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Background Delayed brain function development in small-gestational-age (SGA) infants has been reported. We aimed to quantify rates of immature neonatal EEG patterns and their association with neurodevelopment in SGA full-term neonates. Methods Using a cohort design, 50 SGA (birthweight 3 h. Seventy-three of them were assessed at 2-years-old using Bayley-III-Scales. For EEG analysis, several segments of discontinuous/alternating EEG tracings were selected. Main outcomes measured: (1) Visual analysis (patterns of EEG maturity); (2) Power spectrum in δ, θ, α and β frequency bands; and (3) scores in motor, cognitive and language development. Results (1) SGA infants, compared to AGA, showed: (a) higher percentages of discontinuous EEG, both asynchrony and interhemispheric asymmetry, and bursts with delta-brushes, longer interburst-interval duration and more transients/hour; (b) lower relative power spectrum in δ and higher in α; and (c) lower scores on motor, language and cognitive neurodevelopment. (2) Asymmetry >5%, interburst-interval >5 s, discontinuity >11%, and bursts with delta-brushes >11% were associated with lower scores on Bayley-III. Conclusions In this prospective study, SGA full-term neonates showed high rates of immature EEG patterns. Low-birthweight and immaturity EEG were both correlated with low development scores.

In this paper, we propose a new method, based on the nonlinear energy operator (NLEO), to automatically detect burst---suppression (B---S) patterns in multichannel newborn electroencephalograms (EEGs). The proposed approach consists of two algorithms: (1) per-brain region B---S detection and (2) global B---S detection. At first, B---S patterns are detected in each channel using NLEO. Average of NLEO values obtained for all the channels is then calculated to detect the presence of B---S patterns in each brain region. After local B---S detection, the global B---S detection algorithm classifies a sample-point as burst if most of regions are bursting. Otherwise, the sample-point is classified as suppression. The proposed method is validated using a database composed of multichannel EEG signals acquired from 6 neonates. The experimental results show that the proposed approach can detect bursts which occur locally and classify global B---S patterns with a very high accuracy of 98%.

Neonatal seizures are a common emergency in the neonatal intensive care unit (NICU). There are many questions yet to be answered regarding the temporal/spatial characteristics of seizures from different pathologies, response to medication, effects on neurodevelopment and optimal detection. The dataset presented in this descriptor contains EEG recordings from human neonates, the visual interpretation of the EEG by the human experts, supporting clinical data and codes to assist access. Multi-channel EEG was recorded from 79 term neonates admitted to the NICU at the Helsinki University Hospital. The median recording duration was 74 min (IQR: 64 to 96 min). The presence of seizures in the EEGs was annotated independently by three experts. An average of 460 seizures were annotated per expert in the dataset; 39 neonates had seizures and 22 were seizure free, by consensus. The dataset can be used as a reference set of neonatal seizures, in studies of inter-observer agreement and for the development of automated methods of seizure detection and other EEG analyses. Machine-accessible metadata file describing the reported data (ISA-Tab format)

Infants of drug addicted mothers who terminated drug use prior to the second trimester manifested fewer abnormalities of relative power spectrums of quantitative electroencephalographic (Qeeg) recordings (QSI 9000) of all brain regions compared to infants whose mothers continued to use drugs.

Computerized analysis of the neonatal EEG provides a measure of cerebral function in the very preterm infant. This method has enabled observation of the effects of inotropic infusions on cerebral function in 13 sick infants between 24 and 30 weeks gestation. Inotropes used included dopamine, dobutamine and nor-adrenaline, either singly or in combination as dictated by the clinicians. On commencement of inotropic therapy, no deterioration in EEG was seen and improvement was noted in only 3 of 18 occasions. Monitoring during a further 12 increases in inotropic therapy showed associated improvement in the EEG in only one of these occasions. However, on reduction of the inotropic treatment, which was no longer deemed clinically necessary, there was an associated improvement in EEG in 12 of 16 occasions monitored. The EEG improvement on reduction in inotropic therapy appeared to be related to the duration of use of inotropes and to tho duration of time normotension had been achieved. These results imply that withdrawal of inotropic therapy should perhaps be considered as soon as clinically feasible as this dolotorious effect of inotropic infusions on cerebral function may be related to enchanced cerebro-vascular sympatho-adrenal tone.

The EEG, visual and auditory evoked potentials (VEP, AEP) were evaluated in 16 full-term newborn infants who had intracranial hemorrhage documented by computerized tomography (CT). Three of them had supratentorial, three, supra- and infratentorial hemorrhage, while the other ten had infra- or peri-tentorial bleeding. Three died during the neonatal period. Eight of the 13 surviving infants were neurologically normal and five were abnormal at the time of the follow-up. Those who had normal or mildly abnormal background EEGs all developed normally, while those whose neonatal EEG was severely abnormal subsequently developed neurological sequelae irrespective of the extent of intracranial hemorrhage. The EEG, VEP or AEP is of little value in the diagnosis of intracranial bleeding but the EEG is valuable in assessing the degree of associated parenchymatous damage and is of great prognostic significance.

New methods for the detection of ECG and EOG artefacts in the EEG are introduced, which can also be used for the evaluation of the quality of the elimination procedure. These algorithms are based on the estimation of the power or coherence spectrum by means of FFT. The advantage of this method is that the EEG spectrum is monitored by the test algorithm. The spectrum will be plotted if no influence of the ECG and EOG can be found. On the other hand, if artefacts are detected the correction of the EEG time series will be carried out and the spectrum of the corrected EEG time series will be plotted after repeated monitoring by the test algorithm.

Neonatal EEG and sleep findings are presented from a longitudinal study of the effects of maternal alcohol and marijuana use during pregnancy. Infant outcome has been examined relative to the trimester(s) of pregnancy during which use occurred. Disturbances in sleep cycling, motility, and arousals were noted that were both substance and trimester specific. Alcohol consumed during the first trimester of pregnancy was associated with disruptions in sleep and arousal, whereas marijuana use affected sleep and motility regardless of the trimester in which it was used. Although these findings are preliminary and based on a small sample of women exhibiting only moderate substance use during pregnancy, they do suggest that specific neurophysiological systems may be differentially affected by prenatal alcohol or marijuana exposure even in the absence of morphological abnormalities.

Asleep samples had more slow (0.8–3.0 cps) and less fast (13–32 cps) activity than low voltage awake samples. Abundance of intermediate frequencies (1.4–6.0 cps) was higher in frontal-precentral than parietal-occipital EEGs; this is consistent with greater neural maturation of precentrai gyrus (Conel, 1939). Present results suggest possible quantitative indices of activation level and neural maturation for behavioral studies.