Differences Between Preterm and Full-Term Infants in Electroencephalogram Power Spectral Density Slope.

A growing body of literature suggests that power spectral density (PSD) slope, measured using electroencephalography (EEG), might reflect synaptic activity and be a useful marker of early brain development. The objective of this article is to identify differences between preterm and full-term infants in PSD slope in active and quiet sleep. This is a secondary analysis of two studies, including premature (N = 33) (30 0/7 and 36 0/7 weeks' gestation) and full-term infants (N = 22).

Association between intermittent hypoxemia and neurodevelopmental outcomes in extremely premature infants: A single-center experience.

Objective: To describe the association between intermittent hypoxemic events (IHEs) and severe neurodevelopmental impairment (SNDI) or death in extremely premature infants.

Study Design: Retrospective study of extremely premature infants 23-27 weeks gestational age (GA) and birthweight (BW) ≤1250 grams (g) admitted to a level IV neonatal intensive care unit (NICU) from 2013 to 2017. IHEs, defined as events with SpO ≤ 80 % lasting 10 s to 5 min, were algorithmically identified using data extracted from bedside monitors at 2 s intervals (0.

Age-related trends in aperiodic EEG activity and alpha oscillations during early- to middle-childhood.

Age-related structural and functional changes that occur during brain development are critical for cortical development and functioning. Previous electroencephalography (EEG) and magnetoencephalography (MEG) studies have highlighted the utility of power spectra analyses and have uncovered age-related trends that reflect perceptual, cognitive, and behavioural states as well as their underlying neurophysiology. The aim of the current study was to investigate age-related change in aperiodic and periodic alpha activity across a large sample of pre- and school-aged children (N = 502, age range 4 -11-years-of-age).

Cardiorespiratory signature of neonatal sepsis: development and validation of prediction models in 3 NICUs.

Background: Heart rate characteristics aid early detection of late-onset sepsis (LOS), but respiratory data contain additional signatures of illness due to infection. Predictive models using cardiorespiratory data may improve early sepsis detection. We hypothesized that heart rate (HR) and oxygenation (SpO) data contain signatures that improve sepsis risk prediction over HR or demographics alone.

A Novel Method for ECG Artifact Removal from EEG without Simultaneous ECG.

The electrocardiogram (ECG) is a common source of electrical artifact in electroencephalogram (EEG). Here, we present a novel method for removing ECG artifact that requires neither simultaneous ECG nor transformation of the EEG signals. The approach relies upon processing a subset of EEG channels that contain ECG artifact to identify the times of each R-wave of the ECG.