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Empirically Validating Fully Automated EOG Artifact Correction using Independent Components Analysis

Ian D. Evans1*, Graham Jamieson1, Rodney Croft2 and Trieu T. Pham3
  • 1 University Of New England, School of Behavioural, Cognitive and Social Sciences, Australia
  • 2 Unviersity of Wollongong, Brain & Behaviour Research Insitute, Australia
  • 3 Swinburne University of Technology, Brain Sciences Institute, Australia

Electroencephalographic (EEG) recording remains one of the most powerful methods for collecting temporal-specific data on neural activity, however it remains particularly sensitive to eye movement artifacts. This study sought to test the effectiveness of a theoretically promising but as yet unvalidated method for removing ocular artifacts known as independent components analysis (ICA). ICA was compared to current best practice. The claim that ICA is mathematically superior to linear regression in identifying ocular artifacts was directly tested. EEG data from 23 participants was corrected using three ocular artifact correction methods (linear regression, ICA and ICA without directly measuring eye movement). Whilst all three correction methods proved effective, none were statistically different from each other. As such, the use of ICA in ocular artifact correction can now be considered to be empirically validated, but claims that ICA is superior to linear regression in ocular artifact correction remain unproven.

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Keywords: EOG, ICA, EEG, Artifact correction, RAAA, FASTER

Conference: ACNS-2012 Australasian Cognitive Neuroscience Conference, Brisbane, Australia, 29 Nov - 2 Dec, 2012.

Presentation Type: Poster Presentation

Topic: Other

Citation: Evans ID, Jamieson G, Croft R and Pham TT (2012). Empirically Validating Fully Automated EOG Artifact Correction using Independent Components Analysis. Conference Abstract: ACNS-2012 Australasian Cognitive Neuroscience Conference. doi: 10.3389/conf.fnhum.2012.208.00034

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Received: 25 Oct 2012; Published Online: 07 Nov 2012.

* Correspondence: Mr. Ian D Evans, University Of New England, School of Behavioural, Cognitive and Social Sciences, Armidale, NSW, 2351, Australia, ievans3@une.edu.au