title: Interhemispheric synchrony in the neonatal EEG revisited: activation synchrony index as a promising classifier.
abstract: A key feature of normal neonatal EEG at term age is interhemispheric synchrony (IHS), which refers to the temporal co-incidence of bursting across hemispheres during trace alternant EEG activity. The assessment of IHS in both clinical and scientific work relies on visual, qualitative EEG assessment without clearly quantifiable definitions. A quantitative measure, activation synchrony index (ASI), was recently shown to perform well as compared to visual assessments. The present study was set out to test whether IHS is stable enough for clinical use, and whether it could be an objective feature of EEG normality. We analyzed 31 neonatal EEG recordings that had been clinically classified as normal (n = 14) or abnormal (n = 17) using holistic, conventional visual criteria including amplitude, focal differences, qualitative synchrony, and focal abnormalities. We selected 20-min epochs of discontinuous background pattern. ASI values were computed separately for different channel pair combinations and window lengths to define them for the optimal ASI intraindividual stability. Finally, ROC curves were computed to find trade-offs related to compromised data lengths, a common challenge in neonatal EEG studies. Using the average of four consecutive 2.5-min epochs in the centro-occipital bipolar derivations gave ASI estimates that very accurately distinguished babies clinically classified as normal vs. abnormal. It was even possible to draw a cut-off limit (ASI~3.6) which correctly classified the EEGs in 97% of all cases. Finally, we showed that compromising the length of EEG segments from 20 to 5 min leads to increased variability in ASI-based classification. Our findings support the prior literature that IHS is an important feature of normal neonatal brain function. We show that ASI may provide diagnostic value even at individual level, which strongly supports its use in prospective clinical studies on neonatal EEG as well as in the feature set of upcoming EEG classifiers.
authors.affiliation: Division STADIUS, Department of Electrical Engineering (ESAT), University of Leuven Leuven, Belgium ; iMinds-KU Leuven Medical IT Department Leuven, Belgium.
authors.forename: Ninah
authors.initials: N
authors.lastname: Koolen
authors.affiliation: Department of Development and Regeneration, University of Leuven Leuven, Belgium.
authors.forename: Anneleen
authors.initials: A
authors.lastname: Dereymaeker
authors.affiliation: Department of Signal Processing and Acoustics, Aalto University Espoo, Finland.
authors.forename: Okko
authors.initials: O
authors.lastname: Räsänen
authors.affiliation: Department of Development and Regeneration, University of Leuven Leuven, Belgium.
authors.forename: Katrien
authors.initials: K
authors.lastname: Jansen
authors.affiliation: Department of Development and Regeneration, University of Leuven Leuven, Belgium.
authors.forename: Jan
authors.initials: J
authors.lastname: Vervisch
authors.affiliation: Division STADIUS, Department of Electrical Engineering (ESAT), University of Leuven Leuven, Belgium ; iMinds-KU Leuven Medical IT Department Leuven, Belgium.
authors.forename: Vladimir
authors.initials: V
authors.lastname: Matic
authors.affiliation: Department of Psychology, University of Oldenburg Oldenburg, Germany ; Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford Oxford, UK.
authors.forename: Maarten
authors.initials: M
authors.lastname: De Vos
authors.affiliation: Division STADIUS, Department of Electrical Engineering (ESAT), University of Leuven Leuven, Belgium ; iMinds-KU Leuven Medical IT Department Leuven, Belgium.
authors.forename: Sabine
authors.initials: S
authors.lastname: Van Huffel
authors.affiliation: Department of Development and Regeneration, University of Leuven Leuven, Belgium.
authors.forename: Gunnar
authors.initials: G
authors.lastname: Naulaers
authors.affiliation: Department of Children's Clinical Neurophysiology, HUS Medical Imaging Center and Children's Hospital, Helsinki University Central Hospital and University of Helsinki Helsinki, Finland.
authors.forename: Sampsa
authors.initials: S
authors.lastname: Vanhatalo
keywords: biomarker; brain monitoring; interhemispheric synchrony; neonatal EEG; preterm infant