eye movements) than tonic rapid eye movement (active) sleep in full-term infants (n = 15). This indicates that the behavioural-electrophysiological pillars of rapid eye movement sleep micro-architecture are in place at birth., (Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.)

As an approach of unobtrusive assessment of neonatal sleep state we aimed at an automated sleep state coding based only on heart rate variability obtained from electrocardiography used for regular patient monitoring. We analyzed active and quiet sleep states of preterm infants between 30 and 37weeks postmenstrual age. To determine the sleep states we used a nonlinear kernel support vector machine for sleep state separation based on known heart rate variability features. We used unweighted and weighted misclassification penalties for the imbalanced distribution between sleep states. The validation was performed with leave-one-out-cross-validation based on the annotations of three independent observers. We analyzed the classifier performance with receiver operating curves leading to a maximum mean value for the area under the curve of 0.87. Using this sleep state separation methods, we show that automated active and quiet sleep state separation based on heart rate variability in preterm infants is feasible., (Copyright © 2017 Elsevier B.V. All rights reserved.)

During adulthood, electroencephalogram (EEG) recordings are used to distinguish wake, non-rapid eye movement sleep, and rapid eye movement sleep states. The close association between behavioral states and EEG rhythms is reached late during development, after birth in humans and by the end of the second postnatal week in rats and mice. This critical time is also when cortical activity switches from a discontinuous to a continuous pattern. We review the major cellular and network changes that can account for this transition. After this close link is established, new evidence suggests that the slow waves of non-rapid eye movement sleep may function as markers to track cortical development. However, before the EEG can be used to identify behavioral states, two distinct sleep phases--quiet sleep and active sleep--are identified based on behavioral criteria and muscle activity. During this early phase of development, cortical activity is far from being disorganized, despite the presence of long periods of neuronal silence and the poor modulation by behavioral states. Specific EEG patterns, such as spindle bursts and gamma oscillations, have been identified very early on and are believed to play a significant role in the refinement of brain circuits. Because most early EEG patterns do not map to a specific behavioral state, their contribution to the presumptive role of sleep in brain maturation remains to be established and should be a major focus for future research., (Copyright © 2015 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)