High-Frequency Oscillations in the Scalp Electroencephalogram: Mission Impossible without Computational Intelligence

Computational Intelligence and Neuroscience
Peter HöllerYvonne Höller

Abstract

High-frequency oscillations (HFOs) in the electroencephalogram (EEG) are thought to be a promising marker for epileptogenicity. A number of automated detection algorithms have been developed for reliable analysis of invasively recorded HFOs. However, invasive recordings are not widely applicable since they bear risks and costs, and the harm of the surgical intervention of implantation needs to be weighted against the informational benefits of the invasive examination. In contrast, scalp EEG is widely available at low costs and does not bear any risks. However, the detection of HFOs on the scalp represents a challenge that was taken on so far mostly via visual detection. Visual detection of HFOs is, in turn, highly time-consuming and subjective. In this review, we discuss that automated detection algorithms for detection of HFOs on the scalp are highly warranted because the available algorithms were all developed for invasively recorded EEG and do not perform satisfactorily in scalp EEG because of the low signal-to-noise ratio and numerous artefacts as well as physiological activity that obscures the tiny phenomena in the high-frequency range.

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Citations

Aug 6, 2019·Frontiers in Neurology·Pieter van MierloSerge Vulliemoz
Feb 26, 2019·Frontiers in Neurology·Aljoscha ThomschewskiBirgit Frauscher
Jun 26, 2020·Frontiers in Neurology·Nathalie GernerYvonne Höller
Jan 16, 2021·Clinical Neurophysiology : Official Journal of the International Federation of Clinical Neurophysiology·Tamir AvigdorBirgit Frauscher
Apr 28, 2020·Computers in Biology and Medicine·Shuhan YangFengfeng Zhou
Aug 7, 2021·Nature Neuroscience·Adam LiSridevi V Sarma

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