A comparison of ocular artifact removal methods for block design based electroencephalography experiments

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Abstract

Eye movements and their contribution to electroencephalographic (EEG) recordings as ocular artifacts (OAs) are well studied. Yet their existence is typically regarded as impeding analysis. A widely accepted bypass is artifact avoidance. OA processing is often reduced to rejecting contaminated data. To overcome loss of data and restriction of behavior, research groups have proposed various correction methods. State of the art approaches are data driven and typically require OAs to be uncorrelated with brain activity. This does not necessarily hold for visuomotor tasks. To prevent correlated signals, we examined a two block approach. In a first block, subjects performed saccades and blinks, according to a visually guided paradigm. We then fitted 5 artifact removal algorithms to this data. To test their stationarity regarding artifact attenuation and preservation of brain activity, we recorded a second block one hour later. We found that saccades and blinks could still be attenuated to chance level, while brain activity during rest trials could be retained.
Original languageEnglish
Title of host publicationProceedings of the 7th Graz Brain-Computer Interface Conference 2017
Subtitle of host publicationFrom Vision to Reality
EditorsGernot Müller-Putz, David Steyrl, Selina Wrissnegger, Reinhold Scherer
Place of PublicationGraz
PublisherVerlag der Technischen Universität Graz
Pages236-241
Number of pages6
ISBN (Print)978-3-85125-533-1
DOIs
Publication statusPublished - 18 Sep 2017
Event7th Graz Brain-Computer Interface Conference 2017 -
Duration: 18 Sep 201722 Sep 2017

Conference

Conference7th Graz Brain-Computer Interface Conference 2017
Period18/09/1722/09/17

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Keywords

  • Eletroencephalography
  • Ocular artifacts
  • Independent component analysis
  • regression

Fields of Expertise

  • Human- & Biotechnology

Cite this

Kobler, R., Sburlea, A. I., & Müller-Putz, G. (2017). A comparison of ocular artifact removal methods for block design based electroencephalography experiments. In G. Müller-Putz, D. Steyrl, S. Wrissnegger, & R. Scherer (Eds.), Proceedings of the 7th Graz Brain-Computer Interface Conference 2017: From Vision to Reality (pp. 236-241). [44] Graz: Verlag der Technischen Universität Graz. https://doi.org/10.3217/978-3-85125-533-1-44