Beamforming applied to surface EEG improves ripple visibility

Arjen Mol, Nicole van Klink*, Cyrille Ferrier, Arjan Hillebrand, Geertjan Huiskamp, Maeike Zijlmans

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

417 Downloads (Pure)

Abstract

Objective Surface EEG can show epileptiform ripples in people with focal epilepsy, but identification is impeded by the low signal-to-noise ratio of the electrode recordings. We used beamformer-based virtual electrodes to improve ripple identification. Methods We analyzed ten minutes of interictal EEG of nine patients with refractory focal epilepsy. EEGs with more than 60 channels and 20 spikes were included. We computed ∼79 virtual electrodes using a scalar beamformer and marked ripples (80–250 Hz) co-occurring with spikes in physical and virtual electrodes. Ripple numbers in physical and virtual electrodes were compared, and sensitivity and specificity of ripples for the region of interest (ROI; based on clinical information) were determined. Results Five patients had ripples in the physical electrodes and eight in the virtual electrodes, with more ripples in virtual than in physical electrodes (101 vs. 57, p =.007). Ripples in virtual electrodes predicted the ROI better than physical electrodes (AUC 0.65 vs. 0.56, p =.03). Conclusions Beamforming increased ripple visibility in surface EEG. Virtual ripples predicted the ROI better than physical ripples, although sensitivity was still poor. Significance Beamforming can facilitate ripple identification in EEG. Ripple localization needs to be improved to enable its use for presurgical evaluation in people with epilepsy.

Original languageEnglish
Article number129
Pages (from-to)101-111
Number of pages11
JournalClinical Neurophysiology
Volume129
Issue number1
DOIs
Publication statusPublished - 1 Jan 2018
Externally publishedYes

Funding

This manuscript was supported by the Dutch Brain Foundation fund (number 2013-139 ) and the Dutch Epilepsy Foundation fund 15-09 . M. Zijlmans is supported by the Rudolf Magnus Institute Talent fellowship 2012 and ZonMW veni 91615149.

FundersFunder number
Dutch Brain Foundation2013-139
Dutch Epilepsy Foundation fund15-09
Rudolf Magnus Institute
ZonMw91615149

    Keywords

    • Beamforming
    • Electroencephalography
    • Epilepsy
    • High frequency oscillations
    • Virtual electrodes

    Fingerprint

    Dive into the research topics of 'Beamforming applied to surface EEG improves ripple visibility'. Together they form a unique fingerprint.

    Cite this