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