Scanning strategies for simultainious EEG-fMRI evoked potential studoes at 3T

Tracy Warbrick, Andrew Bagshaw

Research output: Contribution to journalArticle

17 Citations (Scopus)


There are two basic strategies for applying simultaneous EEG-fmRI: either the fMRI data are acquired continuously, or the stimulus is presented during a brief gap in scanning when the EEG data is clear of gradient artefact. The former has the advantage that the protocol for the fMRI data acquisition is not affected by the presence of EEG. This study investigated the effect of these different strategies and the subsequent ballistocardiogram artefact removal methods (Average Artefact Subtraction (AAS) and Optimal Basis Set (OBS)) on EEG data quality recorded in response to a visual stimulus. Continuous scanning generally resulted in VEPs that were no worse, and in some cases were better, than those measured during a gap in scanning. The AAS and OBS methods lead to comparable results at the level of the grand average visual evoked potential (VEP), although when examined at the level of the single trial the OBS method was more effective. The spectral quality of the data was similar across scanning protocols, as demonstrated by the proportion of spectral power in each frequency band, although there was an effect of the artefact removal method on the overall spectral power. Some differences in the VEPs were also noted when a TR of 1.5 s was used relative to a TR of 3 s. The results indicate improved EEG quality when fMRI scanning is continuous and BCG artefacts are removed using the OBS method, confirming that EEG can be added to an fMRI experiment with minimal change to the experimental protocol. (C) 2007 Elsevier B.V. All rights reserved.
Original languageEnglish
Pages (from-to)169-177
Number of pages9
JournalInternational journal of psychophysiology : official journal of the International Organization of Psychophysiology
Issue number3
Publication statusPublished - 1 Mar 2008


  • VEPs
  • BCG artefact removal
  • simultaneous EEG-fMRI
  • EEG data quality


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