Methods for pulse artefact reduction: experiences with EEG data recorded at 9.4 T static magnetic field

Jorge Arrubla, Irene Neuner, Jürgen Dammers, Lukas Breuer, Tracy Warbrick, David Hahn, Michael S. Poole, Frank Boers, N. Jon Shah

Research output: Contribution to journalArticleResearchpeer-review

7 Citations (Scopus)

Abstract

Background: The feasibility of recording electroencephalography (EEG) at ultra-high static magnetic fields up to 9.4. T was recently demonstrated and is expected to be incorporated into functional magnetic resonance imaging (fMRI) studies at 9.4. T. Correction of the pulse artefact (PA) is a significant challenge since its amplitude is proportional to the strength of the magnetic field in which EEG is recorded. New method: We conducted a study in which different PA correction methods were applied to EEG data recorded inside a 9.4. T scanner in order to retrieve visual P100 and auditory P300 evoked potentials. We explored different PA reduction methods, including the optimal basis set (OBS) method as well as objective and subjective component rejection using independent component analysis (ICA). Results: ICA followed by objective rejection of components is optimal for retrieving visual P100 and auditory P300 from EEG data recorded inside the scanner. Comparison with existing methods: Previous studies suggest that OBS or OBS followed by ICA are optimal for retrieving evoked potentials at 3. T. In our EEG data recorded at 9.4. T OBS performed alone was not fully optimal for the identification of evoked potentials. OBS followed by ICA was partially effective. Conclusions: In this study ICA has been shown to be an important tool for correcting the PA in EEG data recorded at 9.4. T, particularly when automated rejection of components is performed.

Original languageEnglish
Pages (from-to)110-117
Number of pages8
JournalJournal of Neuroscience Methods
Volume232
DOIs
Publication statusPublished - 30 Jul 2014
Externally publishedYes

Keywords

  • Auditory evoked potentials
  • EEG
  • Independent component analysis
  • MR
  • Optimal basis set
  • Pulse artefact
  • Ultra-high field
  • Visual evoked potentials

Cite this